Adaptive and neutral markers both show continent‐wide population structure of mountain pine beetle (Dendroctonus ponderosae)

Abstract

Assessments of population genetic structure and demographic history have traditionally been based on neutral markers while explicitly excluding adaptive markers. In this study, we compared the utility of putatively adaptive and neutral single‐nucleotide polymorphisms (SNPs) for inferring mountain pine beetle population structure across its geographic range. Both adaptive and neutral SNPs, and their combination, allowed range‐wide structure to be distinguished and delimited a population that has recently undergone range expansion across northern British Columbia and Alberta. Using an equal number of both adaptive and neutral SNPs revealed that adaptive SNPs resulted in a stronger correlation between sampled populations and inferred clustering. Our results suggest that adaptive SNPs should not be excluded prior to analysis from neutral SNPs as a combination of both marker sets resulted in better resolution of genetic differentiation between populations than either marker set alone. These results demonstrate the utility of adaptive loci for resolving population genetic structure in a nonmodel organism.

Repurposing population genetics data to discern genomic architecture: A case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae)

“…When filtered for HWE and LD (i.e., FF dataset), PCA results support a north-south geographic division among the sampling locations (Figure 2a), in agreement with prior studies (e.g., Samarasekera et al, 2012;Janes et al, 2014;Batista et al, 2016;Trevoy et al, 2018). As demonstrated in Trevoy et al (2018) (Bleiker, Heron, Braithwaite, & Smith, 2013;Janes et al, 2016).…”

“…These methods are not consistently applied, however, and filtering is evaluated on a case‐by‐case basis depending on research needs and study species (Arnold, Corbet‐Detig, Hartl, & Bomblies, ; Narum, Buerkle, Davey, Miller, & Hohenlohe, ). Although neutral markers are useful for investigations of genetic drift and gene flow, recent work has called into question the value of removing non‐neutral markers in SNP assays (Batista, Janes, Boone, Murray, & Sperling, ; Helyar et al, ). Likewise, filtering out repetitive markers in SNP datasets may prevent useful genetic signal from being overwhelmed by a few linked markers, but can hinder the reconciliation of genetic differentiation with genomic architecture.…”

“…In addition to rapid changes in sex chromosomes, changes in climate have expanded MPB's Canadian range northward and eastward into naive landscapes and host plants, providing an opportunity for adaptive radiation (Carroll, Taylor, Regniere, & Safranyik, ; Cullingham, Roe, Sperling, & Coltman, ; Fauria & Johnson, ; Janes et al, ). Within the beetle's Canadian range, MPB population genetic structure has a well‐defined north–south division (Batista et al, ; Cullingham et al, ; Janes et al, ; Mock et al, ; Samarasekera et al, ), but lacks fine‐scale population structure (Janes et al, ).…”

“…Although neutral markers are useful for investigations of genetic drift and gene flow, recent work has called into question the value of removing non-neutral markers in SNP assays (Batista, Janes, Boone, Murray, & Sperling, 2016;Helyar et al, 2011). Likewise, filtering out repetitive markers in SNP datasets may prevent useful genetic signal from being overwhelmed by a few linked markers, but can hinder the reconciliation of genetic differentiation with genomic architecture.…”

Partitioning genetic and species diversity refines our understanding of species–genetic diversity relationships

“…Because genetic diversity estimates are sensitive to the number of genetic markers (Dutoit, Burri, Nater, Mugal, & Ellegren, 2017), such a low number of outlier loci is insufficient to calculate robust genetic diversity estimates of non-neutral diversity. Furthermore, to effectively compare neutral and non-neutral loci patterns, an equal number of both types of loci should ideally be used (Batista et al, 2016).…”