Exploiting selection at linked sites to infer the rate and strength of adaptation

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3