Abstract

Identifying genetic variants responsible for phenotypic variation under selective pressure has the potential to enable productive gains in natural resource conservation and management. Despite this potential, identifying adaptive candidate loci is not trivial, and linking genotype to phenotype is a major challenge in contemporary genetics. Many of the population genetic approaches commonly used to identify adaptive candidates will simultaneously detect false positives, particularly in nonmodel species, where experimental evidence is seldom provided for putative roles of the adaptive candidates identified by outlier approaches. In this study, we use outcomes from population genetics, phenotype association, and gene expression analyses as multiple lines of evidence to validate candidate genes. Using lodgepole and jack pine as our nonmodel study species, we analyzed 17 adaptive candidate loci together with 78 putatively neutral loci at 58 locations across Canada (N > 800) to determine whether relationships could be established between these candidate loci and phenotype related to mountain pine beetle susceptibility. We identified two candidate loci that were significant across all population genetic tests, and demonstrated significant changes in transcript abundance in trees subjected to wounding or inoculation with the mountain pine beetle fungal associate Grosmannia clavigera. Both candidates are involved in central physiological processes that are likely to be invoked in a trees response to stress. One of these two candidate loci showed a significant association with mountain pine beetle attack status in lodgepole pine. The spatial distribution of the attack‐associated allele further coincides with other indicators of susceptibility in lodgepole pine. These analyses, in which population genetics was combined with laboratory and field experimental validation approaches, represent first steps toward linking genetic variation to the phenotype of mountain pine beetle susceptibility in lodgepole and jack pine, and provide a roadmap for more comprehensive analyses.

Highlights

  • Knowledge of adaptive variation is important for many endeavors, such as mitigating the impacts of climate change (Aitken, Yeaman, Holliday, Wang, & Curtis‐McLane, 2008; Jump & Peñuelas, 2005), conserving species (Garcia de Leaniz et al, 2007; Primmer, 2009), and improving value traits in agriculture and forestry (Bruce, Edmeades, & Barker, 2002; Dawson, Lengkeek, Weber, & Jamnadass, 2009; Nelson & Johnsen, 2008)

  • We have used complementary validation appropriate for nonmodel organisms by incorporating evidence from multiple approaches to identify genetic variation potentially contributing to differential responses in lodgepole and jack pine trees to MPB and their fungal associates

  • We have identified a clear association between attack status and genotype for the Lodgc1087‐ containing gene encoding proteasome subunit α7 in lodgepole pine, and provided experimental evidence that this gene is involved in the defense response

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Summary

Introduction

Knowledge of adaptive variation is important for many endeavors, such as mitigating the impacts of climate change (Aitken, Yeaman, Holliday, Wang, & Curtis‐McLane, 2008; Jump & Peñuelas, 2005), conserving species (Garcia de Leaniz et al, 2007; Primmer, 2009), and improving value traits in agriculture and forestry (Bruce, Edmeades, & Barker, 2002; Dawson, Lengkeek, Weber, & Jamnadass, 2009; Nelson & Johnsen, 2008). The number of false positives can be reduced by considering loci that have their outlier status verified across multiple statistical approaches (De Mita et al, 2013; Gosset & Bierne, 2012; Narum & Hess, 2011; Nunes, Beaumont, Butlin, & Paulo, 2011). Loci verified in this manner can be validated by testing for signatures among the same set of loci in different sets of individuals/populations (Bonin, Taberlet, Miaud, & Pompanon, 2006; Stinchcombe & Hoekstra, 2008). Identification of true positives requires experimental or functional validation (Salvi & Tuberosa, 2005)

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