Title
Identifying signatures of natural selection in Indian populations
Date Issued
01 August 2022
Access level
open access
Resource Type
journal article
Author(s)
Mendes M.
Jonnalagadda M.
Ozarkar S.
Torres F.C.L.
Pua V.B.
Kendall C.
Parra E.J.
Universidade Federal de Minas Gerais
Publisher(s)
Public Library of Science
Abstract
In this study, we present the results of a genome-wide scan for signatures of positive selection using data from four tribal groups (Kokana, Warli, Bhil, and Pawara) and two caste groups (Deshastha Brahmin and Kunbi Maratha) from West of the Maharashtra State In India, as well as two samples of South Asian ancestry from the 1KG project (Gujarati Indian from Houston, Texas and Indian Telugu from UK). We used an outlier approach based on different statistics, including PBS, xpEHH, iHS, CLR, Tajima’s D, as well as two recently developed methods: Graph-aware Retrieval of Selective Sweeps (GRoSS) and Ascertained Sequentially Markovian Coalescent (ASMC). In order to minimize the risk of false positives, we selected regions that are outliers in all the samples included in the study using more than one method. We identified putative selection signals in 107 regions encompassing 434 genes. Many of the regions overlap with only one gene. The signals observed using microarray-based data are very consistent with our analyses using high-coverage sequencing data, as well as those identified with a novel coalescence-based method (ASMC). Importantly, at least 24 of these genomic regions have been identified in previous selection scans in South Asian populations or in other population groups. Our study highlights genomic regions that may have played a role in the adaptation of anatomically modern humans to novel environmental conditions after the out of Africa migration.
Volume
17
Issue
8 August
Language
English
OCDE Knowledge area
Antropología
Scopus EID
2-s2.0-85135428015
PubMed ID
Source
PLoS ONE
ISSN of the container
19326203
Sponsor(s)
MM was supported by a Mitacs Globalink Research Award (FR37903) and by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (88887.474324/2020-00), FCLT was supported by Fundacao de Amparo da Pesquisa do Estado de Minas Gerais (FAPEMIG), CK was supported by a SSHRC insight grant to B Viola, ETS was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) from Brazil and EJP has received funding from the Canadian Natural Sciences and Engineering Research Council (NSERC Discovery Grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funding:MMwassupportedbyaMitacsGlobalink ResearchAward(FR37903)andbyCoordenac ¸ão de Aperfeic ¸oamento de Pessoal de Nı ´ vel Superior (CAPES)(88887.474324/2020-00),FCLTwas supportedbyFundacaodeAmparodaPesquisado EstadodeMinasGerais(FAPEMIG),CKwas supportedbyaSSHRCinsightgranttoBViola,ET-SwassupportedbyConselhoNacionalde Desenvolvimento Cientı ´ fico e Tecnolo ´ gico (CNPq) fromBrazilandEJPhasreceivedfundingfromthe
Sources of information: Directorio de Producción Científica Scopus