Identifying signals of positive selection in Peruvian populations

Abstract

Since our origin in Africa, humans have colonise d very diverse environments and confronted distinctive selective pressures that have left traceable signatures across the human genome. Perú is an extremely diverse country, hosting three main ecologically differentiated regions or ecozones: the desert Pacific coast, the Andean highlands and the Amazonian jungle. Our goal is to elucidate novel insights into the adaptive allelic variants and phenotypes that favoured adaptation to the different environments of the three Peruvian ecozones. To do so, we count on a geographically extensive dataset that includes 155 samples from 23 Peruvian populations genotyped with Illumina Infinium® Multi-Ethnic Global Array (MEGA; 1,779,819 SNPs). Global ancestry analyses, including principal component and admixture analyses, were performed to infer population structure and individual ancestry fractions. Broadly, the Native American ancestry component predominantes in all Peruvian populations but especially in the highland ones. On the contrary, only a small fraction of European ancestry component is present mostly in the Amazonian and coastal populations, where some African ancestry component can be appreciated. Signals of positive selection according to the hard sweep model were investigated using tests based on population differentiation (Fixation index [Fst] and Population Branch Statistic [PBS]) and on linkage disequilibrium (integrated Haplotype Score [iHS] and cross-population Extended Haplotype Homozygosity [XP-EHH]). As for signals of polygenic selection, we computed SUMSTAT to check whether particular pathways and gene sets show stronger selection signals than randomly generated gene sets. Preliminary results of tests comparing highland to lowland populations (including the coast and jungle ecozones) confirm previously described candidate genes for adaptation to hypoxia, such as NOS2, BRINP3, EPAS1, FADS2, TGFA and ULBP1. Similarly, several pathways (REACTOME, KEGG) and GO terms associated to cardiovascular health were confirmed to be involved in high-altitude adaptation. Currently, we are investigating the selection signals specific to the Amazonian jungle and desert Pacific coast ecozone.