DOI: 10.5061/dryad.zcrjdfn9p
title: Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

description: Maintaining functional connectivity is critical for the long-term
 conservation of wildlife populations. Landscape genomics provides an
 opportunity to assess long-term functional connectivity by relating
 environmental variables to spatial patterns of genomic variation resulting
 from generations of movement, dispersal, and mating behaviors. Identifying
 landscape features associated with gene flow at large geographic scales
 for highly mobile species is becoming increasingly possible due to more
 accessible genomic approaches, improved analytical methods, and enhanced
 computational power. We characterized the genetic structure and diversity
 of migratory mule deer (Odocoileus hemionus) using 4,051 single nucleotide
 polymorphisms in 406 individuals sampled across multiple habitats
 throughout Wyoming, USA. We then identified environmental variables
 associated with genomic variation within genetic groups and statewide
 using a stepwise approach to first evaluate nonlinear relationships of
 landscape resistance with genetic distances and then use mixed-effects
 modeling to choose top landscape genomic models. We identified three
 admixed genetic groups of mule deer and found that environmental variables
 associated with gene flow varied among genetic groups, revealing
 scale-dependent and regional variation in functional connectivity. At the
 statewide scale, more gene flow occurred in areas with low elevation and
 mixed habitat. In the southern genetic group, more gene flow occurred in
 areas with low elevation. In the northern genetic group, more gene flow
 occurred in grassland and forest habitats, while highways and energy
 infrastructure reduced gene flow. In the western genetic group, the null
 model of isolation by distance best represented genetic patterns. Overall,
 our findings highlight the role of different seasonal ranges on mule deer
 genetic connectivity, and show that anthropogenic features hinder
 connectivity. This study demonstrates the value of combining a large,
 genome-wide marker set with recent advances in landscape genomics to
 evaluate functional connectivity in a wide-ranging migratory species.
description: See readme.txt for
 descriptions of each individual file. This directory contains data,
 protocols, and scripts associated with our publication. The data include
 sample metadata, SNP genotypes, correlation matrices for the landscape
 genomics analyses, and multivariate model results for the landscape
 genomics analyses. The protocols include our genotyping-by-sequencing
 library preparation protocol. We include Unix-based scripts for our
 step-by-step bioinformatics workflow, for parsing raw sequence data by
 sample barcode, for data reduction before CD-HIT assembly, for running bwa
 in parallel, for converting vcf genotypes into a genotype likelihood
 matrix, and for converting a genotype likelihood matrix into a text file.
 We also include R-based scripts for detecting loci with excess levels of
 heterozygosity, for performing PCA on SNP data, and for our landscape
 genomics workflow.