Phylogeography of the pine processionary moth Thaumetopoea wilkinsoni in the Near East.

Molecular Ecology (2007)

16

, 2273–2283 doi: 10.1111/j.1365-294X.2007.03302.x
© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd

Blackwell Publishing Ltd
Phylogeography of the pine processionary moth

Thaumetopoea wilkinsoni

in the Near East

M. S IMONATO,

*

Z . MENDEL,

†

C . KERDELHUÉ,

‡

J . ROUSSELET,

§

E . MAGNOUX,

§

P . SALVATO,

*


A . ROQUES,

§

A . BATTISTI

*

and L . ZANE

¶

*

Dipartimento di Agronomia Ambientale e Produzioni Vegetali Entomologia, Agripolis, Università di Padova, Via Romea 16, 35020
Legnaro PD, Italy,

†

Agricultural Research Organization, Volcani Center — Department of Entomology, PO Box 6, IL-50250 Bet
Dagan, Israel,

‡

INRA Centre de Bordeaux-Pierroton, UMR BIOGECO, Entomologie et Biodiversité, 69 route d’Arcachon, F-33612
Cestas Cedex, France,

§

INRA-Orléans, Zoologie Forestière, BP 20619, F-45166 Olivet Cedex, France,

¶

Dipartimento di Biologia,
Università di Padova, Via G. Colombo 3, 35121 Padova, Italy

Abstract
Phylogeographic structure of the eastern pine processionary moth

Thaumetopoea wilkin-
soni

was explored in this study by means of nested clade phylogeographic analyses of COI
and COII sequences of mitochondrial DNA and Bayesian estimates of divergence times.
Intraspecific relationships were inferred and hypotheses tested to understand historical
spread patterns and spatial distribution of genetic variation. Analyses revealed that all

T. wilkinsoni

sequences were structured in three clades, which were associated with two
major biogeographic events, the colonization of the island of Cyprus and the separation of
southwestern and southeastern Anatolia during the Pleistocene. Genetic variation in popu-
lations of

T. wilkinsoni

was also investigated using amplified fragment length polymorph-
isms and four microsatellite loci. Contrasting nuclear with mitochondrial data revealed
recurrent gene flow between Cyprus and the mainland, related to the long-distance male
dispersal. In addition, a reduction in genetic variability was observed at both mitochon-
drial and nuclear markers at the expanding boundary of the range, consistent with a recent
origin of these populations, founded by few individuals expanding from nearby localities.
In contrast, several populations fixed for one single mitochondrial haplotype showed no
reduction in nuclear variability, a pattern that can be explained by recurrent male gene flow
or selective sweeps at the mitochondrial level. The use of both mitochondrial and nuclear
markers was essential in understanding the spread patterns and the population genetic
structure of

T. wilkinsoni

, and is recommended to study colonizing species characterized by
sex-biased dispersal.

Keywords

: AFLP, microsatellites, mitochondrial DNA,

Pinus

pest, range expansion,

Thaumetopoea
wilkinsoni



Received 3 October 2006; revision received 17 December 2006; accepted 22 January 2007

Introduction

Geographic distributions of species are known to vary
considerably in time, according to a number of factors
including the geological and palaeoclimatic history of the
habitat and the dispersal capacity of the organism (Gaston
2003). In particular, species’ ranges have been strongly
affected by Quaternary [2.4 million years ago (Ma) to
present] climatic fluctuations and ice ages (Hewitt 2000), at
least for European and North American temperate species.
The organisms responded to climatic oscillations by local
extinction in northern regions and survival in southern
refugia during the glacial maxima, and by northward
range expansions during interglacial, warmer periods.
These events played a major role in promoting speciation
through formation of isolating barriers allowing allopatric
divergence, and in shaping species phylogeography (Hewitt
1996). Yet, species display different phylogeographic
patterns, because their response to environmental changes

Correspondence: A. Battisti, Fax: +39 0498272810; E-mail:
andrea.battisti@unipd.it

2274

M . S I M O N A T O

E T A L .

© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd

during the ice ages primarily depended on ecological,
dispersal and life-history traits (Taberlet

et al

. 1998; Hewitt
1999, 2001). Some regions of the world, such as the Near
East, were never covered with ice during the Pleistocene,
but the occurring species may still have been influenced by
climatic oscillations such as cycles of wet and dry periods
(Horowitz 1988). Yet, very few studies have analysed the
phylogeographic history of terrestrial organisms in the
Near East (Tarkhnishvili

et al

. 2001; Veith

et al

. 2003), while
more information is available for other regions (Soltis

et al

.
2006).
Moreover, the geographic distribution of phytophagous
insects is necessarily embedded within the range of the host
plants that provides the potentially exploitable habitat.
Compared to the wealth of information about plants, for
which fossil deposits and pollen series often allow to
reconstruct the distribution over long periods (Klaus 1989;
Willis

et al

. 1998), very little knowledge is available con-
cerning the past distributions of phytophagous insects.
Fossil remains are scarce (Wilf & Labandeira 1999), and it
is rarely possible to directly compare host and associated
insect past distributions (but see Koteja (1990) for scale
insect–pine association since the Cretaceous). In this
context, genetic markers are useful tools to reconstruct the
evolution of insect herbivore lineages in relation to the
history of their host plants (Hewitt 2001). Phylogeographic
analyses of forest insect species have shown interesting
patterns of lineage differentiation, partly driven by host
plant distribution (Burban

et al

. 1999; Stauffer

et al

. 1999;
Kerdelhué

et al

. 2002; Horn

et al

. 2006). These studies indi-
cate a shared host–insect history of habitat colonization,
eventually followed by low interpopulation gene flow.
Different dispersal patterns may result either in low levels
of genetic diversity in new portions of the insect species’
range or in high diversity due to increased interpopulation
gene flow (Bialozyt

et al

. 2006; Oliver 2006). Dispersal
capacities can also affect spatial genetic structure via
strong limitation of gene flow (Kerdelhué

et al

. 2006). Since
dispersal strategies may differ between sexes (Greenwood
& Swingland 1983), the use of sex-specific markers can then
allow investigating the genetic effects and evolutionary
implications of gender-biased dispersal (Burban & Petit
2003; Sallé

et al

. 2007). Adult females of phytophagous
insects, especially among Lepidoptera laying eggs in large
patches, are often constrained by heavy egg loads that
reduce the flight distance (Thompson & Pellmyr 1991). The
combination of powerful sexual pheromones emitted by
the females and mobile males may counterbalance the
negative effects on gene flow caused by a low female vagility
(Salvato

et al

. 2005).
In this study, we explored the phylogeographic structure
of a phytophagous insect endemic of the Near East, the
eastern pine processionary moth

Thaumetopoea wilkinsoni

Tams (Lepidoptera: Notodontidae). It is a univoltine
insect, oligophagous on

Pinus brutia, Pinus halepensis,

and

Pinus nigra

(Schimitschek 1944, Halperin 1990), damaging
trees (Carus 2004; Kanat

et al

. 2005), and threatening public
health by releasing toxic hairs (Turkmen & Oner 2004). The
species was originally described from the island of Cyprus
in 1925 (Tams 1925; Wilkinson 1927). Near East continental
populations of pine processionary moths had long been
considered to belong to its sibling species

Thaumetopoea
pityocampa

(Denis et Schiffermüller), occurring on pine in
southern Europe and northern Africa, until Salvato

et al

.
(2002) provided evidence of species separation.
In particular, we tested the hypothesis that sex-biased
dispersal affects genetic variability, by contrasting patterns
of differentiation of mitochondrial and nuclear markers.
Within this framework, we examined three major phylo-
geographic patterns of

T. wilkinsoni

, such as (i) the genetic
divergence between the populations of the island of
Cyprus, whose formation dates back to the Messinian
period (5.3 Ma; Marra 2005) and Near East populations,
(ii) the differentiation among continental populations, as a
consequence of the climatic fluctuations associated with
ice ages (Hewitt 2001), and (iii) the affinity between core
continental populations and populations of recent origin,
as those resulting from the invasion of the southernmost
Israeli pine stands and of the Turkish coast of the Black Sea.

Materials and methods

Sampling and DNA protocols

Eggs and larvae of

Thaumetopoea wilkinsoni

were collected
at 15 different locations in Turkey, Cyprus, Lebanon and
Israel (Table 1). To reduce the risk of sampling siblings,
each individual used in the analyses was collected from a
different tree, either from an egg batch or from a nest. Eggs
were maintained at room temperature until hatching, after
which the first instar larvae were transferred to ethanol
70%. Alternatively, larvae were directly sampled from
nests in the field and immediately transferred to ethanol
70%. All ethanol-preserved material was stored at

−

20

°

C.
DNA was extracted using a salting-out procedure (Patwary

et al

. 1994). The same individuals were generally used for
all the analyses, different numbers resulted from limitations
imposed by the analytical procedures.
Two mitochondrial DNA (mtDNA) fragments, corre-
sponding to parts of the COI and COII genes, were amplified
from 192 individuals and examined through single-strand
conformation polymorphism (SSCP) analysis, as described
in Salvato

et al

. (2002). For each mobility class, one to five
individuals were sequenced directly using an ABI PRISM
3100 (Applied Biosystems) DNA sequencer and a Big Dye
Terminator Cycle Sequencing Kit (Applied Biosystems) to
check for the accuracy of the SSCP analysis and to determine
the corresponding haplotype. Sequences were aligned using

P H Y L O G E O G R A P H Y O F A F O R E S T P E S T

2275

© 2007 The Authors
Journal compilation © 2007 Blackwell Publishing Ltd

clustal x

(Thompson

et al

. 1997). Sequences of COI (262 bp)
and COII fragments (342 bp) were then concatenated,
resulting in a 604 bp-long final alignment.
Four microsatellite loci (MS-Thpit1, MS-Thpit3, MS-
Thpit4, MS-Thpit5) were characterized on 230 individuals.
Microsatellite primers and amplification conditions are
described in Rousselet

et al

. (2004). Fluorescent (polymerase
chain reaction) PCR products were run and detected on an
ABI PRISM 3100 automatic sequencer (Applied Biosystems)
and product sizes were determined using the

genescan

software (Applied Biosystems).
The amplified fragment length polymorphism (AFLP)
protocol (Vos

et al

. 1995) was used with four primer
combinations yielding 125 bands on 142 larvae analysed.
Approximately 50 ng of DNA were digested with

Eco

RI
and

Mse

I restriction enzymes and ligated to specific AFLP
adapters. Each sample was subsequently diluted 10-fold
and used as template for preselective and selective (

Eco

RI-
AAC/

Mse

I-CAT,

Eco

RI-ACA/

Mse

I-CAG,

Eco

RI-AGC/

Mse

I-CAT,

Eco

RI-AAG/

Mse

I-CAC) PCR amplifications.
AFLP products were run in an ABI PRISM 3700 DNA
Analyser (Applied Biosystems). Band scoring was per-
formed with

genotyper

version 3.7 (Applied Biosystems)
considering bands in the range 70–360 bp. AFLP profiles
were checked by hand for accurate scoring. The intensity of
each individual peak was normalized on the basis of the
total signal intensity and the peak was considered only if
its intensity exceeded a fixed threshold of 100 fluorescent
units. AFLP profiles were recorded in a matrix as presence
or absence of bands for each individual. Both polymorphic
and monomorphic bands were scored.

Data analysis

Homologous mtDNA sequences of two related species,

Thaumetopoea pityocampa

(Salvato

et al

. 2002: GenBank
Accession nos EF015538, EF015542) and

Thaumetopoea pinivora

(from Gotland, Sweden, accession number EF364032,
EF364033), were included in mitochondrial data analysis.
A partition homogeneity test was performed for the COI
and COII fragments using

paup

* v4.0b10 (Swofford 2002).
The test confirmed that these regions contained homo-
geneous signal (

P =

0.35), allowing data to be pooled for
further analyses.
Phylogenetic relationships between haplotypes were
estimated by Bayesian Inference (BI) with MrBayes v3.1
(Huelsenbeck & Ronquist 2001); the analyses were per-
formed without outgroup definition and best trees were
rooted with

T. pityocampa

and

T. pinivora

. BI analysis was
used because it implements codon position partitioned
models (CP models), thus allowing the protein coding
nature of the data to be considered. The best CP model was
selected by comparing the exact likelihood under different
models of a consensus maximum parsimony tree using the

baseml

software of PAML package (Yang 1997). Accord-
ing to published suggestions (Shapiro

et al

. 2006), two CP
models were tested, namely the Hasegawa, Kishino and
Yano model (HKY, Hasegawa

et al

. 1985) and the general
time reversible model (GTR, Lanave

et al

. 1984) with and
without gamma distributed site heterogeneity. The sequences
were partitioned according to codon position, and the chosen
model (and alpha where appropriate) was assumed for all
sites; different rates were allowed for each partition.
Table 1 Location of Thaumetopoea wilkinsoni populations, according to geographic position from southeast to northwest and to the host
plant on which samples were collected
Country Region/district Location Latitude Longitude
Altitude
(m a.s.l.) Host* Collector
Israel S Judean mountains Yatir 31°20′N 35°03′E 550 PA Authors
Israel W Negev Qisufim 31°22′N 34°24′E 50 PA Authors
Israel Judean foothills Haruvit 31°45′N 34°50′E 150 PA Authors
Israel Lower Galilee Segev 32°52′N 35°14′E 400 PA Authors
Israel Upper Galilee Qiryat Shemona 33°11′N 35°33′E 350 PB Authors
Lebanon Beirut Beirut 33°53′N 35°30′E 272 PB American University Beirut
Turkey Antakia Seyhköy 36°04′N 36°10′E 450 PB Authors
Turkey Iskenderun Iskenderun 36°34′N 36°10′E 210 PB Authors
Turkey Taurus mountains Aladag 37°33′N 35°22′E 1100 PB Authors
Turkey Taurus mountains Pozanti 37°17′N 34°51′E 970 PB, PN Authors
Cyprus E Cyprus El Skopi 35°00′N 32°40′E 100–1000 PB, PN Authors
Turkey Antalya Karaoz 36°54′N 30°43′E 200 PB University of Isparta
Turkey Isparta Gunur 37°46′N 30°34′E 1050 PB, PN University of Isparta
Turkey Izmir Aydin 37°51′N 27°50′E 600 PB University of Izmir
Turkey Samsun Samsun 41°17′N 36°20′E 150 PN Authors
*PA: Pinus halepensis, PB: Pinus brutia, PN: Pinus nigra.
m a.s.l., metres above sea level.

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Journal compilation © 2007 Blackwell Publishing Ltd
The best CP model found was then used for Bayesian
phylogenetic inference using mrbayes, with and without
enforcement of the molecular clock. Analyses were run for
1 million generations, and Markov chains were sampled
every 10 generations. The length of the chain was chosen
after that initial trials indicated approximate convergence
after 30 000 generations. The 50% majority rule consensus
tree and the Bayesian posterior probabilities were obtained
from sampled trees, after burning first 25% of the chain.
Clades were approximately dated using beast (Drum-
mond & Rambaut 2003), assuming a sequence divergence
rate of 2–2.3% per million years (DeSalle et al. 1987; Brower
1994). Models of sequence evolution, data partitioning and
clock assumptions followed the results obtained from
previous analyses; Markov chain Monte Carlo (MCMC)
was run for 10 million generations, results being logged
every 1000 generations. After discarding the first 10% of
the chain, convergence was checked by monitoring traces
of sampled parameters and effective sample size following
authors’ suggestions.
A haplotype parsimony network was reconstructed using
tcs 1.21 (Clement et al. 2000) as described by Templeton
et al. (1992), with a probability cut-off set at 93%. The net-
work was used to perform a nested clade phylogeographic
analysis (NCPA) using geodis version 2.0 (Posada et al.
2000), to test the null hypothesis of lack of association
between clades and geographic location. Significant values
were used to discriminate the effects of recurrent gene flow
and historical processes which may have affected the
spatial genetic structure of populations (Templeton 2004)
using the updated inference key (http://darwin.uvigo.es/
download/geodisKey_11Nov05.pdf).
The genetic variability of each population was estimated
for mitochondrial and microsatellite data using arlequin
version 3.1 (Excoffier et al. 2005) and expressed as haplotype
diversity and expected heterozygosity (HE), respectively.
For AFLP markers, the heterozygosity (HS) was estimated
by the Bayesian approach implemented in hickory ver-
sion 1.0 (Holsinger & Lewis 2003), to overcome problems
caused by dominance. In addition, for microsatellite data
only, deviations from Hardy–Weinberg equilibrium were
tested for each locus and population using arlequin, with
10 000 permutations. Comparisons of microsatellite nuclear
diversity among population groups were carried out by
fstat version 2.9.3.2 (Goudet 1995).
For all three markers, the partition of genetic variability
among populations and among group of populations was
defined by analysis of molecular variance (amova, Excoffier
et al. 1992) using arlequin. Pairwise ΦST and FST between
populations were also calculated. Distances used were
Kimura 2-parameters distance for mitochondrial data,
number of different alleles for microsatellites and pairwise
differences (equivalent to simple matching in Apostol et al.
1993) for AFLP. The use of alternative genetic distances for
mitochondrial data resulted in very similar results. Null
hypothesis of genetic homogeneity was assessed by 10 000
replications, reshuffling individuals among populations,
and, when needed, populations among groups.
Results
Mitochondrial DNA phylogeography
The SSCP analysis clearly distinguished 11 mobility classes
for the COI fragment and 15 classes for the COII fragment.
A total of 20 composite mobility classes (COI+COII) were
found. Random sequencing of individuals confirmed
the accuracy of the SSCP method, each mobility class
corresponding to a single haplotype and vice-versa (GenBank
Accession nos EF210075–EF210097). The uncorrected
pairwise divergence between Thaumetopoea wilkinsoni haplo-
types ranged from 0.0017 to 0.0348. When these haplotypes
were aligned with the homologous sequence of the closely
related Thaumetopoea pityocampa and Thaumetopoea pinivora,
the divergence between the three species ranged from
0.0894 to 0.1159.
The best model of sequence evolution was the GTR with
different rates for each codon position; this model was thus
chosen for phylogenetic inference and for the Bayesian
molecular clock analysis. BI consensus tree is showed in
Fig. 1. All T. wilkinsoni sequences were clustered in a single
monophyletic group (A) with 100% support. All haplo-
types from Cyprus were grouped in a cluster (B) with 97%
confidence, and appeared as the sister group of a well-
supported clade (C, 85%) containing all the haplotypes
Fig. 1 Consensus tree obtained from Bayesian inference of COI
and COII data. Numbers above branches indicate, when higher
than 70%, the Bayesian posterior probability of support for the
node. Clades discussed in the text are indicated by capital letters
A-D.

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Journal compilation © 2007 Blackwell Publishing Ltd
from continental sites. Within this latter cluster, a highly
supported group was identified (D, 98%) composed of haplo-
types found in Israel, Lebanon and in southeast Turkey
(Pozanti, Aladag, Iskenderun and Seyköy). The remaining
haplotypes from north and southwest Turkey were not
resolved inside the C group, except for a weak tendency of
haplotype 4H to cluster a sister group of clade D (73%).
The same well-differentiated groups were found in the
parsimony-based network (Fig. 2). It confirmed the strong
divergence of Cyprus (clade B) that differed by at least 12
mutations from the closest continental haplotype, and
identified two groups separated by at least 6 mutations,
corresponding to the D clade previously identified (south-
east Turkey) and a clade containing all haplotypes from
north and southwest Turkey. NCPA further showed that
the geographic distribution of Cypriot haplotypes (clade
3-3) was consistent with allopatric fragmentation, whereas
for the Lebanese, Israeli and southeastern Turkish haplotypes
(clade 3-1), it indicated a contiguous range expansion. No
conclusive indications were obtained concerning the dif-
ferentiation between the groups D and the remaining
clades (clades 3-1 vs. 3-2, Fig. 2).
The age of the most recent ancestor of supported groups
was estimated using beast, assuming a strict molecular
clock because analyses conducted with mrbayes showed
no significant differences in likelihood when the clock was
or was not enforced. Considering the 2–2.3% per million-
year (Myr) divergence rate for arthropod mtDNA, and
bearing in mind the large confidence intervals associated
with these estimates, the split between Cyprus and conti-
nental haplotypes (clade A, Fig. 1), was tentatively dated to
1.90–1.27 Ma. The continental haplotypes (clade C) diverged
1.12–0.74 Ma, and those in Cyprus and southeast Turkey
(clades B and D) diverged 0.30–0.20 Ma and 0.65–0.43 Ma,
respectively.
Comparison between mitochondrial and nuclear markers
Population genetic variability was estimated for the three
markers applied (Table 2). Most microsatellite loci and
populations were at Hardy–Weinberg equilibrium, as
only 8 tests were significant (locus MS-Thpit1 in Aladag,
Iskenderun and Seyhköy; MS-Thpit4 in Karaoz, Aladag,
Samsun and Iskenderun; MS-Thpit3 in Iskenderun). Haplo-
type diversity varied substantially between populations,
ranging from 0 in several populations at the southern and
northern edge of the species range, to 0.71–0.74 in the
Iskenderun and Cyprus samples.
Several populations fixed for a single mitochondrial
haplotype bore substantial microsatellite and AFLP variation.
In particular, among the 9 populations fixed for a single
mitochondrial haplotype, those at the boundary of the
distribution (Samsun in northern Turkey, and the four
southernmost Israeli populations of Segev, Haruvit, Yatir
Table 2 Descriptive statistics of mitochondrial and nuclear (microsatellite and AFLP) DNA markers, with the number of individuals
analysed. The same individuals were generally used for all the analyses, different numbers resulted from limitations imposed by the
analytical procedures. The symbol ± indicates the confidence interval (0.95) of each estimate
Country
and
location
Microsatellites
mtDNA N HE (unbiased) per locus
mean HE SD
AFLP (hickory)
N
Haplotype
diversity Thpit 1 Thpit 3 Thpit 4 Thpit 5 N HS
Israel Yatir 15 0.00 ± 0.00 14 0.20 ± 0.09 0.51 ± 0.04 0.20 ± 0.10 0.00 ± 0.00 0.23 0.21 15 0.15 ± 0.01
Israel Qisufim 10 0.00 ± 0.00 9 0.00 ± 0.00 0.50 ± 0.06 0.29 ± 0.12 0.00 ± 0.00 0.20 0.25 10 0.18 ± 0.01
Israel Haruvit 15 0.00 ± 0.00 14 0.25 ± 0.10 0.45 ± 0.07 0.14 ± 0.08 0.00 ± 0.00 0.21 0.19 15 0.21 ± 0.01
Israel Segev 9 0.00 ± 0.00 10 0.28 ± 0.12 0.44 ± 0.09 0.10 ± 0.09 0.00 ± 0.00 0.21 0.19 9 0.20 ± 0.01
Israel Qyriat Shemona 14 0.00 ± 0.00 13 0.50 ± 0.10 0.32 ± 0.10 0.76 ± 0.06 0.32 ± 0.10 0.48 0.21 14 0.19 ± 0.01
Lebanon Beirut 24 0.00 ± 0.00 24 0.36 ± 0.07 0.47 ± 0.04 0.56 ± 0.08 0.19 ± 0.07 0.39 0.16 9 0.18 ± 0.01
Turkey Seyhköy 11 0.00 ± 0.00 20 0.85 ± 0.02 0.43 ± 0.07 0.55 ± 0.09 0.00 ± 0.08 0.53 0.24 8 0.20 ± 0.01
Turkey Iskenderun 10 0.71 ± 0.12 19 0.82 ± 0.04 0.60 ± 0.06 0.88 ± 0.04 0.10 ± 0.06 0.60 0.35 — —
Turkey Aladag 10 0.51 ± 0.16 20 0.73 ± 0.03 0.49 ± 0.04 0.67 ± 0.05 0.00 ± 0.00 0.47 0.33 9 0.18 ± 0.01
Turkey Pozanti 11 0.51 ± 0.10 20 0.65 ± 0.06 0.36 ± 0.07 0.66 ± 0.05 0.00 ± 0.00 0.42 0.31 10 0.18 ± 0.01
Cyprus El Skopi 18 0.74 ± 0.08 15 0.70 ± 0.05 0.52 ± 0.09 0.94 ± 0.02 0.58 ± 0.10 0.69 0.19 16 0.22 ± 0.01
Turkey Karaoz 8 0.46 ± 0.20 8 0.52 ± 0.13 0.13 ± 0.11 0.88 ± 0.05 0.00 ± 0.00 0.38 0.40 8 0.20 ± 0.01
Turkey Gunur 15 0.00 ± 0.00 13 0.31 ± 0.12 0.09 ± 0.08 0.89 ± 0.05 0.00 ± 0.00 0.32 0.40 13 0.25 ± 0.01
Turkey Aydin 10 0.20 ± 0.15 11 0.00 ± 0.00 0.09 ± 0.08 0.82 ± 0.04 0.09 ± 0.08 0.25 0.38 — —
Turkey Samsun 12 0.00 ± 0.00 20 0.40 ± 0.08 0.00 ± 0.00 0.53 ± 0.07 0.00 ± 0.00 0.23 0.27 6 0.16 ± 0.01
HE, expected heterozygosity.