<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Arnaud BONNAFFOUX</submitter><organism>Homo sapiens</organism><software>CellRanger</software><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16083</full_dataset_link><description>We previously demonstrated that iPSCs derived from a DMD patient and subjected to myogenic differentiation acquire a distinct transcriptomic profile from healthy controls. We observed a branched trajectory with an unbalanced distribution of Healthy and DMD cells on the two daughter branches. While each branch contained 86% of cells from a single line (either Healthy or DMD), we still observed 14% of cells from the other genetic background. This indicates that the choice between the two genetic states is probabilistic and does not strictly depend on the presence of the DMD mutation.  In the present study, we hypothesize that cell fate choice at the bifurcation point is governed by a GRN. To gain insight into the molecular events directly downstream of the mutation, we generated more resolutive scRNA-Seq data around the bifurcation point. We subjected WT and mutant iPS cells to directed myogenic differentiation and we used Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-Seq) to barcode cells collected at 8 time points spanning the bifurcation window between Day 5 and Day 14.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - A total of 20000 cells per pool were loaded on the Chromium Next Controller using the Chromium Next GEM Single Cell 3ʹ GEM, Library &amp; Gel Bead Kit v3.1 (PN-1000121, 10x genomics, Pleasanton, USA).</sample_protocol><sample_protocol>Library Construction - We followed the supplier’s user guide CG000206 Rev D and generated 3’GEX and Cell Surface (CS) libraries using 3’ feature barcode kit (PN-1000079) during pre-amplification step. For PCR index, we used Single Index Kit T Set A, 96 rxns PN-1000213 for 3’GEX CS. All libraries were checked on a Bioanalyzer with a High Sensitivity chip (Caliper Perkin Elmer, Waltham, USA). As expected, 3’ GEX libraries peaked around 350pb and CS at 220pb</sample_protocol><sample_protocol>Sample Collection - Cells were filtered at 70µM and washed (500g, 5min, 4°C) in PBS then counted and checked for viability. They were resuspended in 100 uL of staining buffer (1xPBS with 2%BSA, 0,01% Tween20, 0,22µM filtered) and incubated with 10 µL human FcR blocking reagent (Miltenyi Biotec 130-059-901) for 10 min on ice. 1 µL of anti-human Totalseq-B Hashtag oligonucleotides antibodies (HTOs) (Biolegend, San Diego, USA) were assigned to each sample and incubated for 30 min on ice. Tagged cells were then washed three times in 1mL of staining buffer (500g, 5min, 4°C). Cells were counted and checked for viability, then pooled in equal proportions per sample. The viability of the pools varied between 71-98%.</sample_protocol><sample_protocol>Sequencing - Libraries were then sequenced on a Illumina NOVAseq 6000 (Illumina, San Diego, USA), on a 100-cycle S1 v1.5 flow cell kit (Illumina) with the R1-29pb/i5-0pb/i7-8pb /R2-93pb running program at the Genomic Atlantic (GenoA) platform (IRS-UN, CHU Nantes, France). To associate the sample to each bar code we use this approach: https://www.10xgenomics.com/support/software/cell-ranger/latest/getting-started/cr-3p-what-is-cellplex#antibody-capture</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - No normalization was performed on the raw data submitted</data_protocol><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq 6000</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Homo sapiens</species><pubmed_authors>Arnaud BONNAFFOUX</pubmed_authors></additional><is_claimable>false</is_claimable><name>scRNAseq from iPSC lines derived from a healthy donor and a DMD patient differentiated into the myogenic lineage</name><description>We previously demonstrated that iPSCs derived from a DMD patient and subjected to myogenic differentiation acquire a distinct transcriptomic profile from healthy controls. We observed a branched trajectory with an unbalanced distribution of Healthy and DMD cells on the two daughter branches. While each branch contained 86% of cells from a single line (either Healthy or DMD), we still observed 14% of cells from the other genetic background. This indicates that the choice between the two genetic states is probabilistic and does not strictly depend on the presence of the DMD mutation.  In the present study, we hypothesize that cell fate choice at the bifurcation point is governed by a GRN. To gain insight into the molecular events directly downstream of the mutation, we generated more resolutive scRNA-Seq data around the bifurcation point. We subjected WT and mutant iPS cells to directed myogenic differentiation and we used Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-Seq) to barcode cells collected at 8 time points spanning the bifurcation window between Day 5 and Day 14.</description><dates><release>2026-06-01T00:00:00Z</release><modification>2026-06-01T01:00:57.981Z</modification><creation>2025-11-11T16:34:15.138Z</creation></dates><accession>E-MTAB-16083</accession><cross_references><ENA>ERP184221</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>