Molecular Ecology · 2019 · 33 citations · 107 references
Life SciencesEcologyGeneticsInsect EcologyLandscape GeneticsPopulation GeneticsInsect Genetic DiversityLandscape Connectivity For InsectsLandscape GenomicsLandscape ResistanceNatural SelectionSpatial Genetic PatternsEnvironmental Selection GradientsGene Flow BarriersGenetic Connectivity AssessmentHeterogeneous EnvironmentsLandscape Genetic ConnectivityLandscape Genetic StructureLandscape-scale Gene FlowTrait Variation Across Environmental Gradients
Abstract Widespread species that exhibit both high gene flow and the capacity to occupy heterogeneous environments make excellent models for examining local selection processes along environmental gradients. Here we evaluate the influence of temperature and landscape variables on genetic connectivity and signatures of local adaptation in Phaulacridium vittatum , a widespread agricultural pest grasshopper, endemic to Australia. With sampling across a 900‐km latitudinal gradient, we genotyped 185 P. vittatum from 19 sites at 11,408 single nucleotide polymorphisms (SNPs) using ddRAD sequencing. Despite high gene flow across sites (pairwise F ST = 0.0003–0.08), landscape genetic resistance modelling identified a positive nonlinear effect of mean annual temperature on genetic connectivity. Urban areas and water bodies had a greater influence on genetic distance among sites than pasture, agricultural areas and forest. Together, F ST outlier tests and environmental association analysis (EAA) detected 242 unique SNPs under putative selection, with the highest numbers associated with latitude, mean annual temperature and body size. A combination of landscape genetic connectivity analysis together with EAA identified mean annual temperature as a key driver of both neutral gene flow and environmental selection processes. Gene annotation of putatively adaptive SNPs matched with gene functions for olfaction, metabolic detoxification and ultraviolet light shielding. Our results imply that this widespread agricultural pest has the potential to spread and adapt under shifting temperature regimes and land cover change.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Inference of Population Structure Using Multilocus Genotype Data
Jonathan K. Pritchard, Matthew Stephens, Peter Donnelly · Genetics · 2000 · 34.3K citations · Full text