Abstract
Mechanisms of host-parasite co-adaptation have long been of interest in evolutionary biology; however, determining the genetic basis of parasite resistance has been challenging. Current advances in genome technologies provide new opportunities for obtaining a genome-scale view of the action of parasite-driven natural selection in wild populations and thus facilitate the search for specific genomic regions underlying inter-population differences in pathogen response. European populations of Atlantic salmon (Salmo salar L.) exhibit natural variance in susceptibility levels to the ectoparasite Gyrodactylus salaris Malmberg 1957, ranging from resistance to extreme susceptibility, and are therefore a good model for studying the evolution of virulence and resistance. However, distinguishing the molecular signatures of genetic drift and environment-associated selection in small populations such as land-locked Atlantic salmon populations presents a challenge, specifically in the search for pathogen-driven selection. We used a novel genome-scan analysis approach that enabled us to i) identify signals of selection in salmon populations affected by varying levels of genetic drift and ii) separate potentially selected loci into the categories of pathogen (G. salaris)-driven selection and selection acting upon other environmental characteristics. A total of 4631 single nucleotide polymorphisms (SNPs) were screened in Atlantic salmon from 12 different northern European populations. We identified three genomic regions potentially affected by parasite-driven selection, as well as three regions presumably affected by salinity-driven directional selection. Functional annotation of candidate SNPs is consistent with the role of the detected genomic regions in immune defence and, implicitly, in osmoregulation. These results provide new insights into the genetic basis of pathogen susceptibility in Atlantic salmon and will enable future searches for the specific genes involved.
Highlights
Parasites are considered to be among the strongest selective forces driving the evolution of host populations
By identifying loci detected as outliers in several analysis designs, i.e., overlapping loci, we aimed to avoid the detection of false positives and to pinpoint genomic regions that have a higher probability of being affected by either parasitedriven or salinity-driven selection
The remaining two genomic regions we identified were not identified in the QTL study of Norman et al, [118], this is perhaps not surprising given that North American Atlantic salmon were used in their study, as opposed to European populations in the current study, because the North American and European lineages are thought to have diverged more than one million years ago and include differences in chromosome number [35,121,122]
Summary
Parasites are considered to be among the strongest selective forces driving the evolution of host populations (reviewed by [1,2]). Given that novel pathogens tend to increasingly emerge in natural populations due to environmental changes [8] and human-related activities [9], understanding the mechanisms underlying the formation of host adaptation is of utmost importance. Recent developments in genomic technologies have enabled genome-wide scale approaches for the identification of genes and gene networks affected by natural selection [14,15,16]. These approaches have been used in the immunological research of wild species, including salmon microarray studies (see below)
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