Open AccessRepurposing population genetics data to discern genomic architecture: A case study of linkage cohort detection in mountain pine beetle ( Dendroctonus ponderosae )
Author(s) -
Trevoy Stephen A. L.,
Janes Jasmine K.,
Muirhead Kevin,
Sperling Felix A. H.
Publication year - 2019
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.4803
Subject(s) - linkage disequilibrium , biology , genetic architecture , genomics , population , evolutionary biology , computational biology , mountain pine beetle , single nucleotide polymorphism , genetics , genome , ecology , quantitative trait locus , gene , genotype , medicine , environmental health
Genetic surveys of the population structure of species can be used as resources for exploring their genomic architecture. By adjusting filtering assumptions, genome‐wide single‐nucleotide polymorphism (SNP) datasets can be reused to give new insights into the genetic basis of divergence and speciation without targeted resampling of specimens. Filtering only for missing data and minor allele frequency, we used a combination of principal components analysis and linkage disequilibrium network analysis to distinguish three cohorts of variable SNPs in the mountain pine beetle in western Canada, including one that was sex‐linked and one that was geographically associated. These marker cohorts indicate genomically localized differentiation, and their detection demonstrates an accessible and intuitive method for discovering potential islands of genomic divergence without a priori knowledge of a species’ genomic architecture. Thus, this method has utility for directly addressing the genomic architecture of species and generating new hypotheses for functional research.