Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics
Cite this dataset
LaCava, Melanie E. F. et al. (2021). Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics [Dataset]. Dryad. https://doi.org/10.5061/dryad.zcrjdfn9p
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.
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.
United States Geological Survey, Award: G20AC00062
National Institute of General Medical Sciences, Award: 2P20GM103432
Wyoming Governor's Big Game License Coalition
Carlton Barkhurst Dissertation Fellowship
University of Wyoming
Wyoming Excellence Chair Funds