10.5061/DRYAD.C866T1G3T
Cornetti, Luca
0000-0002-7188-4048
University of Basel
Tschirren, Barbara
0000-0003-4806-4102
University of Exeter
Combining GWAS and FST-based approaches to identify targets of
Borrelia-mediated selection in natural rodent hosts
Dryad
dataset
2020
Disease Biology
Host Parasite Interactions
Natural Selection and Contemporary Evolution
University of Zurich
https://ror.org/02crff812
Baugarten Zürich Stiftung
https://ror.org/058fjhm66
2020-03-18T00:00:00Z
2020-03-18T00:00:00Z
en
https://doi.org/10.1111/mec.15410
66385766 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.