DOI: 10.5061/dryad.7b5m7
title: Data from: The evolution of novel host use is unlikely to be constrained by tradeoffs or a lack of genetic variation

description: The genetic and ecological factors that shape the evolution of animal
 diets remain poorly understood. For herbivorous insects, the expectation
 has been that trade-offs exist, such that adaptation to one host plant
 reduces performance on other potential hosts. We investigated the genetic
 architecture of alternative host use by rearing individual Lycaeides
 melissa butterflies from two wild populations in a crossed design on two
 hosts (one native and one introduced) and analysing the genetic basis of
 differences in performance using genomic approaches. Survival during the
 experiment was highest when butterfly larvae were reared on their natal
 host plant, consistent with local adaptation. However, cross-host
 correlations in performance among families (within populations) were not
 different from zero. We found that L. melissa populations possess genetic
 variation for larval performance and variation in performance had a
 polygenic basis. We documented very few genetic variants with trade-offs
 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. In total, these results suggest that genetic trade-offs are not the
 primary cause of dietary specialization in L. melissa butterflies.
description: PerformanceDataPerformance data from the larval rearing experiments. Each row in the file contains the data for one individual. The columns give the individual number (ind), population (pop), plant treatment (plant), sex, adult weight (weight) whether (1) or not (0) the individual survived (survivorship), and a family number.Lmelissa1FinalAssemblyDraft genome sequence for Lycaeides melissa in fasta format. This assembly was produced by ALLPATHS-LG. It includes 14,029 scaffolds. The assembly report is included as a ReadMe file.LmelissaAnnotation.tarCompressed directory that contains gff (general feature format) files for each scaffold in the Lycaeides melissa genome assembly. These annotations were generated with the maker pipeline. The maker option file that was used for the annotation is included as a ReadMe file.filtered_varMelissaAllCompressed vcf (variant call format) file containing the genetic data for the 206,047 single nucleotide variants included in this study. We generated the variant set with samtools and bcftools.sequence alignmentsThis link provides access to a directory on university supported, permanent box account that includes 12 compressed directories. Each compressed directory (about 5 GB each) contains the bam alignment files for a subset of the sequenced individuals. Alignments were generated with bwa using the Lycaeides melissa reference genome included in this DRYAD submission.Lmelgenotypes.tarGenotype input files for gemma that were used for polygenic modelling (i.e. association mapping). Genotype files are include for each individual treatment (e.g. GLA by Ms) as well as all of the combined treatments (e.g. GLA regardless of host). Posterior mean genotypes were used.Lmelphenotypes.tarPhenotype infiles for gemma that were used for polygenic modelling (i.e. association mapping). Adult weight (first column) and survival (second column) are given in each file. Adult weight has been normal quantile transformed.association (polygenic modelling) resultsMCMC results from polygenic modelling with gemma for each phenotype and treatment. 10 chains were run for each and all are included (see Ch# in file names). File formats are described in the gemma documentation, which can be found at http://www.xzlab.org/software/GEMMAmanual.pdf.gemmaResults.tar.gzperformance dataText file formatted for the phenotypic analyses with R. This file can be read and analyzed the the analyzePheno.R script included with this submission.performance.txtscripts.tarMain computer scripts used to analyze the data in this manuscript. This includes the source code for the C++ program used to estimate allele frequencies and genotypes. This compressed directory includes a README file describing each program.