Genome Research · 2016 · 97 citations · 59 references
Life SciencesGeneticsMolecular GeneticsGenomic Data AnalysisGenomicsMedical GeneticsDna SequencingGenome RearrangementSingle-cell GenomicsStructural Variant AnalysisVariant AnalysisVariant DetectionChromosome RearrangementsGenomic RearrangementsIntrachromosomal RearrangementsSingle-cell Dna SequencingSingle-cell Genome SequencingSingle-cell Genomic Heterogeneity AnalysisStructural Chromosomal RearrangementsStructural Rearrangement Detection
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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