Single cell lineage tracing by endogenous mitochondrial DNA mutations in ATAC-seq data
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA505667 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8191730_1.fastq.gz | Fastqsanger.gz | |||
| SRR8191730_2.fastq.gz | Fastqsanger.gz | |||
| SRR8191740_1.fastq.gz | Fastqsanger.gz | |||
| SRR8191740_2.fastq.gz | Fastqsanger.gz | |||
| SRR8191750_1.fastq.gz | Fastqsanger.gz |
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Project description:Simultaneous measurement of lineage relationship and information on cell fate is desireable for human tissues. Here we describe a new strategy to track cell lineage using endogenous mitochondrial DNA variants in ATAC-seq data, which simultaneously measures the chromatin profiling. We first provide a proof of principle that somatic mutations in the mitochondrial genome can be used as a genetic marker to depict cellular lineage relationships and further quantified the power of lineage definition with these genetic markers. Using this method, we demonstrated the genetic and epigenetic heterogeneity of hematopoietic stem cells from patient with acute myeloid leukemia.
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Project description:Simultaneous measurement of lineage relationship and information on cell fate is desireable for human tissues. Here we describe a new strategy to track cell lineage using endogenous mitochondrial DNA variants in ATAC-seq data, which simultaneously measures the chromatin profiling. We first provide a proof of principle that somatic mutations in the mitochondrial genome can be used as a genetic marker to depict cellular lineage relationships and further quantified the power of lineage definition with these genetic markers. Using this method, we demonstrated the genetic and epigenetic heterogeneity of hematopoietic stem cells from patient with acute myeloid leukemia.
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Project description: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.
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