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. 2022 Aug 4;17(8):e0271767.
doi: 10.1371/journal.pone.0271767. eCollection 2022.

Identifying signatures of natural selection in Indian populations

Affiliations

Identifying signatures of natural selection in Indian populations

Marla Mendes et al. PLoS One. .

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Schematic representation of the approach to identify putative selective regions.
We applied six different methods to identify outliers (top 1% results) and selected regions that were observed in all population groups and were outliers for at least two independent methods. Additionally, we performed analyses using a novel coalescence-based method implemented in the program ASMC.
Fig 2
Fig 2. Overview of our results.
A) Distribution of the number of regions identified for each chromosome; B) Distribution of the number of genes located within putative selective regions identified with two or three methods for each chromosome, for all thresholds (1%, 0.5% and 0.1%).
Fig 3
Fig 3. Ascertained Sequentially Markovian Coalescent (ASMC) results for chromosome 13.
Showing with a greater resolution the region including the gene GPC5 where the highest enrichment in recent coalescence events is concentrated on this chromosome.

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