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Fragmentation and translocation distort the genetic landscape of ungulates: red deer in the Netherlands

Cite this dataset

de Jong, Joost Ferdinand (2020). Fragmentation and translocation distort the genetic landscape of ungulates: red deer in the Netherlands [Dataset]. Dryad.


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.

Usage notes

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:

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:

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: