10.5061/DRYAD.1S04TJ3
Senn, Helen V.
Royal Zoological Society of Scotland
Ghazali, Muhammad
Royal Zoological Society of Scotland
Kaden, Jennifer
Royal Zoological Society of Scotland
Barcaly, David
University of Oxford
Harrower, Ben
Royal Zoological Society of Scotland
Campbell, Ruairidh D.
National Museums Scotland
MacDonald, David W.
University of Oxford
Kitchener, Andrew C.
National Museum
University of Edinburgh
Barclay, David
Royal Zoological Society of Scotland
Data from: Distinguishing the victim from the threat: SNP‐based methods
reveal the extent of introgressive hybridization between wildcats and
domestic cats in Scotland and inform future in situ and ex situ management
options for species restoration
Dryad
dataset
2018
Captive Populations
Felis sylvestris
conservation management
wildcat
2018-10-01T16:59:11Z
2018-10-01T16:59:11Z
en
https://doi.org/10.1111/eva.12720
2179746 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
The degree of introgressive hybridisation between the Scottish wildcat and
domestic cat has long been suspected to be advanced. Here we use a
35-SNP-marker test, designed to assess hybridisation between wildcat and
domestic cat populations in Scotland, to assess a database of 265
wild-living and captive cat samples, and test the assumptions of the test
using 3097 SNP markers generated independently in a subset of the data
using ddRAD. We discovered that despite increased genetic resolution
provided by these methods, wild-living cats in Scotland show a complete
genetic continuum or hybrid swarm structure when judged against reference
data. The historical population of wildcats, although hybridised, clearly
groups at one end of this continuum, as does the captive population of
wildcats. The interpretation of pelage scores against nuclear genetic data
continues to be problematic. This is probably because of a breakdown in
linkage disequilibrium between wildcat pelage genes as the two populations
have become increasingly mixed, meaning that pelage score or SNP score
alone are poor diagnostic predictors of hybrid status. Until better tools
become available, both should be used jointly, where possible, when making
management decisions about individual cats. We recommend that the
conservation community in Scotland must now define clearly what measures
are to be used to diagnose a wildcat in the wild in Scotland, if future
conservation action is to be effective.
35SNP_global_datasetThis dataset consists of 295 individuals, which have
been typed at 35 SNP loci drawn from Nussberger et al. (2013) that have
been identified as discriminatory between the following two groups; [
(Scottish+ mainland European wildcats) versus (UK+ mainland European
domestic cats)]. Justification for the 35 SNP panel used is laid out in
detail in Senn and Ogden (2015). Wet-lab methods consist of PCR
amplification of the samples with 35 Taqman SNP Probes on a StepOne
platform (Senn and Ogden 2015). This dataset was divided into a variety of
sub-datasets based on the different methodologies used to collect the
samples. Since the focus of collection of wild-living cats has shifted
over time, this has been done to assist with understanding how collection
bias might influence conclusions drawn from the results (more later). The
datasets (summarised in Table 1) are: 35SNP_historical_cats: A dataset of
60 cats collected between 1895 and 1985 by National Museums Scotland,
Natural History Museum (London) and the New Walk Museum Leicester. These
cats are primarily cats identified as wildcats that were shot by
gamekeepers. The samples taken from these animals consisted of fragments
of dried or tanned skins taken with sterile scalpels, which were then
extracted with Qiagen Investigators kits (Qiagen) according to
manufacturer’s instructions. Of these cats, 51 were scored for pelage
characters, from the preserved skins by ACK. 35SNP_wildliving_dead_cats: A
dataset of 125 cats collected from ~1990-2015 by National Museums Scotland
with the assistance of a wide variety of partners. The cats are primarily
victims of road-traffic accidents, although in some cases they were shot,
or the fate of specimen is unclear. Note that it was not possible to
include the samples from theBeaumont et al. (2001) study. Sample type
consists of skeletal muscle tissue, which was extracted with Fuji film or
Qiagen blood and tissue kits according to manufacturers’ instructions. Of
these samples 33 have pelage scores taken from photographs of dead cats or
their tanned skins by ACK. 35SNP_wildliving_survey_cats: This dataset
contains 19 cats trapped as part of the Survey of the Priority Areas
conducted prior to the initiation of the current action plan (SNH 2014,
Commissioned Report No. 768.). Sample type of these cats consists of EDTA
blood extracted with Fuji film or Qiagen blood and tissue kits (Qiagen),
according to manufacturers’ instructions. Of these, 18 samples have pelage
scores (following Kitchener et al. 2005), scored from photographs taken
when the cat was under anaesthesia in the field under Scottish Natural
Heritage Animal Licence number 21463 and Animals Scientific Procedures Act
personal licence number 70/25690. 35SNP_captive_cats: A dataset of 72
wildcats, which represented 100% of the potential breeding population
within the UK captive breeding programme as of May 2017. Sample type for
these cats consists of EDTA blood taken during routine health screening,
extracted with Fuji film or Qiagen blood and tissue kits (Qiagen),
according to manufacturers’ instructions. Of these samples 28 have pelage
scores, taken from photographs taken when the cats were under anaesthesia
for routine health screening
(http://www.scottishwildcataction.org/media/42346/protocol-for-photographing-dead-or-anaesthetised-wildliving-cat-dr-andrew-kitchener.pdf). 35SNP_domestic_cat: A dataset of 19 domestic cat samples collected from across the City of Edinburgh region. Pelage data are not available for this dataset.Copy of DRYAD1_35SNP_2.xlsx3097SNP_datasetFor a subset of 68 of the cats typed at 35SNPs and an additional eight cats collected from across the UK, ddRAD analysis of the samples was conducted using a modification of the protocol by (Peterson et al., 2012), which is described in (Bourgeois et al., 2018). A list of all used samples can be found in Supplementary Material 2. In short, DNA quality was assessed via agarose gel electrophoresis on a 1% gel and only non-degraded DNA (as judged by a tight high molecular weight band against a lambda standard) was selected for the library preparation stage. It should be noted here that DNA quality requirements for this protocol preclude running the analysis on poor quality or degraded samples (e.g. most historical or non-invasive sample types). DNA was quantified using a Qubit Broad Range dsDNA Assay (Thermofisher Scientific) and normalised to 7 ng µl-1. Each sample was processed in triplicate or quadruplet to enhance evenness of coverage of samples within the library. Individual genomic DNA was restriction-digested using both SbfI and SphI enzymes and Illumina specific sequencing adaptors (P1 & P2) were then ligated to fragment ends. The pooled samples were size selected (320-590bp fragments) by gel electrophoresis, PCR amplified (15 cycles) and the resultant amplicons (ddRAD library) were purified and quantified. Combinatorial inline barcodes (5 or 7 bases long), included in the P1 &P2 adaptors, allowed each sample replicate to be identified post sequencing. The ddRAD library was sequenced on the Illumina MiSeq Platform (a single paired-end run; v2 chemistry, 2 x 160 bases). Positive control samples were run on all libraries. The sequence data were quality assessed using FastQC (Andrew, 2010) and the reads demultiplexed by barcode and quality filtered using the process_radtags module (default parameters) of the stacks bioinformatics pipeline (Catchen et al. 2013). The retained reads were then trimmed to a standard 135 bases in length. Demultiplexed read files were concatenated into read files for each individual (three or four barcode combinations per individual, see above). Read 1 and Read 2 files were then joined into a single file per individual. The individual data files were then processed using the denovo_map.pl module of Stacks (-M 2, -n 1) to assemble and create a catalogue of genetic loci contained in the data. The Stacks scripts export_sql.pl (snps_l=1, -F snps_u=1, -F pare_l=10, -F alle_u=2) was then used to create a whitelist of all loci, which contained exactly one SNP with two alleles, where the minor variant was present in at least 10 samples. This whitelist was then used to filter the data with the populations function (-r 0.75, -m 10) to create a final dataset, where at each locus a minimum of 75% of individuals had been typed with a depth of at least 10 reads. Further filtering was then conducted in PLINK to remove any loci at which there was >33% missing data. This generated a final data matrix, which consisted of a list of 3097 variable SNPs typed in 76 cats: 20 captive, five domestic and 51 wild-living. The overall % missingness in the data matrix was 6.4%. This data set is referred to as the 3097SNP_dataset. We consider this dataset to represent the most unbiased genetic data for the Scottish wildcat so far. The 35 SNP test was derived from European wildcat data, and thus although effort was made to minimise any impact of bias in subsequent re-design of the test for Scotland (Senn & Ogden 2015), there is the potential that hidden issues with reference data or sub-structuring within the wildcat or domestic cat populations could have biasing consequences on this relatively small panel of markers. The purpose of this dataset here is primarily to the verify the performance 35SNP systemDRYAD2_ddRAD.xlsx
UK
Scotland
United Kingdom