Evolutionary genomics of gypsy moth populations sampled along a latitudinal gradient

Abstract

The European gypsy moth (Lymantria dispar L.) was first introduced to Massachusetts in 1869 and within 150 years has spread throughout eastern North America. This large‐scale invasion across a heterogeneous landscape allows examination of the genetic signatures of adaptation potentially associated with rapid geographical spread. We tested the hypothesis that spatially divergent natural selection has driven observed changes in three developmental traits that were measured in a common garden for 165 adult moths sampled from six populations across a latitudinal gradient covering the entirety of the range. We generated genotype data for 91,468 single nucleotide polymorphisms based on double digest restriction‐site associated DNA sequencing and used these data to discover genome‐wide associations for each trait, as well as to test for signatures of selection on the discovered architectures. Genetic structure across the introduced range of gypsy moth was low in magnitude (FST = 0.069), with signatures of bottlenecks and spatial expansion apparent in the rare portion of the allele frequency spectrum. Results from applications of Bayesian sparse linear mixed models were consistent with the presumed polygenic architectures of each trait. Further analyses indicated spatially divergent natural selection acting on larval development time and pupal mass, with the linkage disequilibrium component of this test acting as the main driver of observed patterns. The populations most important for these signals were two range‐edge populations established less than 30 generations ago. We discuss the importance of rapid polygenic adaptation to the ability of non‐native species to invade novel environments.

Tracking invasions of a destructive defoliator, the gypsy moth (Erebidae: Lymantria dispar): Population structure, origin of intercepted specimens, and Asian introgression into North America

“…All those lines of evidence support the unique genetic status of the North American population (i.e., an independent evolutionary lineage) distinct from contemporary European populations. Future studies are needed to understand whether such distinctiveness is a result of genetic drift, local adaptation (e.g., Friedline et al, 2019), historical admixture from multiple source populations, or a combination of those factors.…”

Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, inDrosophila melanogaster

“…For example, in D. melanogaster , clinal SNPs are also enriched for SNPs influencing cuticular hydrocarbon content [100]. In gypsy moths, SNPs associated with three ecologically relevant traits have consistent clinal signals [101], and in corals, SNPs associated with heat tolerance are more common in warmer reefs and in warmer microclimates within a single reef [102]. Drought-associated SNPs also show spatial variation in European populations of Arabidopsis thaliana [103], and models suggest that those populations with more drought-tolerance alleles may adapt to global warming more effectively.…”

Genomic data reveal deep genetic structure but no support for current taxonomic designation in a grasshopper species complex

“…To examine shape differences between taxa and among populations, we performed principal component analyses (PCA) on the covariance matrix of aligned Procrustes shape coordinates using the function plotTangentSpace . We retained the scores from the two first principal components (PC1 and PC2) for each trait and used multivariate analyses of variance (MANOVA) to investigate if trait shapes were significantly different between taxa and among sampled populations (e.g., Adams & Otarola‐Castillo, ; Friedline et al, ). Statistical significance of MANOVA models was determined using Wilk's λ as the test statistic and α = 0.05 as a significance threshold.…”

“…Statistical significance of MANOVA models was determined using Wilk's λ as the test statistic and α = 0.05 as a significance threshold. Then, we used one‐way analyses of variance (ANOVA) to assess differences between taxa and among sampled populations separately for each phenotypic trait (e.g., Friedline et al, ). The first two PCs for each trait were also used for integrative species delimitation analyses using ibpp (Solis‐Lemus et al, ) and to build matrices of phenotypic differentiation ( P ST ; see below for details).…”