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.

Mountain pine beetle (Dendroctonus ponderosae Hopkins; MPB) is an economically and ecologically important pest of pine species in western North America. Mountain pine beetles form complex multipartite relationships with microbial partners, including the ophiostomoid fungi Grosmannia clavigera (Robinson-Jeffrey and Davidson) Zipfel, de Beer and Wingfield, Ophiostoma montium (Rumbold) von Arx, Grosmannia aurea (Robinson-Jeffrey and Davidson) Zipfel, de Beer and Wingfield, Leptographium longiclavatum (Lee, Kim, and Breuil) and Leptographium terebrantis (Barras and Perry). These fungi are vectored by MPB to new pine hosts, where the fungi overcome host defenses to grow into the sapwood. A tree’s relative susceptibility to these fungi is conventionally assessed by measuring lesions that develop in response to fungal inoculation. However, these lesions represent a symptom of infection, representing both fungal growth and tree defense capacity. In order to more objectively assess fungal virulence and host tree susceptibility in studies of host–pathogen interactions, a reliable, consistent, sensitive method is required to accurately identify and quantify MPB-associated fungal symbionts in planta. We have adapted RNase H2-dependent PCR, a technique originally designed for rare allele discrimination, to develop a novel RNase H2-dependent quantitative PCR (rh-qPCR) assay that shows greater specificity and sensitivity than previously published PCR-based methods to quantify MPB fungal symbionts in pine xylem and MPB whole beetles. Two sets of assay probes were designed: one that amplifies a broad range of ophiostomoid species, and a second that amplifies G. clavigera but not other MPB-associated ophiostomoid species. Using these primers to quantify G. clavigera in pine stems, we provide evidence that lesion length does not accurately reflect the extent of fungal colonization along the stem nor the quantity of fungal growth within this colonized portion of stem. The sensitivity, specificity, reproducibility, cost effectiveness and high-throughput potential of the rh-qPCR assay makes the technology suitable for identification and quantification of a wide array of pathogenic and beneficial microbes that form associations with plants and other organisms, even when the microbial partner is present in low abundance.

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