Combining GWAS and FST-based approaches to identify targets of Borrelia-mediated selection in natural rodent hosts
Cornetti, L; Tschirren, B
Date: 12 March 2020
Journal
Molecular Ecology
Publisher
Wiley
Publisher DOI
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Abstract
Recent advances in high-throughput sequencing technologies provide opportunities to gain novel insights into the genetic basis of phenotypic trait variation. Yet to date, progress in our understanding of genotype-phenotype associations in non-model organisms in general and natural vertebrate populations in particular has been hampered ...
Recent advances in high-throughput sequencing technologies provide opportunities to gain novel insights into the genetic basis of phenotypic trait variation. Yet to date, progress in our understanding of genotype-phenotype associations in non-model organisms in general and natural vertebrate populations in particular has been hampered by small sample sizes typically available for wildlife populations and a resulting lack of statistical power, as well as a limited ability to control for false positive signals. Here we propose to combine a genome-wide association (GWAS) and FST-based approach with population-level replication to partly overcome these limitations. We present a case study in which we used this approach in combination with Genotyping-by-Sequencing (GBS) SNP data to identify genomic regions associated with Borrelia afzelii resistance or susceptibility in the natural rodent host of this Lyme disease-causing spirochete, the bank vole (Myodes glareolus). Using this combined approach we identified four consensus SNPs located in exonic regions of the genes Slc26a4, Tns3, Wscd1 and Espnl, which were significantly associated with the voles’ Borrelia infectious status within and across populations. Functional links between host responses to bacterial infections and most of these genes have previously been demonstrated in other rodent systems, making them promising new candidates for the study of evolutionary host responses to Borrelia emergence. Our approach is applicable to other systems and may facilitate the identification of genetic variants underlying disease resistance or susceptibility, as well as other ecologically relevant traits, in wildlife populations.
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