DOI: 10.5061/dryad.hqbzkh1dp
title: Fragmentation and translocation distort the genetic landscape of ungulates: red deer in the Netherlands

description: Many ungulate populations have a complex history of isolation and
 translocation. Consequently, ungulate populations may have
 experienced substantial reductions in the level of overall gene
 flow, yet simultaneously have augmented levels of long
 distance gene flow. To investigate the effect of this dual
 anthropogenic effect on the genetic landscape of ungulates, we
 genotyped 35K SNPs in 47 red deer (Cervus elaphus) of
 Netherlands, including putative autochthonous relic
 populations as well as allochthonous populations established in
 private estates and rewilding areas. We applied FST and
 ordination analyses to determine the meta-population genetic
 structure and thereby the occurrence of hybridization. At population
 level, we investigated levels of inbreeding through
 individual-based diversity measures, including Runs of
 Homozygosity. We documented that both spatial genetic
 structure and within-population genetic variation differed
 markedly from patterns assumed from present-day abundance and
 distribution. Notwithstanding the small spatial scale, red deer
 populations formed distinct genetic clusters, and some had higher genetic
 similarity to distant than to nearby populations. Moreover, the
 putative autochthonous relic deer populations had much reduced
 levels of polymorphism and multi-locus heterozygosity, despite
 relatively large current population sizes. Accordingly, genomes of these
 deer contained a high proportion of long (&gt;5 Mb) Runs of
 Homozygosity. Whereas the observed high levels of inbreeding
 warrant defragmentation measures, the presence of adjacent
 autochthonous and allochthonous genetic stocks imply that facilitation of
 gene flow would cause genetic homogenization. Such distortions of
 the genetic landscape of ungulates creates management dilemmas
 that cannot be properly anticipated without baseline genetic
 monitoring.
description: The data (SNP genotypes of deer) is provided through means of a R
 object.<br> The R object is in the form of a so called
 'genlight' object, facilitated through the packace
 Adegenet.<br> To open the datafile in R, please follow the code
 below. Instructions to open the deer genotype data in
 R: Step 1: <br> Open R, and then run the
 following two lines:<br>
 install.packages("adegenet")<br>
 library(adegenet) Step 2:<br> After the succesful
 installation of adegenet, open the R object with the deer genotype
 data.<br> Following the line below (hereby we assume that the file
 is stored in the folder "M/My Documents/"):<br>
 readRDS(file = "M:/My
 Documents/red_deer_jong_2020.rds")<br> Now the genlight object
 'dryad' (containing the deer genotypes) is loaded.<br> To
 view the genlight object, simply type:<br> dryad
 In the dryad object, you can find:<br> - the actual SNP
 genotypes<br> - identifier for SNPs<br> - SNP chromosome and
 location<br> - population assignment of individuals (pop
 abbreviations corresponding to abbreviations used in the corresponding
 article)<br> - sex (if known) of individuals  For
 more info about the functionalities of a genlight object, see this
 document:<br> Analysing genome-wide SNP data using adegenet
 2.0.0<br> Thibaut Jombart and Caitlin Collins<br> Imperial
 College London<br> MRC Centre for Outbreak Analysis and
 Modelling<br> June 23, 2015<br> Available through:
 http://adegenet.r-forge.r-project.org/files/tutorial-genomics.pdf