Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/27155
Title: Repurposing population genetics data to discern genomic architecture: A case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae)
Contributor(s): Trevoy, Stephen A L (author); Janes, Jasmine K  (author)orcid ; Muirhead, Kevin (author); Sperling, Felix A H (author)
Publication Date: 2019-02
Early Online Version: 2018-12-26
Open Access: Yes
DOI: 10.1002/ece3.4803
Handle Link: https://hdl.handle.net/1959.11/27155
Abstract: 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.
Publication Type: Journal Article
Source of Publication: Ecology and Evolution, 9(3), p. 1147-1159
Publisher: John Wiley & Sons Ltd
Place of Publication: United Kingdom
ISSN: 2045-7758
Fields of Research (FoR) 2008: 070505 Forestry Pests, Health and Diseases
060408 Genomics
060399 Evolutionary Biology not elsewhere classified
Fields of Research (FoR) 2020: 300704 Forest health and pathology
310509 Genomics
Socio-Economic Objective (SEO) 2008: 820199 Forestry not elsewhere classified
960404 Control of Animal Pests, Diseases and Exotic Species in Forest and Woodlands Environments
Socio-Economic Objective (SEO) 2020: 180602 Control of pests, diseases and exotic species in terrestrial environments
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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