Range-wide patterns of human-mediated hybridisation in European wildcats

Abstract

Hybridisation between wild taxa and their domestic congeners is a significant conservation issue. Domestic species frequently outnumber their wild relatives in population size and distribution and may therefore genetically swamp the native species. The European wildcat (Felis silvestris) has been shown to hybridise with domestic cats (Felis catus). Previously suggested spatially divergent introgression levels have not been confirmed on a European scale due to significant differences in the applied methods to assess hybridisation of the European wildcat. We analysed 926 Felis spp. samples from 13 European countries, using a set of 86 selected ancestry-informative SNPs, 14 microsatellites, and ten mitochondrial and Y-chromosome markers to study regional hybridisation and introgression patterns and population differentiation. We detected 51 hybrids (four F1 and 47 F2 or backcrosses) and 521 pure wildcats throughout Europe. The abundance of hybrids varied considerably among studied populations. All samples from Scotland were identified as F2 hybrids or backcrosses, supporting previous findings that the genetic integrity of that wildcat population has been seriously compromised. In other European populations, low to moderate levels of hybridisation were found, with the lowest levels being in Central and Southeast Europe. The occurrence of distinct maternal and paternal markers between wildcat and domestic cat suggests that there were no severe hybridisation episodes in the past. The overall low (< 1%) prevalence of F1 hybrids suggests a low risk of hybridisation for the long-term genetic integrity of the wildcat in most of Europe. However, regionally elevated introgression rates confirm that hybridisation poses a potential threat. We propose regional in-depth monitoring of hybridisation rates to identify factors driving hybridisation so as to develop effective strategies for conservation.

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Vol.:(0123456789)
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Conservation Genetics (2020) 21:247–260
https://doi.org/10.1007/s10592-019-01247-4
RESEARCH ARTICLE
Range‑wide patterns ofhuman‑mediated hybridisation inEuropean
wildcats
AnnikaTiesmeyer1,2 · LuanaRamos3,4· JoséManuelLucas5· KatharinaSteyer1· PauloC.Alves3,4,6·
ChristosAstaras7· MareikeBrix8· MargheritaCragnolini9,10· CsabaDomokos11· ZsoltHegyeli11· RenéJanssen12·
AndrewC.Kitchener13,14· ClotildeLambinet15· XavierMestdagh16· DespinaMigli17· PedroMonterroso3·
JaapL.Mulder18· VincianeSchockert15· DionisiosYoulatos17· MarkusPfenninger19,20· CarstenNowak1,21
Received: 5 May 2019 / Accepted: 30 December 2019 / Published online: 25 January 2020
© The Author(s) 2020
Abstract
Hybridisation between wild taxa and their domestic congeners is a significant conservation issue. Domestic species frequently
outnumber their wild relatives in population size and distribution and may therefore genetically swamp the native species.
The European wildcat (Felis silvestris) has been shown to hybridise with domestic cats (Felis catus). Previously suggested
spatially divergent introgression levels have not been confirmed on a European scale due to significant differences in the
applied methods to assess hybridisation of the European wildcat. We analysed 926 Felis spp. samples from 13 European
countries, using a set of 86 selected ancestry-informative SNPs, 14 microsatellites, and ten mitochondrial and Y-chromosome
markers to study regional hybridisation and introgression patterns and population differentiation. We detected 51 hybrids
(four F1 and 47 F2 or backcrosses) and 521 pure wildcats throughout Europe. The abundance of hybrids varied considerably
among studied populations. All samples from Scotland were identified as F2 hybrids or backcrosses, supporting previous
findings that the genetic integrity of that wildcat population has been seriously compromised. In other European popula-
tions, low to moderate levels of hybridisation were found, with the lowest levels being in Central and Southeast Europe. The
occurrence of distinct maternal and paternal markers between wildcat and domestic cat suggests that there were no severe
hybridisation episodes in the past. The overall low (< 1%) prevalence of F1 hybrids suggests a low risk of hybridisation for
the long-term genetic integrity of the wildcat in most of Europe. However, regionally elevated introgression rates confirm
that hybridisation poses a potential threat. We propose regional in-depth monitoring of hybridisation rates to identify factors
driving hybridisation so as to develop effective strategies for conservation.
Keywords Conservation genetics· Introgression· Single nucleotide polymorphism· Felis silvestris· Felis catus·
Anthropogenic hybridisation
Introduction
Hybridisation is a naturally occurring process that leads to
contradictory evolutionary outcomes. On one hand, it may
decrease biodiversity by threatening species or populations
with the loss of genetic diversity or outright extinction by
genetic swamping (Rhymer and Simberloff 1996; Allendorf
etal. 2001; Seehausen etal. 2008; Todesco etal. 2016). On
the other hand, hybridisation can contribute to biodiversity
by introducing novel genetic diversity and triggering specia-
tion processes (Mallet 2008; Abbott etal. 2016). Globally,
a large proportion of species is assumed to be susceptible
to hybridisation with related taxa (Seehausen etal. 2008).
Hybridisation occurs when populations that have been repro-
ductively isolated for a certain time eventually come into
contact, for instance due to range shifts (Futuyma 2005).
Currently, rates of hybridisation may also be on the rise due
to human-mediated range expansion of alien taxa, leading
to previously impossible hybridisation events between natu-
rally allopatric taxa (Mooney and Cleland 2001; Sakai etal.
2001; Simberloff etal. 2013). Moreover, the introduction of
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s1059 2-019-01247 -4) contains
supplementary material, which is available to authorized users.
* Annika Tiesmeyer
annika.tiesmeyer@gmail.de
Extended author information available on the last page of the article
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248 Conservation Genetics (2020) 21:247–260
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actively managed taxa for husbandry and sport hunting, as
in the case of livestock, pets and game, may also enhance
opportunities for hybridisation (Todesco etal. 2016). Non-
native and, in particular, domestic taxa have been introduced
on a global scale and often population sizes are substan-
tially larger compared to those of their wild congeners. In
addition to this, traits of domestic taxa have been artificially
selected to meet human needs; the introgression of “domes-
tic” genes in wild taxa may thus lead to decreased fitness or
to outbreeding depression in wild populations (Todesco etal.
2016). Therefore, studying the distribution and causes of
hybridisation between populations of wild and domestic taxa
is highly relevant for species conservation. Hybridisation
between wild and domestic congeners is well recognised,
for example, between wolf (Canis lupus) and domestic dog
(Canis familiaris) (Randi 2008), American bison (Bison
bison) and domestic cattle (Bos taurus) (Halbert and Derr
2007), wild and domestic American mink (Neovison vison)
(Kidd etal. 2009), Europeanpolecat (Mustela putorius) and
domestic ferret (Mustela furo) (Davison etal. 1999), wild
boar (Sus scrofa) and pig (Sus domesticus) (Scandura etal.
2008) and European wildcat (Felis silvestris) and domes-
tic cat (Felis catus) (e.g., Randi etal. 2001; Pierpaoli etal.
2003). Hybridisation in wildcats is a particularly complex
case study, since it involves natural and anthropogenic epi-
sodes. Natural hybridisation occurred between the African
wildcat (Felis lybica) and other taxa in the wildcat group
(Felis spp.) during their evolutionary history (Driscoll etal.
2007; Ottoni etal. 2017; Kitchener etal. 2017). Moreover, F.
silvestris and F. lybica were found to hybridise with domes-
tic cats (Driscoll etal. 2007; LeRoux etal. 2015). Domestic
cats originally derived from F. lybica in the Near East/North
Africa and today the human-mediated dispersal has resulted
in a near global distribution (Driscoll etal. 2007; Ottoni
etal. 2017).
Once widely distributed, the European wildcat underwent
sharp range declines, leading in some cases even to local
extinctions by the early twentieth century due to anthropo-
genic persecution and the loss of suitable habitat (Piechocki
1990; Stahl and Artois 1995; Yamaguchi etal. 2015). Today,
the conservation status of the European wildcat is still unfa-
vourable in most European countries (EC 2015), although
there is recent evidence of increasing populations and natu-
ral recolonisation of the species’ historic range in at least
some regions (Steyer etal. 2016; Nussberger etal. 2018).
Conservation threats include habitat loss and fragmentation,
road mortality, persecution and hybridisation (Klar etal.
2008, 2009; Lozano and Malo 2012; Yamaguchi etal. 2015).
However, there is substantial uncertainty about the relative
importance of these threats, and in particular, regarding the
role of hybridisation.
Previous genetic studies have confirmed the occur-
rence of hybridisation between wildcats and domestic
cats throughout Europe (Randi etal. 2001; Beaumont etal.
2001; Driscoll etal. 2007; Pierpaoli etal. 2003; Lecis
etal. 2006; Randi 2008; Oliveira etal. 2008a, b; O’Brien
etal. 2009; Hertwig etal. 2009; Eckert etal. 2009; Nuss-
berger etal. 2014b, 2018; Steyer etal. 2018). However,
the levels of hybridisation reported varied considerably
between studies, even those involving the same regions
(e.g., Eckert etal. 2009 or Steyer etal. 2018 vs. Hertwig
etal. 2009). This has been suggested to be due to consider-
able differences in the methods applied to identify hybrid
individuals and to measure hybridisation rates, e.g., sam-
pling strategies, size and period, number and type of mark-
ers, as well as the statistical approaches used for hybrid
identification (Steyer etal. 2018). Recently, polymorphic
molecular markers, mainly microsatellites, have been
applied for studying admixture and introgression between
wildcats and domestic cats (e.g., Randi etal. 2001;
Pierpaoli etal. 2003; Eckert etal. 2009). However, the
resolution of hybridisation is limited due to the relatively
low availability, repeatability between labs and technical
capacity to analyse microsatellite markers. High-through-
put analyses of single nucleotide polymorphism (SNP)
arrays substantially improved the in-depth assessment of
hybridisation (e.g., vonHoldt etal. 2013; Goedbloed etal.
2013; Nussberger etal. 2013). SNPs have been shown to
be highly accurate and sensitive in identifying hybrid indi-
viduals between wildcats and domestic cats, irrespective
of origin and available reference database (Oliveira etal.
2015; Steyer etal. 2018; Mattucci etal. 2019).
Here, we analysed wildcat and domestic cat samples
from 13 different countries across Europe using a set of
ancestry-informative SNP markers (96) to study intro-
gression between wildcats and domestic cats (Nussberger
etal. 2013, 2014a). SNP markers were selected to be
diagnostic for identifying wildcat, domestic cat, and their
hybrids, and included recombinant (autosomal) and non-
recombinant markers (mitochondrial and Y-chromosome
markers) (Nussberger etal. 2013, 2014a). Autosomal
SNPs were analysed using Bayesian statistical tools to
identify hybrids and backcrosses. As previous studies
have described an asymmetric and sex-specific hybridisa-
tion directionality (Nussberger etal. 2018; Oliveira etal.
2018), we analysed paternally inherited (Y-chromosome)
and maternally inherited (mitochondrial DNA) SNP mark-
ers and sequences. In addition, we genotyped individuals
using a set of highly polymorphic microsatellite markers
to study the genetic structure of wildcat population.
We present the first large-scale assessment of hybridisa-
tion between Felis spp., representing populations across
Europe. We aimed to provide a first estimation of overall
hybridisation rates in the European wildcat to serve as
an initial baseline for future comprehensive assessments.
Moreover, we addressed the degree of threat posed by
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249Conservation Genetics (2020) 21:247–260
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hybridisation to the long-term persistence of wildcats in
different regions.
Material andmethods
Study area anddesign
Wildcat and domestic cat samples were collected from
13 countries in Europe between 1999 and 2016. In total,
926 samples were analysed from Southwest and Southern
Europe (Portugal n = 69, Spain n = 94, Italy n = 30), Scotland
(n = 17), Central Europe (Belgium n = 107, the Netherlands
n = 10, Luxembourg n = 48, Ger many n = 412, France n = 1,
Austria n = 21) and Southeast Europe (Romania n = 59, Bul-
garia n = 38, Greece n = 20) (Fig.1). Samples from Scotland
were originally provided as examples of clear morphological
hybrids based on pelage, thus reflecting the hybrid swarm
that occurs there today (Senn etal. 2018). Therefore, the
Scottish samples may be biased more towards hybrids that
are closer to domestic cats than wildcats. Samples from
Germany were randomly preselected from a larger dataset
(Steyer etal. 2018) to avoid local overrepresentation (≤ 4
samples per 10 km2). Sampling was performed opportunisti-
cally by collecting samples of carcasses (n = 621), captured
cats (n = 65) and domestic cats from pet owners (n = 30),
by collecting fresh scat samples (n = 24) and other findings
(n = 6), or systematically using hair traps scented with vale-
rian tincture (n = 180) as described by Steyer etal. (2013)
(Supplementary TableS1). Sampling material consisted of
invasive samples (tissue n = 608, blood n = 88, tooth n = 1)
and non-invasive (or minimally invasive) samples (hair
n = 202, scat n = 24, saliva n = 3). No animal was harmed
or sacrificed for the purposes of this study and all samples
were collected in compliance with the respective local and
national laws. Genetic samples of captured cats or pets were
obtained as byproducts of routine analyses of veterinarians
or telemetry studies (Klar etal. 2009; Lammertsma etal.
2011; Streif etal. 2012; Ramos 2014).
Laboratory procedures
Extraction of deoxyribonucleic acid (DNA) was performed
in separate laboratory rooms for invasive and non-invasive
samples. Blood and tissue samples were extracted using
the Q
iagen
Blood and Tissue Kit and the tooth sample was
extracted using the Q
iagen
Investigator Kit following the
manufacturer’s instructions. Saliva samples were extracted
using the Q
iagen
QIAamp DNA Blood Mini Kit (Hilden,
Germany) following the manufacturer’s instructions and hair
samples were extracted using the Q
iagen
Investigator Kit as
described by Steyer etal. (2016). Scat samples were dried
at 60°C for 2days, followed by subsequent DNA extraction
as described by Frantz etal. (2003) and filtering with pre-
rinsed Microcon® YM-30 centrifugal filter units (Millipore,
Billerica, MA). Negative controls were included in all proto-
cols for detecting potential DNA contamination.
Fig. 1 Sampling locations and
wildcat occurrence in Europe.
All genotyped samples (n = 926)
are displayed. The colour codes
represent populations that were
grouped based on microsatel-
lite-based Bayesian clustering.
The distribution of the Euro-
pean wildcat (Felis silvestris)
and Sardinian wildcat (Felis
lybica) in the EU is shown as
light grey grid cells (EC 2015)
0250 500125 Kilometers
1. Iberian Peninsula
2. Scotland
3. Western Central Europe
4. Central Germany
5. Eastern Alpine
6. Central Italy
7. Southeast Europe
Wildcat distribution
1
2
3
4
5
6
7
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250 Conservation Genetics (2020) 21:247–260
1 3
All samples (926) were analysed with a set of 96 SNPs
using SNPtype genotyping assays run on F
luidigm
96.96
Dynamic Arrays (F
luidigm
, San Francisco, USA), follow-
ing Nussberger etal. (2014a), to detect admixture between
wildcats and domestic cats. The SNP set includes 86 auto-
somal markers (75 diagnostic markers and 11 markers for
individualisation), eight mitochondrial markers and two
Y-chromosome markers. All samples were pre-amplified
using specific target amplification reactions. The tooth sam-
ple and blood and tissue samples were pre-amplified using
the manufacturer’s instructions. Pre-amplification of saliva,
scat and hair samples was performed according to Nuss-
berger etal. (2014a). No-template controls were included to
detect potential contamination on every chip. Raw data were
analysed using F
luidigm
SNP Genotyping Analysis Software
v.3.1.2. The analysis of a subset of 154 samples (17%) was
replicated to assess genotyping errors.
A 110 base pair (bp) Felis-specific fragment of the mito-
chondrial (mt) control region was amplified and sequenced
using the primers LF4 (Eckert etal. 2009) and H16498
(Kocher etal. 1989) as described by Steyer etal. (2013).
Sequences were processed and aligned in G
eneious
6 (https
://www.genei ous.com, Kearse etal. 2012) using previously
published haplotypes (Steyer etal. 2013, 2016) down-
loaded from GenBank (Accession Numbers: KR076400-
KR076428, JX045658-JX045661, KX161418-KX161423).
In total, 905 samples were genotyped with microsatel-
lites to detect population structure. A set of 14 polymorphic
microsatellites (Menotti-Raymond etal. 1999) was analysed
following the protocol of Steyer etal. (2013). A multiple
tube approach with a minimum of three polymerase chain
reaction (PCR) replications per sample was applied to meas-
ure genotyping errors of potentially low-quality samples
(Navidi etal. 1992). Fragment length was analysed using
G
enemarker
2.2 (SoftGenetics).
Data processing andanalyses
The SNP data were filtered for quality in a two-step pro-
cedure. Firstly, SNP loci and samples showing more than
90% of missing data were excluded to eliminate markers and
samples that generally failed to amplify. Secondly, samples
and loci showing more than 30% of missing data were finally
removed because an increased rate of failed amplifications
(“No call”) has been shown to be related to increased geno-
typing errors (vonThaden etal. 2017). Genotyping errors
were calculated using a customised R-script in the software
R 3.2.2. (R Development Core Team 2008) based on the
methodology in the software G
imlet
(Valiere 2002). Ampli-
fication success was calculated for all samples and genotyp-
ing errors for replicated samples.
For all replicated SNP and microsatellite genotypes a
consensus genotype was built using a customised R-script in
the software R (R Development Core Team 2008). An allele
was counted if it appeared in at least one out of three repli-
cates, assuming that allelic drop-out occurs more often than
false alleles (Kraus etal. 2015; Steyer etal. 2016). Microsat-
ellite genotypes with < 70% amplification success and > 30%
allelic drop-out rate were excluded from analysis. Micros-
atellite genotypes were checked for multiple recorded indi-
viduals by using a customised R-script to measure genotype
similarities. If available, other criteria, such as mt-haplotype,
sex and sampling location or date, were considered. Only
one genotype per individual was kept for further analysis.
The software N
ew
H
ybrids
1.1 (Anderson and Thompson
2002) was used to assess the hybrid status of SNP-typed
individuals by analysing genotypes of autosomal SNP mark-
ers. The software was configured to estimate posterior prob-
abilities for six different classes: two pure parental groups,
F1-hybrids, F2-hybrids and first-generation backcrosses to
each parental group. N
ew
H
ybrids
uses a Bayesian frame-
work. We excluded pre-convergence values by discarding
(“burn-in”) 100K iterations, and using the 500K itera-
tions of each Markov chain (MCMC). Uninformative (i.e.
uniform) priors were used as recommended by Steyer etal.
(2018). Individuals were considered assigned to one of the
six different classes if the assignment value (q(i)) was ≥ 0.85
as described by Steyer etal. (2018).
Two uniparental diagnostic SNPs on the Y-chromosome
and eight in the mitochondrial DNA were analysed for
paternal and maternal ancestry, respectively. The addition-
ally analysed mitochondrial sequences were aligned and
analysed using the software N
etwork
5.0.0.0 to calculate a
median joining network (Forster 2015). Mitochondrial SNPs
and sequences were aligned further to previously published
mitochondrial clades, which covered partly the same seg-
ments (ND5, ND6) (Driscoll etal. 2007; Ottoni etal. 2017).
We analysed differentiation among all clusters by DAPC
(Discriminant Analysis of Principal Components) in the
Adegenet package (Jombart 2008) in R (R Development
Core Team 2008) based on all SNP genotypes. We also ana-
lysed microsatellite genotypes using the software S
tructure
(Falush etal. 2003) to assess population structure among
wildcats only. The Western Central Europe and Central Ger-
man population were reduced randomly to 35 individuals
each to equalize sample sizes between populations. After
a “burn-in” of 100K iterations, inference was based on the
values of the remaining 200K iterations using an admix-
ture model with correlated allele frequencies and no a priori
information. Analyses were run for a number of clusters
(k) from 1 to 15 in ten independent runs each. The likely
number of clusters was determined based on the Evanno
method (Evanno etal. 2005) as implemented in the applica-
tion S
tructure
H
arvester
(Earl and vonHoldt 2012). Inde-
pendent runs were joined by using the application C
lumpp
(Jakobsson and Rosenberg 2007).
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251Conservation Genetics (2020) 21:247–260
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Results
Genotyping success andgenotyping errors
In total, 926 samples were genotyped with a 96 SNP array.
Of those, 32 samples (3%) failed to amplify and 112 samples
(12%) had more than 30% of missing data. These samples
were excluded from further analysis. Data from 63 autoso-
mal, four mitochondrial and two SRY markers (72%) ful-
filled the quality criteria set out above and were thus kept
for further analyses. Genotyping errors among the replicated
samples (n = 162) showed a rate of 0.7%, representing allelic
drop-out and false alleles. Genotyping of 905 samples with
microsatellites resulted in a mean amplification success of
85% per sample. The mean allelic drop-out rate for micros-
atellites genotypes was 6%. We excluded 159 microsatellite
genotypes (18%) from further analysis. Repeated detections
of the same microsatellite genotype, or if not available of
identical SNP genotypes, were assumed to be the same indi-
vidual and were removed from further analyses (n = 15). In
the end, 767 individual genotypes were used for downstream
analyses.
Hybridisation analysis
Hybridisation analysis with N
ew
H
ybrids
was run for 767
individuals and 54 autosomal SNP markers, excluding
all non-diagnostic markers. In total, 521 individuals were
assigned to pure wildcat, 187 to pure domestic cat, four to
F1 hybrid, ten to F2 hybrid, 28 to backcross to wildcat, and
nine to backcross to domestic cat (Table1). In eight cases,
individuals were not clearly assigned to any of the analysed
categories. Hybrids of the first generation (n = 4, F1 hybrids)
were significantly less frequent than hybrids of the second
generation (n = 47, F2 hybrids and backcrosses). Hybrids
were detected in all studied populations with different abun-
dances (Fig.2). Most hybrids were detected among samples
from Scotland. None of the 17 analysed Scottish samples
was assigned to wildcat. In other populations the propor-
tion of hybrids among pure wildcats varied between 3 and
21% (Table2). Besides the Scottish samples, there was no
apparent pattern in the geographical distribution of hybrids
(Fig.3). The lowest proportion of hybrids (between 3 and
5%) was found in Western Central Europe, Central Germany
and Southeast Europe, especially in the Transylvanian Basin
and the Carpathians (Fig.2, Table1).
Variability atuniparental markers (mtDNA
andY‑chromosome)
A total of 35 different mitochondrial haplotypes was found
among 761 analysed sequences (Fig.4; GenBank Accession
Numbers: KR076400-KR076428, JX045658-JX045661,
KX161418-KX161423, MN518925–MN518932). Three
main haplogroups were distinguished: a wildcat group (FS-
A), a domestic cat group (FS-B) and a group shared between
both (FS-C). The highest frequency of the haplogroup FS-C
was found in Southeast and Central Europe (Supplementary
Fig. S1). Within the groups, private haplotypes were found
for wildcats and domestic cats with very few cytonuclear
discordances (n = 18) (Fig.4). Of identified hybrids, 88%
showed wildcat haplotypes (Fig.2). Among the Scottish
samples 15 out of 17 individuals (88%) carried the same
wildcat haplotype (Supplementary Fig. S2).
Table 1 Assignments of analysed individuals to wildcat, domestic cat or hybrid categories among populations
The results are based on the SNP genotype analysed with the software N
ew
H
ybrids
(a) number of analysed individual SNP genotypes, (b) num-
ber of genotypes assigned to wildcat, (c) domestic cat, (d) F1-hybrid, (e) F2-hybrid, (f) backcross to wildcat, (g) backcross to domestic cat, (h)
individuals that were assigned with a q(i) < 0.85, (i) sum of the reported hybrid individuals under columns (d) to (g), (j) references if presenting
data from sources other than the present study
a Only recent samples were considered
Population (a) N
indi-
viduals
(b) Wildcats (c)
Domes-
tic cats
(d) F1 (e) F2 (f) BxWC (g) BxDC (h) n.a (i) ∑ hybrids (j) References (other
than present data)
Iberian Peninsula 93 42 40 – 4 5 2 – 11
Scotland 17 – – – 5 4 6 2 15
Western Europe 322 223 86 1 – 9 1 2 11
Central Germany 199 155 38 1 – 4 – 1 5
Eastern Alpine 36 20 13 1 – 2 – – 3
Central Italy 8 5 – – – 2 – 1 2
Southeast Europe 92 76 10 1 1 2 – 2 4
Total 767 521 187 4 10 28 9 8 51
Jura (FRA/CH) 224 114 91 2 1 14 2 19 Nussberger etal. (2018)a
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252 Conservation Genetics (2020) 21:247–260
1 3
0
0.2
0.4
0.6
0.8
1.0
12347
56
1 Iberian Peninsula
2 Scotland
3 Western Central Europe
4 Central Germany
5 Eastern Alpine
6 Central Italy
7 Southeast Europe
DC Domestic cats
a
b
c
DC
BxWC
BxDC
F2
F1
WC
DC
n.a.
Fig. 2 Individual assignments with biparental and uniparental SNPs.
All successfully analysed individuals (n = 767) are shown as verti-
cal columns. a Mitochondrial haplotypes were based on a 110 bp
sequence of the control region. Classification of haplotypes was
according to previous comprehensive studies (Steyer et al. 2016,
2018). b SRY-haplotypes were based on two SRY-SNPs. Classifica-
tion of the haplotypes followed Nussberger etal. (2014b). c Assign-
ments based on autosomal diagnostic SNPs (n = 54) analysed with
the software N
ew
H
ybrids
. Each column represents the individual q(i)
value belonging to the respective parental or hybrid cluster. Wildcats
(WC) are shown in blue, domestic cats (DC) in red, F1-hybrids (F1)
in black, F2-hybrids (F2) in orange, backcrosses to wildcats (BxWC)
in light blue and backcrosses to domestic cats (BxDC) in pink and
failed amplifications (n/a) in grey. In case of the SRY-SNPs (c) failed
amplifications also represent female individuals
Table 2 Review of hybridisation rates for wildcat populations in Europe
Hybridsation rates were calculated based on (a) SNP data from present study if no other reference is given and (b) microsatellite data reviewed
from previous studies covering similar study areas. Hybridisation rates were calculated as the number of hybrids (first- and second-generation
hybrids) per total number of individuals. Pure domestic cats were excluded from calculations as they were not considered belonging to the wild-
cat population
a Value is not considered significant due to the small number of samples
Population (a) SNPs (b) Microsatellites
Iberian Peninsula 0.21 (11/53) 0.15 (2/13; Pierpaoli etal. 2003);
0.07 (5/72; Oliveira etal. 2008b);
Portugal: 0.12 (4/34; Oliveira etal. 2008a)
Scotland 1 (15/15) 0.5 (96/191; Beaumont etal. 2001)
Western Europe 0.05 (11/234) Belgium: 0.05 (1/19), Western Germany: 0 (0/24) (Pierpaoli etal. 2003);
Western Germany: 0.43 (12/28) (Hertwig etal. 2009); Western Germany: 0 (0/28) (Eck-
ert etal. 2009); Germany: 0.05 (86/1695) (Steyer etal. 2016)
Central Germany 0.03 (5/160) 0 (0/27) (Pierpaoli etal. 2003);
0.04 (2/46) (Hertwig etal. 2009);
0 (0/38) (Eckert etal. 2009);
Germany: 0.05 (86/1695) (Steyer etal. 2016)
Eastern Alpine 0.13 (3/23) Northern Italy: 0 (0/4) (Randi etal. 2001); Eastern Alpine: 0 (0/4) (Pierpaoli etal. 2003)
Central Italy 2/7a0.03 (1/39) (Randi etal. 2001)
Southeast Europe 0.05 (4/80) 0.17 (1/6) (Pierpaoli etal. 2003);
0.12 (2/17) (Eckert etal. 2009)
Eastern France/ Switzerland 0.16 (21/133) (Nuss-
berger etal. 2018)
0.33 (2/6) (Pierpaoli etal. 2003);
0.24 (31/130) (O’Brien etal. 2009);
Total 0.10 (72/705)
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253Conservation Genetics (2020) 21:247–260
1 3
Based on the mitochondrial SNPs, clades I and IV were
identified corresponding to the classification of Ottoni etal.
(2017) (Supplementary Fig. S3). Clade I was exclusively
found in wildcats and clade IV appeared in wildcats and
domestic cats.
The two SRY-SNPs showed only two different combina-
tions (Y/Y or X/X) classified as domestic cat or wildcat type
according to Nussberger etal. (2013). Among all analysed
samples Y-chromosomes of wildcat type were found in 417
males and of domestic cat type in 133 males. Within these
there was a high concordance with assignments based on
autosomal SNP markers (Fig.2). In case of the SRY SNPs
15 individuals (3%) showed discordant results; four domes-
tic cats carried a Y-chromosome of wildcat ancestry, whilst
11 wildcats carried one of domestic cat ancestry. Seventeen
detected male hybrids carried a Y-chromosome of wildcat
ancestry and 15 of domestic cat ancestry. Among the Scot-
tish samples 9 out of 11 males (81%) carried a domestic cat
Y-chromosome (Fig.2).
Population genetic structure
Results of a clustering analysis in DAPC, using all SNP gen-
otypes, were concordant with those in N
ew
H
ybrids
. Wild-
cats and domestic cats plotted into two distinct groups and
hybrids appeared admixed (Supplementary Fig. S4). SNP
markers were highly discriminating between wildcats and
domestic cats but indicated low informative value (eigen-
value) concerning more fine-scale population structures.
The polymorphic set of 14 microsatellite markers revealed
distinct population structures among wildcat populations
Fig. 3 Distribution of wild-
cats and hybrids in Europe.
Assigned categories are based
on SNP genotypes (n = 572)
analysed with software N
ew
H
y
-
brids
. Pure wildcats (WC) are
shown as blue dots, F1-hybrids
(F1) as orange triangles,
F2-hybrids (F2) as yellow
stars, backcrosses to wildcats
(BxWC) as light blue squares
and backcrosses to domestic
cats (BxDC) as pink squares.
Pure domestic cats (n = 187)
and samples that could not be
assigned to any of the categories
(n = 8) are not displayed. The
known distribution of wildcats
is shown as light grey grid cells
(EC 2015)
DC
F1-hybrid
F2-hybrid
backcross/ WC
backcross/ DC
WC
15
16
60
74
41
18
39
13
12
37
22
23
32
36
34
47
26
70
6
40
5
7
54 31
76
49
68
46
66
63
45
69
65
3
4
FS-A
FS-B
FS-C
Fig. 4 Network of mitochondrial haplotypes with corresponding
hybrid category. The network was calculated with a 110 bp frag-
ment of the control region. Black dots between haplotypes display the
number of mutation steps (added by 1). Each number per haplotype
is concordant with the name provided in GenBank (SGN-HP-FS03
to -FS60), except for haplotypes which have been detected for the
first time (SGN-FS63 to -74). The pie charts per haplotype indicate
the assigned hybrid category based on autosomal SNP genotypes
(n = 759) analysed with the software N
ew
H
ybrids
. The size of the pie
charts corresponds to the number of detections
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254 Conservation Genetics (2020) 21:247–260
1 3
in S
tructure
. The most likely number of genetic clusters
was k = 2, revealing a clear distinction of wildcats in Cen-
tral Germany from other populations (Supplementary Fig.
S5). High likelihood was also achieved for k = 3, k = 4 and
k = 5. In total, five genetic clusters were differentiated and
grouped into populations throughout the study area: Central
Germany, Iberian Peninsula, Western Central Europe (West-
ern Germany, Belgium, Netherlands, Luxembourg, France),
Eastern Alpine (Austria, Northern Italy) and Southeast
Europe (Romania, Bulgaria, Greece) (Fig.1). Individuals
from Romania, Bulgaria and Greece did not reveal popula-
tion substructure. The individuals from central Italy (n = 8)
appeared admixed between clusters and were grouped as a
separate population consistent with previous studies (Mat-
tucci etal. 2013). Individuals from Scotland were also
grouped separately because of the lack of samples assigned
as wildcats. In total, samples were grouped into seven popu-
lations throughout the study area (Fig.1).
Discussion
The aim of this study was to assess hybridisation levels
between the European wildcat and the domestic cat through-
out Europe and to compare findings between different areas
of its distribution. The 51 hybrids were found among 521
wildcat individuals throughout the wildcat’s distribution in
Europe (Fig.3). Levels of hybridisation varied considerably
in frequency and distribution in the populations considered
(Table1). They were low to moderate in Central, South-
east and Southwest Europe. In contrast, all samples from
Scotland were identified as backcross hybrids, supporting
findings of previous studies that the genetic integrity of the
wildcat population in Scotland is seriously compromised
(Kitchener etal. 2005; Kitchener and Daniels 2008; Kilshaw
etal. 2016; Senn etal. 2018). However, since the Scottish
samples were explicitly morphological hybrids, this may
have biased the result. On the other hand, the lack of cats
with typical wildcat appearance probably reflects the hybrid
swarm status of this population.
In most populations, maternal and paternal haplotypes
were both coincident with the autosomal DNA result, which
suggests that there have been no intense hybridisation epi-
sodes in the past. Hence, our SNP analyses confirm previous
findings based on microsatellites that the genetic integrity
of the European wildcat has persisted in most regions to
date (e.g., Randi etal. 2001; Pierpaoli etal. 2003; Mattucci
etal. 2016). Most Scottish samples carried a mitochondrial
haplotype of wildcat type and Y-chromosomes of domes-
tic cat type, which may reflect a sex-biased directionality
of gene flow. However, this may also result from the lim-
ited sample size or reflect a potential bias in these Scottish
samples towards the advanced level of introgression within
this population (Senn etal. 2018).
Irrespective of these findings, it remains unclear to which
degree both forms are affected by historic gene flow because
available current hybridisation assessments are restricted
to measuring contemporary differentiation between wild-
cats and domestic cats. Palaeogenetic or genomic studies
investigating proportions of admixture in wildcats need to
be developed. Mattucci etal. (2019) recently developed an
approach to detect genomic traces originating from hybridi-
sation events that occurred from 6 to 22 generations in the
past.
While we found hybrids throughout all studied wildcat
populations, we also assessed low to moderate levels of
hybridisation in most regions. Hybridisation levels, assessed
with SNP data, were generally similar to previously reported
results based on microsatellite data (summarised in Table2)
The lowest proportion of hybrids (3–5%) was detected in
Central Europe, which is supported by previous studies
(Pierpaoli etal. 2003; Hertwig etal. 2009; Eckert etal.
2009; Steyer etal. 2018), excepting for a high hybridisa-
tion rate of 43% for western Germany, described by Hertwig
etal. (2009). This finding was not supported here and in pre-
vious studies covering the same study areas (Pierpaoli etal.
2003; Eckert etal. 2009; Steyer etal. 2016). Steyer etal.
(2018) suggested that the discrepancy derives from meth-
odological differences related to the problem of reference
population assignment when relying on microsatellite data.
In Southeast Europe, we found similarly low hybridisation
levels (5%), which are the first genetically confirmed results
covering several regions in this area (Table2). Findings of
moderate hybridisation rates in the Iberian Peninsula were in
line with previous findings that were based on microsatellite
analyses (Table2; Pierpaoli etal. 2003; Oliveira etal. 2008a,
b). In the Eastern Alpine region, we detected one F1 and two
backcross hybrids among 23 individuals, which are, to our
knowledge, the first genetically confirmed hybrids in this
area. In Scotland, we found exclusively hybrids of differ-
ent classes, indicating that hybridisation has been occurring
for several generations and crossbreeding between different
hybrid classes (Kitchener etal. 2005; Kilshaw etal. 2016;
Mattucci etal. 2016; Senn etal. 2018).
Most previous studies addressing recent hybridisation
between wildcats and domestic cats were based on regional
sampling and/or relied on limited sets of microsatellite
markers (usually 14 or less). Broad-scale comparisons of
hybridisation rates had low informative value due to meth-
odological constraints, namely to the use of different mark-
ers, statistical approaches and thresholds. The application
of SNPs provides several advantages, namely that they are
abundant and broadly distributed in genomes and compatible
with high-throughput approaches (reviewed by Garvin etal.
2010). The applied SNP-set has been previously shown to
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255Conservation Genetics (2020) 21:247–260
1 3
be statistically powerful in differentiating wildcats, domes-
tic cats and F1, F2 and first-generation backcrosses (cor-
rect assignments of 99.6% (Nussberger etal. 2013); correct
assignments of F1 hybrids 100%, second generation hybrids
96–98% (Steyer etal. 2018)). The microsatellite set ana-
lysed in this study has been previously shown to fail in dif-
ferentiating among hybrid classes (Steyer etal. 2018) and
was thus not considered in the assessment of hybridisation.
However, obstacles in comparing hybridisation rates are
not completely overcome, includingdiverse use of refer-
ence populations, differences in sampling techniques and
intensity throughout the species distribution (Steyer etal.
2018). Future research needs to address a harmonisation of
sampling approaches for European wildcats for conducting
more comprehensive assessments.
While admixture between European wildcats and domes-
tic cats was widespread throughout the species’ range, we
found low or moderate levels of recent hybridisation in
most regions. If only F1 hybrids are considered, the overall
proportion of hybrids among studied samples was less than
1%, since most hybrids were F2 and backcrosses. However,
the very low frequency of observed F1s should be taken
with caution, since this can reflect a sample bias (animals
too similar to domestic cats may be not sampled). Overall,
our findings generally suggest that the genetic integrity of
European wildcats persists in the longterm despite hybridi-
sation events. Conversely, we confirmed regionally elevated
introgression rates, as in Scotland: all analysed samples were
identified as backcrossed hybrids. In this population, a high
proportion of F2 hybrids (29%) was also detected, although
this is likely to be due to a sampling bias, since F2 hybrids
(F1 × F1) are expected to occur in rare incidences only. The
use of strict hybrid categories might have caused the misas-
signments of individuals that are descended from repeated
crossbreeding between different hybrid generations (see also
Senn etal. 2018). These findings confirm that hybridisation
has been continuing for several generations.
Increased hybridisation rates, leading to considerable
introgression, have significant consequences for the con-
servation of wildcat populations (Yamaguchi etal. 2015).
Considering the emblematic case of the Scottish European
wildcat population, it is important to understand the fac-
tors that affect the frequency of hybridisation. Domestic
cats have a worldwide distribution and the number of pet
cats exceeds 65 million in European countries with wildcat
presence (EPFI 2017). The total number of domestic cats is
estimated to be higher by several orders of magnitude than
that of European wildcats. Differences in population sizes
between hybridising taxa, as seen for wildcat and domestic
cat in Europe, may increase the likelihood of extinction of
the smaller population (Rhymer and Simberloff 1996). The
actual number of free-ranging domestic cats is unknown
because some pet cats are kept indoors and solid estimates
of feral domestic cats are lacking. The degree of dependence
of domestic cats on humans is expected to be highly variable
and it is generally difficult to assess data on feral cats.
Considering the hybridisation levels for mainland Europe
and the level of anthropogenic disturbance in the area, we
think that ecological and/or ethological factors, limiting pan-
mixia between both forms, must exist in most populations.
Previous studies have reported that hybrids occurred more
frequently at the periphery of the ranges of wildcats (Randi
etal. 2001), wolves (Randi 2008) or golden jackals (Canis
aureus; Galov etal. 2015). The peripheral parts of popula-
tions are expected to have lower population densities than
core areas, which may affect ethological factors affecting
mate choice, also known as the Allee effect (Allee 1931).
Previous studies have shown that recent range expansions
of wildcat populations have led to increased hybridisation
rates in Switzerland and France (Nussberger etal. 2014b,
2018). As male cats generally disperse farther than females
(Sunquist and Sunquist 2002), an asymmetric distribution of
maternal or paternal markers can reflect population-dynamic
processes. In addition, male wildcats have been shown to tol-
erate low quality habitat better compared to females, which
may also affect directionality of hybridisation (Oliveira etal.
2018). In the Jura region of eastern Switzerland and west-
ern France, an increased rate of introgression of domestic
cat mitochondrial haplotypes into wildcats was found and
explained by a sex-biased dispersal of male wildcats enter-
ing domestic cat ranges (Nussberger etal. 2014b, 2018).
Among the Scottish samples, we found an opposite pattern
of hybrids, which mostly carry a domestic-cat-type Y-chro-
mosome but a wildcat-type mitochondrial haplotype, which
may suggest an opposite sex-biased directionality of gene
flow. This may be explained by prevalent gene flow between
hybrids and male domestic cats and female wildcats, but this
finding needs to be confirmed on a larger sampling set. Inter-
estingly, hybrids have been observed to occupy the same
habitat as wildcats and partly the same as domestic cats
(Germain etal. 2008; Kilshaw etal. 2016). Hence, hybrids
may play a role as vectors for gene flow between both popu-
lations, accelerating admixture between both species.
Encounters between wildcats and domestic cats are
expected to be a result of individual movements, which are
affected by habitat and population status (Gil-Sánchez etal.
2015). Movement data on both wildcats and domestic cats
have shown low spatio-temporal overlap on a local scale
(Germain etal. 2008). In Central Europe, wildcats have
been observed to prefer habitats with a proximity to forests
and a critical distance of several hundred meters from vil-
lages, single houses and roads to avoid human disturbance
(Klar etal. 2008). In contrast, domestic cats prefer habitats
in proximity to human settlements, because of access to pro-
vided resources (Biró etal. 2004; Ferreira etal. 2011), while
feral domestic cats may be less dependent on supplied food
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256 Conservation Genetics (2020) 21:247–260
1 3
resources. Consequently, encounters between wildcats and
domestic cats may occur frequently at the edges or outside
preferred wildcat habitat. In addition, encounters may take
place through exploratory movements outside their home
ranges, particularly during the mating season (Germain etal.
2008). Domestic cats, for instance, have been detected within
protected areas at a considerable distance from human set-
tlements (e.g., Sarmento etal. 2009; Zwijacz-Kozica etal.
2017). Wildcats and domestic cats have also been shown
to occur at the same locations, at least occasionally (Nuss-
berger etal. 2014b; Kilshaw etal. 2016; Steyer etal. 2016;
Beutel etal. 2017). We assume that habitat fragmentation
may enhance the chance of encounters between wildcats
and domestic cats because of the higher proportion of land
being subject to an edge effect. The high hybridisation rate
in Hungary has been explained by the occurrence of wildcats
in highly fragmented areas of forest patches, agriculture and
human settlements (Pierpaoli etal. 2003; Lecis etal. 2006;
Randi 2008). In Central Europe, we found a low hybridisa-
tion rate (Table2) despite a relatively high level of land-
scape fragmentation. This result may be explained by the
persistence of considerable amounts of broad-leaf and mixed
forest habitats, particularly in the moderately populated low
mountain regions (Steyer etal. 2018).
Hybridisation between the European wildcat and the early
forms of domestic cat may have been occurring in Europe
since the spread of Neolithic farming (Ottoni etal. 2017).
There is evidence for prehistoric gene flow between mem-
bers of the Felis silvestris/lybica species complex, suggest-
ing a complicated phylogenetic relationship (Driscoll etal.
2007; Ottoni etal. 2017). In our study, we analysed non-
recombinant paternal markers to assess current distribution
and frequency of uniparental lineages in European wildcats
and domestic cats. Interestingly, the assignment of mito-
chondrial haplotypes revealed that wildcats and domestic
cats do not appear as completely distinct maternal clades.
Besides a wildcat clade (FS-A) and a domestic cat clade (FS-
B), there is a shared one between both taxa (FS-C; Fig.4).
Similar findings have been described in previous studies
(Driscoll etal. 2007; Eckert etal. 2009; Steyer etal. 2016,
2018).
In our study, the individual haplotypes within the clade
FS-C appeared exclusively for domestic cats or wildcats.
Hence, a derivation from recently occurring hybridisation
is highly unlikely. The two wildcat haplotypes within the
clade FS-C (FS22 and FS23) occurred commonly in sev-
eral studied wildcat populations showing highest frequen-
cies in Southeast Europe and Central Germany. Baca etal.
(2018) suggested that ancient hybridisation may have led to
introgression from early arriving domestic cats to wildcats.
Ottoni etal. (2017) found evidence for ancient gene flow
taking place between F. silvestris and F. lybica, the ancestor
of domestic cats. They suggest that the range of F. lybica
extended temporarily beyond the formerly existing Bospho-
rus land bridge between Europe and Asia due to climatic
fluctuations during Late Pleistocene (Ottoni etal. 2017).
During the last glacial period populations of the European
wildcat drastically declined and persisted in several small
refugia in southern Europe (Sommer and Benecke 2006).
When domestic cats firstly arrived in Southeast Europe from
around 6000years ago (Ottoni etal. 2017), the postglacial
range expansion of the European wildcat already included
large parts of Central Europe (Sommer and Benecke 2006).
The clear prevalence of haplotypes FS22 and FS23 in wild-
cat populations in Southeast and Central Europe today may
support an introgression event that occurred before the
postglacial expansion of the European wildcat. However,
a derivation from incomplete lineage sorting, as suggested
by Eckert etal. (2009), may lead to similar patterns and
thus serves as another explanation. Considering the com-
plex phylogenetic relations between members of the Felis
silvestris/lybica species complex, it is highly recommended
to include recombinant nuclear markers when identifying
species or hybrids and, if available, also to use diagnostic
morphological characters.
Conclusions andimplications
forconservation
Using a panel of discriminative SNP markers, we confirmed
that hybridisation between wildcats and their domestic con-
geners is a widespread phenomenon throughout the species’
range. However, the overall level of hybridization is moder-
ate, suggesting that long-term coexistence with the domes-
tic cat may allow the persistence of the genetic integrity
of wildcat populations, even in anthropogenically disturbed
landscapes with high abundances of domestic cats. Never-
theless, frequent hybridisation with the domestic cat may
regionally threaten the genetic integrity of the European
wildcat, as documented by the example of the wildcat in
Scotland and potentially leading even to the genetic extinc-
tion of local populations.
Our findings highlight the need for regionally adapted
conservation management for wildcats, which accounts for
the geographically varying importance of hybridisation as
a threat for the long-term integrity of the species. Regular
monitoring of wildcat populations and hybridisation rates
is highly recommended. We strongly urge the application
of harmonised nuclear marker panels throughout Europe to
achieve supra-regional comparisons of hybridisation rates
and degrees of introgression in local wildcats. Only the col-
lection of further large-scale data allows a deeper insight
into the reasons and mechanisms of regionally accelerated
hybridisation rates in different regions and particularly at
the edges of the species’ distribution that may be more
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257Conservation Genetics (2020) 21:247–260
1 3
susceptible to hybridisation. To understand the dynamics
and consequences of hybridisation between wildcats and
domestic cats, we highlight the need for interdisciplinary
research involving palaeobiology, landscape ecology, ethol-
ogyand genomics.
Acknowledgements Open Access funding wasprovided by Projekt
DEAL. Samples used in the frame of this study were collected over
several years, and we warmly appreciate the help of numerous wildcat
experts. In particular, we thank Thomas Mölich and Burkhard Vogel
(BUND), Franz Müller, Manfred Trinzen, Annette Kohnen (FVA),
Malte Götz, Gisbert Geisler, Ole Anders (Nationalpark Harz) and
several federal conservation agencies (Thuringian State Department
for Environment and Geology, Lower Saxon State Department for
Waterway, Coastal and Nature Conservation, State Department for
Environmental Protection Sachsen-Anhalt). We appreciate the techni-
cal support of several members of the Conservation Genetics group:
Tobias Erik Reiners, Berardino Cocchiararo, Alina von Thaden, Han-
nah Jüngling, Yvonne Puder. AT received partial funding in the frame
of the BUND-led project “Wildkatzensprung” funded by the German
Federal Agency for Nature Conservation (BfN) with resources provided
by the Federal Ministry for the Environment, Nature Conservation and
Nuclear Safety (BMU). ACK thanks the Negaunee Foundation for its
generous support of a curatorial preparator who prepared the samples
from Scotland. MC thanks Luca Lapini (Friulian Museum of Natu-
ral History), Andrea Sforzi (Natural History Museum of Maremma)
and Prof. Martin Fischer (Friedrich-Schiller University, Jena) for
making the collection of the Italian samples possible. PM enjoyed a
postdoctoral fellowship funded by FEDER funds through the Opera-
tional Programme for Competitiveness Factors—COMPETE, and by
National Funds through FCT—Foundation for Science and Technology
(UID/BIA/50027/2013 and POCI-01-0145-FEDER-006821).
Data accessibility Sampling locations, all genetic raw data, and results
from the software analyses as reported in this study, including mito-
chondrial sequences, genotypes from microsatellites, and SNPs, are
available in supplementary information files. DNA sequence data
used for haplotype network have been submitted to GenBank and have
accession numbers KR076400-KR076428, JX045658-JX045661,
KX161418-KX161423, and MN518925-MN518932. Customized
R-Script are available from the corresponding authors on reasonable
request.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
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AnnikaTiesmeyer1,2 · LuanaRamos3,4· JoséManuelLucas5· KatharinaSteyer1· PauloC.Alves3,4,6·
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3 CIBIO, Centro de Investigação Em Biodiversidade E
Recursos Genéticos, Universidade doPorto, InBIO
- Laboratório Associado, Vairão, Portugal
4 Departamento de Biologia, Faculdade de Ciências da
Universidade doPorto, Porto, Portugal
5 Departamento de Zoología y Antropología Física, Facultad
de Veterinaria, Universidad de Murcia, Campus de
Espinardo, 30100Murcia, Spain
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Germany
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