Human lineage tracing enabled by mitochondrial mutations and single cell genomics [TF1_clones_ATAC]
UID: 10883
- Description
- Summary from GEO:
"Lineage tracing provides unprecedented insights into the fate of individual cells and their progeny in complex organisms. While effective genetic approaches have been developed in vitro and in animal models, these cannot be used to interrogate human physiology in vivo. Instead, naturally occurring somatic mutations have been utilized to infer clonality and lineal relationships between cells in human tissues, but current approaches are limited by high error rates and scale, and provide little information about the state or function of the cells. Here, we show how somatic mutations in mitochondrial DNA (mtDNA) can be tracked by current single cell RNA-Seq (scRNA-Seq) or single cell ATAC-Seq (scATAC-Seq) for simultaneous analysis of single cell lineage and state. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their use as clonal markers to infer lineal relationships. We trace the lineage of human cells by somatic mtDNA mutations in a native context both in vitro and in vivo, and relate it to expression profiles and chromatin accessibility. Our approach should allow lineage tracing at a 100- to 1,000-fold greater scale than with single cell whole genome sequencing, while providing information on cell state, opening the way to chart detailed cell lineage and fate maps in human health and disease.
A variety of experimental designs using cells derived from both in vitro and in vivo to determine the efficacy of using mtDNA mutations in human clonal tracing."
Overall design from GEO:
"TF1 (sub-)clones were clonally derived by single cell sorting in an iterative manner and expanded before processing each clone with bulk ATAC-seq. Sample names reflect the clonal lineage order."
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Access via GEO
Accession #: GSE115208Access via BioProject
Accession #: PRJNA474186Access via SRA
Accession #: SRP149534 - Access Restrictions
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Free to All
- Access Instructions
- The NCBI Gene Expression Omnibus, SRA and BioProject databases provide open access to these files.
- Associated Publications
- Equipment Used
- Dataset Format(s)
- CSV, TSV, BED
- Dataset Size
- 3 KB (CSV), 4.1 KB (TSV), 3.7 MB (TSV),
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