{"database": "metadata", "table": "run_metadata", "rows": [[70455, "SRR19859708", "SRX15903236", "SRS13591716", "SRP383719", "PRJNA853194", "The synergistic effect of c Myb hyperactivation and Pu.1 deficiency in inducing Pelger Hu\u00ebt anomaly and promoting sAML transformation", "GSE206979", "Transcriptome Analysis", "Patients with acute myeloid leukemia developed from myelodysplastic syndrome MDS/AML have poor prognosis with more complex genetic mutations. Genomic analyses have shown complex association among mutant genes  including co occurring and mutually exclusive. It has been reported that hyperactivation of MYB or deficiency of PU.1 could induce myeloid preleukemia. The simultaneous abnormal expression of these two proteins has been documented in some AML patients. However  the association of MYB and PU.1 in the pathogenesis of malignant hematopoiesis remains unclear. In this study  we used the c Myb hyperactivation and Pu.1 deficient double strain c mybhyper;pu.1G242D/G242D zebrafish to clarify the synergistic role of c Myb and Pu.1 in promoting MDS/AML development. We found that the c mybhyper;pu.1G242D/G242D mutant displayed excessive expansion and differentiation arrest of neutrophils  and progressed to MDS/AML with a high ratio. Interestingly  a group of poorly differentiated Pelger Hu\u00ebt like neutrophils was identified in c mybhyper;pu.1G242D/G242D maturity and might be associated with MDS/AML progression. Moreover  treated the c mybhyper;pu.1G242D/G242D zebrafish with a combination of the cell cycle inhibitor cytarabine Ara C and the differential inducer all trans retinoic acid ATRA could effectively relieve the leukemic symptoms. Our findings revealed that c Myb hyperactivation and Pu.1 deficiency synergistically induced MDS/AML. Furthermore  c mybhyper;pu.1G242D/G242D zebrafish might serve as a suitable MDS/AML model for drug screening. Overall design: Kidney marrow of the wildtype  c mybhyper  pu.1G242D/G242D  c mybhyper;pu.1G242D/G242D zebrafish were isolated separetely. Blood cells were collected from these tissues by pipetting and filtering and analyzed using scRNAseq.", null, "pubmed:40020188", null, "km  wildtype  replicate 1", "GSM6267520", null, "source name:kidney marrow|development stage:1 year old|tissue:kidney marrow|cell type:blood cells|genotype:wt", "km  wildtype  replicate 1", "10X Genomics Cell Ranger software version 3.1.0 was used to convert raw BCL files to FASTQ files  alignment and counts quantification. Doublet GEMs was achieved by using the tool DoubletFinder v2.0.3 by the generation of artificial doublets  using the PC distance to find each cell\u2019s proportion of artificial k nearest neighbors pANN and ranking them according to the expected number of doublets The cell by gene matrices for each sample were individually imported to Seurat  version 3.1.1 for downstream analysis. Cells with unusually high number of UMIs \u226540000 or mitochondrial gene percent \u226515% were filtered out. We also excluded cells with less than 200 or more than 3500 genes detected. post removing unwanted cells from the dataset  we employed a global scaling normalization method \u201cLogNormalize\u201d that normalizes the gene expression measurements for each cell by the total expression  multiplies this by a scale factor 10 000 by default  and log transforms the results. Seurat embed cells in a shared nearest neighbor SNN graph  with edges drawn between cells via similar gene expression patterns. To partition this graph into highly interconnected quasi cliques or communities  we first constructed the SNN graph based on the euclidean distance in PCA space and refined the edge weights between any two cells based on the shared overlap in their local neighborhoods Jaccard distance. We then cluster cells using the Louvain[6] method to maximize modularity. For visualization of clusters  t distributed Stochastic Neighbor Embedding t SNE were generated using the same PCs. Assembly: GRCz11 Ensembl release 100 Supplementary files format and content: tab separated values files  matrix files", "kidney marrow", null, "Kidney marrow were isolated from 1 year old fish  placed in PBS with 5% fetal bovine serum  triturated by pipet  and filtered through a 40 \u03bcm cell strainer. The cells were counted and the proportion of living cells was calculated. post ensuring that the proportion of living cells was \u226590%  the cell concentration was adjusted to 1 000 cells/\u03bcL. Libraries were generated and sequenced from the cDNAs with Chromium Next GEM Single Cell 3\u2019 Reagent Kits v3.1. Briefly  blood cell suspensions were loaded on a 10X Genomics GemCode Single cell instrument to generates single cell Gel Bead In EMlusion GEMs. Upon dissolution of the Gel Bead in a GEM  primers containing an Illumina\u00ae R1 sequence  a 16 nt 10x Barcode  a 10 nt Unique Molecular Identifier UMI  and a poly dT primer sequence were released and mixed with cell lysate and Master Mix. Barcoded  full length cDNAs were then reverse transcribed from poly adenylated mRNA. The pooled barcoded cDNA was then cleaned up with silane magnetic beads  amplified by PCR to generate sufficient mass for library construction. During the library construction Ilumina R2 primer sequence  paired end constructs with P5 and P7 sequences and a sample index were added.", null, "development stage:1 year old|tissue:kidney marrow|cell type:blood cells|genotype:wt", "GSM6267520", "GSM6267520: km  wildtype  replicate 1; Danio rerio; RNA Seq", "GSM6267520 r1", "GSM6267520", "1", "Kidney marrow were isolated from 1 year old fish  placed in PBS with 5% fetal bovine serum  triturated by pipet  and filtered through a 40 \u03bcm cell strainer. The cells were counted and the proportion of living cells was calculated. post ensuring that the proportion of living cells was \u226590%  the cell concentration was adjusted to 1 000 cells/\u03bcL. Libraries were generated and sequenced from the cDNAs with Chromium Next GEM Single Cell three prime Reagent Kits v3.1. Briefly  blood cell suspensions were loaded on a 10X Genomics GemCode Single cell instrument to generates single cell Gel Bead In EMlusion GEMs. Upon dissolution of the Gel Bead in a GEM  primers containing an Illumina\u00ae R1 sequence  a 16 nt 10x Barcode  a 10 nt Unique Molecular Identifier UMI  and a poly dT primer sequence were released and mixed with cell lysate and Master Mix. Barcoded  full length cDNAs were then reverse transcribed from poly adenylated mRNA. The pooled barcoded cDNA was then cleaned up with silane magnetic beads  amplified by PCR to generate sufficient mass for library construction. During the library construction Ilumina R2 primer sequence  paired end constructs with P5 and P7 sequences and a sample index were added.", null, "RNA-Seq", "TRANSCRIPTOMIC SINGLE CELL", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP383719", null, null, "wildtype_S1_L004_R1_001.fastq.gz wildtype_S1_L004_R2_001.fastq.gz", "fastq fastq", 27767976900.0, 92559923.0, "GSM6267520 r4", "0:150 1:150", "A:10620981494;C:5311554239;G:4991425527;T:6843535693;N:479947", 150, 150, null, null, 10620981494, 5311554239, 4991425527, 6843535693, 479947, "SRX15903236", "SRS13591716", "SRA1444282", "Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology", "Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology", 2, 0.0, 0.90991, 0.0, 0.06382, 1.0, 0.83814, null, 0.46543, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "full_length", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2022-06-27", "Adult", "Adult", "Kidney", "Renal System"]], "columns": ["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"], "primary_keys": ["rowid"], "primary_key_values": ["70455"], "units": {}, "query_ms": 12.479471988626756}