Genetic, phenotypic, and environmental drivers of local adaptation and climate-change induced maladaptation in yellow warblers

Understanding processes driving local adaptation in wild species is a key goal in evolutionary biology, but linking genotype to phenotype to environmental drivers of natural selection remains challenging. This dataset contains the necessary data to replicate the analyses in Rodriguez et al, which explores the connections between genotypes, phenotypes, and environment in yellow warblers across their breeding range. First, we conduct genome-wide association studies (GWAS) to identify loci related to bill shape and individual quality. We then conduct a gene-environment association (GEA) analysis on the resulting loci and find precipitation is underlying putative selection on bill shape. Finally, we test whether contemporary individuals whose bill shape deviates from historical relationships with precipitation exhibit increased stress—measured by telomere length—resulting from maladaptation. We collected samples from 121 yellow warblers from two reference populations in Michigan and Pe..., We collected samples from 121 yellow warblers from two reference populations in Michigan and Pennsylvania. At each site, birds were captured using mist-netting, bill depth measurements were taken, and blood samples were collected via brachial venipuncture and preserved in Queens lysis buffer. Further, we collected an additional 171 genetic samples from 22 sites across the yellow warbler breeding range to validate associations between allele frequencies and environmental variables in key loci. From the 171 samples, 63 samples with bill depth measurements from 10 sites across the breeding range were also used to validate the associations between bill depth and environmental variables.
Whole genome sequencing libraries were prepared following modifications of Illumina’s Nextera Library Preparation protocol with a target sequencing depth of 2X per individual. We used the program Trimmomatic 0.39 to trim the sequence data to remove Illumina adapter sequences and polyG tails using a sliding w..., , # Data from: Genetic, phenotypic, and environmental drivers of local adaptation and climate-change induced maladaptation in yellow warblers

[https://doi.org/10.5061/dryad.hmgqnk9tp](https://doi.org/10.5061/dryad.hmgqnk9tp)

## Description of the data and file structure

The following datasets include the required input files needed to conduct genome-wide association studies (GWAS) to identify loci related to bill shape and telomere length in yellow warbler reference populations. This includes the .bed files (binary biallelic genotype tables), .bim files (extended variant information files), and the .fam files (sample information file) for both telomere length and bill depth, as well as the kinship matrix GWAS_relate.cXX.txt. The metadata file for the GWAS data is located in GWAS.samples_121inds_meta.csv, and includes the sample IDs, the coordinates, and the telomere and bill depth measurement for each individual. 

This dataset also includes the data needed to conduct a gene-environmen...,