4.8 Article

Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling

Journal

NATURE BIOTECHNOLOGY
Volume 39, Issue 4, Pages 451-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41587-020-0645-6

Keywords

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Funding

  1. National Institutes of Health [F31 CA232670, R01 CA208756, P01 CA206978, U10 CA180861, R01 DK103794, R33 HL120791]
  2. New York Stem Cell Foundation (NYSCF)
  3. Howard Hughes Medical Institute
  4. Klarman Cell Observatory
  5. Kay Kendall Leukaemia Fund
  6. German Research Foundation (DFG)
  7. Stand Up To Cancer Peggy Prescott Early Career Scientist Award in Colorectal Cancer Research
  8. Paul C. Zamecnick chair
  9. Allen Distinguished Investigator Program

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This study combines ATAC-seq and mitochondrial DNA sequencing to reveal clonal variation in human cells and tissues. It enables the inference of clonal relationships, mtDNA heteroplasmy, and chromatin variability in individual cells, linking epigenomic variability to subclonal evolution and cellular dynamics in vivo. Overall, this approach allows for the study of cellular population dynamics and clonal properties in vivo.
Combining droplet-based ATAC-seq and mitochondrial DNA sequencing reveals clonal variation in human cells and tissues. Natural mitochondrial DNA (mtDNA) mutations enable the inference of clonal relationships among cells. mtDNA can be profiled along with measures of cell state, but has not yet been combined with the massively parallel approaches needed to tackle the complexity of human tissue. Here, we introduce a high-throughput, droplet-based mitochondrial single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), a method that combines high-confidence mtDNA mutation calling in thousands of single cells with their concomitant high-quality accessible chromatin profile. This enables the inference of mtDNA heteroplasmy, clonal relationships, cell state and accessible chromatin variation in individual cells. We reveal single-cell variation in heteroplasmy of a pathologic mtDNA variant, which we associate with intra-individual chromatin variability and clonal evolution. We clonally trace thousands of cells from cancers, linking epigenomic variability to subclonal evolution, and infer cellular dynamics of differentiating hematopoietic cells in vitro and in vivo. Taken together, our approach enables the study of cellular population dynamics and clonal properties in vivo.

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