4.8 Article

Mitochondrial variant enrichment from high-throughput single-cell RNA sequencing resolves clonal populations

期刊

NATURE BIOTECHNOLOGY
卷 40, 期 7, 页码 1030-+

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NATURE PORTFOLIO
DOI: 10.1038/s41587-022-01210-8

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资金

  1. Ludwig Center at Harvard
  2. Harvard Medical School Epigenetics & Gene Dynamics Initiative
  3. National Institutes of Health (NIH) R00 Award [CA218832]
  4. Gilead Sciences
  5. Bertarelli Rare Cancers Fund
  6. Glenn Foundation for Medical Research
  7. American Federation for Aging Research (AFAR) Grant
  8. American Brain Tumor Association Basic Research Fellowship
  9. UK Brain Tumour Charities Future Leaders Award [GN-000701]
  10. Stanford Science Fellowship
  11. Parker Scholar award
  12. NIH [U01CA260852, R01 DK103794]
  13. Cancer Research Institute Technology Impact Award
  14. Pew-Stewart Scholars for Cancer Research Award
  15. German Research Foundation [LU 2336/2-1]
  16. National Cancer Institute [P30-CA14051]
  17. Koch Institute-Dana-Farber/Harvard Cancer Center Bridge Project
  18. Food Allergy Science Initiative at the Broad Institute
  19. New York Stem Cell Foundation

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The combination of single-cell transcriptomics and mitochondrial DNA variant detection is useful for establishing lineage relationships in primary human cells, but current methods are not suitable for analyzing complex tissues. In this study, researchers combined common 3' single-cell RNA-sequencing protocols with mitochondrial transcriptome enrichment to significantly increase coverage and enable high-confidence mutation detection. This method successfully identified skewed immune cell expansions in primary human clonal hematopoiesis.
The combination of single-cell transcriptomics with mitochondrial DNA variant detection can be used to establish lineage relationships in primary human cells, but current methods are not scalable to interrogate complex tissues. Here, we combine common 3' single-cell RNA-sequencing protocols with mitochondrial transcriptome enrichment to increase coverage by more than 50-fold, enabling high-confidence mutation detection. The method successfully identifies skewed immune-cell expansions in primary human clonal hematopoiesis.

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