Genome-Wide Association Mapping of Phenotypic Traits Subject to a Range of Intensities of Natural Selection in Timema cristinae*

abstract: The genetic architecture of adaptive traits can reflect the evolutionary history of populations and also shape divergence among populations. Despite this central role in evolution, relatively little is known regarding the genetic architecture of adaptive traits in nature, particularly for traits subject to known selection intensities. Here we quantitatively describe the genetic architecture of traits that are subject to known intensities of differential selection between host plant species in Timema cristinae stick insects. Specifically, we used phenotypic measurements of 10 traits and 211,004 single-nucleotide polymorphisms (SNPs) to conduct multilocus genome-wide association mapping. We identified a modest number of SNPs that were associated with traits and sometimes explained a large proportion of trait variation. These SNPs varied in their strength of association with traits, and both major and minor effect loci were discovered. However, we found no relationship between variation in levels of divergence among traits in nature and variation in parameters describing the genetic architecture of those same traits. Our results provide a first step toward identifying loci underlying adaptation in T. cristinae. Future studies will examine the genomic location, population differentiation, and response to selection of the trait-associated SNPs described here

Caterpillars on a Phytochemical Landscape: The Case of Alfalfa and the Melissa Blue Butterfly

Modern metabolomic approaches that generate more comprehensive phytochemical profiles than were previously available are providing new opportunities for understanding plant‐animal interactions. Specifically, we can characterize the phytochemical landscape by asking how a larger number of individual compounds affect herbivores and how compounds covary among plants. Here we use the recent colonization of alfalfa (Medicago sativa) by the Melissa blue butterfly (Lycaeides melissa) to investigate the effects of indivdiual compounds and suites of covarying phytochemicals on caterpillar performance. We find that survival, development time, and adult weight are all associated with variation in nutrition and toxicity, including biomolecules associated with plant cell function as well as putative anti‐herbivore action. The plant‐insect interface is complex, with clusters of covarying compounds in many cases encompassing divergent effects on different aspects of caterpillar performance. Individual compounds with the strongest associations are largely specialized metabolites, including alkaloids, phenolic glycosides, and saponins. The saponins are represented in our data by more than 25 individual compounds with beneficial and detrimental effects on L. melissa caterpillars, which highlights the value of metabolomic data as opposed to approaches that rely on total concentrations within broad defensive classes

FHA_gprob_s090p001.txt.bz2

Posterior genotype probabilities that were determined by MCMC from FHA_variants.flt_s090p001.bcf. Uncompressed file size: 7.5

N1_gprob_s090p001.txt.bz2

Posterior genotype probabilities that were determined by MCMC from N1_variants.flt_s090p001.bcf. Uncompressed file size: 4.3

FHA_inVar_snpIDs_bins_s090p001.txt.bz2

Positions of all sites (variants and invariant nucleotides) and their 20-kb bins for population FHA, discarding variants where less than 90% of individuals were covere

N1_inVar_snpIDs_bins_s090p001.txt.bz2

Positions of all sites (variants and invariant nucleotides) and their 20-kb bins for population N1, discarding variants where less than 90% of individuals were covere

Genomic insights on the recent evolution of novel host use in the Melissa blue butterfly

The factors that shape the evolution of animal diets remain poorly known. For herbivorous insects, the expectation has been that trade­offs exist, such that adaptation to one host plant reduces success on other potential hosts. We investigated the genomic basis of alternative host plant use in Melissa blue butterflies (Lycaeides melissa) by analyzing genetic variation in natural and experimental butterfly populations. We showed that distinct Melissa blue butterfly populations have independently colonized alfalfa since the 1800s when this plant was introduced, and that these populations have adapted to this novel resource. We documented segregating polygenic variation within and among butterfly populations for performance on alfalfa, and showed that different instances of adaptation to alfalfa have occurred via selection on a mixture of the same and different genes. Genetic variants in transposable elements might be particularly important for host adaptation. We documented very few loci with genetic trade­offs that would inherently constrain diet breadth by preventing the optimization of performance across hosts. Instead most genetic variants that affected performance on one host had little to no effect on the other host

Alignment script

This perl script generates shell scripts to submit to a SLURM job scheduler to run bwa, which we used for DNA sequence alignments. Note that this depends on having a bwa module installed on a cluster running SLURM

Data from: Genetic constraints on wing pattern variation in Lycaeides butterflies: a case study on mapping complex, multifaceted traits in structured populations

Patterns of phenotypic variation within and among species can be shaped and constrained by trait genetic architecture. This is particularly true for complex traits, such as butterfly wing patterns, that consist of multiple elements. Understanding the genetics of complex trait variation across species boundaries is difficult, as it necessitates mapping in structured populations and can involve many loci with small or variable phenotypic effects. Here, we investigate the genetic architecture of complex wing pattern variation in Lycaeides butterflies as a case study of mapping multivariate traits in wild populations that include multiple nominal species or groups. We identify conserved modules of integrated wing pattern elements within populations and species. We show that trait covariances within modules have a genetic basis, and thus represent genetic constraints that can channel evolution. Consistent with this, we find evidence that evolutionary changes in wing patterns among populations and species occur mostly in the directions of genetic covariances within these groups. Thus, we show that genetic constraints affect patterns of biological diversity (wing pattern) in Lycaeides, and we provide an analytical template for similar work in other systems

G- and P-matrix infiles and analyses

This compressed directory includes the genome estimated breeding values from genomic prediction (catbv*csv) for each groups, phenotypic data for P-matrixes (resid*) and a R script that runs analyses on these files, matcomp.R (which has annotations throughout). The R script runs the comparisons of P and G-matrixes and the evolvability/constraint analyses, as well as making related plots