CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data

Abstract

AbstractTo 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 (a) most published genomes being <1 × coverage, (ii) ancient DNA fragments being typically <80 bps. These characteristics preclude state-of-the-art CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, an algorithm tailored for genotyping deletion and duplication events in genomes with low depths of coverage. Simulations show that CONGA can genotype deletions and duplications >1 Kbps with F-scores >0.77 and >0.82 at ≥ 0.5 ×, respectively. Further, down-sampling experiments using published ancient BAM files reveal that >1 Kbps deletions could be genotyped at F-score >0.75 at ≥ 1 × coverage. Using CONGA, we analyse deletion events at 10,018 loci in 56 ancient human genomes spanning the last 50,000 years, with coverages 0.4× -26 ×. We find inter-individual genetic diversity measured using deletions and SNPs to be highly correlated, suggesting that deletion frequencies broadly reflect demographic history. We also identify signatures of purifying selection on deletions, such as an excess of singletons compared to those in SNPs. CONGA paves the way for systematic studies of drift, mutation load, and adaptation in ancient and modern-day gene pools through the lens of CNVs.