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Mitochondrial DNA and microsatellite analyses of
the genetic status of the presumed subspecies
Cervus elaphus montanus (Carpathian red deer)
PGD Feulner
1
, W Bielfeldt
2
, FE Zachos
2
, J Bradvarovic
3
, I Eckert
2
and GB Hartl
2
1
Institut fu
¨
r Biochemie und Biologie, Evolutionsbiologie/Spezielle Zoologie, Universita
¨
t Potsdam, Karl-Liebknecht-Str. 24-25 (Haus 25),
14476 Golm, Germany;
2
Institut fu
¨
r Haustierkunde, Christian-Albrechts-Universita
¨
t, Olshausenstr. 40, 24118 Kiel, Germany;
3
26 340
Bela Crkva, ul. Dositejeva 8, Serbia, Yugoslavia
The possibly distinct Carpathian red deer was compared
genetically to other European populations. We screened 120
red deer specimens from Serbia, the Romanian lowland and
the Romanian Carpathians for genetic variability using
582 bp of the mitochondrial control region and nine poly-
morphic nuclear microsatellite loci. The study aimed at a
population genetic characterization of the Carpathian red
deer, which are often treated as a distinct subspecies
(Cervus elaphus montanus). The genetic integrity of the
Carpathian populations was confirmed through the haplotype
distribution, private alleles and genetic distances. The
Carpathian red deer are thus identified as one of the few
remaining natural populations of this species, deserving
special attention among game and conservation biologists.
The history of the populations studied, in particular the
introduction of Carpathian red deer into Romanian lowland
areas in the 20th century, was reflected by the genetic data.
Heredity (2004) 93, 299–306. doi:10.1038/sj.hdy.6800504
Publishedonline30June2004
Keywords: red deer; Carpathians; mitochondrial DNA; microsatellites; population genetics
Introduction
Subspecific designations of populations have an important
bearing on conservation biology and management plans
(O’Brien and Mayr, 1991) although the subspecies concept
is partly arbitrary since it is based upon ‘diagnostic
morphological characters’ (Mayr, 1963, p 348), which
makes it impossible to consider subspecies to be real
evolutionary units (Mayr, 1942, 1963). From a population
biological point of view, it is genetic integrity rather than
taxonomic status that renders populations worthy to be
treated as evolutionary and conservation units.
The European red deer (Cervus elaphus) has been
undergoing human influences such as translocations,
habitat fragmentation and selective hunting throughout
Europe for many centuries (Lowe and Gardiner, 1974;
Hartl et al, 2003). As a consequence, genetic boundaries
between populations have been blurred and few stocks
are historically indigenous. In Italy, for example, the only
native red deer population is that from the Mesola
sanctuary in the Po delta area (Geist, 1998; Lorenzini et al,
1998). The Carpathian red deer are interesting in that
they have been considered both to be indigenous (Nedic,
1940; Philipowicz, 1961) and to be a distinct subspecies,
characterized morphologically by their grayish color, the
absence of a dark mark on the rump patch, and the lack
of a mane (Dobroruka, 1960; Groves and Grubb, 1987).
The first to ascribe Carpathian deer taxonomic status was
Botezat (1903), and since then, the Carpathian red deer,
when granted subspecific status, has been called
C. elaphus montanus (but see Grubb, 2000, who presents
evidence that the name montanus is taxonomically
invalid). According to Dobroruka (1960), the geographic
distribution of C. elaphus montanus ranges from the
eastern Carpathians to southern Ukraine and the Crimea,
while Groves and Grubb (1987) extend its northern range
as far as the Baltic coast. The Carpathian red deer is thus
considered to be geographically intermediate between
C. e. hippelaphus in the west and C. e. maral in the east. No
genetic analysis of this presumed subspecies has been
carried out. Our study does not aim at corroborating any
taxonomical designation but rather at elucidating the
genetic status in terms of isolation and differentiation of
the Carpathian red deer in order to test the hypothesis of
its genetic integrity, and thus possibly identify another
natural red deer stock in Europe. The molecular markers
chosen are nine microsatellite loci and sequence data
from the mitochondrial control region – both powerful
tools for population genetic analyses (Avise et al, 1987;
Schlo
¨
tterer and Pemberton, 1994; Goldstein and Schlo
¨
t-
terer, 1999) which have been used in previous studies on
red deer (eg Coulson et al, 1998; Slate et al, 2000; Randi
et al, 2001; Kuehn et al, 2003; Zachos et al, 2003). The
mitochondrial control region is the noncoding and, with
a large number of point mutations, insertions and
deletions, it is the most variable part of the mitochondrial
DNA (Moritz et al, 1987). A combination of these two
markers is a comprehensive approach that combines the
highly polymorphic microsatellites whose high mutation
rates (Weber and Wong, 1993; Hancock, 1999) allow for
Received 23 October 2003; accepted 8 April 2004; published online
30 June 2004
Correspondence: FE Zachos, Institut fu
¨
r Haustierkunde, Christian-
Albrechts-Universita
¨
t, Olshausenstr. 40, 24118 Kiel, Germany.
E-mail: fzachos@ifh.uni-kiel.de
Heredity (2004) 93, 299–306
&
2004 Nature Publishing Group All rights reserved 0018-067X/04 $30.00
www.nature.com/hdy
small-scale resolution of demographic events with
mitochondrial lineages which are often used in analyses
of phylogeographic events dating further back in time
(eg Avise et al, 1987; Randi et al, 1998; Barnes et al, 2002).
Material and methods
Sampling
The study is based on 120 specimens of C. elaphus from
10 different locations in Serbia and Romania (abbrevia-
tions and sample sizes of mtDNA/microsatellite ana-
lyses given in parentheses): Bachka (BAC, 33/30), Banat
(BAO: free-living animals, 13/13; BAF: animals from a
fenced area, 8/8), Temishvar (TEM, 10/10), Arad (ARA,
15/12), Karansebesh (KAR, 1/0), Brashow (BRA, 12/10),
Covasna (COV, 8/8), Harghita (HAR, 11/11), and Reghin
(REG, 9/9) (Figure 1). From Karansebesh only one
individual was available and was excluded from the
population genetic analyses, but its mtDNA haplotype
was included in the phylogenetic analysis. Muscle tissue
was collected from culled animals during the hunting
seasons 2000 and 2002 by local hunters and was stored at
201C until further analysis.
The extinct Banat population was refounded in the
20th century (1938, 1943 and 1994) with 29 individuals of
native Bachka red deer (Bradvarovic et al, 1994; Bjedov
et al, 1997; Bradvarovic, 1997). Between 1960 and 1980, an
introduction project of Carpathian red deer throughout
Romania was carried out with the aim of replacing the
Romanian lowland deer, which had been introduced
there from game parks in Hungary, Austria and
Czechoslovakia in the 18th and 19th century, with the
stronger Carpathian ones in order to improve the quality
of antler trophies (Almasan, 1988). Consequently, the
populations in Karansebesh and Arad are a mixture of
Carpathian and central European red deer. In Temishvar,
on the other hand, the red deer are free from Carpathian
introgressions. There are no migration barriers within the
Carpathians, but, according to local hunters’ experience,
there is no migration between the Carpathians and the
Romanian lowland. Red deer are known to cross the
border between the Banat region in Serbia and the
adjacent region in Romania, and the Bachka population
is in contact with stocks in Croatia (via the Danube which
the animals are able to cross) and Hungary.
Mitochondrial DNA
Total genomic DNA of frozen muscle tissue was
extracted by means of the Super QuikGene-Extraction
kit (Genetic Analytical Testing Center). Amplification of
the mitochondrial control region was performed using
the primers Pro-L and Phe-Hb (cf Zachos et al, 2003).
PCR amplification was conducted according to Zachos
et al (2003). Conditions were as follows: 40 cycles of 75 s
at 941C, 90 s at 591C and 75 s at 721C, preceded by a 5 min
initial denaturation at 951C and followed by a 7 min
terminal elongation at 721C. PCR products were se-
quenced with an automatic sequencer (ABI Sequencer
373) using the forward primer Pro-L. Sequences were
aligned manually using BioEdit version 5.0.9 (Hall, 1999).
Haplotype and nucleotide diversities (Nei, 1987) were
calculated using DnaSP3.51 (Rozas and Rozas, 1999).
Relationships among haplotypes were visualized using
neighbor-joining (based on Kimura-2-parameter dis-
tances), maximum likelihood and maximum parsimony
methods as implemented in PHYLIP (Felsenstein, 1993).
These three methods were chosen to check if the trees
based on distances (neighbor-joining), character states
(maximum parsimony, an algorithm constructing the tree
with the minimum number of mutations) and likelihood
approaches yielded consistent results. In order to carry
out population comparisons, genetic distances after
Reynolds et al (1983) were derived from haplotype
frequencies using PHYLIP, and a neighbor-joining tree
was constructed. Support for nodes was assessed by
bootstrap resampling using 100 (maximum likelihood) or
1000 replicates. A Mantel-test was conducted with the
software
NTSYS-pc 1.80 (Rohlf, 1994) to test for a
correlation between genetic and geographic distances.
Contrary to absolute genetic differentiation as assessed
by pairwise distances, Wright’s F-statistics provides a
means of hierarchical analysis of genetic diversity. We
calculated the overall F
ST
value, yielding the proportion
of the total genetic diversity accounted for by the
differentiation among populations, using Arlequin
(Schneider et al, 2000). For the construction of mtDNA
trees, a sequence of C. alfredi, a close relative of C. elaphus,
waschosenasoutgroup(http://www.ncbi.nlm.nih.gov./,
accession number AF291891, Randi et al, 2001). Addi-
tional red deer sequences from Randi et al (2001,
accession numbers AF291885-9) and Zachos et al (2003)
were integrated into an extended analysis, which was
conducted on the basis of 332 bp because this was the
length of the sequences analysed by Zachos et al (2003).
Microsatellites
Microsatellite amplification was performed as described
above except reaction volumes were 37.5 ml and micro-
satellite-specific annealing temperatures ranging from 55
to 631C were used. Nine polymorphic loci developed in a
variety of other ungulates were analysed: BM888,
Figure 1 Geographic location of the populations studied in Serbia
and Romania. Bachka, Banat, Arad, Temishvar and Karansebesh are
lowland populations; Reghin, Harghita, Covasna and Brashow lie
within the Carpathians. From Banat, two populations were studied,
one free-ranging and one from a fenced area.
Genetic integrity of Carpathian red deer
PGD Feulner et al
300
Heredity
BM4208, BM4513 (Bishop et al, 1994), MAF35 (Swarbrick
et al, 1991), MAF109 (Swarbrick and Crawford, 1992),
INRA11 (Vaiman et al, 1992), OarCP26 (Ede et al, 1995),
OarFCB304 (Buchanan and Crawford, 1993), and
CSSM43 (Moore et al, 1994). Microsatellite loci were
tested for linkage disequilibrium with GENEPOP 3.2
(Raymond and Rousset, 1995). Observed and expected
heterozygosities as well as deviations from Hardy–
Weinberg equilibrium and overall F
ST
were calculated
using Arlequin. To obtain a measure of allelic diversity
(mean number of alleles per locus) independent of
sample sizes, allelic richness values were calculated with
FSTAT (Goudet, 1995). Private alleles (Slatkin, 1985) were
counted and a population differentiation test (GENEPOP
3.2) and an assignment test based on individual
genotypes (Paetkau et al, 1995) were carried out. In the
assignment test, all individuals are assigned to the
population of which their genotype is most typical.
Incorrect assignments indicate little genetic differentia-
tion between the respective populations. Population
differentiation was further quantified with Nei’s (1972)
genetic standard distances D and chord distances
(Cavalli-Sforza and Edwards, 1967), both calculated
using PHYLIP. Correlation between genetic and geo-
graphic distances was tested as described above.
Neighbor-joining and Fitch-Margoliash trees (1000 boot-
strap replications) based on standard and chord
distances were constructed with the PHYLIP package.
An additional microsatellite tree based on seven of the
nine loci was constructed with data taken from Zachos
et al (2003). The seven loci used were the same as those
analysed by Zachos et al (2003).
Results
Mitochondrial DNA
A total of 120 individuals from 10 sampling sites were
screened for variation in the mitochondrial control
region. Sequencing of 582 bp revealed 36 variable sites
(31 transitions, two transversions, and three deletions)
and resulted in the detection of 14 putative haplotypes
(Table 1). Haplotypes 14 and 9 were the most common
sampled with overall frequencies of 46 and 24%,
respectively. The former haplotype was found in the
Serbian populations (where 53 out of 54 individuals
showed this haplotype) and in Arad while the latter was
confined to the four Carpathian populations in each of
which it was by far the most common. Haplotype 4 was
the most divergent, separated from the other 13
haplotypes by at least 18 mutations, and was found in
only one individual from Reghin in the Carpathians. The
four Carpathian populations yielded six haplotypes four
of which were found nowhere else; the remaining two
haplotypes also occurred in Arad (Table 1) where
Carpathian deer were introduced in the second half of
the 20th century (see above). Overall differentiation
among all studied populations (F
ST
value) was 61.65%,
indicating considerable differentiation between popula-
tions. Haplotype diversities ranged from 0.000 to 0.810
and nucleotide diversities from 0.000 to 0.954% (Table 2),
and in both cases the highest values were exhibited by
the hybrid population from Arad. Among the Car-
pathian populations, net nucleotide diversities were very
low, ranging from 0.000 to 0.134 while those between
Table 1 Distribution of mitochondrial haplotypes (HT)
BAC BAO BAF TEM ARA KAR BRA COV HAR REG S
HT 1 7 7
HT 2 1 2 3
HT 3 1 1
HT 4 1 1
HT 5 1 1 2
HT 6 6 1 7
HT 7 2 2
HT 8 2 2
HT 9 6 6 9 8 29
HT 10 3 1 4
HT 11 4 1 5
HT 12 1 1
HT 13 1 1
HT 14 32 13 8 2 55
S 33 13 8 10 15 1 12 8 11 9 120
For population abbreviations see text. Note that haplotype 9, the
most common in the Carpathian populations (BRA, COV, HAR,
REG), is exclusive to this region.
Table 2 Haplotype (HD) and nucleotide (p) diversities for the red
deer populations in Serbia and Romania
Pop HD p (%)
BAC 0.061 0.010
BAO 0.000 0.000
BAF 0.000 0.000
TEM 0.511 0.463
ARA 0.810 0.954
BRA 0.667 0.845
COV 0.464 0.461
HAR 0.327 0.451
REG 0.222 0.691
Table 3 Net nucleotide diversities (in %) between populations as a pairwise distance measure based on 582 bp of the mitochondrial control
region
BAC BAO BAF TEM ARA BRA COV HAR REG
BAC —
BAO 0.000 —
BAF 0.000 0.000 —
TEM 1.000 1.000 1.000 —
ARA 0.468 0.468 0.468 0.419 —
BRA 0.697 0.701 0.701 0.208 0.361 —
COV 1.046 1.048 1.048 0.162 0.475 0.014 —
HAR 1.162 1.162 1.162 0.199 0.471 0.134 0.000 —
REG 1.279 1.280 1.280 0.215 0.545 0.125 0.000 0.000 —
Genetic integrity of Carpathian red deer
PGD Feulner et al
301
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Carpathian and non-Carpathian populations ranged
from 0.162 to 1.280 (Table 3).
The phylogenetic trees based on the haplotypes were
consistent irrespective of the underlying construction
algorithm, but yielded no clear geographic pattern. The
inclusion of sequences from other south European red
deer populations (southern Spain, northern Italy, Sardi-
nia, and Bulgaria, Zachos et al, 2003) as well as from
single specimens from Spain, Norway, Italy, and Sardinia
(Randi et al, 2001) did not change tree topology. The
divergent haplotype 4, along with the two sequences
from Spanish and Norwegian red deer taken from Randi
et al (2001), clustered with some of the Spanish and
Sardinian samples from Zachos et al (2003) while all
other haplotypes from Serbia and Romania formed a
clade with the sequences from Italian and Bulgarian red
deer (Figure 2).
When genetic distances derived from haplotype
frequencies were used for tree reconstruction, the
resulting topology was consistent with the geographic
location of the respective populations (cf Figure 3). In
particular, all four Carpathian populations clustered
together. However, genetic and geographic distances
between all populations under study (neglecting only the
Figure 2 Maximum parsimony consensus tree of the fourteen haplotypes found in this study (Haplo 1–14) combined with red deer sequences
from the literature. Haplotypes represented by three capital letters are taken from Zachos et al (2003), numbers and abbreviations are the same
as in the original publication (SSP ¼ southern Spain; VDS ¼ Val di Susa, Italy; TAR ¼ Tarvis, Italy; SAR ¼ Sardinia; BUL ¼ Bulgaria). The
sequences denoted Cervus alfredi (outgroup), C. e. corsicanus (Sardinia), C. e. hispanicus (Spain), C. e. atlanticus (Norway) and C. e. hippelaphus
(Italy) are taken from Randi et al (2001, for gene bank accession numbers see text). Numbers at nodes denote support from 1000 bootstrap
replications. Haplotypes 5 and 10 as well as 13 and 14 of this study are identical in this tree because the sequences had to be reduced to 332 bp
to be comparable to those of Zachos et al (2003). The topology of this tree is consistent with the results gained from other tree reconstruction
algorithms (neighbor-joining, maximum likelihood). For details, see text.
Genetic integrity of Carpathian red deer
PGD Feulner et al
302
Heredity
deer from the fenced area in Banat) did not show a
statistically significant correlation (Mantel-test).
Microsatellites
All loci were polymorphic with between 16 and 37 alleles
and there was no linkage disequilibrium after Bonferroni
correction for multiple testing so that all loci were
included in the analysis. The PCR-amplification for locus
MAF109 failed in 10 out of 11 individuals of the Harghita
population, suggesting the existence of a nearly fixed
mutation in the primer binding region resulting in null
alleles (Callen et al, 1993; Koorey et al, 1993; for
microsatellite null alleles in red deer cf Pemberton et al,
1995). In order to rule out the possibility of a bias due to
these putative null alleles, further calculations were
performed both with and without MAF109. Results were
the same in both approaches and only analyses including
MAF109 data are presented here.
Values of allelic diversity and allelic richness are given
in Table 4. Out of 657 alleles 68 (10.4%), were private
alleles. The proportion of private alleles in the Car-
pathian populations was very low (0.68–4.9%). When
these four populations were combined, the proportion of
private Carpathian alleles was 16.6% with one allele (152
at locus BM4513) occurring in all four populations.
Overall expected and observed heterozygosities ranged
from 0.79 to 0.90 and 0.47 to 0.62, respectively (Table 4).
Significant deviations from Hardy–Weinberg-equili-
brium, all due to an excess of homozygotes, occurred
in all populations under study, in one (Bachka) for all
nine loci. The test of population differentiation revealed
significant differences between the populations (Po0.05)
and the assignment test yielded a proportion of correct
assignments of 55%. Incorrect assignments occurred
especially often among the four Carpathian populations,
but only four out of 38 Carpathian individuals were
assigned to a non-Carpathian population. Overall genetic
differentiation (F
ST
value) was 3.6%, a value much lower
than that for mtDNA sequences, but this is due largely to
the high number of alleles in microsatellites leading to a
large amount of genetic diversity within populations.
The pairwise genetic distances given in Table 5 clearly
show that differentiation among the Carpathian popula-
tions is considerably lower than between the Carpathian
and the other populations. The resulting neighbor-
Figure 3 Neighbor-joining tree based on Nei’s standard distances
derived from microsatellite allele frequencies. Numbers at nodes
denote support from 1000 bootstrap replications. The neighbor-
joining tree based on the mtDNA haplotype frequencies (distance
values according to Reynolds et al, 1983) yielded a consistent
topology. The geographic location of the populations (cf. Figure 1) is
reflected by the dendrogramm.
Table 4 Average (mean over all loci) values of allelic diversity (AD),
allelic richness (AR), expected and observed heterozygosity (H
E
and
H
O
) based upon the analysis of nine microsatellites
Pop. AD AR H
E
H
O
BAC 12.8 1.813 0.82 0.53
BAO 7.3 1.784 0.81 0.57
BAF 5.4 1.748 0.79 0.61
TEM 8.5 1.867 0.90 0.58
ARA 9.3 1.869 0.90 0.47
BRA 7.5 1.830 0.87 0.50
COV 6.7 1.830 0.88 0.62
HAR 7.7 1.849 0.88 0.55
REG 6.3 1.834 0.87 0.52
Table 5 Nei’s standard (below diagonal) and Cavalli-Sforza and Edwards’ chord (above diagonal) distances between populations based
upon allele frequencies of nine polymorphic microsatellite loci
BAC BAO BAF TEM ARA BRA COV HAR REG
BAC — 0.063 0.053 0.068 0.068 0.073 0.088 0.085 0.083
BAO 0.448 — 0.076 0.020 0.085 0.102 0.098 0.101 0.102
BAF 0.263 0.492 — 0.082 0.079 0.092 0.108 0.105 0.095
TEM 0.612 0.726 0.595 — 0.062 0.078 0.100 0.089 0.096
ARA 0.540 0.722 0.573 0.330 — 0.075 0.095 0.095 0.084
BRA 0.569 0.917 0.660 0.653 0.624 — 0.055 0.057 0.058
COV 0.855 0.928 1.053 0.988 0.879 0.458 — 0.060 0.075
HAR 0.767 1.028 0.858 0.691 0.787 0.383 0.414 — 0.055
REG 0.736 1.061 0.704 0.765 0.627 0.385 0.529 0.370 —
Genetic integrity of Carpathian red deer
PGD Feulner et al
303
Heredity
joining trees (Figure 3, the Fitch-Margoliash trees yielded
very similar topologies and are not shown) confirm the
genetic integrity of the Carpathian deer by clustering the
four populations with very high bootstrap support. This
topology is consistent with that based on the mtDNA
haplotype frequencies in that it reflects the geographic
location of the studied populations: the Carpathian and
the Serbian populations are connected by the geographi-
cally intermediate populations of Arad and Temishvar.
In accordance with the results obtained from the mtDNA
sequences, there was no statistically significant correla-
tion between genetic and geographic distances (Mantel-
test). The trees obtained from the extended data set
(including populations from Spain, mainland Italy,
Sardinia, and Bulgaria, cf Zachos et al, 2003) did not
reveal a close relationship between any of the popula-
tions of the two studies but yielded two distinct clusters,
one comprising the populations of the present study, the
other those from Zachos et al (2003).
Discussion
Genetic variability of the studied populations as revealed
by haplotype and nucleotide diversity, allelic diversity
and heterozygosity were within the range of values
previously found for red deer (Martinez et al, 2002;
Kuehn et al, 2003; Zachos et al, 2003). With the exception
of Reghin, haplotype and nucleotide diversity were
correlated. The Reghin population showed little haplo-
type diversity but a high nucleotide diversity, which is
explained by the fact that one of the two haplotypes
found in Reghin, haplotype 4, was rare but at the same
time very divergent (leading to a high nucleotide
diversity, which is not only based on the number of
different haplotypes but also on their degree of differ-
ence). The striking deviations from Hardy–Weinberg
equilibrium yielded by our microsatellite analysis could
be a consequence of the relation between sample size and
microsatellite variability: given the high allele numbers
in the different populations, Hardy–Weinberg frequen-
cies are a priori not very probable with sample sizes
ranging from 8 to 30 animals per population. Another
possible explanation is that migration occurs. As stated
above, there are no migration barriers within the
Carpathian region, and migration is known to take place
between western Romania and the Banat as well as
between Bachka, Hungary and Croatia. The population
of Arad is remarkable in that it exhibits both the lowest
observed and (together with Temishvar) the highest
expected heterozygosities. Arad also shows the highest
allelic richness and the second highest allelic diversity
(second only to Bachka where the sample size is more
than twice as high). Regarding mitochondrial DNA,
Arad has the highest number of haplotypes (6 vs 1–4 in
the other populations) and the highest haplotype and
nucleotide diversity. Such a large genetic variability may
well be a consequence of the different origins of the deer
in Arad. The low observed heterozygosity and hence the
excess of homozygotes could be the result of inbreeding
in the recent past. This inbreeding may have only
affected the highly variable microsatellite loci so far but
not the more conservative mitochondrial DNA. Alter-
natively, the Arad population could be composed of
different subpopulations (Wahlund effect).
The data presented here show that there are both
congruences and incongruences between the mtDNA
and microsatellite analyses. One of the most striking
differences is the genetic variability of the Serbian red
deer as represented by haplotype or nucleotide diversity
vs allelic diversity and heterozygosity: while the latter
was well within the range of the values for the other
populations studied, mtDNA variability of Serbian red
deer was practically nonexistent. The phylogenetic
analysis of haplotypes revealed, contrary to the distribu-
tion analysis of microsatellite alleles, no geographic
pattern. Interestingly, such a pattern emerged when the
distribution of haplotypes was examined. These findings
could be interpreted as evidence that the mtDNA
haplotypes themselves (as opposed to their distribution)
are too old to uncover the recent population biological
processes in the area under study. The resolving power
of microsatellites, which have a higher mutation rate
than mtDNA, seems to be high enough to detect genetic
variability even in populations without haplotypic
variation as is exemplified by the Serbian populations
of Bachka and Banat. While all deer analysed from Banat,
both free-living and captive, showed the same haplotype
as the Bachka deer (from which they are derived, see
above), the genetic distances based on microsatellites
were within the range of those among the Carpathian
populations. Since mtDNA patterns are of purely
maternal origin sex-specific differences in migration
may also account for different patterns yielded by
mitochondrial and nuclear markers. While this may
partly be true for both Banat and Bachka where
migration has been observed (see above), it is hard to
believe that migration alone could explain the discre-
pancy between usual microsatellite distances on the one
hand and 53 out of 54 Serbian red deer exhibiting the
same mitochondrial haplotype on the other. Alterna-
tively, it could be speculated that a selective sweep
generated by an advantageous mutation in a mitochon-
drial gene almost led to the fixation of this particular
haplotype although this scenario does not seem very
probable.
As mentioned earlier, the populations in Karansebesh
and Arad contain both Carpathian and central European
red deer while the Temishvar population is free from
Carpathian introgressions. These historical data are in
line with our population genetic findings: whereas the
Carpathians share two haplotypes with Arad, they have
none in common with Temishvar. The single individual
from Karansebesh showed a haplotype that was also
found in Arad but not in the Carpathians, and this
haplotype may be a legacy of the introductions from
central Europe in the 18th and 19th century.
As outlined in the introduction, the main aim of the
present study was to examine the status of the
Carpathian red deer. Our data unequivocally confirm
their genetic integrity, suggesting that they are indeed
historically indigenous. The distance values based on
both mitochondrial DNA (net nucleotide diversities) and
microsatellites (standard and chord distances) among the
four populations of Reghin, Harghita, Covasna and
Brashow are lower than between the Carpathian and
the other populations. The proportion of private micro-
satellite alleles of the four Carpathian populations
pooled is 16.6%, that is, one out of six alleles is confined
to this region. Haplotype 9 is exclusive to the region and
Genetic integrity of Carpathian red deer
PGD Feulner et al
304
Heredity
was found in 29 out of 40 individuals. Altogether, four
out of six mitochondrial haplotypes were exclusive to the
Carpathians, the remaining two only occurring in Arad
where Carpathian deer have been introduced. Thus, the
Carpathian red deer did not share any haplotypes with
truly non-Carpathian populations. Incorrect assignments
based on microsatellite genotypes often occurred among
Reghin, Harghita, Covasna, and Brashow, whereas only
four out of 38 Carpathian individuals were incorrectly
assigned to a population outside the Carpathians. There
is also a high bootstrap support for the Carpathian
branch in the trees based on mitochondrial haplotype
and microsatellite allele frequencies. The fact that, in
spite of the clear geographic pattern displayed by the
frequency distribution trees, there is no statistically
significant correlation between genetic and geographic
distances might be accounted for by the blurring of the
original pattern through migration and the extensive
introductions in Serbia and the Romanian lowland.
Regarding microsatellite variability as revealed by
allelic diversity, allelic richness and heterozygosity, the
Carpathian populations exhibited values similar to those
found in the other populations studied. When compared
to the endangered red deer population on Sardinia
(allelic diversity ¼ 3.2, H
E
¼ 0.52, H
O
¼ 0.36, Zachos et al,
2003), Carpathian deer showed much higher variability
values. mtDNA variability, however, was lower on
average than in the populations from southern Europe
studied by Zachos et al (2003), including Sardinia (only
the Brashow population had both a higher haplotype
and a higher nucleotide diversity than the Sardinian
deer), but mitochondrial variability of the Sardinian red
deer was unexpectedly high given its population history
and its isolation. Carpathian red deer thus show no signs
of being threatened by genetic depletion in the near
future. Nevertheless, whether they are granted subspe-
cific rank or not, the Carpathian red deer represent one of
the few remaining historically indigenous red deer
stocks in Europe and as such deserve attention among
game and conservation biologists – their genetic integrity
should be preserved and any introgression from foreign
stocks should be avoided.
Acknowledgements
We thank local hunters in Serbia and Romania for their
assistance in collecting tissue samples. John FY Brook-
field and two anonymous reviewers made valuable
comments on an earlier version of this manuscript. Their
suggestions are gratefully acknowledged.
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