rowid,run.accession,experiment.accession,sample.accession,study.accession,bioproject,study.title,study.alias,study.type,study.abstract,study.attributes,study.PMIDs,sample.description,sample.title,sample.alias,sample.centername,sample.attributes,GEOsample.title,GEOsample.dataprocessing,GEOsample.source,GEOsample.treatmentprotocol,GEOsample.extractprotocol,GEOsample.growthprotocol,GEOsample.characteristics,GEOsample.accession,experiment.title,experiment.alias,experiment.library_name,experiment.design_description,experiment.library_construction_protocol,experiment.attributes,experiment.library_strategy,experiment.library_source,experiment.library_selection,experiment.library_layout,experiment.platform,experiment.instrument_model,experiment.spot_descriptor,experiment.study_ref,run.title,run.attributes,run.filename,run.semantic_name,run.total_bases,run.total_spots,run.alias,run.read_lengths,run.base_counts,run.r1_length,run.r2_length,run.r3_length,run.r4_length,run.Acount,run.Ccount,run.Gcount,run.Tcount,run.Ncount,run.experiment,run.pool_member,submission.accession,submission.srasource,submission.bioprojectsource,seqdetective.n_mates,seqdetective.mapping_rate.mate1,seqdetective.mapping_rate.mate2,seqdetective.nofeature_rate.mate1,seqdetective.nofeature_rate.mate2,seqdetective.sparsity.mate1,seqdetective.sparsity.mate2,seqdetective.pos_strand_rate.mate1,seqdetective.pos_strand_rate.mate2,seqdetective.readlen.mate1,seqdetective.readlen.mate2,seqdetective.judgement.mate1,seqdetective.judgement.mate2,seqdetective.judgement.reason,platform_family,instrument_generation,read_bias,selection_class,prep_kit,sc_or_bulk,tech_class,technology,tech_variant,submission.bioprojectsource.country,earliest_date,devstage_curation,devstage_curation_coarse,tissue_curation,tissue_curation_coarse
38,DRR408248,DRX393854,DRS407179,DRP012042,PRJDB14275,Zebrafish EN/ENCDC RNA seq,DRP012042,Transcriptome Analysis,A project to find differential expressed genes between enteric neurons ENs and enteric neural crest derived cells ENCDCs in larval zebrafish gut. We dissected guts of transgenic line  TgSAGFFLF217B; uas:gfp for ENs and Tgsox10:cre; EF1alpha:loxP gfp loxP dsred for ENCDCs  and isolated GFP+ ENs and dsRed+ ENCDCs.  Three duplicates for each of ENs and ENCDCs are prepared. Libraries for NGS are prepared using SMART Seq V4 Ultra Low Input RNA Kit.,,,zebrafish 5 day DsRed positive enteric neural crest derived cells replicate 3,zebrafish ENCDC replicate 3,SAMD00529468,,sample name:zebrafish ENCDC replicate 3|biological replicate:enteric neural crest derived cells 3|strain:Tgsox10:cre; EF3alpha:loxP gfp loxP dsred,,,,,,,,,NextSeq 550 paired end sequencing of SAMD00529468,DRX393854,190326ENvsNC N706 5day;NeuralCrestDerivedCell;rep3,1,1,,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,NextSeq 550,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>160</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>81</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP012042,NextSeq 550 paired end sequencing of SAMD00529468,,,,3803721121.0,24526633.0,DRR408248,0:77.54 1:77.54,A:999106107;C:897663781;G:921501114;T:979486853;N:5963266,77,77,,,999106107,897663781,921501114,979486853,5963266,DRX393854,DRS407179,DRA014886,"NIBB|NIBB core research facilities, National Institute for Basic Biology",University of Hyogo,,,,,,,,,,,,B,B,biological fallback assumption,illumina,nextseq,unknown,random_priming,unknown,bulk,unknown,unknown,,Japan,2024-09-22,Undetermined,Larval,Brain,Nervous System
39,DRR408247,DRX393853,DRS407178,DRP012042,PRJDB14275,Zebrafish EN/ENCDC RNA seq,DRP012042,Transcriptome Analysis,A project to find differential expressed genes between enteric neurons ENs and enteric neural crest derived cells ENCDCs in larval zebrafish gut. We dissected guts of transgenic line  TgSAGFFLF217B; uas:gfp for ENs and Tgsox10:cre; EF1alpha:loxP gfp loxP dsred for ENCDCs  and isolated GFP+ ENs and dsRed+ ENCDCs.  Three duplicates for each of ENs and ENCDCs are prepared. Libraries for NGS are prepared using SMART Seq V4 Ultra Low Input RNA Kit.,,,zebrafish 5 day DsRed positive enteric neural crest derived cells replicate 2,zebrafish ENCDC replicate 2,SAMD00529467,,sample name:zebrafish ENCDC replicate 2|biological replicate:enteric neural crest derived cells 2|strain:Tgsox10:cre; EF2alpha:loxP gfp loxP dsred,,,,,,,,,NextSeq 550 paired end sequencing of SAMD00529467,DRX393853,190326ENvsNC N705 5day;NeuralCrestDerivedCell;rep2,1,1,,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,NextSeq 550,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>160</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>81</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP012042,NextSeq 550 paired end sequencing of SAMD00529467,,,,3436798274.0,22156202.0,DRR408247,0:77.56 1:77.56,A:900848174;C:812031426;G:832960423;T:885671203;N:5287048,77,77,,,900848174,812031426,832960423,885671203,5287048,DRX393853,DRS407178,DRA014886,"NIBB|NIBB core research facilities, National Institute for Basic Biology",University of Hyogo,,,,,,,,,,,,B,B,biological fallback assumption,illumina,nextseq,unknown,random_priming,unknown,bulk,unknown,unknown,,Japan,2024-09-22,Undetermined,Larval,Brain,Nervous System
40,DRR408246,DRX393852,DRS407177,DRP012042,PRJDB14275,Zebrafish EN/ENCDC RNA seq,DRP012042,Transcriptome Analysis,A project to find differential expressed genes between enteric neurons ENs and enteric neural crest derived cells ENCDCs in larval zebrafish gut. We dissected guts of transgenic line  TgSAGFFLF217B; uas:gfp for ENs and Tgsox10:cre; EF1alpha:loxP gfp loxP dsred for ENCDCs  and isolated GFP+ ENs and dsRed+ ENCDCs.  Three duplicates for each of ENs and ENCDCs are prepared. Libraries for NGS are prepared using SMART Seq V4 Ultra Low Input RNA Kit.,,,zebrafish 5 day DsRed positive enteric neural crest derived cells replicate 1,zebrafish ENCDC replicate 1,SAMD00529466,,sample name:zebrafish ENCDC replicate 1|biological replicate:enteric neural crest derived cells 1|strain:Tgsox10:cre; EF1alpha:loxP gfp loxP dsred,,,,,,,,,NextSeq 550 paired end sequencing of SAMD00529466,DRX393852,190326ENvsNC N704 5day;NeuralCrestDerivedCell;rep1,1,1,,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,NextSeq 550,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>160</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>81</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP012042,NextSeq 550 paired end sequencing of SAMD00529466,,,,3582073512.0,23135170.0,DRR408246,0:77.41 1:77.42,A:943152815;C:841972211;G:863627245;T:927361159;N:5960082,77,77,,,943152815,841972211,863627245,927361159,5960082,DRX393852,DRS407177,DRA014886,"NIBB|NIBB core research facilities, National Institute for Basic Biology",University of Hyogo,,,,,,,,,,,,B,B,biological fallback assumption,illumina,nextseq,unknown,random_priming,unknown,bulk,unknown,unknown,,Japan,2024-09-22,Undetermined,Larval,Brain,Nervous System
101,DRR189403,DRX179868,DRS200418,DRP003977,PRJDB4470,Gene expression analysis of the zebrafish brain,DRP003977,Other,Gene expression profiling by RNA seq of specific regions and subpopulations of neurons in the zebrafish brain that control behaviors.,,,,Telencephalon of adult zebrafrish  30 min post test session of 2 weeks memory test in non trace 2 Way Active Avoidance coditioning 3,SAMD00182246,,sample name:CSUS Tel 30 2w memory 3|genotype:wild type|tissue:brain,,,,,,,,,Illumina HiSeq 3000 sequencing of SAMD00182246,DRX179868,CSUS Tel 30 2w memory 3,1,SureSelect Strand Specific RNA Library Prep Kit,,RNA-Seq,TRANSCRIPTOMIC,PolyA,SINGLE,ILLUMINA,Illumina HiSeq 3000,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>36</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003977,Illumina HiSeq 3000 sequencing of SAMD00182246,,,,2791119960.0,77531110.0,DRR189403,0:36,A:685050951;C:641519684;G:664655385;T:799677669;N:216271,36,,,,685050951,641519684,664655385,799677669,216271,DRX179868,DRS200418,DRA008865,NIG|National Institute of Genetics (Japan),National Institute of Genetics (Japan),1,0.89653,,0.1773,,0.70725,,0.49873,,36,,B,,usable mapping rate,illumina,hiseq_era,unknown,poly_a,unknown,bulk,unknown,unknown,,Japan,2021-08-08,Larval,Larval,Brain,Nervous System
102,DRR189402,DRX179867,DRS200417,DRP003977,PRJDB4470,Gene expression analysis of the zebrafish brain,DRP003977,Other,Gene expression profiling by RNA seq of specific regions and subpopulations of neurons in the zebrafish brain that control behaviors.,,,,Telencephalon of adult zebrafrish  30 min post test session of 2 weeks memory test in non trace 2 Way Active Avoidance coditioning 2,SAMD00182245,,sample name:CSUS Tel 30 2w memory 2|genotype:wild type|tissue:brain,,,,,,,,,Illumina HiSeq 3000 sequencing of SAMD00182245,DRX179867,CSUS Tel 30 2w memory 2,1,SureSelect Strand Specific RNA Library Prep Kit,,RNA-Seq,TRANSCRIPTOMIC,PolyA,SINGLE,ILLUMINA,Illumina HiSeq 3000,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>36</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003977,Illumina HiSeq 3000 sequencing of SAMD00182245,,,,1505449224.0,41818034.0,DRR189402,0:36,A:369895057;C:346914787;G:358624651;T:429897489;N:117240,36,,,,369895057,346914787,358624651,429897489,117240,DRX179867,DRS200417,DRA008865,NIG|National Institute of Genetics (Japan),National Institute of Genetics (Japan),1,0.89514,,0.17677,,0.7025,,0.49571,,36,,B,,usable mapping rate,illumina,hiseq_era,unknown,poly_a,unknown,bulk,unknown,unknown,,Japan,2021-08-08,Larval,Larval,Brain,Nervous System
103,DRR189401,DRX179866,DRS200416,DRP003977,PRJDB4470,Gene expression analysis of the zebrafish brain,DRP003977,Other,Gene expression profiling by RNA seq of specific regions and subpopulations of neurons in the zebrafish brain that control behaviors.,,,,Telencephalon of adult zebrafrish  30 min post test session of 2 weeks memory test in non trace 2 Way Active Avoidance coditioning 1,SAMD00182244,,sample name:CSUS Tel 30 2w memory 1|genotype:wild type|tissue:brain,,,,,,,,,Illumina HiSeq 3000 sequencing of SAMD00182244,DRX179866,CSUS Tel 30 2w memory 1,1,SureSelect Strand Specific RNA Library Prep Kit,,RNA-Seq,TRANSCRIPTOMIC,PolyA,SINGLE,ILLUMINA,Illumina HiSeq 3000,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>36</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003977,Illumina HiSeq 3000 sequencing of SAMD00182244,,,,2088507024.0,58014084.0,DRR189401,0:36,A:516255405;C:478036869;G:496415722;T:597637091;N:161937,36,,,,516255405,478036869,496415722,597637091,161937,DRX179866,DRS200416,DRA008865,NIG|National Institute of Genetics (Japan),National Institute of Genetics (Japan),1,0.89533,,0.18553,,0.70981,,0.49554,,36,,B,,usable mapping rate,illumina,hiseq_era,unknown,poly_a,unknown,bulk,unknown,unknown,,Japan,2021-08-08,Larval,Larval,Brain,Nervous System
156,DRR067143,DRX061087,DRS034141,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Bergmann glial cells using Tg line SAGFFLF251A sample 2,SAMD00057666,,sample name:Zebrafish 251A 02|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:bergmann glial cells|dev stage:14 dpf|replicate:biological replicate 2,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057666,DRX061087,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057666,,,,2040373922.0,10100861.0,DRR067143,0:101 1:101,A:577691972;C:445051245;G:472607289;T:544962357;N:61059,101,101,,,577691972,445051245,472607289,544962357,61059,DRX061087,DRS034141,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.83407,0.83802,0.12612,0.12666,0.73675,0.74079,0.4948,0.49282,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
157,DRR067142,DRX061086,DRS034140,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Bergmann glial cells using Tg line SAGFFLF251A sample 1,SAMD00057665,,sample name:Zebrafish 251A 01|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:bergmann glial cells|dev stage:14 dpf|replicate:biological replicate 1,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057665,DRX061086,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057665,,,,2033951534.0,10069067.0,DRR067142,0:101 1:101,A:589558269;C:431084184;G:460501802;T:552746498;N:60781,101,101,,,589558269,431084184,460501802,552746498,60781,DRX061086,DRS034140,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.8958,0.90339,0.13764,0.1385,0.72563,0.72865,0.49373,0.49916,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
158,DRR067141,DRX061085,DRS034139,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Purkinje cells using Tg line aldoca:GAP Venus sample 3,SAMD00057664,,sample name:Zebrafish aldoca 03|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:purkinje cells|dev stage:14 dpf|replicate:biological replicate 3,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057664,DRX061085,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057664,,,,1931908608.0,9563904.0,DRR067141,0:101 1:101,A:558444394;C:409856521;G:429168864;T:534380258;N:58571,101,101,,,558444394,409856521,429168864,534380258,58571,DRX061085,DRS034139,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.88632,0.89109,0.15695,0.15773,0.75694,0.7599,0.46875,0.49236,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
159,DRR067140,DRX061084,DRS034138,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Purkinje cells using Tg line aldoca:GAP Venus sample 2,SAMD00057663,,sample name:Zebrafish aldoca 02|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:purkinje cells|dev stage:14 dpf|replicate:biological replicate 2,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057663,DRX061084,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057663,,,,1851108406.0,9163903.0,DRR067140,0:101 1:101,A:537339104;C:390802782;G:416335529;T:506575762;N:55229,101,101,,,537339104,390802782,416335529,506575762,55229,DRX061084,DRS034138,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.9055,0.91341,0.1515,0.15333,0.76495,0.76719,0.49219,0.49012,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
160,DRR067139,DRX061083,DRS034137,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Purkinje cells using Tg line aldoca:GAP Venus sample 1,SAMD00057662,,sample name:Zebrafish aldoca 01|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:purkinje cells|dev stage:14 dpf|replicate:biological replicate 1,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057662,DRX061083,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057662,,,,2000078962.0,9901381.0,DRR067139,0:101 1:101,A:583169141;C:420603631;G:446949308;T:549297272;N:59610,101,101,,,583169141,420603631,446949308,549297272,59610,DRX061083,DRS034137,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.9056,0.90932,0.15092,0.15179,0.76173,0.7654,0.49028,0.49604,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
161,DRR067138,DRX061082,DRS034136,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for granule cells using Tg line gSA2AzGFF152B sample 2,SAMD00057661,,sample name:Zebrafish 152B 02|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:granule cells|dev stage:14 dpf|replicate:biological replicate 2,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057661,DRX061082,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057661,,,,1997432156.0,9888278.0,DRR067138,0:101 1:101,A:578466824;C:423038930;G:449779231;T:546086391;N:60780,101,101,,,578466824,423038930,449779231,546086391,60780,DRX061082,DRS034136,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.90322,0.91109,0.1463,0.14811,0.75452,0.75633,0.48303,0.48557,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
162,DRR067137,DRX061081,DRS034135,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for granule cells using Tg line gSA2AzGFF152B sample 1,SAMD00057660,,sample name:Zebrafish 152B 01|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:granule cells|dev stage:14 dpf|replicate:biological replicate 1,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057660,DRX061081,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057660,,,,1908437218.0,9447709.0,DRR067137,0:101 1:101,A:552150223;C:401993096;G:427236477;T:527000978;N:56444,101,101,,,552150223,401993096,427236477,527000978,56444,DRX061081,DRS034135,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.90474,0.91043,0.17336,0.17401,0.76108,0.76359,0.483,0.48537,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
163,DRR067136,DRX061080,DRS034134,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Inferior olive nuclei using Tg line hspGFFDMC28C sample 3,SAMD00057659,,sample name:Zebrafish 28C 03|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:hindbrain|cell type:inferior olive nuclei|dev stage:14 dpf|replicate:biological replicate 3,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057659,DRX061080,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057659,,,,1982971178.0,9816689.0,DRR067136,0:101 1:101,A:504064758;C:488246993;G:520130333;T:470469799;N:59295,101,101,,,504064758,488246993,520130333,470469799,59295,DRX061080,DRS034134,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.53386,0.54375,0.06072,0.06189,0.76351,0.76641,0.4872,0.48857,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
164,DRR067135,DRX061079,DRS034133,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Inferior olive nuclei using Tg line hspGFFDMC28C sample 2,SAMD00057658,,sample name:Zebrafish 28C 02|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:hindbrain|cell type:inferior olive nuclei|dev stage:14 dpf|replicate:biological replicate 2,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057658,DRX061079,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057658,,,,1961048320.0,9708160.0,DRR067135,0:101 1:101,A:557469151;C:424691789;G:455244994;T:523583601;N:58785,101,101,,,557469151,424691789,455244994,523583601,58785,DRX061079,DRS034133,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.84854,0.8526,0.10311,0.1042,0.75227,0.75499,0.49321,0.49435,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
165,DRR067134,DRX061078,DRS034132,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for Inferior olive nuclei using Tg line hspGFFDMC28C sample 1,SAMD00057657,,sample name:Zebrafish 28C 01|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:hindbrain|cell type:inferior olive nuclei|dev stage:14 dpf|replicate:biological replicate 1,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057657,DRX061078,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057657,,,,1931802760.0,9563380.0,DRR067134,0:101 1:101,A:546501397;C:422500710;G:452200521;T:510543489;N:56643,101,101,,,546501397,422500710,452200521,510543489,56643,DRX061078,DRS034132,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.85439,0.85613,0.09867,0.09897,0.76871,0.77082,0.48943,0.48936,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
166,DRR067133,DRX061077,DRS034131,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for eurydendroid cells using Tg line hspzGFFgDMC156A sample 2,SAMD00057656,,sample name:Zebrafish 156A 02|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:eurydendroid cells|dev stage:14 dpf|replicate:biological replicate 2,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057656,DRX061077,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057656,,,,2054289096.0,10169748.0,DRR067133,0:101 1:101,A:563764176;C:464768863;G:497506420;T:528187503;N:62134,101,101,,,563764176,464768863,497506420,528187503,62134,DRX061077,DRS034131,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.69311,0.6968,0.12309,0.12389,0.76428,0.76676,0.48379,0.48227,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
167,DRR067132,DRX061076,DRS034130,DRP003275,PRJDB4941,Gene expression profiling of granule cells and Purkinje cells in zebrafish cerebellum,DRP003275,Other,An RNA seq analysis was performed using zebrafish granule cells  Purkinje cells  IO neurons  and glial cells. The transcriptomes were sequenced using Illumina HiSeq with paired end libraries employing the Quartz seq method for low amount total RNA.,,,,Zebrafish RNA seq for eurydendroid cells using Tg line hspzGFFgDMC156A sample 1,SAMD00057655,,sample name:Zebrafish 156A 01|strain:Tg|biomaterial provider:Bioscience and Biotechnology Center  Nagoya University|tissue type:cerebellum|cell type:eurydendroid cells|dev stage:14 dpf|replicate:biological replicate 1,,,,,,,,,Illumina HiSeq 1500 paired end sequencing of SAMD00057655,DRX061076,1,1,Quartz seq for low amount total RNA,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina HiSeq 1500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>202</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>102</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,DRP003275,Illumina HiSeq 1500 paired end sequencing of SAMD00057655,,,,2152665722.0,10656761.0,DRR067132,0:101 1:101,A:585252781;C:495382257;G:522677749;T:549287359;N:65576,101,101,,,585252781,495382257,522677749,549287359,65576,DRX061076,DRS034130,DRA004955,RIKEN_CLST_DBFDI|Phyloinformatics Unit,RIKEN CLST,2,0.67771,0.68253,0.12949,0.1303,0.77216,0.77542,0.4951,0.49452,101,101,B,B,biological fallback assumption,illumina,hiseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,quartzseq,,Japan,2016-09-19,Larval,Larval,Brain,Nervous System
9331,ERR2862354,ERX2868592,ERS2866329,ERP111743,PRJEB29441,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E-MTAB-7349,Transcriptome Analysis,Oncogenic transformation of individual cell fates by developmental signaling cascades and transcription factors triggers diverse cancer types. Chordoma is a rare  aggressive tumor arising from transformed notochord remnants. Various potentially oncogenic factors have been found deregulated in chordoma and its metastases  yet clear causation remains uncertain. In particular  expression of the notochord controlling transcription factor Brachyury is hypothesized as key molecular driver in chordoma formation  yet an in vivo model to causally test its oncogenic potential in the notochord is missing. Here  we apply a zebrafish model of chordoma onset to identify the notochord transforming potential of tumor implicated candidate genes in vivo. We find that overexpression of human and zebrafish Brachyury  including a version with augmented transcriptional activity  is insufficient to initiate notochord hyperplasia in vivo. In contrast  the repeatedly chordoma implicated receptor tyrosine kinase RTK genes EGFR and KDR/VEGFR2 are sufficient to transform developmental notochord cells  akin to direct activation of Ras. Analysis of transcriptome and sub cellular organization from transformed notochords suggests that aberrant activation of RTK/Ras signaling attenuates processes required for the differentiation of notochord cells. Taken together  our results provide first in vivo indication for a lack of tumor initiating potential of Brachyury expression in the notochord  and suggest activated RTK signaling as potent hyperplasia initiating event in chordoma.,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 10 30,,Protocols: 8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,TUC,SAMEA5055152,UZH,ENA FIRST PUBLIC:2018 12 01T17:03:21Z|ENA LAST UPDATE:2018 10 30T13:30:13Z|External Id:SAMEA5055152|INSDC center name:UZH|INSDC first public:2018 12 01T17:03:21Z|INSDC last update:2018 10 30T13:30:13Z|INSDC status:public|Submitter Id:E MTAB 7349:TUC|age:8|broker name:ArrayExpress|common name:zebrafish|developmental stage:embryo|genotype:wild type genotype|individual:mixed pool of 30 to 50 embryos|organism part:notochord|sample name:E MTAB 7349:TUC|scientific name:Danio rerio|sex:mixed,,,,,,,,,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E MTAB 7349:TUC p,TUC p,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,Experimental Factor: genotype:wild type genotype,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,Illumina HiSeq 2500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>200</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_LABEL>F</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_LABEL>R</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>101</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,ERP111743,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 11 16,AGCGATAG_AGGCTATA__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_1.fq.gz AGCGATAG_AGGCTATA__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_2.fq.gz,fastq fastq,12890102400.0,64450512.0,E MTAB 7349:AGCGATAG AGGCTATA  160520 I127 FCH732GBBXX L8 CDKPEI160513002 ,0:100 1:100,A:3347844573;C:3078635366;G:3118813009;T:3343385073;N:1424379,100,100,,,3347844573,3078635366,3118813009,3343385073,1424379,ERX2868592,ERS2866329,ERA1640550,European Nucleotide Archive,European Nucleotide Archive,2,0.89165,0.8896,0.26768,0.26518,0.75142,0.75459,0.60855,0.6105,100,100,B,B,biological fallback assumption,illumina,hiseq_era,unknown,random_priming,trueseq,bulk,unknown,unknown,,Unknown,2018-10-30,Larval,Larval,Brain,Nervous System
9332,ERR2862353,ERX2868591,ERS2866328,ERP111743,PRJEB29441,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E-MTAB-7349,Transcriptome Analysis,Oncogenic transformation of individual cell fates by developmental signaling cascades and transcription factors triggers diverse cancer types. Chordoma is a rare  aggressive tumor arising from transformed notochord remnants. Various potentially oncogenic factors have been found deregulated in chordoma and its metastases  yet clear causation remains uncertain. In particular  expression of the notochord controlling transcription factor Brachyury is hypothesized as key molecular driver in chordoma formation  yet an in vivo model to causally test its oncogenic potential in the notochord is missing. Here  we apply a zebrafish model of chordoma onset to identify the notochord transforming potential of tumor implicated candidate genes in vivo. We find that overexpression of human and zebrafish Brachyury  including a version with augmented transcriptional activity  is insufficient to initiate notochord hyperplasia in vivo. In contrast  the repeatedly chordoma implicated receptor tyrosine kinase RTK genes EGFR and KDR/VEGFR2 are sufficient to transform developmental notochord cells  akin to direct activation of Ras. Analysis of transcriptome and sub cellular organization from transformed notochords suggests that aberrant activation of RTK/Ras signaling attenuates processes required for the differentiation of notochord cells. Taken together  our results provide first in vivo indication for a lack of tumor initiating potential of Brachyury expression in the notochord  and suggest activated RTK signaling as potent hyperplasia initiating event in chordoma.,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 10 30,,Protocols: 8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,TUB,SAMEA5055151,UZH,ENA FIRST PUBLIC:2018 12 01T17:03:21Z|ENA LAST UPDATE:2018 10 30T13:30:13Z|External Id:SAMEA5055151|INSDC center name:UZH|INSDC first public:2018 12 01T17:03:21Z|INSDC last update:2018 10 30T13:30:13Z|INSDC status:public|Submitter Id:E MTAB 7349:TUB|age:8|broker name:ArrayExpress|common name:zebrafish|developmental stage:embryo|genotype:wild type genotype|individual:mixed pool of 30 to 50 embryos|organism part:notochord|sample name:E MTAB 7349:TUB|scientific name:Danio rerio|sex:mixed,,,,,,,,,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E MTAB 7349:TUB p,TUB p,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,Experimental Factor: genotype:wild type genotype,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,Illumina HiSeq 2500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>200</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_LABEL>F</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_LABEL>R</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>101</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,ERP111743,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 11 16,TCTCGCGC_AGGCTATA__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_2.fq.gz TCTCGCGC_AGGCTATA__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_1.fq.gz,fastq fastq,15345882200.0,76729411.0,E MTAB 7349:TCTCGCGC AGGCTATA  160520 I127 FCH732GBBXX L8 CDKPEI160513002 ,0:100 1:100,A:4257362303;C:3394893224;G:3451042837;T:4240872487;N:1711349,100,100,,,4257362303,3394893224,3451042837,4240872487,1711349,ERX2868591,ERS2866328,ERA1640550,European Nucleotide Archive,European Nucleotide Archive,2,0.86888,0.86735,0.45025,0.44476,0.72036,0.72529,0.56048,0.56274,100,100,B,B,biological fallback assumption,illumina,hiseq_era,unknown,random_priming,trueseq,bulk,unknown,unknown,,Unknown,2018-10-30,Larval,Larval,Brain,Nervous System
9333,ERR2862352,ERX2868590,ERS2866327,ERP111743,PRJEB29441,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E-MTAB-7349,Transcriptome Analysis,Oncogenic transformation of individual cell fates by developmental signaling cascades and transcription factors triggers diverse cancer types. Chordoma is a rare  aggressive tumor arising from transformed notochord remnants. Various potentially oncogenic factors have been found deregulated in chordoma and its metastases  yet clear causation remains uncertain. In particular  expression of the notochord controlling transcription factor Brachyury is hypothesized as key molecular driver in chordoma formation  yet an in vivo model to causally test its oncogenic potential in the notochord is missing. Here  we apply a zebrafish model of chordoma onset to identify the notochord transforming potential of tumor implicated candidate genes in vivo. We find that overexpression of human and zebrafish Brachyury  including a version with augmented transcriptional activity  is insufficient to initiate notochord hyperplasia in vivo. In contrast  the repeatedly chordoma implicated receptor tyrosine kinase RTK genes EGFR and KDR/VEGFR2 are sufficient to transform developmental notochord cells  akin to direct activation of Ras. Analysis of transcriptome and sub cellular organization from transformed notochords suggests that aberrant activation of RTK/Ras signaling attenuates processes required for the differentiation of notochord cells. Taken together  our results provide first in vivo indication for a lack of tumor initiating potential of Brachyury expression in the notochord  and suggest activated RTK signaling as potent hyperplasia initiating event in chordoma.,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 10 30,,Protocols: 8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,TUA,SAMEA5055150,UZH,ENA FIRST PUBLIC:2018 12 01T17:03:21Z|ENA LAST UPDATE:2018 10 30T13:30:13Z|External Id:SAMEA5055150|INSDC center name:UZH|INSDC first public:2018 12 01T17:03:21Z|INSDC last update:2018 10 30T13:30:13Z|INSDC status:public|Submitter Id:E MTAB 7349:TUA|age:8|broker name:ArrayExpress|common name:zebrafish|developmental stage:embryo|genotype:wild type genotype|individual:mixed pool of 30 to 50 embryos|organism part:notochord|sample name:E MTAB 7349:TUA|scientific name:Danio rerio|sex:mixed,,,,,,,,,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E MTAB 7349:TUA p,TUA p,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,Experimental Factor: genotype:wild type genotype,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,Illumina HiSeq 2500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>200</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_LABEL>F</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_LABEL>R</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>101</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,ERP111743,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 11 16,TCCGCGAA_AGGCTATA__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_1.fq.gz TCCGCGAA_AGGCTATA__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_2.fq.gz,fastq fastq,11985547000.0,59927735.0,E MTAB 7349:TCCGCGAA AGGCTATA  160520 I127 FCH732GBBXX L8 CDKPEI160513002 ,0:100 1:100,A:3239652711;C:2732996991;G:2737809176;T:3273773368;N:1314754,100,100,,,3239652711,2732996991,2737809176,3273773368,1314754,ERX2868590,ERS2866327,ERA1640550,European Nucleotide Archive,European Nucleotide Archive,2,0.91524,0.91585,0.32418,0.32053,0.72616,0.72671,0.59362,0.42478,100,100,B,B,biological fallback assumption,illumina,hiseq_era,unknown,random_priming,trueseq,bulk,unknown,unknown,,Unknown,2018-10-30,Larval,Larval,Brain,Nervous System
9334,ERR2862351,ERX2868589,ERS2866326,ERP111743,PRJEB29441,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E-MTAB-7349,Transcriptome Analysis,Oncogenic transformation of individual cell fates by developmental signaling cascades and transcription factors triggers diverse cancer types. Chordoma is a rare  aggressive tumor arising from transformed notochord remnants. Various potentially oncogenic factors have been found deregulated in chordoma and its metastases  yet clear causation remains uncertain. In particular  expression of the notochord controlling transcription factor Brachyury is hypothesized as key molecular driver in chordoma formation  yet an in vivo model to causally test its oncogenic potential in the notochord is missing. Here  we apply a zebrafish model of chordoma onset to identify the notochord transforming potential of tumor implicated candidate genes in vivo. We find that overexpression of human and zebrafish Brachyury  including a version with augmented transcriptional activity  is insufficient to initiate notochord hyperplasia in vivo. In contrast  the repeatedly chordoma implicated receptor tyrosine kinase RTK genes EGFR and KDR/VEGFR2 are sufficient to transform developmental notochord cells  akin to direct activation of Ras. Analysis of transcriptome and sub cellular organization from transformed notochords suggests that aberrant activation of RTK/Ras signaling attenuates processes required for the differentiation of notochord cells. Taken together  our results provide first in vivo indication for a lack of tumor initiating potential of Brachyury expression in the notochord  and suggest activated RTK signaling as potent hyperplasia initiating event in chordoma.,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 10 30,,Protocols: 8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,HRASC,SAMEA5055149,UZH,ENA FIRST PUBLIC:2018 12 01T17:03:21Z|ENA LAST UPDATE:2018 10 30T13:30:13Z|External Id:SAMEA5055149|INSDC center name:UZH|INSDC first public:2018 12 01T17:03:21Z|INSDC last update:2018 10 30T13:30:13Z|INSDC status:public|Submitter Id:E MTAB 7349:HRASC|age:8|broker name:ArrayExpress|common name:zebrafish|developmental stage:embryo|genotype:Tgtwhh:Gal4;TgUAS:EGFP HRASV12|individual:mixed pool of 30 to 50 embryos|organism part:notochord|sample name:E MTAB 7349:HRASC|scientific name:Danio rerio|sex:mixed,,,,,,,,,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E MTAB 7349:HRASC p,HRASC p,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,Experimental Factor: genotype:Tgtwhh:Gal4;TgUAS:EGFP HRASV12,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,Illumina HiSeq 2500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>200</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_LABEL>F</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_LABEL>R</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>101</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,ERP111743,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 11 16,CGGCTATG_GTCAGTAC__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_1.fq.gz CGGCTATG_GTCAGTAC__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_2.fq.gz,fastq fastq,11297151800.0,56485759.0,E MTAB 7349:CGGCTATG GTCAGTAC  160520 I127 FCH732GBBXX L8 CDKPEI160513002 ,0:100 1:100,A:3202944476;C:2429970659;G:2461948398;T:3201079699;N:1208568,100,100,,,3202944476,2429970659,2461948398,3201079699,1208568,ERX2868589,ERS2866326,ERA1640550,European Nucleotide Archive,European Nucleotide Archive,2,0.89842,0.86269,0.32455,0.30708,0.74245,0.75191,0.7454,0.74185,100,100,B,B,biological fallback assumption,illumina,hiseq_era,unknown,random_priming,trueseq,bulk,unknown,unknown,,Unknown,2018-10-30,Larval,Larval,Brain,Nervous System
9335,ERR2862350,ERX2868588,ERS2866325,ERP111743,PRJEB29441,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E-MTAB-7349,Transcriptome Analysis,Oncogenic transformation of individual cell fates by developmental signaling cascades and transcription factors triggers diverse cancer types. Chordoma is a rare  aggressive tumor arising from transformed notochord remnants. Various potentially oncogenic factors have been found deregulated in chordoma and its metastases  yet clear causation remains uncertain. In particular  expression of the notochord controlling transcription factor Brachyury is hypothesized as key molecular driver in chordoma formation  yet an in vivo model to causally test its oncogenic potential in the notochord is missing. Here  we apply a zebrafish model of chordoma onset to identify the notochord transforming potential of tumor implicated candidate genes in vivo. We find that overexpression of human and zebrafish Brachyury  including a version with augmented transcriptional activity  is insufficient to initiate notochord hyperplasia in vivo. In contrast  the repeatedly chordoma implicated receptor tyrosine kinase RTK genes EGFR and KDR/VEGFR2 are sufficient to transform developmental notochord cells  akin to direct activation of Ras. Analysis of transcriptome and sub cellular organization from transformed notochords suggests that aberrant activation of RTK/Ras signaling attenuates processes required for the differentiation of notochord cells. Taken together  our results provide first in vivo indication for a lack of tumor initiating potential of Brachyury expression in the notochord  and suggest activated RTK signaling as potent hyperplasia initiating event in chordoma.,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 10 30,,Protocols: 8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,HRASB 1A,SAMEA5055148,UZH,ENA FIRST PUBLIC:2018 12 01T17:03:21Z|ENA LAST UPDATE:2018 10 30T13:30:13Z|External Id:SAMEA5055148|INSDC center name:UZH|INSDC first public:2018 12 01T17:03:21Z|INSDC last update:2018 10 30T13:30:13Z|INSDC status:public|Submitter Id:E MTAB 7349:HRASB 1A|age:8|broker name:ArrayExpress|common name:zebrafish|developmental stage:embryo|genotype:Tgtwhh:Gal4;TgUAS:EGFP HRASV12|individual:mixed pool of 30 to 50 embryos|organism part:notochord|sample name:E MTAB 7349:HRASB 1A|scientific name:Danio rerio|sex:mixed,,,,,,,,,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E MTAB 7349:HRASB 1A p,HRASB 1A p,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,Experimental Factor: genotype:Tgtwhh:Gal4;TgUAS:EGFP HRASV12,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,Illumina HiSeq 2500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>200</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_LABEL>F</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_LABEL>R</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>101</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,ERP111743,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 11 16,TCTCGCGC_GTCAGTAC__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_1.fq.gz TCTCGCGC_GTCAGTAC__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_2.fq.gz,fastq fastq,13035635000.0,65178175.0,E MTAB 7349:TCTCGCGC GTCAGTAC  160520 I127 FCH732GBBXX L8 CDKPEI160513002 ,0:100 1:100,A:3518767071;C:2991842048;G:3005014068;T:3518541297;N:1470516,100,100,,,3518767071,2991842048,3005014068,3518541297,1470516,ERX2868588,ERS2866325,ERA1640550,European Nucleotide Archive,European Nucleotide Archive,2,0.89434,0.89384,0.28234,0.28093,0.7274,0.72813,0.6198,0.62424,100,100,B,B,biological fallback assumption,illumina,hiseq_era,unknown,random_priming,trueseq,bulk,unknown,unknown,,Unknown,2018-10-30,Larval,Larval,Brain,Nervous System
9336,ERR2862349,ERX2868587,ERS2866324,ERP111743,PRJEB29441,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E-MTAB-7349,Transcriptome Analysis,Oncogenic transformation of individual cell fates by developmental signaling cascades and transcription factors triggers diverse cancer types. Chordoma is a rare  aggressive tumor arising from transformed notochord remnants. Various potentially oncogenic factors have been found deregulated in chordoma and its metastases  yet clear causation remains uncertain. In particular  expression of the notochord controlling transcription factor Brachyury is hypothesized as key molecular driver in chordoma formation  yet an in vivo model to causally test its oncogenic potential in the notochord is missing. Here  we apply a zebrafish model of chordoma onset to identify the notochord transforming potential of tumor implicated candidate genes in vivo. We find that overexpression of human and zebrafish Brachyury  including a version with augmented transcriptional activity  is insufficient to initiate notochord hyperplasia in vivo. In contrast  the repeatedly chordoma implicated receptor tyrosine kinase RTK genes EGFR and KDR/VEGFR2 are sufficient to transform developmental notochord cells  akin to direct activation of Ras. Analysis of transcriptome and sub cellular organization from transformed notochords suggests that aberrant activation of RTK/Ras signaling attenuates processes required for the differentiation of notochord cells. Taken together  our results provide first in vivo indication for a lack of tumor initiating potential of Brachyury expression in the notochord  and suggest activated RTK signaling as potent hyperplasia initiating event in chordoma.,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 10 30,,Protocols: 8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,2A,SAMEA5055147,UZH,ENA FIRST PUBLIC:2018 12 01T17:03:21Z|ENA LAST UPDATE:2018 10 30T13:30:13Z|External Id:SAMEA5055147|INSDC center name:UZH|INSDC first public:2018 12 01T17:03:21Z|INSDC last update:2018 10 30T13:30:13Z|INSDC status:public|Submitter Id:E MTAB 7349:2A|age:8|broker name:ArrayExpress|common name:zebrafish|developmental stage:embryo|genotype:Tgtwhh:Gal4;TgUAS:EGFP HRASV12|individual:mixed pool of 30 to 50 embryos|organism part:notochord|sample name:E MTAB 7349:2A|scientific name:Danio rerio|sex:mixed,,,,,,,,,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,E MTAB 7349:2A p,2A p,Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,8 dpf wildtype and Tgtwhh:Gal4;TgUAS:EGFP HRASV12 were euthanized with 3% Tricaine methanesulfonate Sigma. Embryos were decapitated and incubated in Tripsin EDTA Sigma for 30 minutes to facilitate tissue dissociation. Notochords were then dissected using tungsten needles and immediately transferred to Trizol LS Ambion. We isolated 30 50 notochords per replicate  with a total of 3 replicates per condition 3x wildtype  3x HRASV12. Notochord RNA was extracted following the manufacturer's protocol using Trizol LS. RNA seq libraries were constructed using the Truseq stranded total RNA kit.,Experimental Factor: genotype:Tgtwhh:Gal4;TgUAS:EGFP HRASV12,RNA-Seq,TRANSCRIPTOMIC,RANDOM,PAIRED,ILLUMINA,Illumina HiSeq 2500,<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>200</SPOT_LENGTH><READ_SPEC><READ_INDEX>0</READ_INDEX><READ_LABEL>F</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Forward</READ_TYPE><BASE_COORD>1</BASE_COORD></READ_SPEC><READ_SPEC><READ_INDEX>1</READ_INDEX><READ_LABEL>R</READ_LABEL><READ_CLASS>Application Read</READ_CLASS><READ_TYPE>Reverse</READ_TYPE><BASE_COORD>101</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>,ERP111743,Illumina HiSeq 2500 paired end sequencing; Receptor Tyrosine Kinase pathway activation is sufficient to trigger chordoma in zebrafish,ENA FIRST PUBLIC:2018 12 01|ENA LAST UPDATE:2018 11 16,TCCGCGAA_GTCAGTAC__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_2.fq.gz TCCGCGAA_GTCAGTAC__160520_I127_FCH732GBBXX_L8_CDKPEI160513002_1.fq.gz,fastq fastq,11671772800.0,58358864.0,E MTAB 7349:TCCGCGAA GTCAGTAC  160520 I127 FCH732GBBXX L8 CDKPEI160513002 ,0:100 1:100,A:3164806186;C:2661342106;G:2677258036;T:3167072669;N:1293803,100,100,,,3164806186,2661342106,2677258036,3167072669,1293803,ERX2868587,ERS2866324,ERA1640550,European Nucleotide Archive,European Nucleotide Archive,2,0.89879,0.89878,0.28162,0.28061,0.73212,0.73452,0.59632,0.60115,100,100,B,B,biological fallback assumption,illumina,hiseq_era,unknown,random_priming,trueseq,bulk,unknown,unknown,,Unknown,2018-10-30,Larval,Larval,Brain,Nervous System
11047,ERR10476807,ERX9997150,ERS13672475,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day6,SAMEA111562619,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d6 1|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star pos d6 1|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:183 283033,Sample 0256 076 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_076_FR_NSP_TR1_SL1_S7_L001_R1_001-pooled.fastq.gz 0256_076_FR_NSP_TR1_SL1_S7_L001_R2_001-pooled.fastq.gz,fastq fastq,2974117224.0,29158012.0,ena RUN TAB 09 11 2022 11:52:59:183 283034,0:51 1:51,A:816102587;C:662715848;G:672777315;T:822487687;N:33787,51,51,,,816102587,662715848,672777315,822487687,33787,ERX9997150,ERS13672475,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11050,ERR10476814,ERX9997157,ERS13672482,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day13,SAMEA111562626,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d13 3|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star pos d13 3|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:186 283047,Sample 0256 083 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_083_FR_NSP_TR2_SL1_S14_L001_R1_001-pooled.fastq.gz 0256_083_FR_NSP_TR2_SL1_S14_L001_R2_001-pooled.fastq.gz,fastq fastq,5492667156.0,53849678.0,ena RUN TAB 09 11 2022 11:52:59:186 283048,0:51 1:51,A:1546610275;C:1178241230;G:1195797489;T:1571955787;N:62375,51,51,,,1546610275,1178241230,1195797489,1571955787,62375,ERX9997157,ERS13672482,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11051,ERR10476829,ERX9997172,ERS13672497,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day6,SAMEA111562641,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d6 3|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star neg d6 3|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:192 283077,Sample 0256 103 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_103_FR_NSP_TR1_SL1_S32_L001_R1_001-pooled.fastq.gz 0256_103_FR_NSP_TR1_SL1_S32_L001_R2_001-pooled.fastq.gz,fastq fastq,3120070248.0,30588924.0,ena RUN TAB 09 11 2022 11:52:59:193 283078,0:51 1:51,A:846274026;C:707353227;G:707836608;T:858570820;N:35567,51,51,,,846274026,707353227,707836608,858570820,35567,ERX9997172,ERS13672497,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11053,ERR10476796,ERX9997139,ERS13672464,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day13,SAMEA111562608,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d13 5|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:tu wt d13 5|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:178 283011,Sample 0256 010 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_010_FR_NSP_TR1_SL1_S21_L001_R1_001-pooled.fastq.gz 0256_010_FR_NSP_TR1_SL1_S21_L001_R2_001-pooled.fastq.gz,fastq fastq,2969687772.0,29114586.0,ena RUN TAB 09 11 2022 11:52:59:179 283012,0:51 1:51,A:762435544;C:713336460;G:731717998;T:762096042;N:101728,51,51,,,762435544,713336460,731717998,762096042,101728,ERX9997139,ERS13672464,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11055,ERR10476836,ERX9997179,ERS13672504,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day13,SAMEA111562648,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d13 5|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star neg d13 5|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:195 283091,Sample 0256 110 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_110_FR_NSP_TR2_SL1_S39_L001_R1_001-pooled.fastq.gz 0256_110_FR_NSP_TR2_SL1_S39_L001_R2_001-pooled.fastq.gz,fastq fastq,2758547160.0,27044580.0,ena RUN TAB 09 11 2022 11:52:59:196 283092,0:51 1:51,A:732517446;C:640766914;G:643632251;T:741598802;N:31747,51,51,,,732517446,640766914,643632251,741598802,31747,ERX9997179,ERS13672504,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11056,ERR10476808,ERX9997151,ERS13672476,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day6,SAMEA111562620,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d6 2|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star pos d6 2|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:184 283035,Sample 0256 077 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_077_FR_NSP_TR1_SL1_S8_L001_R1_001-pooled.fastq.gz 0256_077_FR_NSP_TR1_SL1_S8_L001_R2_001-pooled.fastq.gz,fastq fastq,3595088328.0,35245964.0,ena RUN TAB 09 11 2022 11:52:59:184 283036,0:51 1:51,A:985480827;C:803117311;G:811895458;T:994553698;N:41034,51,51,,,985480827,803117311,811895458,994553698,41034,ERX9997151,ERS13672476,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11058,ERR10476827,ERX9997170,ERS13672495,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day6,SAMEA111562639,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d6 1|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star neg d6 1|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:192 283073,Sample 0256 101 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_101_FR_NSP_TR1_SL1_S30_L001_R1_001-pooled.fastq.gz 0256_101_FR_NSP_TR1_SL1_S30_L001_R2_001-pooled.fastq.gz,fastq fastq,3504125952.0,34354176.0,ena RUN TAB 09 11 2022 11:52:59:192 283074,0:51 1:51,A:947138693;C:797358353;G:798903844;T:960685108;N:39954,51,51,,,947138693,797358353,798903844,960685108,39954,ERX9997170,ERS13672495,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11060,ERR10476794,ERX9997137,ERS13672462,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day13,SAMEA111562606,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d13 3|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:tu wt d13 3|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:178 283007,Sample 0256 008 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_008_FR_NSP_TR1_SL1_S1_L001_R1_001-pooled.fastq.gz 0256_008_FR_NSP_TR1_SL1_S1_L001_R2_001-pooled.fastq.gz,fastq fastq,2659023618.0,26068859.0,ena RUN TAB 09 11 2022 11:52:59:178 283008,0:51 1:51,A:670947753;C:637136773;G:677570266;T:673338670;N:30156,51,51,,,670947753,637136773,677570266,673338670,30156,ERX9997137,ERS13672462,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11061,ERR10476833,ERX9997176,ERS13672501,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day13,SAMEA111562645,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d13 2|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star neg d13 2|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:194 283085,Sample 0256 107 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_107_FR_NSP_TR2_SL1_S36_L001_R1_001-pooled.fastq.gz 0256_107_FR_NSP_TR2_SL1_S36_L001_R2_001-pooled.fastq.gz,fastq fastq,3282322362.0,32179631.0,ena RUN TAB 09 11 2022 11:52:59:194 283086,0:51 1:51,A:898607442;C:734331926;G:739939203;T:909406172;N:37619,51,51,,,898607442,734331926,739939203,909406172,37619,ERX9997176,ERS13672501,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11063,ERR10476828,ERX9997171,ERS13672496,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day6,SAMEA111562640,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d6 2|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star neg d6 2|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:192 283075,Sample 0256 102 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_102_FR_NSP_TR1_SL1_S31_L001_R1_001-pooled.fastq.gz 0256_102_FR_NSP_TR1_SL1_S31_L001_R2_001-pooled.fastq.gz,fastq fastq,3969901404.0,38920602.0,ena RUN TAB 09 11 2022 11:52:59:192 283076,0:51 1:51,A:1079447747;C:894502841;G:908706945;T:1087198510;N:45361,51,51,,,1079447747,894502841,908706945,1087198510,45361,ERX9997171,ERS13672496,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11068,ERR10476790,ERX9997133,ERS13672458,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day6,SAMEA111562602,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d6 4|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:tu wt d6 4|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:176 282999,Sample 0256 004 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_004_FR_NSP_TR1_SL1_S16_L001_R1_001-pooled.fastq.gz 0256_004_FR_NSP_TR1_SL1_S16_L001_R2_001-pooled.fastq.gz,fastq fastq,2693489520.0,26406760.0,ena RUN TAB 09 11 2022 11:52:59:176 283000,0:51 1:51,A:701762127;C:639663261;G:643729664;T:708242984;N:91484,51,51,,,701762127,639663261,643729664,708242984,91484,ERX9997133,ERS13672458,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11070,ERR10476791,ERX9997134,ERS13672459,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day6,SAMEA111562603,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d6 5|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:tu wt d6 5|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:176 283001,Sample 0256 005 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_005_FR_NSP_TR1_SL1_S17_L001_R1_001-pooled.fastq.gz 0256_005_FR_NSP_TR1_SL1_S17_L001_R2_001-pooled.fastq.gz,fastq fastq,2904430620.0,28474810.0,ena RUN TAB 09 11 2022 11:52:59:176 283002,0:51 1:51,A:777892611;C:666758312;G:672026589;T:787654140;N:98968,51,51,,,777892611,666758312,672026589,787654140,98968,ERX9997134,ERS13672459,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11074,ERR10476788,ERX9997131,ERS13672456,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day6,SAMEA111562600,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d6 2|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:tu wt d6 2|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:175 282995,Sample 0256 002 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_002_FR_NSP_TR1_SL1_S14_L001_R1_001-pooled.fastq.gz 0256_002_FR_NSP_TR1_SL1_S14_L001_R2_001-pooled.fastq.gz,fastq fastq,2385303456.0,23385328.0,ena RUN TAB 09 11 2022 11:52:59:175 282996,0:51 1:51,A:620601269;C:567608030;G:568555174;T:628457831;N:81152,51,51,,,620601269,567608030,568555174,628457831,81152,ERX9997131,ERS13672456,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11077,ERR10476816,ERX9997159,ERS13672484,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day13,SAMEA111562628,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d13 5|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star pos d13 5|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:187 283051,Sample 0256 085 FR NSP TRP SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_085_FR_NSP_TRP_SL1_S16_L001_R1_001-pooled.fastq.gz 0256_085_FR_NSP_TRP_SL1_S16_L001_R2_001-pooled.fastq.gz,fastq fastq,3264856596.0,32008398.0,ena RUN TAB 09 11 2022 11:52:59:187 283052,0:51 1:51,A:908889213;C:708892816;G:727180747;T:919857088;N:36732,51,51,,,908889213,708892816,727180747,919857088,36732,ERX9997159,ERS13672484,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11078,ERR10476813,ERX9997156,ERS13672481,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day13,SAMEA111562625,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d13 2|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star pos d13 2|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:186 283045,Sample 0256 082 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_082_FR_NSP_TR2_SL1_S13_L001_R1_001-pooled.fastq.gz 0256_082_FR_NSP_TR2_SL1_S13_L001_R2_001-pooled.fastq.gz,fastq fastq,3037654248.0,29780924.0,ena RUN TAB 09 11 2022 11:52:59:186 283046,0:51 1:51,A:859112641;C:645943863;G:660257800;T:872305592;N:34352,51,51,,,859112641,645943863,660257800,872305592,34352,ERX9997156,ERS13672481,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11079,ERR10476832,ERX9997175,ERS13672500,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day13,SAMEA111562644,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d13 1|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star neg d13 1|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:194 283083,Sample 0256 106 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_106_FR_NSP_TR1_SL1_S35_L001_R1_001-pooled.fastq.gz 0256_106_FR_NSP_TR1_SL1_S35_L001_R2_001-pooled.fastq.gz,fastq fastq,2761703040.0,27075520.0,ena RUN TAB 09 11 2022 11:52:59:194 283084,0:51 1:51,A:761065450;C:610246142;G:622228689;T:768131440;N:31319,51,51,,,761065450,610246142,622228689,768131440,31319,ERX9997175,ERS13672500,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11080,ERR10476810,ERX9997153,ERS13672478,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day6,SAMEA111562622,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d6 4|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star pos d6 4|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:184 283039,Sample 0256 079 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_079_FR_NSP_TR1_SL1_S10_L001_R1_001-pooled.fastq.gz 0256_079_FR_NSP_TR1_SL1_S10_L001_R2_001-pooled.fastq.gz,fastq fastq,2745379674.0,26915487.0,ena RUN TAB 09 11 2022 11:52:59:185 283040,0:51 1:51,A:762974242;C:602287296;G:611894421;T:768192503;N:31212,51,51,,,762974242,602287296,611894421,768192503,31212,ERX9997153,ERS13672478,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11081,ERR10476811,ERX9997154,ERS13672479,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day6,SAMEA111562623,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d6 5|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star pos d6 5|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:185 283041,Sample 0256 080 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_080_FR_NSP_TR1_SL1_S11_L001_R1_001-pooled.fastq.gz 0256_080_FR_NSP_TR1_SL1_S11_L001_R2_001-pooled.fastq.gz,fastq fastq,3212151870.0,31491685.0,ena RUN TAB 09 11 2022 11:52:59:185 283042,0:51 1:51,A:890500591;C:706313900;G:715518225;T:899782352;N:36802,51,51,,,890500591,706313900,715518225,899782352,36802,ERX9997154,ERS13672479,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11085,ERR10476809,ERX9997152,ERS13672477,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day6,SAMEA111562621,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d6 3|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star pos d6 3|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:184 283037,Sample 0256 078 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_078_FR_NSP_TR1_SL1_S9_L001_R1_001-pooled.fastq.gz 0256_078_FR_NSP_TR1_SL1_S9_L001_R2_001-pooled.fastq.gz,fastq fastq,3412655106.0,33457403.0,ena RUN TAB 09 11 2022 11:52:59:184 283038,0:51 1:51,A:942783320;C:753155142;G:767154692;T:949522969;N:38983,51,51,,,942783320,753155142,767154692,949522969,38983,ERX9997152,ERS13672477,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11086,ERR10476789,ERX9997132,ERS13672457,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day6,SAMEA111562601,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d6 3|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:tu wt d6 3|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:175 282997,Sample 0256 003 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_003_FR_NSP_TR1_SL1_S15_L001_R1_001-pooled.fastq.gz 0256_003_FR_NSP_TR1_SL1_S15_L001_R2_001-pooled.fastq.gz,fastq fastq,2999816634.0,29409967.0,ena RUN TAB 09 11 2022 11:52:59:176 282998,0:51 1:51,A:771170539;C:720448182;G:729961101;T:778133283;N:103529,51,51,,,771170539,720448182,729961101,778133283,103529,ERX9997132,ERS13672457,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11087,ERR10476830,ERX9997173,ERS13672498,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day6,SAMEA111562642,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d6 4|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star neg d6 4|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:193 283079,Sample 0256 104 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_104_FR_NSP_TR1_SL1_S33_L001_R1_001-pooled.fastq.gz 0256_104_FR_NSP_TR1_SL1_S33_L001_R2_001-pooled.fastq.gz,fastq fastq,2943756210.0,28860355.0,ena RUN TAB 09 11 2022 11:52:59:193 283080,0:51 1:51,A:806343784;C:657990854;G:663721905;T:815666113;N:33554,51,51,,,806343784,657990854,663721905,815666113,33554,ERX9997173,ERS13672498,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11088,ERR10476835,ERX9997178,ERS13672503,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day13,SAMEA111562647,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d13 4|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star neg d13 4|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:195 283089,Sample 0256 109 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_109_FR_NSP_TR2_SL1_S38_L001_R1_001-pooled.fastq.gz 0256_109_FR_NSP_TR2_SL1_S38_L001_R2_001-pooled.fastq.gz,fastq fastq,3406677396.0,33398798.0,ena RUN TAB 09 11 2022 11:52:59:195 283090,0:51 1:51,A:928579532;C:768636951;G:771636154;T:937786376;N:38383,51,51,,,928579532,768636951,771636154,937786376,38383,ERX9997178,ERS13672503,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11090,ERR10476787,ERX9997130,ERS13672455,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day6,SAMEA111562599,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d6 1|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:tu wt d6 1|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:174 282993,Sample 0256 001 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_001_FR_NSP_TR1_SL1_S13_L001_R1_001-pooled.fastq.gz 0256_001_FR_NSP_TR1_SL1_S13_L001_R2_001-pooled.fastq.gz,fastq fastq,2739613002.0,26858951.0,ena RUN TAB 09 11 2022 11:52:59:174 282994,0:51 1:51,A:716316048;C:647929778;G:649844718;T:725429229;N:93229,51,51,,,716316048,647929778,649844718,725429229,93229,ERX9997130,ERS13672455,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11091,ERR10476812,ERX9997155,ERS13672480,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day13,SAMEA111562624,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d13 1|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star pos d13 1|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:185 283043,Sample 0256 081 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_081_FR_NSP_TR2_SL1_S12_L001_R1_001-pooled.fastq.gz 0256_081_FR_NSP_TR2_SL1_S12_L001_R2_001-pooled.fastq.gz,fastq fastq,2976324300.0,29179650.0,ena RUN TAB 09 11 2022 11:52:59:185 283044,0:51 1:51,A:831817738;C:637392987;G:662609648;T:844470228;N:33699,51,51,,,831817738,637392987,662609648,844470228,33699,ERX9997155,ERS13672480,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11094,ERR10476831,ERX9997174,ERS13672499,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day6,SAMEA111562643,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d6 5|collection date:2019 12|common name:zebrafish|dev stage:6 dpf|geographic location country and/or sea:Germany|sample name:star neg d6 5|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:193 283081,Sample 0256 105 FR NSP TR1 SL2,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_105_FR_NSP_TR1_SL2_S34_L001_R1_001-pooled.fastq.gz 0256_105_FR_NSP_TR1_SL2_S34_L001_R2_001-pooled.fastq.gz,fastq fastq,3118607160.0,30574580.0,ena RUN TAB 09 11 2022 11:52:59:193 283082,0:51 1:51,A:849321742;C:701271960;G:711995793;T:855982293;N:35372,51,51,,,849321742,701271960,711995793,855982293,35372,ERX9997174,ERS13672499,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11095,ERR10476793,ERX9997136,ERS13672461,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day13,SAMEA111562605,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d13 2|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:tu wt d13 2|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:177 283005,Sample 0256 007 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_007_FR_NSP_TR1_SL1_S19_L001_R1_001-pooled.fastq.gz 0256_007_FR_NSP_TR1_SL1_S19_L001_R2_001-pooled.fastq.gz,fastq fastq,2806322430.0,27512965.0,ena RUN TAB 09 11 2022 11:52:59:177 283006,0:51 1:51,A:715863946;C:680964497;G:693755104;T:715642850;N:96033,51,51,,,715863946,680964497,693755104,715642850,96033,ERX9997136,ERS13672461,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11101,ERR10476795,ERX9997138,ERS13672463,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day13,SAMEA111562607,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d13 4|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:tu wt d13 4|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:178 283009,Sample 0256 009 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_009_FR_NSP_TR1_SL1_S20_L001_R1_001-pooled.fastq.gz 0256_009_FR_NSP_TR1_SL1_S20_L001_R2_001-pooled.fastq.gz,fastq fastq,2524225518.0,24747309.0,ena RUN TAB 09 11 2022 11:52:59:178 283010,0:51 1:51,A:643453173;C:607310608;G:630496995;T:642879275;N:85467,51,51,,,643453173,607310608,630496995,642879275,85467,ERX9997138,ERS13672463,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11102,ERR10476792,ERX9997135,ERS13672460,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,wildtype whole brain  pooled 15 brains,wildtype whole brain day13,SAMEA111562604,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:tu wt d13 1|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:tu wt d13 1|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:177 283003,Sample 0256 006 FR NSP TR1 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_006_FR_NSP_TR1_SL1_S18_L001_R1_001-pooled.fastq.gz 0256_006_FR_NSP_TR1_SL1_S18_L001_R2_001-pooled.fastq.gz,fastq fastq,2436931062.0,23891481.0,ena RUN TAB 09 11 2022 11:52:59:177 283004,0:51 1:51,A:622664838;C:583373590;G:613974641;T:616835192;N:82801,51,51,,,622664838,583373590,613974641,616835192,82801,ERX9997135,ERS13672460,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11104,ERR10476834,ERX9997177,ERS13672502,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC /  whole brain  pooled 15 brains,star:bPAC /  whole brain day13,SAMEA111562646,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star neg d13 3|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star neg d13 3|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:195 283087,Sample 0256 108 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_108_FR_NSP_TR2_SL1_S37_L001_R1_001-pooled.fastq.gz 0256_108_FR_NSP_TR2_SL1_S37_L001_R2_001-pooled.fastq.gz,fastq fastq,3252093438.0,31883269.0,ena RUN TAB 09 11 2022 11:52:59:195 283088,0:51 1:51,A:901696576;C:701023909;G:729587564;T:919748293;N:37096,51,51,,,901696576,701023909,729587564,919748293,37096,ERX9997177,ERS13672502,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
11105,ERR10476815,ERX9997158,ERS13672483,ERP138527,PRJEB53713,Time course whole brain transcriptome and methylome profiles of early life high GC exposed zebrafish,f79d57b2-1e93-4ca0-8fda-fd881a2a0c1e,Other,Whole brain transcriptome mRNA profiles of zebrafish which exposed to elavated glucocorticoid GC optogenetically at 6  13  120 dpf dpf  and post predatory stress looming dots stress at xxx dpf. All subjective adults at 120 dpf were female.  Tubingen strain was used as wildtype control and brains from transgenic line Tgstar:bPAC 2A tdTomatouoe300 +/  and  /  were sequenced on Illumina NovaSeq6000 by TRON gGmbH Mainz  Germany. Paired end TruSeq Stranded mRNA libraries Illumina  CA  USA were constructed  and over 20M of 50 bp reads/sample were sequenced.  Oxford Nanopore sequencing was used for DNA methylation identification.  These data were generated for the study by Choi et al. 2024. https://www.biorxiv.org/content/10.1101/2023.02.13.528363v4,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,,star:bPAC+/  whole brain  pooled 15 brains,star:bPAC+/  whole brain day13,SAMEA111562627,"Living Systems Institute, University of Exeter",INSDC center name:Living Systems Institute  University of Exeter|Submitter Id:star pos d13 4|collection date:2019 12|common name:zebrafish|dev stage:13 dpf|geographic location country and/or sea:Germany|sample name:star pos d13 4|scientific name:Danio rerio|sex:N/A|strain:Tübingen|tissue type:brain,,,,,,,,,Illumina NovaSeq 6000 paired end sequencing,ena EXPERIMENT TAB 09 11 2022 11:52:59:186 283049,Sample 0256 084 FR NSP TR2 SL1,1,,,RNA-Seq,TRANSCRIPTOMIC,Oligo-dT,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,ERP138527,Illumina NovaSeq 6000 paired end sequencing,ENA FIRST PUBLIC:2024 02 06|ENA LAST UPDATE:2024 02 06,0256_084_FR_NSP_TR2_SL1_S15_L001_R1_001-pooled.fastq.gz 0256_084_FR_NSP_TR2_SL1_S15_L001_R2_001-pooled.fastq.gz,fastq fastq,4118541720.0,40377860.0,ena RUN TAB 09 11 2022 11:52:59:187 283050,0:51 1:51,A:1136484689;C:909656648;G:924700451;T:1147653128;N:46804,51,51,,,1136484689,909656648,924700451,1147653128,46804,ERX9997158,ERS13672483,ERA18581410,"living systems institute, university of exeter|European Nucleotide Archive","living systems institute, university of exeter|European Nucleotide Archive",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,full_length,poly_a,trueseq,bulk,unknown,unknown,,United Kingdom,2024-02-06,Larval,Larval,Brain,Nervous System
26490,SRR26034374,SRX21751583,SRS18859090,SRP459779,PRJNA1015242,Gene expression data from zebrafish SHH medulloblastoma brains and normal brains.,GSE242897,Transcriptome Analysis,Zebrafish SHH MB tumors were generated by CRISPR Cas9 mediated mutation of ptch1 in the context of tp53 heterozygous and tp53 mutant animals. Gene expression of the entire brain for ptch1 crispant animals and tp53 mutant control animals was analyzed by RNA seq. Overall design: Whole brains were collected from 3 individual tp53 mutant control animals  3 individual tp53 mutant and ptch1 crispant animals  and 3 individual tp53 heterozygous and ptch1 crispant animals.,,pubmed:39078737,,19521X3 tp53mut tumor,GSM7774459,,source name:brain|tissue:brain|tumor status:tumor|age:4 wpf|genotype:tp53 mutant|geo loc name:missing|collection date:missing,19521X3 tp53mut tumor,The Illumina adapters were trimmed using cutadapt version 1.16. Fastq files were aligned to the genome using STAR version 2.7.9a Differentially expressed genes were found using DESeq2 version 1.32.0 and the hciR package on Github. Assembly: GRCz11 Supplementary files format and content: Tab delimited text file containing gene id  log2FC  padj  and raw counts.,brain,Brains were frozen at  80C in RNA stabilization solution QIAGEN.,Homogenization and total RNA isolation performed according to QIAGEN miRNeasy micro kit Qiagen 217084. Homogenization was performed with a 20 25.5 gauge needle 10 times. Samples were Dnase treated. Illumina TruSeq Stranded Total RNA Library Prep Ribo Zero Gold Illumina 20020598.,Zebrafish were maintained in the animal facility in accordance with the Utah Institutional Animal Care and Use Committee.,tissue:brain|tumor status:tumor|age:4 wpf|genotype:tp53 mutant,GSM7774459,GSM7774459: 19521X3 tp53mut tumor; Danio rerio; RNA Seq,GSM7774459 r1,GSM7774459,1,Homogenization and total RNA isolation performed according to QIAGEN miRNeasy micro kit Qiagen 217084. Homogenization was performed with a 20 25.5 gauge needle 10 times. Samples were Dnase treated. Illumina TruSeq Stranded Total RNA Library Prep Ribo Zero Gold Illumina 20020598.,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP459779,,loader:fastq load.py,19521X3_220211_A00421_0418_AHGVTMDSX3_S174_L003_R1_001.fastq.gz 19521X3_220211_A00421_0418_AHGVTMDSX3_S174_L003_R2_001.fastq.gz,fastq fastq,14792155696.0,48980648.0,GSM7774459 r1,0:151 1:151,A:4164614124;C:3233958816;G:3393302319;T:4000129008;N:151429,151,151,,,4164614124,3233958816,3393302319,4000129008,151429,SRX21751583,SRS18859090,SRA1710210,Huntsman Cancer Institute,"Oncological Sciences, University of Utah",2,0.89303,0.8944,0.32883,0.32864,0.68024,0.68091,0.48335,0.48739,151,151,B,B,biological fallback assumption,illumina,novaseq_era,unknown,rrna_depletion,trueseq,bulk,bulk,bulk,,United States,2023-09-11,Larval,Larval,Brain,Nervous System
30276,SRR27747452,SRX23412768,SRS20268089,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  phox2a /   replicate 4,GSM8038036,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  phox2a /   replicate 4,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / ,GSM8038036,GSM8038036: Hindbrain vestibular neurons  phox2a /   replicate 4; Danio rerio; RNA Seq,GSM8038036 r1,GSM8038036,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1209_phox2a_S31_L002_R1_001.fastq.gz 1209_phox2a_S31_L002_R2_001.fastq.gz,fastq fastq,4002287934.0,39238117.0,GSM8038036 r1,0:51 1:51,A:1128557040;C:810913651;G:820439585;T:1242297099;N:80559,51,51,,,1128557040,810913651,820439585,1242297099,80559,SRX23412768,SRS20268089,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,T,T,mates < 9% mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30277,SRR27747453,SRX23412767,SRS20268088,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  siblings  replicate 4,GSM8038035,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  siblings  replicate 4,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ ,GSM8038035,GSM8038035: Hindbrain vestibular neurons  siblings  replicate 4; Danio rerio; RNA Seq,GSM8038035 r1,GSM8038035,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1209_siblings_S32_L002_R1_001.fastq.gz 1209_siblings_S32_L002_R2_001.fastq.gz,fastq fastq,4533715686.0,44448193.0,GSM8038035 r1,0:51 1:51,A:1331986982;C:918253301;G:901739294;T:1381651915;N:84194,51,51,,,1331986982,918253301,901739294,1381651915,84194,SRX23412767,SRS20268088,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30278,SRR27747454,SRX23412766,SRS20268087,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  phox2a /   replicate 3,GSM8038034,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  phox2a /   replicate 3,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / ,GSM8038034,GSM8038034: Hindbrain vestibular neurons  phox2a /   replicate 3; Danio rerio; RNA Seq,GSM8038034 r1,GSM8038034,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1201_phox2a_S29_L002_R1_001.fastq.gz 1201_phox2a_S29_L002_R2_001.fastq.gz,fastq fastq,6231969582.0,61097741.0,GSM8038034 r1,0:51 1:51,A:1936318076;C:1131055224;G:1080268483;T:2084206449;N:121350,51,51,,,1936318076,1131055224,1080268483,2084206449,121350,SRX23412766,SRS20268087,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30279,SRR27747455,SRX23412765,SRS20268084,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  siblings  replicate 3,GSM8038033,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  siblings  replicate 3,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ ,GSM8038033,GSM8038033: Hindbrain vestibular neurons  siblings  replicate 3; Danio rerio; RNA Seq,GSM8038033 r1,GSM8038033,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1201_siblings_S30_L002_R1_001.fastq.gz 1201_siblings_S30_L002_R2_001.fastq.gz,fastq fastq,3665201598.0,35933349.0,GSM8038033 r1,0:51 1:51,A:1089767593;C:738549860;G:726974766;T:1109839399;N:69980,51,51,,,1089767593,738549860,726974766,1109839399,69980,SRX23412765,SRS20268084,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30280,SRR27747456,SRX23412764,SRS20268085,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  phox2a /   replicate 2,GSM8038032,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  phox2a /   replicate 2,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / ,GSM8038032,GSM8038032: Hindbrain vestibular neurons  phox2a /   replicate 2; Danio rerio; RNA Seq,GSM8038032 r1,GSM8038032,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1122_phox2a_S27_L002_R1_001.fastq.gz 1122_phox2a_S27_L002_R2_001.fastq.gz,fastq fastq,3449800956.0,33821578.0,GSM8038032 r1,0:51 1:51,A:1024161989;C:698197523;G:689509862;T:1037871222;N:60360,51,51,,,1024161989,698197523,689509862,1037871222,60360,SRX23412764,SRS20268085,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30281,SRR27747457,SRX23412763,SRS20268086,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  siblings  replicate 2,GSM8038031,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  siblings  replicate 2,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ ,GSM8038031,GSM8038031: Hindbrain vestibular neurons  siblings  replicate 2; Danio rerio; RNA Seq,GSM8038031 r1,GSM8038031,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1122_siblings_S28_L002_R1_001.fastq.gz 1122_siblings_S28_L002_R2_001.fastq.gz,fastq fastq,3326329752.0,32611076.0,GSM8038031 r1,0:51 1:51,A:939623583;C:720094628;G:722500041;T:944060444;N:51056,51,51,,,939623583,720094628,722500041,944060444,51056,SRX23412763,SRS20268086,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30282,SRR27747458,SRX23412762,SRS20268083,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  phox2a /   replicate 1,GSM8038030,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  phox2a /   replicate 1,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a / ,GSM8038030,GSM8038030: Hindbrain vestibular neurons  phox2a /   replicate 1; Danio rerio; RNA Seq,GSM8038030 r1,GSM8038030,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1019_phox2a_S25_L002_R1_001.fastq.gz 1019_phox2a_S25_L002_R2_001.fastq.gz,fastq fastq,3186783246.0,31242973.0,GSM8038030 r1,0:51 1:51,A:955687278;C:636490356;G:630374686;T:964170971;N:59955,51,51,,,955687278,636490356,630374686,964170971,59955,SRX23412762,SRS20268083,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
30283,SRR27747459,SRX23412761,SRS20268082,SRP486175,PRJNA1069777,Effect of phox2a knockout on the molecular profiles of hindbrain vestibular neurons in the larval zebrafish bulk RNA Seq,GSE254345,Transcriptome Analysis,Sensorimotor reflex circuits engage distinct neuronal subtypes  defined by precise connectivity  to transform sensation into compensatory behavior. Whether and how motor partner populations shape the subtype fate and connectivity of their pre motor counterparts remains controversial. Here  we discovered that motor partners are dispensable for proper connectivity across an entire vestibular reflex circuit that stabilizes gaze. We first measured activity following vestibular sensation in pre motor projection neurons post constitutive loss of their extraocular motor neuron partners.We observed normal responses and topography consistent with unchanged functional connectivity between sensory neurons and projection neurons. Next  we show that projection neurons remain anatomically and molecularly poised to connect appropriately with their motor partners. Lastly  we show that the transcriptional signatures of projection neuron subtypes develop independently of motor partners. Our findings comprehensively overturn a long standing model: that connectivity in the circuit for gaze stabilization is retrogradely determined by motor partner derived signals. By defining the contribution of motor neurons to canonical sensorimotor circuit assembly  our work speaks to comparable processes in spinal circuits and advances our understanding of general principles of neural development. Overall design: Hindbrain vestibular neurons  labeled by Tg 6.7Tru.Hcrtr2:GAL4 VP16;TgUAS:E1b Kaede  harvested from zebrafish embryos between 72 hpf 74 hpf. Embyros were from two conditions: larvae from a stable line of phox2a /  mutants  and sibling controls phox2a+/+ or +/ . Fluorescent neurons were isolated by fluorescence activated cell sorting FACS according to Kaede fluorescence. Four experimental repeats were performed  each generating two samples phox2a /  and sibling control. Bulk RNA sequencing was performed.,,,,Hindbrain vestibular neurons  siblings  replicate 1,GSM8038029,,tissue:Hindbrain vestibular neurons|time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ |geo loc name:missing|collection date:missing,Hindbrain vestibular neurons  siblings  replicate 1,DESeq2 Assembly: GRCz11 Supplementary files format and content: excel file includes raw counts for each sample Supplementary files format and content: excel file includes normalized counts for each sample,Hindbrain vestibular neurons,,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,time:72 hpf 74 hpf type:Hindbrain vestibular neurons|genotype:Tg 6.7Tru.Hcrtr2:GAL4 VP16; TgUAS:E1b Kaede; Tgisl1:GFP; phox2a+/+ or +/ ,GSM8038029,GSM8038029: Hindbrain vestibular neurons  siblings  replicate 1; Danio rerio; RNA Seq,GSM8038029 r1,GSM8038029,1,RNA was isolated using an RNAqueous Total RNA Isolation Kit. RNA quality and concentration was assessed using an RNA 6000 Pico Kit and a 2100 BioAnalyzer system. Libraries for bulk RNA sequencing were prepared using the low input Clontech SMART Seq HT with Nxt HT kit Takara,,RNA-Seq,TRANSCRIPTOMIC,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP486175,,loader:fastq load.py,1019_siblings_S26_L002_R1_001.fastq.gz 1019_siblings_S26_L002_R2_001.fastq.gz,fastq fastq,3481817226.0,34135463.0,GSM8038029 r1,0:51 1:51,A:1015152374;C:724318215;G:717469149;T:1024812342;N:65146,51,51,,,1015152374,724318215,717469149,1024812342,65146,SRX23412761,SRS20268082,SRA1792521,"Neuroscience Institute, New York University Grossman School of Medicine","Neuroscience Institute, New York University Grossman School of Medicine",,,,,,,,,,,,B,B,biological fallback assumption,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_plate,smartseq,,United States,2024-01-26,Larval,Larval,Brain,Nervous System
32373,SRR29181693,SRX24701872,SRS21429401,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb4 linB2.2 14.124.2  brain4  SABER Seq,GSM8290063,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb4 linB2.2 14.124.2  brain4  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290063,GSM8290063: SABERb4 linB2.2 14.124.2  brain4  SABER Seq; Danio rerio; RNA Seq,GSM8290063 r1,GSM8290063,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb4_linB2.2-14.124.2_S2_L002_I1_001.fastq.gz SABERb4_linB2.2-14.124.2_S2_L002_I2_001.fastq.gz SABERb4_linB2.2-14.124.2_S2_L002_R1_001.fastq.gz SABERb4_linB2.2-14.124.2_S2_L002_R2_001.fastq.gz,fastq fastq fastq fastq,28009093188.0,140749212.0,GSM8290063 r1,0:10 1:10 2:28 3:151,A:5808319224;C:5111068156;G:5728880143;T:4604800178;N:63311,10,10,28,151,5808319224,5111068156,5728880143,4604800178,63311,SRX24701872,SRS21429401,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.03458,,0.03418,,0.99959,,0.4035,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32374,SRR29181692,SRX24701871,SRS21429400,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb4 linB2.1 13.123.2  brain4  SABER Seq,GSM8290062,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb4 linB2.1 13.123.2  brain4  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290062,GSM8290062: SABERb4 linB2.1 13.123.2  brain4  SABER Seq; Danio rerio; RNA Seq,GSM8290062 r1,GSM8290062,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb4_linB2.1-13.123.2_S1_L002_R2_001.fastq.gz SABERb4_linB2.1-13.123.2_S1_L002_R1_001.fastq.gz SABERb4_linB2.1-13.123.2_S1_L002_I2_001.fastq.gz SABERb4_linB2.1-13.123.2_S1_L002_I1_001.fastq.gz,fastq fastq fastq fastq,22391839991.0,112521809.0,GSM8290062 r1,0:10 1:10 2:28 3:151,A:4658062266;C:4632110229;G:4512962055;T:3187608704;N:49905,10,10,28,151,4658062266,4632110229,4512962055,3187608704,49905,SRX24701871,SRS21429400,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.00192,,0.00168,,0.99951,,0.67647,,151,,T,,under 1.2% mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32375,SRR29181679,SRX24701870,SRS21429399,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb4 brainB2 2  brain4  transcriptome,GSM8290056,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb4 brainB2 2  brain4  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290056,GSM8290056: SABERb4 brainB2 2  brain4  transcriptome; Danio rerio; RNA Seq,GSM8290056 r1,GSM8290056,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb4_brainB2_2_S4_L001_R2_001.fastq.gz SABERb4_brainB2_2_S4_L001_R1_001.fastq.gz SABERb4_brainB2_2_S4_L001_I2_001.fastq.gz SABERb4_brainB2_2_S4_L001_I1_001.fastq.gz,fastq fastq fastq fastq,22587540571.0,113505229.0,GSM8290056 r1,0:10 1:10 2:28 3:151,A:5299086616;C:3418923384;G:3717477937;T:4703769200;N:32442,10,10,28,151,5299086616,3418923384,3717477937,4703769200,32442,SRX24701870,SRS21429399,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.88382,,0.22459,,0.76524,,0.54792,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32376,SRR29181684,SRX24701869,SRS21429398,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb4 brainB2 1  brain4  transcriptome,GSM8290055,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb4 brainB2 1  brain4  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290055,GSM8290055: SABERb4 brainB2 1  brain4  transcriptome; Danio rerio; RNA Seq,GSM8290055 r1,GSM8290055,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb4_brainB2_1_S3_L001_I1_001.fastq.gz SABERb4_brainB2_1_S3_L001_I2_001.fastq.gz SABERb4_brainB2_1_S3_L001_R1_001.fastq.gz SABERb4_brainB2_1_S3_L001_R2_001.fastq.gz,fastq fastq fastq fastq,20888284944.0,104966256.0,GSM8290055 r1,0:10 1:10 2:28 3:151,A:4874988462;C:3170609788;G:3451838907;T:4352436953;N:30546,10,10,28,151,4874988462,3170609788,3451838907,4352436953,30546,SRX24701869,SRS21429398,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.88685,,0.21914,,0.76171,,0.54873,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32377,SRR29181683,SRX24701868,SRS21429397,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb3 brainB1 2  brain3  transcriptome,GSM8290054,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb3 brainB1 2  brain3  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290054,GSM8290054: SABERb3 brainB1 2  brain3  transcriptome; Danio rerio; RNA Seq,GSM8290054 r1,GSM8290054,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb3_brainB1_2_S2_L001_I1_001.fastq.gz SABERb3_brainB1_2_S2_L001_I2_001.fastq.gz SABERb3_brainB1_2_S2_L001_R1_001.fastq.gz SABERb3_brainB1_2_S2_L001_R2_001.fastq.gz,fastq fastq fastq fastq,20587460226.0,103454574.0,GSM8290054 r1,0:10 1:10 2:28 3:151,A:4824812347;C:3103279976;G:3383117839;T:4310400919;N:29593,10,10,28,151,4824812347,3103279976,3383117839,4310400919,29593,SRX24701868,SRS21429397,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.87976,,0.21404,,0.77433,,0.52975,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32378,SRR29181682,SRX24701867,SRS21429396,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb3 brainB1 1  brain3  transcriptome,GSM8290053,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb3 brainB1 1  brain3  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290053,GSM8290053: SABERb3 brainB1 1  brain3  transcriptome; Danio rerio; RNA Seq,GSM8290053 r1,GSM8290053,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb3_brainB1_1_S1_L001_I1_001.fastq.gz SABERb3_brainB1_1_S1_L001_I2_001.fastq.gz SABERb3_brainB1_1_S1_L001_R1_001.fastq.gz SABERb3_brainB1_1_S1_L001_R2_001.fastq.gz,fastq fastq fastq fastq,23045577279.0,115806921.0,GSM8290053 r1,0:10 1:10 2:28 3:151,A:5424649891;C:3461670114;G:3767563304;T:4832928748;N:33014,10,10,28,151,5424649891,3461670114,3767563304,4832928748,33014,SRX24701867,SRS21429396,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.87779,,0.21879,,0.76934,,0.52923,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32379,SRR29181681,SRX24701866,SRS21429395,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD3091523wk3  Novogene Run1  brain2  transcriptome,GSM8290052,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD3091523wk3  Novogene Run1  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290052,GSM8290052: SABERb2 brainD3091523wk3  Novogene Run1  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290052 r1,GSM8290052,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD3091523wk3_CKDL230038569-1A_HHVLTDSX7_S6_L002_I1_001.fastq.gz SABERb2_brainD3091523wk3_CKDL230038569-1A_HHVLTDSX7_S6_L002_I2_001.fastq.gz SABERb2_brainD3091523wk3_CKDL230038569-1A_HHVLTDSX7_S6_L002_R1_001.fastq.gz SABERb2_brainD3091523wk3_CKDL230038569-1A_HHVLTDSX7_S6_L002_R2_001.fastq.gz,fastq fastq fastq fastq,14986744960.0,46833578.0,GSM8290052 r1,0:10 1:10 2:150 3:150,A:4103966301;C:2123224314;G:2431703551;T:5390322981;N:856253,10,10,150,150,4103966301,2123224314,2431703551,5390322981,856253,SRX24701866,SRS21429395,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.31404,0.88682,0.119,0.21308,0.96812,0.76295,0.52318,0.54494,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32380,SRR29181680,SRX24701865,SRS21429394,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD2091523wk3  Novogene Run1  brain2  transcriptome,GSM8290051,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD2091523wk3  Novogene Run1  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290051,GSM8290051: SABERb2 brainD2091523wk3  Novogene Run1  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290051 r1,GSM8290051,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD2091523wk3_CKDL230038569-1A_HHVLTDSX7_S1_L002_I1_001.fastq.gz SABERb2_brainD2091523wk3_CKDL230038569-1A_HHVLTDSX7_S1_L002_I2_001.fastq.gz SABERb2_brainD2091523wk3_CKDL230038569-1A_HHVLTDSX7_S1_L002_R1_001.fastq.gz SABERb2_brainD2091523wk3_CKDL230038569-1A_HHVLTDSX7_S1_L002_R2_001.fastq.gz,fastq fastq fastq fastq,13432883520.0,41977761.0,GSM8290051 r1,0:10 1:10 2:150 3:150,A:3699233635;C:1894101532;G:2175321862;T:4823892315;N:778956,10,10,150,150,3699233635,1894101532,2175321862,4823892315,778956,SRX24701865,SRS21429394,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.32482,0.8828,0.12828,0.21873,0.96668,0.76534,0.51473,0.5505,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32381,SRR29181685,SRX24701864,SRS21429393,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD1091523wk3  Novogene Run1  brain2  transcriptome,GSM8290050,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD1091523wk3  Novogene Run1  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290050,GSM8290050: SABERb2 brainD1091523wk3  Novogene Run1  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290050 r1,GSM8290050,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD1091523wk3_CKDL230038569-1A_HHVLTDSX7_S2_L002_I1_001.fastq.gz SABERb2_brainD1091523wk3_CKDL230038569-1A_HHVLTDSX7_S2_L002_I2_001.fastq.gz SABERb2_brainD1091523wk3_CKDL230038569-1A_HHVLTDSX7_S2_L002_R1_001.fastq.gz SABERb2_brainD1091523wk3_CKDL230038569-1A_HHVLTDSX7_S2_L002_R2_001.fastq.gz,fastq fastq fastq fastq,17465671680.0,54580224.0,GSM8290050 r1,0:10 1:10 2:150 3:150,A:4799554780;C:2476125093;G:2831285237;T:6266103981;N:998109,10,10,150,150,4799554780,2476125093,2831285237,6266103981,998109,SRX24701864,SRS21429393,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.32322,0.88514,0.12316,0.2147,0.96644,0.76378,0.54067,0.54053,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32382,SRR29181686,SRX24701863,SRS21429392,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD3  Medgenome Run2  brain2  transcriptome,GSM8290049,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD3  Medgenome Run2  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290049,GSM8290049: SABERb2 brainD3  Medgenome Run2  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290049 r1,GSM8290049,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD3_S5_L002_I1_001.fastq.gz SABERb2_brainD3_S5_L002_I2_001.fastq.gz SABERb2_brainD3_S5_L002_R1_001.fastq.gz SABERb2_brainD3_S5_L002_R2_001.fastq.gz,fastq fastq fastq fastq,3868768652.0,27832868.0,GSM8290049 r1,0:10 1:10 2:28 3:91,A:764050790;C:511319919;G:550304072;T:707108210;N:7997,10,10,28,91,764050790,511319919,550304072,707108210,7997,SRX24701863,SRS21429392,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91168,,0.2331,,0.75933,,0.55432,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32383,SRR29181687,SRX24701863,SRS21429392,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD3  Medgenome Run2  brain2  transcriptome,GSM8290049,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD3  Medgenome Run2  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290049,GSM8290049: SABERb2 brainD3  Medgenome Run2  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290049 r1,GSM8290049,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD3_S10_L002_I1_001.fastq.gz SABERb2_brainD3_S10_L002_I2_001.fastq.gz SABERb2_brainD3_S10_L002_R1_001.fastq.gz SABERb2_brainD3_S10_L002_R2_001.fastq.gz,fastq fastq fastq fastq,13116158150.0,94360850.0,GSM8290049 r2,0:10 1:10 2:28 3:91,A:2577084188;C:1740165795;G:1880702045;T:2388863291;N:22031,10,10,28,91,2577084188,1740165795,1880702045,2388863291,22031,SRX24701863,SRS21429392,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91186,,0.23328,,0.76088,,0.55129,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32384,SRR29181688,SRX24701862,SRS21429391,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD2  Medgenome Run2  brain2  transcriptome,GSM8290048,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD2  Medgenome Run2  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290048,GSM8290048: SABERb2 brainD2  Medgenome Run2  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290048 r1,GSM8290048,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD2_S9_L002_I1_001.fastq.gz SABERb2_brainD2_S9_L002_I2_001.fastq.gz SABERb2_brainD2_S9_L002_R1_001.fastq.gz SABERb2_brainD2_S9_L002_R2_001.fastq.gz,fastq fastq fastq fastq,11592953894.0,83402546.0,GSM8290048 r2,0:10 1:10 2:28 3:91,A:2297377264;C:1526045472;G:1656319764;T:2109869221;N:19965,10,10,28,91,2297377264,1526045472,1656319764,2109869221,19965,SRX24701862,SRS21429391,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.90894,,0.24209,,0.76106,,0.55154,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32385,SRR29181700,SRX24701862,SRS21429391,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD2  Medgenome Run2  brain2  transcriptome,GSM8290048,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD2  Medgenome Run2  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290048,GSM8290048: SABERb2 brainD2  Medgenome Run2  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290048 r1,GSM8290048,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD2_S4_L002_R2_001.fastq.gz SABERb2_brainD2_S4_L002_R1_001.fastq.gz SABERb2_brainD2_S4_L002_I2_001.fastq.gz SABERb2_brainD2_S4_L002_I1_001.fastq.gz,fastq fastq fastq fastq,3703512386.0,26643974.0,GSM8290048 r1,0:10 1:10 2:28 3:91,A:738064510;C:484883852;G:525588346;T:676057082;N:7844,10,10,28,91,738064510,484883852,525588346,676057082,7844,SRX24701862,SRS21429391,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.90684,,0.24166,,0.75982,,0.55283,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32386,SRR29181698,SRX24701861,SRS21429390,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD1  Medgenome Run2  brain2  transcriptome,GSM8290047,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD1  Medgenome Run2  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290047,GSM8290047: SABERb2 brainD1  Medgenome Run2  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290047 r1,GSM8290047,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD1_S3_L002_R2_001.fastq.gz SABERb2_brainD1_S3_L002_R1_001.fastq.gz SABERb2_brainD1_S3_L002_I2_001.fastq.gz SABERb2_brainD1_S3_L002_I1_001.fastq.gz,fastq fastq fastq fastq,4228010816.0,30417344.0,GSM8290047 r1,0:10 1:10 2:28 3:91,A:837646182;C:556752228;G:601753997;T:771817125;N:8772,10,10,28,91,837646182,556752228,601753997,771817125,8772,SRX24701861,SRS21429390,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.90883,,0.23676,,0.75885,,0.54147,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32387,SRR29181699,SRX24701861,SRS21429390,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 brainD1  Medgenome Run2  brain2  transcriptome,GSM8290047,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 brainD1  Medgenome Run2  brain2  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290047,GSM8290047: SABERb2 brainD1  Medgenome Run2  brain2  transcriptome; Danio rerio; RNA Seq,GSM8290047 r1,GSM8290047,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_brainD1_S8_L002_R2_001.fastq.gz SABERb2_brainD1_S8_L002_R1_001.fastq.gz SABERb2_brainD1_S8_L002_I2_001.fastq.gz SABERb2_brainD1_S8_L002_I1_001.fastq.gz,fastq fastq fastq fastq,13317155486.0,95806874.0,GSM8290047 r2,0:10 1:10 2:28 3:91,A:2627361333;C:1762774581;G:1907012086;T:2421255352;N:22182,10,10,28,91,2627361333,1762774581,1907012086,2421255352,22182,SRX24701861,SRS21429390,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91093,,0.23629,,0.75913,,0.55525,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32388,SRR29181697,SRX24701860,SRS21429389,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 brainC2091523wk3  Novogene Run1  brain1  transcriptome,GSM8290046,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 brainC2091523wk3  Novogene Run1  brain1  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290046,GSM8290046: SABERb1 brainC2091523wk3  Novogene Run1  brain1  transcriptome; Danio rerio; RNA Seq,GSM8290046 r1,GSM8290046,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_brainC2091523wk3_CKDL230038568-1A_HHVLTDSX7_S1_L003_I1_001.fastq.gz SABERb1_brainC2091523wk3_CKDL230038568-1A_HHVLTDSX7_S1_L003_I2_001.fastq.gz SABERb1_brainC2091523wk3_CKDL230038568-1A_HHVLTDSX7_S1_L003_R1_001.fastq.gz SABERb1_brainC2091523wk3_CKDL230038568-1A_HHVLTDSX7_S1_L003_R2_001.fastq.gz,fastq fastq fastq fastq,11765562880.0,36767384.0,GSM8290046 r1,0:10 1:10 2:150 3:150,A:3147712431;C:1679368969;G:1942592895;T:4259959905;N:581000,10,10,150,150,3147712431,1679368969,1942592895,4259959905,581000,SRX24701860,SRS21429389,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.30773,0.88409,0.11212,0.21315,0.968,0.77344,0.54045,0.54846,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32389,SRR29181691,SRX24701859,SRS21429388,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 linD3  brain2  SABER Seq,GSM8290061,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 linD3  brain2  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290061,GSM8290061: SABERb2 linD3  brain2  SABER Seq; Danio rerio; RNA Seq,GSM8290061 r1,GSM8290061,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_linD3_S3_L001_I1_001.fastq.gz SABERb2_linD3_S3_L001_I2_001.fastq.gz SABERb2_linD3_S3_L001_R1_001.fastq.gz SABERb2_linD3_S3_L001_R2_001.fastq.gz,fastq fastq fastq fastq,6191572570.0,31113430.0,GSM8290061 r1,0:10 1:10 2:28 3:151,A:1332572499;C:1250769086;G:1304188511;T:810567656;N:30178,10,10,28,151,1332572499,1250769086,1304188511,810567656,30178,SRX24701859,SRS21429388,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.00992,,0.00222,,0.98762,,0.5329,,151,,T,,under 1.2% mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32390,SRR29181690,SRX24701858,SRS21429387,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 linD2  brain2  SABER Seq,GSM8290060,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 linD2  brain2  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290060,GSM8290060: SABERb2 linD2  brain2  SABER Seq; Danio rerio; RNA Seq,GSM8290060 r1,GSM8290060,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_linD2_S2_L001_I1_001.fastq.gz SABERb2_linD2_S2_L001_I2_001.fastq.gz SABERb2_linD2_S2_L001_R1_001.fastq.gz SABERb2_linD2_S2_L001_R2_001.fastq.gz,fastq fastq fastq fastq,4643470776.0,23334024.0,GSM8290060 r1,0:10 1:10 2:28 3:151,A:780662288;C:1082797960;G:929037112;T:730916888;N:23376,10,10,28,151,780662288,1082797960,929037112,730916888,23376,SRX24701858,SRS21429387,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.01556,,0.00414,,0.98571,,0.48742,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32391,SRR29181689,SRX24701857,SRS21429386,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb2 linD1  brain2  SABER Seq,GSM8290059,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb2 linD1  brain2  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290059,GSM8290059: SABERb2 linD1  brain2  SABER Seq; Danio rerio; RNA Seq,GSM8290059 r1,GSM8290059,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb2_linD1_S1_L001_I1_001.fastq.gz SABERb2_linD1_S1_L001_I2_001.fastq.gz SABERb2_linD1_S1_L001_R1_001.fastq.gz SABERb2_linD1_S1_L001_R2_001.fastq.gz,fastq fastq fastq fastq,1567865877.0,7878723.0,GSM8290059 r1,0:10 1:10 2:28 3:151,A:285711189;C:311873916;G:350305565;T:241788400;N:8103,10,10,28,151,285711189,311873916,350305565,241788400,8103,SRX24701857,SRS21429386,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.04511,,0.013,,0.96644,,0.48124,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32392,SRR29181694,SRX24701856,SRS21429385,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 linC2  brain1  SABER Seq,GSM8290058,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 linC2  brain1  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290058,GSM8290058: SABERb1 linC2  brain1  SABER Seq; Danio rerio; RNA Seq,GSM8290058 r1,GSM8290058,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_linC2_S5_L001_I1_001.fastq.gz SABERb1_linC2_S5_L001_I2_001.fastq.gz SABERb1_linC2_S5_L001_R1_001.fastq.gz SABERb1_linC2_S5_L001_R2_001.fastq.gz,fastq fastq fastq fastq,5550858638.0,27893762.0,GSM8290058 r1,0:10 1:10 2:28 3:151,A:1146922069;C:1156473192;G:1103601022;T:804934064;N:27715,10,10,28,151,1146922069,1156473192,1103601022,804934064,27715,SRX24701856,SRS21429385,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.01311,,0.00298,,0.98762,,0.53959,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32393,SRR29181695,SRX24701855,SRS21429384,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 linC1  brain1  SABER Seq,GSM8290057,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 linC1  brain1  SABER Seq,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. Assembly: GRCz11 Supplementary files format and content: *.h5 files contain fileted features/genes and barcode data generated from cell ranger pipeline. Supplementary files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. Supplementary files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290057,GSM8290057: SABERb1 linC1  brain1  SABER Seq; Danio rerio; RNA Seq,GSM8290057 r1,GSM8290057,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using HiSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_linC1_S4_L001_I1_001.fastq.gz SABERb1_linC1_S4_L001_I2_001.fastq.gz SABERb1_linC1_S4_L001_R1_001.fastq.gz SABERb1_linC1_S4_L001_R2_001.fastq.gz,fastq fastq fastq fastq,6470197047.0,32513553.0,GSM8290057 r1,0:10 1:10 2:28 3:151,A:1299285410;C:1322983894;G:1431353449;T:855891198;N:32552,10,10,28,151,1299285410,1322983894,1431353449,855891198,32552,SRX24701855,SRS21429384,SRA1878107,University of Pennsylvania,University of Pennsylvania,1,0.01874,,0.00435,,0.98334,,0.48429,,151,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32394,SRR29181696,SRX24701854,SRS21429383,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 brainC1091523wk3  Novogene Run1  brain1  transcriptome,GSM8290045,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 brainC1091523wk3  Novogene Run1  brain1  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290045,GSM8290045: SABERb1 brainC1091523wk3  Novogene Run1  brain1  transcriptome; Danio rerio; RNA Seq,GSM8290045 r1,GSM8290045,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_brainC1091523wk3_CKDL230038568-1A_HHVLTDSX7_S3_L003_I1_001.fastq.gz SABERb1_brainC1091523wk3_CKDL230038568-1A_HHVLTDSX7_S3_L003_I2_001.fastq.gz SABERb1_brainC1091523wk3_CKDL230038568-1A_HHVLTDSX7_S3_L003_R1_001.fastq.gz SABERb1_brainC1091523wk3_CKDL230038568-1A_HHVLTDSX7_S3_L003_R2_001.fastq.gz,fastq fastq fastq fastq,13715941760.0,42862318.0,GSM8290045 r1,0:10 1:10 2:150 3:150,A:3643210069;C:2019746784;G:2321631965;T:4873417599;N:688983,10,10,150,150,3643210069,2019746784,2321631965,4873417599,688983,SRX24701854,SRS21429383,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.38679,0.89762,0.1285,0.20804,0.95881,0.76877,0.53381,0.54347,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32395,SRR29181704,SRX24701853,SRS21429382,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 brainC2  Medgenome Run2  brain1  transcriptome,GSM8290044,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 brainC2  Medgenome Run2  brain1  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290044,GSM8290044: SABERb1 brainC2  Medgenome Run2  brain1  transcriptome; Danio rerio; RNA Seq,GSM8290044 r1,GSM8290044,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_brainC2_S2_L002_I1_001.fastq.gz SABERb1_brainC2_S2_L002_I2_001.fastq.gz SABERb1_brainC2_S2_L002_R1_001.fastq.gz SABERb1_brainC2_S2_L002_R2_001.fastq.gz,fastq fastq fastq fastq,3635949490.0,26157910.0,GSM8290044 r1,0:10 1:10 2:28 3:91,A:726922983;C:475009000;G:515409063;T:663020855;N:7909,10,10,28,91,726922983,475009000,515409063,663020855,7909,SRX24701853,SRS21429382,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91216,,0.23091,,0.76495,,0.55384,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32396,SRR29181705,SRX24701853,SRS21429382,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 brainC2  Medgenome Run2  brain1  transcriptome,GSM8290044,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 brainC2  Medgenome Run2  brain1  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290044,GSM8290044: SABERb1 brainC2  Medgenome Run2  brain1  transcriptome; Danio rerio; RNA Seq,GSM8290044 r1,GSM8290044,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_brainC2_S7_L002_I1_001.fastq.gz SABERb1_brainC2_S7_L002_I2_001.fastq.gz SABERb1_brainC2_S7_L002_R1_001.fastq.gz SABERb1_brainC2_S7_L002_R2_001.fastq.gz,fastq fastq fastq fastq,11551358978.0,83103302.0,GSM8290044 r2,0:10 1:10 2:28 3:91,A:2291886666;C:1518484627;G:1649680085;T:2102329631;N:19473,10,10,28,91,2291886666,1518484627,1649680085,2102329631,19473,SRX24701853,SRS21429382,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91457,,0.23286,,0.76674,,0.5505,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32397,SRR29181702,SRX24701852,SRS21429381,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 brainC1  Medgenome Run2  brain1  transcriptome,GSM8290043,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 brainC1  Medgenome Run2  brain1  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290043,GSM8290043: SABERb1 brainC1  Medgenome Run2  brain1  transcriptome; Danio rerio; RNA Seq,GSM8290043 r1,GSM8290043,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_brainC1_S1_L002_I1_001.fastq.gz SABERb1_brainC1_S1_L002_I2_001.fastq.gz SABERb1_brainC1_S1_L002_R1_001.fastq.gz SABERb1_brainC1_S1_L002_R2_001.fastq.gz,fastq fastq fastq fastq,3575922201.0,25726059.0,GSM8290043 r1,0:10 1:10 2:28 3:91,A:706764997;C:473784835;G:514720645;T:645793304;N:7588,10,10,28,91,706764997,473784835,514720645,645793304,7588,SRX24701852,SRS21429381,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91627,,0.22683,,0.76469,,0.54848,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32398,SRR29181703,SRX24701852,SRS21429381,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,SABERb1 brainC1  Medgenome Run2  brain1  transcriptome,GSM8290043,,source name:zebrafish whole brain|tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,SABERb1 brainC1  Medgenome Run2  brain1  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish whole brain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish whole brain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290043,GSM8290043: SABERb1 brainC1  Medgenome Run2  brain1  transcriptome; Danio rerio; RNA Seq,GSM8290043 r1,GSM8290043,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,SABERb1_brainC1_S6_L002_R2_001.fastq.gz SABERb1_brainC1_S6_L002_R1_001.fastq.gz SABERb1_brainC1_S6_L002_I2_001.fastq.gz SABERb1_brainC1_S6_L002_I1_001.fastq.gz,fastq fastq fastq fastq,9218042845.0,66316855.0,GSM8290043 r2,0:10 1:10 2:28 3:91,A:1809678331;C:1230188279;G:1336832583;T:1658118873;N:15739,10,10,28,91,1809678331,1230188279,1336832583,1658118873,15739,SRX24701852,SRS21429381,SRA1989588,University of Pennsylvania,University of Pennsylvania,1,0.91802,,0.22377,,0.76254,,0.54853,,91,,B,,usable mapping rate,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32399,SRR29181701,SRX24701851,SRS21429380,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,zBrHb C1hind021023wk3  hindbrain  transcriptome,GSM8290042,,source name:zebrafish hindbrain|tissue:zebrafish hindbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,zBrHb C1hind021023wk3  hindbrain  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish hindbrain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish hindbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290042,GSM8290042: zBrHb C1hind021023wk3  hindbrain  transcriptome; Danio rerio; RNA Seq,GSM8290042 r1,GSM8290042,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,zBrHb_C2hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S2_L004_I1_001.fastq.gz zBrHb_C2hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S2_L004_I2_001.fastq.gz zBrHb_C2hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S2_L004_R1_001.fastq.gz zBrHb_C2hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S2_L004_R2_001.fastq.gz,fastq fastq fastq fastq,64546948800.0,201709215.0,GSM8290042 r2,0:10 1:10 2:150 3:150,A:19999216483;C:7881744410;G:8397001445;T:24234036869;N:765293,10,10,150,150,19999216483,7881744410,8397001445,24234036869,765293,SRX24701851,SRS21429380,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.16904,0.87311,0.05961,0.20305,0.98169,0.771,0.4964,0.52096,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32400,SRR29181710,SRX24701851,SRS21429380,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,zBrHb C1hind021023wk3  hindbrain  transcriptome,GSM8290042,,source name:zebrafish hindbrain|tissue:zebrafish hindbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,zBrHb C1hind021023wk3  hindbrain  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish hindbrain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish hindbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290042,GSM8290042: zBrHb C1hind021023wk3  hindbrain  transcriptome; Danio rerio; RNA Seq,GSM8290042 r1,GSM8290042,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,zBrHb_C1hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S4_L004_R2_001.fastq.gz zBrHb_C1hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S4_L004_R1_001.fastq.gz zBrHb_C1hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S4_L004_I2_001.fastq.gz zBrHb_C1hind021023wk3_CKDL230006230-1A_HW3J5DSX5_S4_L004_I1_001.fastq.gz,fastq fastq fastq fastq,65651641280.0,205161379.0,GSM8290042 r1,0:10 1:10 2:150 3:150,A:20160289471;C:8227800878;G:8724732321;T:24434818500;N:772530,10,10,150,150,20160289471,8227800878,8724732321,24434818500,772530,SRX24701851,SRS21429380,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.20153,0.88953,0.07095,0.20427,0.97944,0.77007,0.47788,0.5233,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32401,SRR29181708,SRX24701850,SRS21429379,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,zBrMb B1mid021023wk3  midbrain  transcriptome,GSM8290041,,source name:zebrafish midbrain|tissue:zebrafish midbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,zBrMb B1mid021023wk3  midbrain  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish midbrain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish midbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290041,GSM8290041: zBrMb B1mid021023wk3  midbrain  transcriptome; Danio rerio; RNA Seq,GSM8290041 r1,GSM8290041,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,zBrMb_B1mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S1_L004_I1_001.fastq.gz zBrMb_B1mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S1_L004_I2_001.fastq.gz zBrMb_B1mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S1_L004_R1_001.fastq.gz zBrMb_B1mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S1_L004_R2_001.fastq.gz,fastq fastq fastq fastq,57396728320.0,179364776.0,GSM8290041 r1,0:10 1:10 2:150 3:150,A:17624133070;C:7302355189;G:7764883537;T:21117377617;N:683387,10,10,150,150,17624133070,7302355189,7764883537,21117377617,683387,SRX24701850,SRS21429379,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.17325,0.90421,0.06608,0.18333,0.98508,0.78303,0.51396,0.52463,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32402,SRR29181709,SRX24701850,SRS21429379,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,zBrMb B1mid021023wk3  midbrain  transcriptome,GSM8290041,,source name:zebrafish midbrain|tissue:zebrafish midbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,zBrMb B1mid021023wk3  midbrain  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish midbrain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish midbrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290041,GSM8290041: zBrMb B1mid021023wk3  midbrain  transcriptome; Danio rerio; RNA Seq,GSM8290041 r1,GSM8290041,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,zBrMb_B2mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S6_L004_R2_001.fastq.gz zBrMb_B2mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S6_L004_R1_001.fastq.gz zBrMb_B2mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S6_L004_I2_001.fastq.gz zBrMb_B2mid021023wk3_CKDL230006230-1A_HW3J5DSX5_S6_L004_I1_001.fastq.gz,fastq fastq fastq fastq,61698264000.0,192807075.0,GSM8290041 r2,0:10 1:10 2:150 3:150,A:18951447819;C:7712374364;G:8225043540;T:22952522047;N:734730,10,10,150,150,18951447819,7712374364,8225043540,22952522047,734730,SRX24701850,SRS21429379,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.18731,0.88885,0.07427,0.21742,0.98088,0.77662,0.50039,0.51547,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32403,SRR29181706,SRX24701849,SRS21429378,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,zBrFb A1fore021023wk3  forebrain  transcriptome,GSM8290040,,source name:zebrafish forebrain|tissue:zebrafish forebrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,zBrFb A1fore021023wk3  forebrain  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish forebrain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish forebrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290040,GSM8290040: zBrFb A1fore021023wk3  forebrain  transcriptome; Danio rerio; RNA Seq,GSM8290040 r1,GSM8290040,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,zBrFb_A1fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S5_L004_R2_001.fastq.gz zBrFb_A1fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S5_L004_R1_001.fastq.gz zBrFb_A1fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S5_L004_I2_001.fastq.gz zBrFb_A1fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S5_L004_I1_001.fastq.gz,fastq fastq fastq fastq,60327497600.0,188523430.0,GSM8290040 r1,0:10 1:10 2:150 3:150,A:18406517456;C:7463455362;G:7981015888;T:22705319066;N:721228,10,10,150,150,18406517456,7463455362,7981015888,22705319066,721228,SRX24701849,SRS21429378,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.17216,0.88979,0.06088,0.22548,0.98206,0.76654,0.50967,0.49721,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32404,SRR29181707,SRX24701849,SRS21429378,SRP509892,PRJNA1116548,Barcoding Notch signaling in the developing brain,GSE268356,Other,Developmental signaling inputs are fundamental for shaping cell fates and behavior. However  traditional fluorescent based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER seq  a CRISPR Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single cell transcriptomics. We applied SABER seq to record Notch signaling in developing zebrafish brains. SABER seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER seq with an expanded juvenile brain atlas to identify cell types derived from Notch active founders. Our data reveals rare examples where differential Notch activity in ancestral progenitors is detected in terminally differentiated neuronal subtypes. SABER seq is a novel platform for rapid  scalable and high resolution mapping of signaling activity during development. Overall design: 10x Genomics libraries of single cell transcriptomes and SABER seq data  and genomic DNA SABER data,,pubmed:39575683,,zBrFb A1fore021023wk3  forebrain  transcriptome,GSM8290040,,source name:zebrafish forebrain|tissue:zebrafish forebrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB|geo loc name:missing|collection date:missing,zBrFb A1fore021023wk3  forebrain  transcriptome,Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes.  The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline  similar to the transcriptomic reads. A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. post loading filtered barcode matrices into R  error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously7 35. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. scRNA seq data was analyzed using the following protocol. Raw FASTQ reads were aligned against zebrafish genome  built from GRCz.109.gtf and the GRCz11.fa files  using the Cell Ranger count pipeline to generate gene by cell count matrices filtered barcode matrix. The count matrices were processed using the standard workflow of the Seurat v5.0.2 R package with modifications. Briefly  all count matrices were separately loaded into R. Seurat objects were then created with modified parameters  requiring features to be detected in at least 3 cells and cells to contain at least 300 genes. Subsequently  the Seurat objects were merged to create a single Seurat object. Cells with RNA counts between 300 and 4000 and a mitochondrial gene percentage of less than 9% were selected for downstream analysis. Gene expression values were log normalized with the default parameters and scaled for the top 3000 variable genes. The scaled data was then used to compute the 50 principal components. Cells were iteratively clustered using the Louvain algorithm post identifying neighboring cells. Differentially expressed genes for each cluster were identified using genes that are detected in at least 10% of cells in either of the two clusters and genes showing a minimum difference of 10% between the two clusters. Cell types were annotated using known marker genes. Finally  the data was visualized using UMAP. SABER seq barcode analysis was performed using the following protocol. The SABER seq FASTQ reads were processed using the Cell Ranger count pipeline.A bash script was then used to generate a text file containing all FASTQ headers and error corrected cell barcodes for SABER seq data. Error corrected cell barcodes from transcriptomic reads were isolated and matched against those in the text file to identify common cell barcode that are shared between the transcriptomic and SABER seq datasets. The resulting text file contained redundant error corrected cell barcodes associated with different UMIs for the same cell. Thus  unique error corrected cell barcodes were isolated to create a text file containing unique FASTQ headers and error corrected barcodes. Subsequently  FASTQ reads matching the FASTQ headers in this file were extracted from the SABER seq raw reads using a Python script. SABER seq barcodes were analyzed using the scGESTALT pipeline available on Github as described previously. To analyze differences in barcode detection and editing frequencies between cell types a binomial test was used. genome build/assembly: GRCz11 processed data files format and content: *.h5 files contain filtered features/genes and barcode data generated from cell ranger pipeline. processed data files format and content: LinC1 Filtered Fastq Headers CB.txt LinC2 Filtered Fastq Headers CB.txt LinD1 Filtered Fastq Headers CB.txt LinD2 Filtered Fastq Headers CB.txt LinD3 Filtered Fastq Headers CB.txt files contain filtered and unique fastq headers and cell barcodes post matching the trasncriptomic cell barcodes. processed data files format and content: SABERb1 linC1 S4 BrainC1 S6.CB.xlsx SABERb1 linC2 S5 BrainC2 S7.CB.xlsx SABERb2 linD1 S1 BrainD1 S8.CB.xlsx SABERb2 linD2 S2 BrainD2 S9.CB.xlsx SABERb2 linD3 S3 BrainD3 S10.CB.xlsx SABERb4 linB2.1 13.123.2.With.Primer.stats.xlsx SABERb4 linB2.2 14.124.2.With.Primer.stats.xlsx files contain the SABER Seq output post matching reads to the reference sequence.,zebrafish forebrain,,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer’s instructions Single Cell 3’ v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,This work was performed under protocol numbers 807110 and 807259  which were approved by the University of Pennsylvania’s Office of Animal Welfare of Institutional Animal Care and Use Committee IACUC. All zebrafish work in this study follows the University of Pennsylvania Institutional Animal Care and Use Committee regulations.,tissue:zebrafish forebrain|developmental stage:21 dpf 23 dpf  Juvenile|genotype:WT/TLAB,GSM8290040,GSM8290040: zBrFb A1fore021023wk3  forebrain  transcriptome; Danio rerio; RNA Seq,GSM8290040 r1,GSM8290040,1,Wild type and SABER x her4.3:switchCas9 zebrafish brains were harvested and dissociated at 21 dpf 23 dpf as described previously Raj et. al 2018  Nature Biotechnology  with the following modifications. All microcentrifuge tubes were treated with 1% BSA/DPBS overnight to prevent cell loss due to adhesion. Brains were dissociated with 1 mL of 20 units/ml papain in EBSS media and incubated at 37 °C for 20 min. Cells were resuspended with 150 μl ice cold 1%BSA/DPBS solution. Transcriptome libraries were processed according to the manufacturer's instructions Single Cell three prime v3 kit. Transcriptome libraries were sequenced using NovaSeq S4 300 cycle kits Novogene and Novaseq SP 100 and 200 cycle kits MedGenome. To generate SABER seq libraries  samples post cDNA amplification and prior to fragmentation were split into two parts. One part was processed for transcriptome libraries as instructed by the manufacturer. The other part was processed for SABER seq libraries as follows. To enrich for SABER barcodes  5 µl of the whole transcriptome cDNA was PCR amplified with 10X p140v1UP  GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT CGTCGTAGATCTTCATCGTGATG and 10XPCR1F CTACACGACGCTCTTCCGATCT primers and Q5 polymerase. The reaction conditions were: 98 °C  30 s; [98 °C  10 s; 68 °C  25 s; 72 °C  15 s] x 14 cycles; 72 °C  2 min. The reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer. A second PCR was carried out using 3 µl of PCR1 product and 10XPCR1F and 10X p140v2Sa GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT GAAACTACATGGGGTcaGCTC primers. Reaction conditions were same as PCR1 except only 13 cycles were completed. At this point  2 different clean up conditions were used: iteration 1 SABER seq v0 and iteration 2 SABER seq v1. For iteration 1  the reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB buffer similar to PCR1.  For iteration 2  an optimization was trialed  and the reaction was cleaned up with right side size selection using SPRIselect beads 0.6X beads used initially and supernatant was rebound with 1.5X beads. The product was eluted in 20 µl EB. Finally  adapters and sample indices were incorporated in a third PCR reaction using 5 7 µl of a 1:10 dilution of PCR2 product. Reactions conditions were same as PCR1 except 9 10 cycles were completed. Primers used: 10XP5Dual Hx AATGATACGGCGACCACCGAGATCTACAC xxxxxxx xxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  10XP7Dual H5 AATGATACGGCGAC CACCGAGATCTACAC xxxxxxxxxx ACACTCTTTCCCTACACGACGCTCTTCCGATCT  where x represents index bases from the 10X Dual Index Kit TT  SetA H index entries. For iteration 1  the third PCR reaction was cleaned up with 0.8X SPRISelect beads and eluted in 20 µl elution buffer EB to generate final libraries. For iteration 2  the third PCR reaction was cleaned up with right side size selection using SPRIselect beads 0.65X beads used initially and supernatant was rebound with 1.5X beads. SABER seq libraries were sequenced using Novaseq SP 200 cycle kits MedGenome with 5 10% PhiX spike in. Sequencing parameters: Read1 28 cycles  Read2 151 cycles  Index1 10 cycles  Index2 10 cycles. Standard sequencing primers were used.,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP509892,,loader:fastq load.py,zBrFb_A2fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S3_L004_I1_001.fastq.gz zBrFb_A2fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S3_L004_R1_001.fastq.gz zBrFb_A2fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S3_L004_R2_001.fastq.gz zBrFb_A2fore021023wk3_CKDL230006230-1A_HW3J5DSX5_S3_L004_I2_001.fastq.gz,fastq fastq fastq fastq,68647176320.0,214522426.0,GSM8290040 r2,0:10 1:10 2:150 3:150,A:21091878705;C:8438830095;G:8989975904;T:25835224348;N:818748,10,10,150,150,21091878705,8438830095,8989975904,25835224348,818748,SRX24701849,SRS21429378,SRA1989588,University of Pennsylvania,University of Pennsylvania,2,0.18856,0.87876,0.06876,0.22256,0.9809,0.77151,0.51907,0.53004,150,150,T,B,mate1 technical by mapping diff,illumina,novaseq_era,full_length,random_priming,unknown,sc,single_cell_droplet,10x,,United States,2024-05-25,Larval,Larval,Brain,Nervous System
32553,SRR30792563,SRX26194054,SRS22736395,SRP512205,PRJNA1120771,Transcriptomic neuron types vary topographically in function and morphology,GSE269232,Transcriptome Analysis,We transcriptionally profiled the neuronal types of the zebrafish larvae optic tectum and matched them with their functional and morphological properties. Overall design: Wild type larvae were raised until 6 or 7 dpf. The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were then carefully dissected under a stereoscope followed by cell dissociation and sequencing. Please note that batches 5  6  and 8 the raw data with technical replica i.e. replica 1  replica 2 were processed together  and the resulting processed data is linked to the corresponding replica 1 sample records.,,pubmed:39939759,,optic tectum batch 12  scRNAseq  additional sequencing,GSM8536814,,source name:optic tectum|tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment|geo loc name:missing|collection date:missing,optic tectum batch 12  scRNAseq  additional sequencing,Demultiplexing  barcoded processing  gene counting and aggregation were made using the Cell Ranger software v7.1.0 Assembly: GRCz11 genome assembly Ensembl release 98 Supplementary files format and content: Tab separated values files and matrix files,optic tectum,,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer’s instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment,GSM8536814,GSM8536814: optic tectum batch 12  scRNAseq  additional sequencing; Danio rerio; RNA Seq,GSM8536814 r1,GSM8536814,1,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer's instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP512205,,loader:fastq load.py,dr_7_dpf_tectum12_S1_b_L001_I1_001.fastq.gz dr_7_dpf_tectum12_S1_b_L001_I2_001.fastq.gz dr_7_dpf_tectum12_S1_b_L001_R1_001.fastq.gz dr_7_dpf_tectum12_S1_b_L001_R2_001.fastq.gz,fastq fastq fastq fastq,8950711602.0,64860229.0,GSM8536814 r1,0:10 1:10 2:28 3:90,A:1849918393;C:1118618358;G:1252858411;T:1615952915;N:72533,10,10,28,90,1849918393,1118618358,1252858411,1615952915,72533,SRX26194054,SRS22736395,SRA1978976,Max Planck Institute for Biological Intelligence,Max Planck Institute for Biological Intelligence,,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Germany,2024-09-25,Larval,Larval,Brain,Nervous System
32554,SRR30792564,SRX26194054,SRS22736395,SRP512205,PRJNA1120771,Transcriptomic neuron types vary topographically in function and morphology,GSE269232,Transcriptome Analysis,We transcriptionally profiled the neuronal types of the zebrafish larvae optic tectum and matched them with their functional and morphological properties. Overall design: Wild type larvae were raised until 6 or 7 dpf. The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were then carefully dissected under a stereoscope followed by cell dissociation and sequencing. Please note that batches 5  6  and 8 the raw data with technical replica i.e. replica 1  replica 2 were processed together  and the resulting processed data is linked to the corresponding replica 1 sample records.,,pubmed:39939759,,optic tectum batch 12  scRNAseq  additional sequencing,GSM8536814,,source name:optic tectum|tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment|geo loc name:missing|collection date:missing,optic tectum batch 12  scRNAseq  additional sequencing,Demultiplexing  barcoded processing  gene counting and aggregation were made using the Cell Ranger software v7.1.0 Assembly: GRCz11 genome assembly Ensembl release 98 Supplementary files format and content: Tab separated values files and matrix files,optic tectum,,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer’s instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment,GSM8536814,GSM8536814: optic tectum batch 12  scRNAseq  additional sequencing; Danio rerio; RNA Seq,GSM8536814 r1,GSM8536814,1,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer's instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP512205,,loader:fastq load.py,dr_7_dpf_tectum12_S1_b_L002_I1_001.fastq.gz dr_7_dpf_tectum12_S1_b_L002_I2_001.fastq.gz dr_7_dpf_tectum12_S1_b_L002_R1_001.fastq.gz dr_7_dpf_tectum12_S1_b_L002_R2_001.fastq.gz,fastq fastq fastq fastq,8935347924.0,64748898.0,GSM8536814 r2,0:10 1:10 2:28 3:90,A:1847321882;C:1116555840;G:1250841040;T:1612644614;N:37444,10,10,28,90,1847321882,1116555840,1250841040,1612644614,37444,SRX26194054,SRS22736395,SRA1978976,Max Planck Institute for Biological Intelligence,Max Planck Institute for Biological Intelligence,,,,,,,,,,,,B,,usable mapping rate,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Germany,2024-09-25,Larval,Larval,Brain,Nervous System
32555,SRR30792565,SRX26194053,SRS22736394,SRP512205,PRJNA1120771,Transcriptomic neuron types vary topographically in function and morphology,GSE269232,Transcriptome Analysis,We transcriptionally profiled the neuronal types of the zebrafish larvae optic tectum and matched them with their functional and morphological properties. Overall design: Wild type larvae were raised until 6 or 7 dpf. The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were then carefully dissected under a stereoscope followed by cell dissociation and sequencing. Please note that batches 5  6  and 8 the raw data with technical replica i.e. replica 1  replica 2 were processed together  and the resulting processed data is linked to the corresponding replica 1 sample records.,,pubmed:39939759,,optic tectum batch 12  scRNAseq,GSM8536813,,source name:optic tectum|tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment|geo loc name:missing|collection date:missing,optic tectum batch 12  scRNAseq,Demultiplexing  barcoded processing  gene counting and aggregation were made using the Cell Ranger software v7.1.0 Assembly: GRCz11 genome assembly Ensembl release 98 Supplementary files format and content: Tab separated values files and matrix files,optic tectum,,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer’s instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment,GSM8536813,GSM8536813: optic tectum batch 12  scRNAseq; Danio rerio; RNA Seq,GSM8536813 r1,GSM8536813,1,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer's instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP512205,,loader:fastq load.py|options:  readTypes=TTBB   read1PairFiles=dr 7 dpf tectum12 S1 a L001 I1 001.fastq.gz   read2PairFiles=dr 7 dpf tectum12 S1 a L001 I2 001.fastq.gz   read3PairFiles=dr 7 dpf tectum12 S1 a L001 R1 001.fastq.gz   read4PairFiles=dr 7 dpf tectum12 S1 a L001 R2 001.fastq.gz,dr_7_dpf_tectum12_S1_a_L001_I1_001.fastq.gz dr_7_dpf_tectum12_S1_a_L001_I2_001.fastq.gz dr_7_dpf_tectum12_S1_a_L001_R1_001.fastq.gz dr_7_dpf_tectum12_S1_a_L001_R2_001.fastq.gz,fastq fastq fastq fastq,23572948584.0,170818468.0,GSM8536813 r1,0:10 1:10 2:28 3:90,A:6107921876;C:4130886894;G:4414017585;T:5503600966;N:151903,10,10,28,90,6107921876,4130886894,4414017585,5503600966,151903,SRX26194053,SRS22736394,SRA1978976,Max Planck Institute for Biological Intelligence,Max Planck Institute for Biological Intelligence,,,,,,,,,,,,T,B,sc-like readlen,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Germany,2024-09-25,Larval,Larval,Brain,Nervous System
32556,SRR30792566,SRX26194053,SRS22736394,SRP512205,PRJNA1120771,Transcriptomic neuron types vary topographically in function and morphology,GSE269232,Transcriptome Analysis,We transcriptionally profiled the neuronal types of the zebrafish larvae optic tectum and matched them with their functional and morphological properties. Overall design: Wild type larvae were raised until 6 or 7 dpf. The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were then carefully dissected under a stereoscope followed by cell dissociation and sequencing. Please note that batches 5  6  and 8 the raw data with technical replica i.e. replica 1  replica 2 were processed together  and the resulting processed data is linked to the corresponding replica 1 sample records.,,pubmed:39939759,,optic tectum batch 12  scRNAseq,GSM8536813,,source name:optic tectum|tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment|geo loc name:missing|collection date:missing,optic tectum batch 12  scRNAseq,Demultiplexing  barcoded processing  gene counting and aggregation were made using the Cell Ranger software v7.1.0 Assembly: GRCz11 genome assembly Ensembl release 98 Supplementary files format and content: Tab separated values files and matrix files,optic tectum,,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer’s instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment,GSM8536813,GSM8536813: optic tectum batch 12  scRNAseq; Danio rerio; RNA Seq,GSM8536813 r1,GSM8536813,1,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer's instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP512205,,loader:fastq load.py|options:  readTypes=TTBB   read1PairFiles=dr 7 dpf tectum12 S1 a L002 I1 001.fastq.gz   read2PairFiles=dr 7 dpf tectum12 S1 a L002 I2 001.fastq.gz   read3PairFiles=dr 7 dpf tectum12 S1 a L002 R1 001.fastq.gz   read4PairFiles=dr 7 dpf tectum12 S1 a L002 R2 001.fastq.gz,dr_7_dpf_tectum12_S1_a_L002_I1_001.fastq.gz dr_7_dpf_tectum12_S1_a_L002_I2_001.fastq.gz dr_7_dpf_tectum12_S1_a_L002_R1_001.fastq.gz dr_7_dpf_tectum12_S1_a_L002_R2_001.fastq.gz,fastq fastq fastq fastq,23121529194.0,167547313.0,GSM8536813 r2,0:10 1:10 2:28 3:90,A:6007640381;C:4040815909;G:4320973941;T:5401000398;N:152305,10,10,28,90,6007640381,4040815909,4320973941,5401000398,152305,SRX26194053,SRS22736394,SRA1978976,Max Planck Institute for Biological Intelligence,Max Planck Institute for Biological Intelligence,,,,,,,,,,,,T,B,sc-like readlen,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Germany,2024-09-25,Larval,Larval,Brain,Nervous System
32557,SRR30792567,SRX26194052,SRS22736393,SRP512205,PRJNA1120771,Transcriptomic neuron types vary topographically in function and morphology,GSE269232,Transcriptome Analysis,We transcriptionally profiled the neuronal types of the zebrafish larvae optic tectum and matched them with their functional and morphological properties. Overall design: Wild type larvae were raised until 6 or 7 dpf. The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were then carefully dissected under a stereoscope followed by cell dissociation and sequencing. Please note that batches 5  6  and 8 the raw data with technical replica i.e. replica 1  replica 2 were processed together  and the resulting processed data is linked to the corresponding replica 1 sample records.,,pubmed:39939759,,optic tectum batch 11  replica 2  scRNAseq,GSM8536812,,source name:optic tectum|tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment|geo loc name:missing|collection date:missing,optic tectum batch 11  replica 2  scRNAseq,Demultiplexing  barcoded processing  gene counting and aggregation were made using the Cell Ranger software v7.1.0 Assembly: GRCz11 genome assembly Ensembl release 98 Supplementary files format and content: Tab separated values files and matrix files,optic tectum,,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer’s instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,tissue:optic tectum|age:7 dpf type:all cells|genotype:wild type|treatment:no treatment,GSM8536812,GSM8536812: optic tectum batch 11  replica 2  scRNAseq; Danio rerio; RNA Seq,GSM8536812 r1,GSM8536812,1,The optic tectum and torus longitudinalis of 6 dpf and 7 dpf larvae were carefully dissected under a stereoscope. Cell dissociation was performed using the Papain Dissociation System Worthington Biochemical Corporation. libraries according to the manufacturer's instructions Chromium Single Cell 3′ Reagent Kit v3  10x Genomics. single cell 3′ barcoded cDNA,,RNA-Seq,TRANSCRIPTOMIC SINGLE CELL,cDNA,PAIRED,ILLUMINA,Illumina NovaSeq 6000,,SRP512205,,loader:fastq load.py|options:  readTypes=TTBB   read1PairFiles=dr 7 dpf tectum11 S2 L001 I1 001.fastq.gz   read2PairFiles=dr 7 dpf tectum11 S2 L001 I2 001.fastq.gz   read3PairFiles=dr 7 dpf tectum11 S2 L001 R1 001.fastq.gz   read4PairFiles=dr 7 dpf tectum11 S2 L001 R2 001.fastq.gz,dr_7_dpf_tectum11_S2_L001_I1_001.fastq.gz dr_7_dpf_tectum11_S2_L001_I2_001.fastq.gz dr_7_dpf_tectum11_S2_L001_R1_001.fastq.gz dr_7_dpf_tectum11_S2_L001_R2_001.fastq.gz,fastq fastq fastq fastq,30954771030.0,224309935.0,GSM8536812 r1,0:10 1:10 2:28 3:90,A:8181398647;C:5295898232;G:5819369308;T:7171704687;N:201456,10,10,28,90,8181398647,5295898232,5819369308,7171704687,201456,SRX26194052,SRS22736393,SRA1978976,Max Planck Institute for Biological Intelligence,Max Planck Institute for Biological Intelligence,,,,,,,,,,,,T,B,sc-like readlen,illumina,novaseq_era,unknown,cdna_unspecified,unknown,sc,single_cell_droplet,10x,,Germany,2024-09-25,Larval,Larval,Brain,Nervous System