@article{098cdc8cecaa44829e5ab97ed0e2d268,
title = "Application of a novel haplotype-based scan for local adaptation to study high-altitude adaptation in rhesus macaques",
abstract = "When natural populations split and migrate to different environments, they may experience different selection pressures that can lead to local adaptation. To capture the genomic patterns of a local selective sweep, we develop XP-nSL, a genomic scan for local adaptation that compares haplotype patterns between two populations. We show that XP-nSL has power to detect ongoing and recently completed hard and soft sweeps, and we then apply this statistic to search for evidence of adaptation to high altitude in rhesus macaques. We analyze the whole genomes of 23 wild rhesus macaques captured at high altitude (mean altitude > 4000 m above sea level) to 22 wild rhesus macaques captured at low altitude (mean altitude < 500 m above sea level) and find evidence of local adaptation in the high-altitude population at or near 303 known genes and several unannotated regions. We find the strongest signal for adaptation at EGLN1, a classic target for convergent evolution in several species living in low oxygen environments. Furthermore, many of the 303 genes are involved in processes related to hypoxia, regulation of ROS, DNA damage repair, synaptic signaling, and metabolism. These results suggest that, beyond adapting via a beneficial mutation in one single gene, adaptation to high altitude in rhesus macaques is polygenic and spread across numerous important biological systems.",
author = "Szpiech, {Zachary A.} and Novak, {Taylor E.} and Bailey, {Nick P.} and Stevison, {Laurie S.}",
note = "Funding Information: The authors would like to thank members of the Stevison Lab for helpful discussions, Lawrence Uricchio for helpful comments on early versions of the manuscript, and two very helpful anonymous reviewers. This work was supported by start-up funds from the Department of Biological Sciences at Auburn University (L.S.S.) and the Department of Biology at the Pennsylvania State University (Z.A.S.). Z.A.S. was partially supported by NSF-DEB EAGER No. 1939090 (L.S.S.). Portions of this research were performed on the Pennsylvania State University's Institute for Computational Data Sciences{\textquoteright} Roar supercomputer. Funding Information: The authors would like to thank members of the Stevison Lab for helpful discussions, Lawrence Uricchio for helpful comments on early versions of the manuscript, and two very helpful anonymous reviewers. This work was supported by start‐up funds from the Department of Biological Sciences at Auburn University (L.S.S.) and the Department of Biology at the Pennsylvania State University (Z.A.S.). Z.A.S. was partially supported by NSF‐DEB EAGER No. 1939090 (L.S.S.). Portions of this research were performed on the Pennsylvania State University's Institute for Computational Data Sciences{\textquoteright} Roar supercomputer. Publisher Copyright: {\textcopyright} 2021 The Authors. Evolution Letters published by Wiley Periodicals LLC on behalf of Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEB).",
year = "2021",
month = aug,
doi = "10.1002/evl3.232",
language = "English (US)",
volume = "5",
pages = "408--421",
journal = "Evolution Letters",
issn = "2056-3744",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "4",
}