4.7 Article

Characterizing polymorphic inversions in human genomes by single-cell sequencing

Journal

GENOME RESEARCH
Volume 26, Issue 11, Pages 1575-1587

Publisher

COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.201160.115

Keywords

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Funding

  1. University of British Columbia
  2. Natural Science and Engineering Research Council
  3. Canadian Institutes of Health Research [RMF-92093]
  4. US National Institutes of Health [R01GM094146]
  5. Canadian Cancer Society
  6. Terry Fox Foundation [018006, 105265]
  7. European Research Council (ERC Grant) [294740]
  8. European Research Council (ERC) [294740] Funding Source: European Research Council (ERC)

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Identifying genomic features that differ between individuals and cells can help uncover the functional variants that drive phenotypes and disease susceptibilities. For this, single-cell studies are paramount, as it becomes increasingly clear that the contribution of rare but functional cellular subpopulations is important for disease prognosis, management, and progression. Until now, studying these associations has been challenged by our inability to map structural rearrangements accurately and comprehensively. To overcome this, we coupled single-cell sequencing of DNA template strands (Strand-seq) with custom analysis software to rapidly discover, map, and genotype genomic rearrangements at high resolution. This allowed us to explore the distribution and frequency of inversions in a heterogeneous cell population, identify several polymorphic domains in complex regions of the genome, and locate rare alleles in the reference assembly. We then mapped the entire genomic complement of inversions within two unrelated individuals to characterize their distinct inversion profiles and built a nonredundant global reference of structural rearrangements in the human genome. The work described here provides a powerful new framework to study structural variation and genomic heterogeneity in single-cell samples, whether from individuals for population studies or tissue types for biomarker discovery.

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