Abstract

Over the last several hundred years, donkeys have adapted to high-altitude conditions on the Tibetan Plateau. Interestingly, the kiang, a closely related equid species, also inhabits this region. Previous reports have demonstrated the importance of specific genes and adaptive introgression in divergent lineages for adaptation to hypoxic conditions on the Tibetan Plateau. Here, we assessed whether donkeys and kiangs adapted to the Tibetan Plateau via the same or different biological pathways and whether adaptive introgression has occurred. We assembled a de novo genome from a kiang individual and analyzed the genomes of five kiangs and 93 donkeys (including 24 from the Tibetan Plateau). Our analyses suggested the existence of a strong hard selective sweep at the EPAS1 locus in kiangs. In Tibetan donkeys, however, another gene, i.e., EGLN1, was likely involved in their adaptation to high altitude. In addition, admixture analysis found no evidence for interspecific gene flow between kiangs and Tibetan donkeys. Our findings indicate that despite the short evolutionary time scale since the arrival of donkeys on the Tibetan Plateau, as well as the existence of a closely related species already adapted to hypoxia, Tibetan donkeys did not acquire adaptation via admixture but instead evolved adaptations via a different biological pathway.

Highlights

  • Expression profile analysis of Positively selected genes (PSGs) in kiang using human expression data As it is difficult to obtain expression data for kiangs, we used publicly available human expression data to examine the expression patterns of genes that are positively selected in kiangs

  • Using the same methodology, we found no evidence of positive selection at EPAS1 in the Tibetan donkey and no evidence that it was affected by adaptive admixture from the kiang

  • We assembled a draft de novo genome of the kiang and performed large-scale re-sequencing of kiang and domestic donkey genomes

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Summary

Introduction

Expression profile analysis of PSGs in kiang using human expression data As it is difficult to obtain expression data for kiangs, we used publicly available human expression data to examine the expression patterns of genes that are positively selected in kiangs. Analysis was performed as described in our previous study (Li et al, 2013). Human gene expression data (Human U133A Gene Atlas) from 84 tissues or cells were downloaded from BioGPS (Wu et al, 2016) (http://biogps.org/#goto= welcome) with the GEO code GSE1133. To avoid bias expression in different tissues, the expression levels of PSGs were normalized by dividing each tissue value by the average whole-genome expression level. The top 10 tissues/cell lines are presente

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