Comparative genomics reveals putative evidence for high-elevation adaptation in the American pika (Ochotona princeps)

Abstract

High elevation environments have lower atmospheric oxygen content, reduced temperatures, and higher levels of UV radiation than found at lower elevations. As such, species living at high elevations must overcome these challenges to survive, grow and reproduce. American pikas (Ochotona princeps) are alpine lagomorphs that are habitat specialists typically found at elevations >2000m. Previous research has shown putative evidence for high elevation adaptation, however, investigations to date have been limited to a fraction of the genome. Here, we took a comparative genomics approach to identify putative regions under selection using a chromosomal reference genome assembly for the American pika relative to eight other mammalian species targeted based on phylogenetic relatedness and (dis)similarity in ecology. We first identified orthologous gene groups across species and then extracted groups containing only American pika genes as well as unclustered pika genes to inform functional enrichment analyses; among these, we found 141 enriched terms with many related to hypoxia, metabolism, mitochondrial function/development, and DNA repair. We identified 15 significantly expanded gene families within the American pika across all orthologous gene groups that displayed functionally enriched terms associated with hypoxia adaptation. We further detected 196 positively selected genes, 41 of which have been associated with putative adaptation to hypoxia, cold tolerance, and response to UV following a literature review. In particular, OXNAD1, NRDC, and those genes critical in DNA repair represent important targets for future research to examine their functional implications in the American pika, especially as they may relate to adaptation to rapidly changing environments.

Evaluating genotyping‐in‐thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non‐invasive and archival samples

“…We selected putatively adaptive SNPs from three previously generated datasets: robust NRM outliers (i.e. NRM‐specific SNPs indicated as outliers by two different methods; see Section 2.2.1 and Appendix A ), SNPs annotated to positively selected genes (Sjodin & Russello, 2022 ), and elevation‐associated variants (Schmidt et al., 2021 ). From the set of environmentally‐associated SNPs detected previously within the NRM lineage (see Section 2.2.1 and Appendix A ), we first considered outliers identified within both RDA and LFMM analyses (i.e.…”

“…We identified the genes annotated to these SNPs with the Ensembl VEP (McLaren et al., 2016 ) as described in Section 2.2.2 and investigated them in the literature for evidence of association with climate adaptation, using the search terms in Google Scholar: “[gene symbol]” OR “[full gene name]” “cold stress” OR “cold response” OR “cold resistance” OR “hypoxia” OR “high altitude” OR “UV damage” OR “climate” OR “heat stress” OR “precipitation” OR “water stress.” For each unique gene, we reviewed the top 20 search results; outlier SNPs associated with genes demonstrating a potential link to environmental adaptation were included in the initial panel. We also considered candidate SNPs from positively selected genes (PSGs) originally identified in a comparative genomics study using the reference genomes of American pika and eight other mammal species (Sjodin & Russello, 2022 ). Of these candidate SNPs, only those also independently classified as robust outliers within the NRM lineage or among all lineages (approach described in Appendix A ) were included in the GT‐seq panel.…”

“…For each unique gene, we reviewed the top 20 search results; outlier SNPs associated with genes demonstrating a potential link to environmental adaptation were included in the initial panel. We also considered candidate SNPs from positively selected genes (PSGs) originally identified in a comparative genomics study using the reference genomes of American pika and eight other mammal species (Sjodin & Russello, 2022). Of these candidate SNPs, only those also indepen- First, we extracted DNA from 15 mg of liver tissue for each sample using a Qiagen DNeasy® Blood & Tissue Kit following the manufacturer's protocol with RNAse A treatment.…”

“…We selected putatively adaptive SNPs from three previously generated datasets: robust NRM outliers (i.e. NRM-specific SNPs indicated as outliers by two different methods; see Section 2.2.1 and Appendix A), SNPs annotated to positively selected genes (Sjodin & Russello, 2022), and elevation-associated variants (Schmidt et al, 2021). OR "hypoxia" OR "high altitude" OR "UV damage" OR "climate" OR "heat stress" OR "precipitation" OR "water stress."…”

“…Of the 155 unique genes associated with robust NRM-specific outliers, 72 genes demonstrated a putative link to environmental adaptation, for which 56 unique SNPs were annotated and included in the panel. Four SNPs were associated with both PSGs(Sjodin & Russello, 2022) and robust outliers, including one NRMspecific outlier and three range-wide outliers. For the elevationassociated outlier SNPs fromSchmidt et al (2021), 590 unique SNPs exhibited a significant correlation between allele frequency and elevation using linear (n = 297) or logistic regression (n = 558).…”