Fragmentation and translocation distort the genetic landscape of ungulates: red deer in the Netherlands - de Jong, Joost Ferdinand (Dryad, 2020)
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 (>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.
The data (SNP genotypes of deer) is provided through means of a R object.
The R object is in the form of a so called 'genlight' object,
facilitated through the packace Adegenet. To open the datafile in R,
please follow the code below. Instructions to open the deer genotype data
in R: Step 1:  Open R, and then run the following two lines:
install.packages("adegenet") library(adegenet) Step 2: After the
succesful installation of adegenet, open the R object with the deer
genotype data. Following the line below (hereby we assume that the file is
stored in the folder "M/My Documents/"): readRDS(file =
"M:/My Documents/red_deer_jong_2020.rds") Now the genlight
object 'dryad' (containing the deer genotypes) is loaded. To
view the genlight object, simply type: dryad In the dryad object, you can
find: - the actual SNP genotypes - identifier for SNPs - SNP chromosome
and location - population assignment of individuals (pop abbreviations
corresponding to abbreviations used in the corresponding article) - sex
(if known) of individuals  For more info about the
functionalities of a genlight object, see this document: Analysing
genome-wide SNP data using adegenet 2.0.0 Thibaut Jombart and Caitlin
Collins Imperial College London MRC Centre for Outbreak Analysis and
Modelling June 23, 2015 Available through:
http://adegenet.r-forge.r-project.org/files/tutorial-genomics.pdf
Keywords: FOS: Natural sciences