PLoS Computational BiologyGenomicsPeer-reviewed journal article
CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data
Arda SöyleviD, Sevim Seda ÇokoğluiD, Dilek KoptekiniD, Can AlkaniD, Mehmet SomeliD
Abstract
AO_SCPLOWBSTRACTC_SCPLOWTo date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low coverage (1 kbps with F-scores >0.75 at [≥]1x, and distinguish between heterozygous and homozygous states. We applied CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages 0.44x-26x (median 4x) and read lengths 52-121 bp (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are strongly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 6
- FWCI
- 0.60
- Field percentile
- top 35%
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