metadata: run_metadata: 17 rows where experiment.library_selection = "size fractionation", experiment.platform = "ILLUMINA" and tissue

17 rows where experiment.library_selection = "size fractionation", experiment.platform = "ILLUMINA" and tissue_curation = "Heart"

descending

Link	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.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.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.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	submission.bioprojectsource.country	earliest_date	devstage_curation	devstage_curation_coarse	tissue_curation	tissue_curation_coarse
37134	37134	SRR997335	SRX355601	SRS483796	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Control rep4	GSM1234963	source name:Heart Control\|tissue:heart	Heart Control rep4	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234963	GSM1234963: Heart Control rep4; Danio rerio; RNA Seq	GSM1234963		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234963	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		C3PO_0053_s_7_sequence.txt.gz	fastq	1111882122.0	28509798.0	GSM1234963 r1	0:39	A:239964076;C:229590501;G:337557042;T:303257677;N:1512826	39		239964076	229590501	337557042	303257677	1512826	SRX355601	SRS483796	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.11195		0.03776		0.98871		0.16576		39		B		usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37135	37135	SRR997334	SRX355600	SRS483795	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Control rep3	GSM1234962	source name:Heart Control\|tissue:heart	Heart Control rep3	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234962	GSM1234962: Heart Control rep3; Danio rerio; RNA Seq	GSM1234962		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234962	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		C3PO_0053_s_6_sequence.txt.gz	fastq	1221305046.0	31315514.0	GSM1234962 r1	0:39	A:263520584;C:251263128;G:372262308;T:332218529;N:2040497	39		263520584	251263128	372262308	332218529	2040497	SRX355600	SRS483795	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.11552		0.03865		0.98679		0.1927		39		B		usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37136	37136	SRR997333	SRX355599	SRS483794	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Control rep2	GSM1234961	source name:Heart Control\|tissue:heart	Heart Control rep2	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234961	GSM1234961: Heart Control rep2; Danio rerio; RNA Seq	GSM1234961		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234961	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		R2D2_0122_s_7_sequence.txt.gz	fastq	1462542939.0	37501101.0	GSM1234961 r1	0:39	A:313173840;C:298865755;G:440814004;T:409066990;N:622350	39		313173840	298865755	440814004	409066990	622350	SRX355599	SRS483794	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.01745		0.00554		0.99101		0.42928		39		B		usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37137	37137	SRR997332	SRX355598	SRS483793	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Control rep1	GSM1234960	source name:Heart Control\|tissue:heart	Heart Control rep1	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234960	GSM1234960: Heart Control rep1; Danio rerio; RNA Seq	GSM1234960		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234960	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		R2D2_0122_s_6_sequence.txt.gz	fastq	1447346355.0	37111445.0	GSM1234960 r1	0:39	A:311132663;C:297266985;G:441400778;T:396960907;N:585022	39		311132663	297266985	441400778	396960907	585022	SRX355598	SRS483793	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.06118		0.01997		0.98752		0.43741		39		B		usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37138	37138	SRR997331	SRX355597	SRS483792	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Resected rep4	GSM1234959	source name:Heart Resected\|tissue:heart	Heart Resected rep4	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234959	GSM1234959: Heart Resected rep4; Danio rerio; RNA Seq	GSM1234959		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234959	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		C3PO_0053_s_5_sequence.txt.gz	fastq	703519557.0	18038963.0	GSM1234959 r1	0:39	A:142685665;C:144259439;G:215526965;T:199924689;N:1122799	39		142685665	144259439	215526965	199924689	1122799	SRX355597	SRS483792	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.00172		0.00045		0.99738		0.34873		39		T		under 1.2% mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37139	37139	SRR997330	SRX355596	SRS483791	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Resected rep3	GSM1234958	source name:Heart Resected\|tissue:heart	Heart Resected rep3	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234958	GSM1234958: Heart Resected rep3; Danio rerio; RNA Seq	GSM1234958		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234958	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		C3PO_0053_s_4_sequence.txt.gz	fastq	918978177.0	23563543.0	GSM1234958 r1	0:39	A:188056254;C:191217660;G:283318445;T:255042736;N:1343082	39		188056254	191217660	283318445	255042736	1343082	SRX355596	SRS483791	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.09453		0.03085		0.98559		0.18337		39		B		usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37140	37140	SRR997329	SRX355595	SRS483789	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Resected rep2	GSM1234957	source name:Heart Resected\|tissue:heart	Heart Resected rep2	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234957	GSM1234957: Heart Resected rep2; Danio rerio; RNA Seq	GSM1234957		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234957	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		R2D2_0122_s_5_sequence.txt.gz	fastq	1420874247.0	36432673.0	GSM1234957 r1	0:39	A:290914118;C:295973738;G:440368910;T:393019696;N:597785	39		290914118	295973738	440368910	393019696	597785	SRX355595	SRS483789	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.00472		0.00131		0.99431		0.42832		39		T		under 1.2% mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37141	37141	SRR997328	SRX355594	SRS483790	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418		Heart Resected rep1	GSM1234956	source name:Heart Resected\|tissue:heart	Heart Resected rep1	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected		Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001		tissue:heart	GSM1234956	GSM1234956: Heart Resected rep1; Danio rerio; RNA Seq	GSM1234956		1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234956	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II		SRP030036		C3PO_0054_s_8_sequence.txt.gz	fastq	1073339514.0	27521526.0	GSM1234956 r1	0:39	A:223670054;C:219603945;G:328718329;T:300891777;N:455409	39		223670054	219603945	328718329	300891777	455409	SRX355594	SRS483790	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.05133		0.01643		0.9893		0.25792		39		B		usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37991	37991	SRR1265766	SRX529160	SRS598857	SRP041544	PRJNA245824	Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish	GSE57169	Transcriptome Analysis	The role of microRNAs in gene regulation has been well established. The extent of miRNA regulation also increases with increasing genome complexity. Though the number of genes appear to be equal between human and zebrafish substantially less microRNAs have been discovered in zebrafish compared to human Release 19. It appears that most of the miRNAs in zebrafish are yet to be discovered. We sequenced small RNAs from brain gut liver ovary testis eye heart and embryo of zebrafish. In brain gut and liver sequencing was done in male and female separately. Majority of the sequenced reads 16 62% mapped to known miRNAs with the exception of ovary 5.7% and testis 7.8%. Using the miRNA discovery tool miRDeep2 we discovered novel miRNAs from the un annotated reads that ranged from 7.6 to 23.0% with exceptions of ovary 51.4% and testis 55.2%. The prediction tool identified a total of 459 novel pre miRNAs. We compared expression of miRNAs between different tissues and between males and females to identify tissue associated and sex associated miRNAs respectively. These miRNAs could serve as putative biomarkers for these tissues. The brain and liver had highest number of tissue associated 22 and sex associated 34 miRNAs respectively. This study comprehensively identifies tissue and sex associated miRNAs in zebrafish. Further we have discovered 459 novel pre miRNAs 30% seed homology to human miRNA as a genomic resource which can facilitate further investigations to understand miRNA mRNA gene regulatory networks in zebrafish which will have implications in understanding the function of human homologs. Overall design: Known miRNA profiling novel miRNA discovery and identification of tissue associated and sex associated miRNAs from sRNA deep sequencing data of different tissues and embryo of zebrafish in triplicate was carried out using the Illumina HiSeq 2000 platform.		pubmed:26574018		Heart Replicate 3 sRNAseq	GSM1376649	source name:Heart\|tissue:Heart\|genetic background:Wild type Singapore strain	Heart Replicate 3 sRNAseq	Illumina Casava 1.8.2 software used for basecalling. The sequenced reads were first subjected to adapter removal through the cutadapt program Martin 2011. The trimmed reads were then collapsed to remove redundancy and to obtain a unique sequence fasta file through the mapper module of miRDeep2 package Friedländer et al. 2012. The unique reads fasta file was then put through an elimination pipeline module Vaz et al. 2010 comprising of a series of sequence similarity searches with the annotated databases. At each step the reads were matched to an annotated database with a maximum of two mismatches. The matched reads were removed and the unmatched ones were further matched to another annotated database finally culminating into an un annotated pool of reads that served as a source of novel miRNAs and novel sRNAs. The known miRNA expression profile was generated by using the quantifier module of the miRDeep2 package that gives the read counts for the known miRNAs. The quantifier.pl command line used: perl quantifier.pl p <zebrafish precursor miRNA fasta file> m <zebrafish mature miRNA fasta file> r <unique reads fasta file> t Zebrafish The raw reads expression profile generated for all the replicates of the samples were subjected to Trimmed Mean of M values TMM normalisation using the Bioconductor package edgeR Robinson et al. 2010. Genome build: ZV9 Supplementary files format and content: 1. 'Danio rerio known miRNA Rel19 profile Raw.txt': Tab delimited text file that includes the raw counts for the known mature miRNA miRBase Release 19. Supplementary files format and content: 2. 'Danio rerio known miRNA Rel19 profile Normalised.txt': Tab delimited text file that includes the Trimmed Mean of M values TMM normalised counts for the known mature miRNA miRBase Release 19. One of the replicate of Heart MZH008 failed to cluster with the other two replicates on basis of its known miRNA expression profile and hence was not used for further analysis.	Heart	N/A	Total RNA were extracted using mirVana™ miRNA Isolation Kit AM1560 Life Technologies. Tissues were homogenised in 1.5 ml microfuge tube containing Lysis/Binding buffer provided in the mirVana™ miRNA Isolation using a hand held pestle. Total RNA containing small RNA were purified following the manufacturer protocol. Small RNA libraries were prepared for sequencing using TruSeq Small RNA Sample Preparation Kit RS 200 0012 Illumina Inc.. Libraries were prepared according to manufacturer instructions. Briefly 1µg of good quality Total RNA per sample was used as starting material. 5’ and 3’ RNA adapters were ligated to each RNA molecule before reverse transcription to create single stranded cDNA. The cDNA was then amplified with PCR using a common primer and a primer containing a unique index sequence. The resulting PCR reactions were electrophoresed on 6% Novex TBE PAGE Gel Life Technologies and bands corresponding to adapter ligated constructs derived from 22 30 nucleotides small RNA fragments were excised from the gel. The small RNA were purified from the excised gel and validated on High Sensitivity DNA chips on a Bioanalyser Agilent Technologies before sequencing.	Fishes were purchased from a local supplier and acclimatized before tissue extraction.	tissue:Heart\|genetic background:Wild type Singapore strain	GSM1376649	GSM1376649: Heart Replicate 3 sRNAseq; Danio rerio; miRNA Seq	GSM1376649		1	Total RNA were extracted using mirVana™ miRNA Isolation Kit AM1560 Life Technologies. Tissues were homogenised in 1.5 ml microfuge tube containing Lysis/Binding buffer provided in the mirVana™ miRNA Isolation using a hand held pestle. Total RNA containing small RNA were purified following the manufacturer protocol. Small RNA libraries were prepared for sequencing using TruSeq Small RNA Sample Preparation Kit RS 200 0012 Illumina Inc.. Libraries were prepared according to manufacturer instructions. Briefly 1µg of good quality Total RNA per sample was used as starting material. 5’ and 3’ RNA adapters were ligated to each RNA molecule before reverse transcription to create single stranded cDNA. The cDNA was then amplified with PCR using a common primer and a primer containing a unique index sequence. The resulting PCR reactions were electrophoresed on 6% Novex TBE PAGE Gel Life Technologies and bands corresponding to adapter ligated constructs derived from 22 30 nucleotides small RNA fragments were excised from the gel. The small RNA were purified from the excised gel and validated on High Sensitivity DNA chips on a Bioanalyser Agilent Technologies before sequencing.	GEO Accession:GSM1376649	miRNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina HiSeq 2000		SRP041544		MZH008_GATCAG_L005_R1.fastq.gz	fastq	4401229692.0	57910917.0	GSM1376649 r1	0:76	A:1009381958;C:1130057881;G:1173217392;T:1088123982;N:448479	76		1009381958	1130057881	1173217392	1088123982	448479	SRX529160	SRS598857	SRA160430	GEO	Expression and Signaling in Mesenchymal and Hematopoietic Stem Cells, Genome and Gene Expression Data Analysis Division, Bioinformatics Institute, A*STAR, Singapore	1	0.00129		0.00046		0.99882		0.51351		76		T		under 1.2% mapping rate	illumina	hiseq_era	unknown	size_fractionation	trueseq	bulk	unknown	unknown	Singapore	2014-04-29	Undetermined	Embryo	Heart	Cardiovascular System
37992	37992	SRR1265765	SRX529159	SRS598856	SRP041544	PRJNA245824	Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish	GSE57169	Transcriptome Analysis	The role of microRNAs in gene regulation has been well established. The extent of miRNA regulation also increases with increasing genome complexity. Though the number of genes appear to be equal between human and zebrafish substantially less microRNAs have been discovered in zebrafish compared to human Release 19. It appears that most of the miRNAs in zebrafish are yet to be discovered. We sequenced small RNAs from brain gut liver ovary testis eye heart and embryo of zebrafish. In brain gut and liver sequencing was done in male and female separately. Majority of the sequenced reads 16 62% mapped to known miRNAs with the exception of ovary 5.7% and testis 7.8%. Using the miRNA discovery tool miRDeep2 we discovered novel miRNAs from the un annotated reads that ranged from 7.6 to 23.0% with exceptions of ovary 51.4% and testis 55.2%. The prediction tool identified a total of 459 novel pre miRNAs. We compared expression of miRNAs between different tissues and between males and females to identify tissue associated and sex associated miRNAs respectively. These miRNAs could serve as putative biomarkers for these tissues. The brain and liver had highest number of tissue associated 22 and sex associated 34 miRNAs respectively. This study comprehensively identifies tissue and sex associated miRNAs in zebrafish. Further we have discovered 459 novel pre miRNAs 30% seed homology to human miRNA as a genomic resource which can facilitate further investigations to understand miRNA mRNA gene regulatory networks in zebrafish which will have implications in understanding the function of human homologs. Overall design: Known miRNA profiling novel miRNA discovery and identification of tissue associated and sex associated miRNAs from sRNA deep sequencing data of different tissues and embryo of zebrafish in triplicate was carried out using the Illumina HiSeq 2000 platform.		pubmed:26574018		Heart Replicate 2 sRNAseq	GSM1376648	source name:Heart\|tissue:Heart\|genetic background:Wild type Singapore strain	Heart Replicate 2 sRNAseq	Illumina Casava 1.8.2 software used for basecalling. The sequenced reads were first subjected to adapter removal through the cutadapt program Martin 2011. The trimmed reads were then collapsed to remove redundancy and to obtain a unique sequence fasta file through the mapper module of miRDeep2 package Friedländer et al. 2012. The unique reads fasta file was then put through an elimination pipeline module Vaz et al. 2010 comprising of a series of sequence similarity searches with the annotated databases. At each step the reads were matched to an annotated database with a maximum of two mismatches. The matched reads were removed and the unmatched ones were further matched to another annotated database finally culminating into an un annotated pool of reads that served as a source of novel miRNAs and novel sRNAs. The known miRNA expression profile was generated by using the quantifier module of the miRDeep2 package that gives the read counts for the known miRNAs. The quantifier.pl command line used: perl quantifier.pl p <zebrafish precursor miRNA fasta file> m <zebrafish mature miRNA fasta file> r <unique reads fasta file> t Zebrafish The raw reads expression profile generated for all the replicates of the samples were subjected to Trimmed Mean of M values TMM normalisation using the Bioconductor package edgeR Robinson et al. 2010. Genome build: ZV9 Supplementary files format and content: 1. 'Danio rerio known miRNA Rel19 profile Raw.txt': Tab delimited text file that includes the raw counts for the known mature miRNA miRBase Release 19. Supplementary files format and content: 2. 'Danio rerio known miRNA Rel19 profile Normalised.txt': Tab delimited text file that includes the Trimmed Mean of M values TMM normalised counts for the known mature miRNA miRBase Release 19. One of the replicate of Heart MZH008 failed to cluster with the other two replicates on basis of its known miRNA expression profile and hence was not used for further analysis.	Heart	N/A	Total RNA were extracted using mirVana™ miRNA Isolation Kit AM1560 Life Technologies. Tissues were homogenised in 1.5 ml microfuge tube containing Lysis/Binding buffer provided in the mirVana™ miRNA Isolation using a hand held pestle. Total RNA containing small RNA were purified following the manufacturer protocol. Small RNA libraries were prepared for sequencing using TruSeq Small RNA Sample Preparation Kit RS 200 0012 Illumina Inc.. Libraries were prepared according to manufacturer instructions. Briefly 1µg of good quality Total RNA per sample was used as starting material. 5’ and 3’ RNA adapters were ligated to each RNA molecule before reverse transcription to create single stranded cDNA. The cDNA was then amplified with PCR using a common primer and a primer containing a unique index sequence. The resulting PCR reactions were electrophoresed on 6% Novex TBE PAGE Gel Life Technologies and bands corresponding to adapter ligated constructs derived from 22 30 nucleotides small RNA fragments were excised from the gel. The small RNA were purified from the excised gel and validated on High Sensitivity DNA chips on a Bioanalyser Agilent Technologies before sequencing.	Fishes were purchased from a local supplier and acclimatized before tissue extraction.	tissue:Heart\|genetic background:Wild type Singapore strain	GSM1376648	GSM1376648: Heart Replicate 2 sRNAseq; Danio rerio; miRNA Seq	GSM1376648		1	Total RNA were extracted using mirVana™ miRNA Isolation Kit AM1560 Life Technologies. Tissues were homogenised in 1.5 ml microfuge tube containing Lysis/Binding buffer provided in the mirVana™ miRNA Isolation using a hand held pestle. Total RNA containing small RNA were purified following the manufacturer protocol. Small RNA libraries were prepared for sequencing using TruSeq Small RNA Sample Preparation Kit RS 200 0012 Illumina Inc.. Libraries were prepared according to manufacturer instructions. Briefly 1µg of good quality Total RNA per sample was used as starting material. 5’ and 3’ RNA adapters were ligated to each RNA molecule before reverse transcription to create single stranded cDNA. The cDNA was then amplified with PCR using a common primer and a primer containing a unique index sequence. The resulting PCR reactions were electrophoresed on 6% Novex TBE PAGE Gel Life Technologies and bands corresponding to adapter ligated constructs derived from 22 30 nucleotides small RNA fragments were excised from the gel. The small RNA were purified from the excised gel and validated on High Sensitivity DNA chips on a Bioanalyser Agilent Technologies before sequencing.	GEO Accession:GSM1376648	miRNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina HiSeq 2000		SRP041544		MZH007_ACTTGA_L005_R1.fastq.gz	fastq	3202357508.0	42136283.0	GSM1376648 r1	0:76	A:666309720;C:845347679;G:846066601;T:844306103;N:327405	76		666309720	845347679	846066601	844306103	327405	SRX529159	SRS598856	SRA160430	GEO	Expression and Signaling in Mesenchymal and Hematopoietic Stem Cells, Genome and Gene Expression Data Analysis Division, Bioinformatics Institute, A*STAR, Singapore	1	0.00042		3e-05		0.99924		0.56521		76		T		under 1.2% mapping rate	illumina	hiseq_era	unknown	size_fractionation	trueseq	bulk	unknown	unknown	Singapore	2014-04-29	Undetermined	Embryo	Heart	Cardiovascular System
37993	37993	SRR1265764	SRX529158	SRS598855	SRP041544	PRJNA245824	Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish	GSE57169	Transcriptome Analysis	The role of microRNAs in gene regulation has been well established. The extent of miRNA regulation also increases with increasing genome complexity. Though the number of genes appear to be equal between human and zebrafish substantially less microRNAs have been discovered in zebrafish compared to human Release 19. It appears that most of the miRNAs in zebrafish are yet to be discovered. We sequenced small RNAs from brain gut liver ovary testis eye heart and embryo of zebrafish. In brain gut and liver sequencing was done in male and female separately. Majority of the sequenced reads 16 62% mapped to known miRNAs with the exception of ovary 5.7% and testis 7.8%. Using the miRNA discovery tool miRDeep2 we discovered novel miRNAs from the un annotated reads that ranged from 7.6 to 23.0% with exceptions of ovary 51.4% and testis 55.2%. The prediction tool identified a total of 459 novel pre miRNAs. We compared expression of miRNAs between different tissues and between males and females to identify tissue associated and sex associated miRNAs respectively. These miRNAs could serve as putative biomarkers for these tissues. The brain and liver had highest number of tissue associated 22 and sex associated 34 miRNAs respectively. This study comprehensively identifies tissue and sex associated miRNAs in zebrafish. Further we have discovered 459 novel pre miRNAs 30% seed homology to human miRNA as a genomic resource which can facilitate further investigations to understand miRNA mRNA gene regulatory networks in zebrafish which will have implications in understanding the function of human homologs. Overall design: Known miRNA profiling novel miRNA discovery and identification of tissue associated and sex associated miRNAs from sRNA deep sequencing data of different tissues and embryo of zebrafish in triplicate was carried out using the Illumina HiSeq 2000 platform.		pubmed:26574018		Heart Replicate 1 sRNAseq	GSM1376647	source name:Heart\|tissue:Heart\|genetic background:Wild type Singapore strain	Heart Replicate 1 sRNAseq	Illumina Casava 1.8.2 software used for basecalling. The sequenced reads were first subjected to adapter removal through the cutadapt program Martin 2011. The trimmed reads were then collapsed to remove redundancy and to obtain a unique sequence fasta file through the mapper module of miRDeep2 package Friedländer et al. 2012. The unique reads fasta file was then put through an elimination pipeline module Vaz et al. 2010 comprising of a series of sequence similarity searches with the annotated databases. At each step the reads were matched to an annotated database with a maximum of two mismatches. The matched reads were removed and the unmatched ones were further matched to another annotated database finally culminating into an un annotated pool of reads that served as a source of novel miRNAs and novel sRNAs. The known miRNA expression profile was generated by using the quantifier module of the miRDeep2 package that gives the read counts for the known miRNAs. The quantifier.pl command line used: perl quantifier.pl p <zebrafish precursor miRNA fasta file> m <zebrafish mature miRNA fasta file> r <unique reads fasta file> t Zebrafish The raw reads expression profile generated for all the replicates of the samples were subjected to Trimmed Mean of M values TMM normalisation using the Bioconductor package edgeR Robinson et al. 2010. Genome build: ZV9 Supplementary files format and content: 1. 'Danio rerio known miRNA Rel19 profile Raw.txt': Tab delimited text file that includes the raw counts for the known mature miRNA miRBase Release 19. Supplementary files format and content: 2. 'Danio rerio known miRNA Rel19 profile Normalised.txt': Tab delimited text file that includes the Trimmed Mean of M values TMM normalised counts for the known mature miRNA miRBase Release 19. One of the replicate of Heart MZH008 failed to cluster with the other two replicates on basis of its known miRNA expression profile and hence was not used for further analysis.	Heart	N/A	Total RNA were extracted using mirVana™ miRNA Isolation Kit AM1560 Life Technologies. Tissues were homogenised in 1.5 ml microfuge tube containing Lysis/Binding buffer provided in the mirVana™ miRNA Isolation using a hand held pestle. Total RNA containing small RNA were purified following the manufacturer protocol. Small RNA libraries were prepared for sequencing using TruSeq Small RNA Sample Preparation Kit RS 200 0012 Illumina Inc.. Libraries were prepared according to manufacturer instructions. Briefly 1µg of good quality Total RNA per sample was used as starting material. 5’ and 3’ RNA adapters were ligated to each RNA molecule before reverse transcription to create single stranded cDNA. The cDNA was then amplified with PCR using a common primer and a primer containing a unique index sequence. The resulting PCR reactions were electrophoresed on 6% Novex TBE PAGE Gel Life Technologies and bands corresponding to adapter ligated constructs derived from 22 30 nucleotides small RNA fragments were excised from the gel. The small RNA were purified from the excised gel and validated on High Sensitivity DNA chips on a Bioanalyser Agilent Technologies before sequencing.	Fishes were purchased from a local supplier and acclimatized before tissue extraction.	tissue:Heart\|genetic background:Wild type Singapore strain	GSM1376647	GSM1376647: Heart Replicate 1 sRNAseq; Danio rerio; miRNA Seq	GSM1376647		1	Total RNA were extracted using mirVana™ miRNA Isolation Kit AM1560 Life Technologies. Tissues were homogenised in 1.5 ml microfuge tube containing Lysis/Binding buffer provided in the mirVana™ miRNA Isolation using a hand held pestle. Total RNA containing small RNA were purified following the manufacturer protocol. Small RNA libraries were prepared for sequencing using TruSeq Small RNA Sample Preparation Kit RS 200 0012 Illumina Inc.. Libraries were prepared according to manufacturer instructions. Briefly 1µg of good quality Total RNA per sample was used as starting material. 5’ and 3’ RNA adapters were ligated to each RNA molecule before reverse transcription to create single stranded cDNA. The cDNA was then amplified with PCR using a common primer and a primer containing a unique index sequence. The resulting PCR reactions were electrophoresed on 6% Novex TBE PAGE Gel Life Technologies and bands corresponding to adapter ligated constructs derived from 22 30 nucleotides small RNA fragments were excised from the gel. The small RNA were purified from the excised gel and validated on High Sensitivity DNA chips on a Bioanalyser Agilent Technologies before sequencing.	GEO Accession:GSM1376647	miRNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina HiSeq 2000		SRP041544		MZH002_CAGATC_L005_R1.fastq.gz	fastq	3777814232.0	49708082.0	GSM1376647 r1	0:76	A:791204432;C:1050679958;G:1001897360;T:933655799;N:376683	76		791204432	1050679958	1001897360	933655799	376683	SRX529158	SRS598855	SRA160430	GEO	Expression and Signaling in Mesenchymal and Hematopoietic Stem Cells, Genome and Gene Expression Data Analysis Division, Bioinformatics Institute, A*STAR, Singapore	1	0.00034		4e-05		0.99943		0.62264		76		T		under 1.2% mapping rate	illumina	hiseq_era	unknown	size_fractionation	trueseq	bulk	unknown	unknown	Singapore	2014-04-29	Undetermined	Embryo	Heart	Cardiovascular System
42495	42495	SRR5666979	SRX2902577	SRS2269173	SRP108989	PRJNA390119	HLX & Hematopoiesis	PRJNA390119	Other	HLX & Hematopoiesis			rnaseq and atacseq	hlx hematopoiesis	hlx	isolate:multiisolates\|age:N/A\|sex:pooled male and female\|tissue:heart\|BioSampleModel:Model organism or animal									kdrl GFP cells hlx1 MO rep2	3	kdrl GFP cells hlx1 MO rep2	SMART SEQ ultra low RNA seq kit Clonetech			RNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 2500	<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>150</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>76</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>	SRP108989	assembly:danRer10	flk_gfp_hlx_8ng_48hrs_2_R1.fastq.gz flk_gfp_hlx_8ng_48hrs_2_R2.fastq.gz	fastq fastq	1887289200.0	12581928.0	flk gfp hlx 8ng 48hrs 2 R1.fastq.gz	0:75 1:75	A:493825524;C:448630716;G:436118597;T:508410442;N:303921	75	75	493825524	448630716	436118597	508410442	303921	SRX2902577	SRS2269173	SRA573518	BRFAA\|Molecular Biology	BRFAA	2	0.9202	0.9216	0.09499	0.09558	0.73805	0.73878	0.48809	0.48787	75	75	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown	Greece	2017-06-13	Undetermined	Undetermined	Heart	Cardiovascular System
42496	42496	SRR5666980	SRX2902576	SRS2269173	SRP108989	PRJNA390119	HLX & Hematopoiesis	PRJNA390119	Other	HLX & Hematopoiesis			rnaseq and atacseq	hlx hematopoiesis	hlx	isolate:multiisolates\|age:N/A\|sex:pooled male and female\|tissue:heart\|BioSampleModel:Model organism or animal									kdrl GFP cells hlx1 MO rep1	2	kdrl GFP cells hlx1 MO rep1	SMART SEQ ultra low RNA seq kit Clonetech			RNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 2500	<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>150</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>76</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>	SRP108989	assembly:danRer10	flk_gfp_hlx_8ng_48hrs_1_R1.fastq.gz flk_gfp_hlx_8ng_48hrs_1_R2.fastq.gz	fastq fastq	1561083900.0	10407226.0	flk gfp hlx 8ng 48hrs 1 R2.fastq.gz	0:75 1:75	A:412744284;C:366776465;G:356834742;T:424473871;N:254538	75	75	412744284	366776465	356834742	424473871	254538	SRX2902576	SRS2269173	SRA573518	BRFAA\|Molecular Biology	BRFAA	2	0.9172	0.91824	0.09957	0.09961	0.73965	0.73975	0.48906	0.48977	75	75	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown	Greece	2017-06-13	Undetermined	Undetermined	Heart	Cardiovascular System
42497	42497	SRR5666981	SRX2902575	SRS2269173	SRP108989	PRJNA390119	HLX & Hematopoiesis	PRJNA390119	Other	HLX & Hematopoiesis			rnaseq and atacseq	hlx hematopoiesis	hlx	isolate:multiisolates\|age:N/A\|sex:pooled male and female\|tissue:heart\|BioSampleModel:Model organism or animal									kdrl GFP cells control 2	1	kdrl GFP cells control 2	SMART SEQ ultra low RNA seq kit Clonetech			RNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 2500	<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>150</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>76</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>	SRP108989	assembly:danRer10	flk_gfp_48hrs_con2_R1.fastq.gz flk_gfp_48hrs_con2_R2.fastq.gz	fastq fastq	2042164500.0	13614430.0	flk gfp 48hrs con2 R1.fastq.gz	0:75 1:75	A:537008617;C:483956616;G:465380092;T:555490621;N:328554	75	75	537008617	483956616	465380092	555490621	328554	SRX2902575	SRS2269173	SRA573518	BRFAA\|Molecular Biology	BRFAA	2	0.91492	0.91762	0.10575	0.10669	0.75519	0.75546	0.49482	0.49617	75	75	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown	Greece	2017-06-13	Undetermined	Undetermined	Heart	Cardiovascular System
42498	42498	SRR5666982	SRX2902574	SRS2269173	SRP108989	PRJNA390119	HLX & Hematopoiesis	PRJNA390119	Other	HLX & Hematopoiesis			rnaseq and atacseq	hlx hematopoiesis	hlx	isolate:multiisolates\|age:N/A\|sex:pooled male and female\|tissue:heart\|BioSampleModel:Model organism or animal									kdrl GFP cells control 1	0	kdrl GFP cells control 1	SMART SEQ ultra low RNA seq kit Clonetech			RNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 2500	<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>150</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>76</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>	SRP108989	assembly:danRer10	flk_gfp_48hrs_con1_R2.fastq.gz flk_gfp_48hrs_con1_R1.fastq.gz	fastq fastq	1678987200.0	11193248.0	flk gfp 48hrs con1 R2.fastq.gz	0:75 1:75	A:437283407;C:401234553;G:387947515;T:452257282;N:264443	75	75	437283407	401234553	387947515	452257282	264443	SRX2902574	SRS2269173	SRA573518	BRFAA\|Molecular Biology	BRFAA	2	0.91593	0.91737	0.08937	0.08988	0.75607	0.75696	0.50103	0.45539	75	75	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown	Greece	2017-06-13	Undetermined	Undetermined	Heart	Cardiovascular System
42499	42499	SRR5666985	SRX2902571	SRS2269173	SRP108989	PRJNA390119	HLX & Hematopoiesis	PRJNA390119	Other	HLX & Hematopoiesis			rnaseq and atacseq	hlx hematopoiesis	hlx	isolate:multiisolates\|age:N/A\|sex:pooled male and female\|tissue:heart\|BioSampleModel:Model organism or animal									fli GFP cells hHLXOE rep 2	5	fli GFP cells hHLXOE rep 2	SMART SEQ ultra low RNA seq kit Clonetech			RNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 2500	<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>150</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>76</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>	SRP108989	assembly:danRer10	fli_gal4_uas_hlx_endo_48h_s2_R2.fastq.gz fli_gal4_uas_hlx_endo_48h_s2_R1.fastq.gz	fastq fastq	4490898450.0	29939323.0	fli gal4 uas hlx endo 48h s2 R2.fastq.gz	0:75 1:75	A:870349076;C:1346136891;G:1401796534;T:869066463;N:3549486	75	75	870349076	1346136891	1401796534	869066463	3549486	SRX2902571	SRS2269173	SRA573518	BRFAA\|Molecular Biology	BRFAA	2	0.5714	0.57344	0.27957	0.28321	0.85102	0.85342	0.53304	0.53368	75	75	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown	Greece	2017-06-13	Undetermined	Undetermined	Heart	Cardiovascular System
42500	42500	SRR5666986	SRX2902570	SRS2269173	SRP108989	PRJNA390119	HLX & Hematopoiesis	PRJNA390119	Other	HLX & Hematopoiesis			rnaseq and atacseq	hlx hematopoiesis	hlx	isolate:multiisolates\|age:N/A\|sex:pooled male and female\|tissue:heart\|BioSampleModel:Model organism or animal									fli GFP cells hHLXOE rep 1	4	fli GFP cells hHLXOE rep 1	SMART SEQ ultra low RNA seq kit Clonetech			RNA-Seq	TRANSCRIPTOMIC	size fractionation	PAIRED	ILLUMINA	Illumina HiSeq 2500	<SPOT_DESCRIPTOR><SPOT_DECODE_SPEC><SPOT_LENGTH>150</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>76</BASE_COORD></READ_SPEC></SPOT_DECODE_SPEC></SPOT_DESCRIPTOR>	SRP108989	assembly:danRer10	fli_gal4_uas_hlx_endo_48h_s1_R1.fastq.gz fli_gal4_uas_hlx_endo_48h_s1_R2.fastq.gz	fastq fastq	3459602100.0	23064014.0	fli gal4 uas hlx endo 48h s1 R1.fastq.gz	0:75 1:75	A:658343595;C:1050309687;G:1097759573;T:650443491;N:2745754	75	75	658343595	1050309687	1097759573	650443491	2745754	SRX2902570	SRS2269173	SRA573518	BRFAA\|Molecular Biology	BRFAA	2	0.57077	0.57481	0.2173	0.2185	0.79553	0.79762	0.50405	0.48708	75	75	B	B	biological fallback assumption	illumina	hiseq_era	unknown	size_fractionation	unknown	bulk	unknown	unknown	Greece	2017-06-13	Undetermined	Undetermined	Heart	Cardiovascular System

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CREATE TABLE run_metadata("run.accession" VARCHAR, "experiment.accession" VARCHAR, "sample.accession" VARCHAR, "study.accession" VARCHAR, bioproject VARCHAR, "study.title" VARCHAR, "study.alias" VARCHAR, "study.type" VARCHAR, "study.abstract" VARCHAR, "study.attributes" VARCHAR, "study.PMIDs" VARCHAR, "sample.description" VARCHAR, "sample.title" VARCHAR, "sample.alias" VARCHAR, "sample.centername" VARCHAR, "sample.attributes" VARCHAR, "GEOsample.title" VARCHAR, "GEOsample.dataprocessing" VARCHAR, "GEOsample.source" VARCHAR, "GEOsample.treatmentprotocol" VARCHAR, "GEOsample.extractprotocol" VARCHAR, "GEOsample.growthprotocol" VARCHAR, "GEOsample.characteristics" VARCHAR, "GEOsample.accession" VARCHAR, "experiment.title" VARCHAR, "experiment.alias" VARCHAR, "experiment.library_name" VARCHAR, "experiment.design_description" VARCHAR, "experiment.library_construction_protocol" VARCHAR, "experiment.attributes" VARCHAR, "experiment.library_strategy" VARCHAR, "experiment.library_source" VARCHAR, "experiment.library_selection" VARCHAR, "experiment.library_layout" VARCHAR, "experiment.platform" VARCHAR, "experiment.instrument_model" VARCHAR, "experiment.spot_descriptor" VARCHAR, "experiment.study_ref" VARCHAR, "run.title" VARCHAR, "run.attributes" VARCHAR, "run.filename" VARCHAR, "run.semantic_name" VARCHAR, "run.total_bases" DOUBLE, "run.total_spots" DOUBLE, "run.alias" VARCHAR, "run.read_lengths" VARCHAR, "run.base_counts" VARCHAR, "run.r1_length" BIGINT, "run.r2_length" BIGINT, "run.r3_length" BIGINT, "run.r4_length" BIGINT, "run.Acount" BIGINT, "run.Ccount" BIGINT, "run.Gcount" BIGINT, "run.Tcount" BIGINT, "run.Ncount" BIGINT, "run.experiment" VARCHAR, "run.pool_member" VARCHAR, "submission.accession" VARCHAR, "submission.srasource" VARCHAR, "submission.bioprojectsource" VARCHAR, "seqdetective.n_mates" BIGINT, "seqdetective.mapping_rate.mate1" DOUBLE, "seqdetective.mapping_rate.mate2" DOUBLE, "seqdetective.nofeature_rate.mate1" DOUBLE, "seqdetective.nofeature_rate.mate2" DOUBLE, "seqdetective.sparsity.mate1" DOUBLE, "seqdetective.sparsity.mate2" DOUBLE, "seqdetective.pos_strand_rate.mate1" DOUBLE, "seqdetective.pos_strand_rate.mate2" DOUBLE, "seqdetective.readlen.mate1" BIGINT, "seqdetective.readlen.mate2" BIGINT, "seqdetective.judgement.mate1" VARCHAR, "seqdetective.judgement.mate2" VARCHAR, "seqdetective.judgement.reason" VARCHAR, platform_family VARCHAR, instrument_generation VARCHAR, read_bias VARCHAR, selection_class VARCHAR, prep_kit VARCHAR, sc_or_bulk VARCHAR, tech_class VARCHAR, technology VARCHAR, tech_variant VARCHAR, "submission.bioprojectsource.country" VARCHAR, earliest_date DATE, devstage_curation VARCHAR, devstage_curation_coarse VARCHAR, tissue_curation VARCHAR, tissue_curation_coarse VARCHAR);;
CREATE INDEX idx_run_bioproject ON run_metadata(bioproject);;
CREATE INDEX idx_run_run_accession ON run_metadata("run.accession");;