DOI: 10.5061/dryad.1s04tj3
title: 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

description: 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.
description: 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 &gt;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