Author:
Uricchio Lawrence H.,Petrov Dmitri A.,Enard David
Abstract
Genomic data encodes past evolutionary events and has the potential to reveal the strength, rate, and biological drivers of adaptation. However, robust estimation of adaptation rate (α) and adaptation strength remains a challenging problem because evolutionary processes such as demography, linkage, and non-neutral polymorphism can confound inference. Here, we exploit the influence of background selection to reduce the fixation rate of weakly-beneficial alleles to jointly infer the strength and rate of adaptation. We develop a novel MK-based method (ABC-MK) to infer adaptation rate and strength, and estimate α = 0.135 in human protein-coding sequences, 72% of which is contributed by weakly adaptive variants. We show that in this adaptation regime α is reduced ≈ 25% by linkage genome-wide. Moreover, we show that virus-interacting proteins (VIPs) undergo adaptation that is both stronger and nearly twice as frequent as the genome average (α = 0.224, 56% due to strongly-beneficial alleles). Our results suggest that while most adaptation in human proteins is weakly-beneficial, adaptation to viruses is often strongly-beneficial. Our method provides a robust framework for estimating adaptation rate and strength across species.
Publisher
Cold Spring Harbor Laboratory
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献