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Lack of association between winter coat colour and
genetic population structure in the Japanese hare,
Lepus brachyurus (Lagomorpha: Leporidae)
MITSUO NUNOME1*, GOHTA KINOSHITA2, MORIHIKO TOMOZAWA3, HARUMI TORII4,
RIKYU MATSUKI5, FUMIO YAMADA6, YOICHI MATSUDA1and HITOSHI SUZUKI2
1Laboratory of Animal Genetics, Department of Applied Molecular Biosciences, Graduate School of
Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan
2Laboratory of Ecology and Genetics, Faculty of Environmental Earth Science, Hokkaido University,
Kita-ku, Sapporo 060-0810, Japan
3Department of Biology, Keio University, Yokohama 223-8521, Japan
4Center for Natural Environment Education, Nara University of Education, Takabatake-cho, Nara
630-8528, Japan
5Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry,
1646 Abiko, Chiba 270-1194, Japan
6Forestry and Forest Products Research Institute, PO Box 16, Tsukuba Norin, Ibaraki 305-8687,
Japan
Received 3 October 2013; revised 11 December 2013; accepted for publication 11 December 2013
Seasonal changes in fur colour in some mammalian species have long attracted the attention of biologists,
especially in species showing population variation in these seasonal changes. Genetic differences among popula-
tions that show differences in seasonal changes in coat colour have been poorly studied. Because the Japanese hare
(Lepus brachyurus) has two allopatric morphotypes that show remarkably different coat colours in winter, we
examined the population genetic structure of the species using partial sequences of the SRY gene and six autosomal
genes: three coat colour-related genes (ASIP,TYR, and MC1R) and three putatively neutral genes (TSHB,APOB,
and SPTBN1). The phylogenetic tree of SRY sequences exhibited two distinct lineages that diverged approsimately
1 Mya. Although the two lineages exhibited a clear allopatric distribution, it was not consistent with the
distribution of morphotypes. In addition, six nuclear gene sequences failed to reveal genetic differences between
morphotypes. Population network trees for 11 expedient populations divided the populations into four groups.
Genetic structure analysis revealed an admixture of four genetic clusters in L. brachyurus, two of which showed
large genetic differences. Our results suggest ancient vicariance in L. brachyurus, and we detected no genetic
differences between the two morphotypes. © 2014 The Linnean Society of London, Biological Journal of the
Linnean Society, 2014, 111, 761–776.
ADDITIONAL KEYWORDS: adaptation – natural selection – phylogeography – seasonal change.
INTRODUCTION
The coat colours of some mammalian and avian
species that live in middle to high latitudinal areas,
such as grouses, foxes, martens, weasels, hares, and
hamsters, change seasonally, from dark colours in
summer to light colours in winter. Such seasonal
changes in coat colour have attracted the interest of
numerous researchers for many years (Grange, 1932;
Hewson, 1958; Rust, 1965; Flux, 1970; Watson, 1973;
Walsberg, 1991; Russell & Tumlison, 1996; Stoner,
Bininda-Emonds & Caro, 2003; Scherbarth &
Steinlechner, 2010). Morphological studies have been
*Corresponding author.
E-mail: mtnunome@agr.nagoya-u.ac.jp
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Biological Journal of the Linnean Society, 2014, 111, 761–776. With 4 figures
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776 761
performed in hares aiming to understand seasonal
variation in fur colour and to identify environmental
cues that induce the change (Hewson, 1958; Otsu,
1967; Flux, 1970; Kuderling et al., 1984). These
studies have indicated that day length is a definite
signal for changes in coat colour, and that tempera-
ture is another important cue for the timing of these
changes (Mills et al., 2013). Hare species also change
reproductive activities in response to day length. In
addition, some hare species show intraspecific varia-
tion in the seasonality of coat colour. In such species,
animals in northern areas show seasonal coat colour
changes, whereas those in southern areas retain dark
pelages year-round.
Intraspecific variation in winter coat colour is con-
sidered to originate from genetic differences among
populations. This hypothesis is supported by various
observations as described below. However, the genes
that regulate seasonal changes in coat colour have
not yet been identified in hares or other animals.
Although variation in the melanocortin 1 receptor
(MC1R) gene is known to be associated with variation
in winter coat colour in the Arctic fox (Alopex lagopus)
(Vage et al., 2005), the gene is not involved in the
regulation of seasonal changes in coat colour in the
Japanese marten (Martes melampus) (Hosoda et al.,
2005) or the willow grouse (Skoglund & Hoglund,
2010). Moreover, few studies have examined genetic
differences between populations that show differences
in seasonal moult (Meinke, Kapel & Arctander, 2001;
Sato, Yasuda & Hosoda, 2009). In these studies, no
remarkable genetic differences were found between
the two morphotypes. In Lepus species, which are
well known to show seasonal moult, the genetic
basis of morphotypic differences has not been well
studied, although numerous morphological, physi-
ological, and phylogeographical studies have been
conducted (Grange, 1932; Hewson, 1958; Watson,
1963; Flux, 1970; Kuderling et al., 1984; Iason &
Ebling, 1989; Koutsogiannouli et al., 2012). Thus,
uncovering the genetic basis of the two morphotypes
in hare species is crucial not only for identifying the
gene(s) involved in seasonal moult, but also for under-
standing how differences in winter coat colour are
related to population genetic structure.
The Japanese hare Lepus brachyurus Temminck,
1845 is an appropriate model in which to examine the
genetic basis of winter colour morphotypes because of
its restricted geographical distribution and genetic
status. Lepus brachyurus is endemic to the Japanese
archipelago and is distributed throughout three of
the main islands (Honshu, Shikoku, and Kyushu),
as well as in peripheral islands, including Sado
Island and the Oki Islands (Fig. 1). The species has a
much smaller range than other Lepus species that are
found on the continent. In addition, although several
hare species are known to have experienced genetic
introgression from other species (Alves et al., 2008;
Liu et al., 2011; Kinoshita et al., 2012), mitochondrial
phylogenetic studies have confirmed the genetic
purity of L. brachyurus (Yamada, Takaki & Suzuki,
2002; Wu et al., 2005; Nunome et al., 2010). Thus,
compared to other hare species on the continent,
the examination of genetic population structure
is relatively simple in almost all populations of
L. brachyurus.
Lepus brachyurus is divided principally into north-
ern and southern groups based on winter coat colour
(Fig. 1). The coat colours of hares in northern areas
change from brown in summer to white in winter,
whereas hares in southern areas have brown pelages
year-round (Imaizumi, 1960; Hirata, 1999). This
intraspecific difference in winter pelage has led to the
consideration of the northern and southern groups as
subspecies; white winter pelage animals are desig-
nated Lepus brachyurus angustidens Hollister, 1912,
and pigmented winter pelage animals are classified
as Lepus brachyurus brachyurus Temminck, 1845,
excluding two subspecies on Sado Island and the Oki
Islands. Hereafter, for descriptive purposes, hares
with white and pigmented winter coats on the main
islands are referred to as ‘Lba’ and ‘Lbb’, respectively.
When Lba is bred in areas where Lbb is dominant,
Lba changes its coat colour from brown in summer to
white in winter (Hirata, 1999), suggesting that the
seasonal change in coat colour of Lba is not triggered
by environmental cues but, instead, is determined by
genetic factor(s). The distribution ranges of Lba and
Lbb do not display simple north–south parapatry but
are strongly related to annual snowfall in the archi-
pelago. On Honshu Island, the amount of annual
snowfall differs distinctly between the heavy-snow
region on the Japan Sea side and the low-snow region
on the Pacific side as a result of the presence of high
mountain chains that run north–south through the
middle of the island. Winter coat colour may provide
cryptic coloration in snowy environments. That is,
clear geographical differences in annual snowfall
within the archipelago strongly affect the ranges of
the two morphotypes, resulting into genetic diver-
gence between them.
A previous phylogeographical study of mitochondrial
DNA variation in L. brachyurus found two distinct
lineages. However, the geographical distributions of
the lineages were not consistent with the distributions
of the morphotypes, and genetic differences between
the morphotypes remain to be examined (Fig. 2)
(Nunome et al., 2010). In the present study, we exam-
ined genetic variation in L. brachyurus using multiple
nuclear DNA sequences to clarify genetic differences
between the two morphotypes. First, a phylogene-
tic tree of L. brachyurus was constructed using the
762 M. NUNOME ET AL.
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
Y-linked, sex-determining gene SRY to confirm the two
distinct lineages of the species that were exhibited in
cytochrome b gene (CYT B) sequences in a previous
study (Nunome et al., 2010). Second, to determine
whether any of the three coat colour genes is the basis
of the two morphotypes of L. brachyurus, we assessed
genetic variation in six nuclear DNA loci among
11 expedient populations. Three of the six markers
were thyrotropin beta subunit (TSHB), beta spectrin
(SPTBN1), and apolipoprotein B 100 (APOB), which
have been used widely as neutral markers in
phylogenetic analyses of mammals, including Lepus
species (TSHB and SPTBN1: Matthee et al., 2004;
Hoofer et al., 2008; APOB: Amrine-Madsen et al.,
2003). The other three markers were agouti signalling
protein (ASIP), Tyrosinase (TYR) and MC1R, which
are known to be responsible for light and dark coat-
colour variations in mammalian species, including
lagomorphs (Chen, Duhl & Barsh, 1996; Aigner et al.,
2000; Miltenberger et al., 2002; Nachman, Hoekstra &
D’Agostino, 2003; Kambe et al., 2011). Third, we con-
ducted population genetic structure analyses with
the six autosomal loci to evaluate genetic differences
between the two morphotypes.
MATERIAL AND METHODS
SAMPLING AND DNA EXTRACTION
Total genomic DNA was extracted from skin, liver
(sampled from road-killed or hunted animals) and
faeces using a traditional phenol/chloroform protocol
(Sambrook & Russell, 2001). Tissue samples of
L. brachyurus were obtained from 50 localities
across the distribution area (Fig. 1, Table 1). Partial
sequences of genes were amplified for one Y-linked
gene (SRY) and six autosomal genes (ASIP,MC1R,
TYR,APOB,SPTBN1, and TSHB) using the polymer-
ase chain reaction (PCR) method. Amplifications
were performed in a total volume of 20 μL containing
approximately 10 ng of genomic DNA, 10 pmol of each
primer and 10 μL of AmpliTaq Gold®360 Master Mix
(Life Technologies). Cycling conditions for PCR were:
initial denaturation at 95 °C for 10 min, followed by
35 cycles at 95 °C for 30 s, 52 °C–62 °C for 30 s, and
70 °C for 30 s. The primers and exact annealing tem-
perature for each locus are shown in the Supporting
information (Table S1). Double-stranded PCR prod-
ucts were purified using the 20% polyethylene glycol/
2.5 M NaCl precipitation method. The PCR products
10°N
20°
30°
40°
50°
90° 100° 110° 120° 130°80°E 140°
17
18 16
14
13
12
25
24
22
28
29
31
32
33
35
38
36 37
41
43
45 48
46
39
40
10
4
67
9
8
20
21
23
19
15
11
26
27
30
34
42
44
49
50
1
5
23
47
Honshu
Tohoku
Kanto
Chubu
Kinki
Shikoku
Kyushu
Chugoku
Sado isl.
Oki isls.
pop1
pop4
pop9
pop8
pop10
pop7
pop2
pop6 pop5
pop3
pop11
Figure 1. Map of sampling locations. The darkly shaded area indicates the distribution area of animals that have white
pelages in winter. Samples were divided into 11 populations according to their geographical locations and phylogenetic
trees of CYT B and SRY.
POPULATION GENETIC STRUCTURE IN JAPANESE HARE 763
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
were sequenced from both directions with a BigDye
Terminator cycle sequencing kit, version 3.1 (Life
Technologies) and analyzed using an ABI 3100
automated sequencer (Applied Biosystems). DNA
sequences were aligned visually using PROSEQ,
version 2.9.1 (Filatov, 2001).
PHYLOGENETIC ANALYSIS AND DIVERGENCE TIME
ESTIMATION FOR SRY
A Neighbour-joining (NJ) tree (Saitou & Nei, 1987) was
constructed using PAUP 4.0b10 (Swofford, 2002). As a
distance model for the NJ tree, the Hasegawa–
Kishino–Yano (HKY) distance model was chosen based
on a hierarchical likelihood ratio test implemented
with MODELTEST, version 3.7 (Posada & Crandall,
1998). Published SRY sequences (DDBJ/EMBL/
GenBank) for the European hare (L. europaeus;
EF437189, EF437190) were used as an outgroup.
One thousand bootstrap replicates were performed
to assess the robustness of each node. A maximum-
likelihood tree was reconstructed using PHYML,
version 3.0 (Guindon & Gascuel, 2003; Guindon et al.,
2005). Node robustness in the tree was evaluated using
100 bootstrap replicates. Divergence times between
Japanese hare lineages were inferred using BEAST,
version 1.4.8 (Drummond et al., 2005). SRY sequences
for rabbit (Oryctolagus cuniculus; AY785433) were
included in the dataset to set a calibration point
for estimating divergence times. The divergences
between O. cuniculus and the Lepus group, and
between L. europaeus and L. brachyurus, were set
at 11 Mya and 3.5 Mya, respectively, based on esti-
mates from previous molecular phylogenetic studies
(Matthee et al., 2004; Wu et al., 2005). The HKY with
the SRD06 model was used as a substitution model.
Analyses were run for 10 million generations, with
sampling conducted every 1000 generations following
one million burn-in generations. Convergence was
assessed using TRACER, version 1.5 (Rambaut &
Drummond, 2007).
SEQUENCE ANALYSIS FOR SIX AUTOSOMAL LOCI
The minimum numbers of recombinations (Rms;
Hudson & Kaplan, 1985) in the sequences of six
autosomal genes were examined using DNASP,
version 5.0.0 (Librado & Rozas, 2009), and the longest
18
24
32
33
38
36 37
41
39
67
8
15
30
46
47
35
17
16
12
22
23
1
3
0.001
8_NIG218
47_OHIT88
46_FKOK85
23_TYM129
EF437189LU
6_GNM225
17_IBRK82
41_KCH136
38_SHMN36
3_AKT238
18_TCG101
18_TCG102
32_NARA57
22_TYM128
36_HRSM25
36_HRSM27
7_GNM216
3_AKT242
37_HRSM32
24_SZOK04
12_IBRK71
15_IBRK83
16_IBRK81
35_AWJ_18
30_MIE_70
1_AKT251
EF437190LU
38_SHMN39
6_GNM214
39_OKNS43
33_NARA84
33_NARA59
95/95
63/62
95/97
62/64
lineage N
lineage S
outgroup
Figure 2. Phylogenetic tree of partial DNA sequences of SRY. Codes at the tips of the tree represent the numbers of
sampling locations, followed by the sample codes. Values on branches indicate bootstrap values for the Neighbour-joining
(left) and maximum-likelihood (right) methods. The geographical border between the two lineages in the tree is indicated
by a dotted line on the map of sampling localities. The grey dotted line on the map indicates the geographical border
between two clades of the mitochondrial CYT B gene (Nunome et al., 2010).
764 M. NUNOME ET AL.
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
Table 1. Details of samples used in the present study
Population
number
Sample
name
Locality
number District Prefecture City (Gun) Latitude Longitude
1 LbAKT251 1 Tohoku Akita Kitaakita 140.37 40.23
LbAKT235 2 Tohoku Akita Nikaho 139.91 39.20
LbAKT236 2 Tohoku Akita Nikaho 139.91 39.20
LbAKT237 3 Tohoku Akita Yuzawa 140.49 39.16
LbAKT238 3 Tohoku Akita Yuzawa 140.49 39.16
LbAKT239 3 Tohoku Akita Yuzawa 140.49 39.16
LbAKT240 3 Tohoku Akita Yuzawa 140.49 39.16
LbAKT241 3 Tohoku Akita Yuzawa 140.49 39.16
LbAKT242 3 Tohoku Akita Yuzawa 140.49 39.16
LbAKT243 3 Tohoku Akita Yuzawa 140.49 39.16
LbIWT205 4 Tohoku Iwate Shimohei 141.87 39.69
LbIWT206 5 Tohoku Iwate Morioka 141.19 39.67
2 LbGNM210 6 Kanto Gunma Azuma 138.50 36.50
LbGNM211 6 Kanto Gunma Azuma 138.50 36.50
LbGNM212 6 Kanto Gunma Azuma 138.50 36.50
LbGNM214 6 Kanto Gunma Azuma 138.50 36.50
LbGNM225 6 Kanto Gunma Azuma 138.50 36.50
LbGNM215 7 Kanto Gunma Tone 139.05 36.73
LbGNM216 7 Kanto Gunma Tone 139.05 36.73
LbGNM217 7 Kanto Gunma Tone 139.05 36.73
LbNIG218 8 Chubu Niigata Tokamachi 138.76 37.13
LbNIG219 8 Chubu Niigata MinamiUonuma 138.82 36.95
LbNIG220 9 Chubu Niigata MinamiUonuma 138.82 36.95
LbSAD189 10 Sado isl. Niigata Sado 138.37 38.02
LbSAD190 10 Sado isl. Niigata Sado 138.37 38.02
LbSAD191 10 Sado isl. Niigata Sado 138.37 38.02
3 LbIBRK55 20 Chubu Nagano KitaSaku 138.55 36.33
LbIBRK77 20 Chubu Nagano KitaSaku 138.55 36.33
LbIBRK71 20 Chubu Nagano KitaSaku 138.55 36.33
LbIBRK73 20 Chubu Nagano KitaSaku 138.55 36.33
LbIBRK75 21 Chubu Nagano Shimotakai 138.43 36.81
LbIBRK76 21 Chubu Nagano Shimotakai 138.43 36.81
LbIBRK78 22 Chubu Toyama Toyama 137.21 36.70
LbIBRK83 23 Chubu Toyama Oyabe 137.00 36.68
4 LbIBRK81 11 Kanto Ibaraki Tsukuba 140.07 36.04
LbIBRK82 11 Kanto Ibaraki Tsukuba 140.07 36.04
LbTCG100 12 Kanto Ibaraki Bando 139.89 36.04
LbTCG101 13 Kanto Ibaraki – 140.28 36.25
LbTCG102 14 Kanto Ibaraki Kasama 140.24 36.38
LbTCG103 14 Kanto Ibaraki Kasama 140.24 36.38
LbTCG104 15 Kanto Ibaraki Kasumigaura 140.32 36.08
LbTCG106 15 Kanto Ibaraki Kasumigaura 140.32 36.08
LbTCG107 16 Kanto Ibaraki Mito 140.45 36.37
LbTCG209 17 Kanto Ibaraki Takahagi 140.70 36.72
LbNGN221 18 Kanto Tochigi Nikko 139.60 36.74
LbNGN222 18 Kanto Tochigi Nikko 139.60 36.74
LbNGN223 18 Kanto Tochigi Nikko 139.60 36.74
LbNGN224 18 Kanto Tochigi Nikko 139.60 36.74
LbNGN226 18 Kanto Tochigi Nikko 139.60 36.74
LbNGN227 18 Kanto Tochigi Nikko 139.60 36.74
LbTYM128 18 Kanto Tochigi Nikko 139.60 36.74
LbTYM129 19 Kanto Tochigi Nasushiobara 140.05 36.96
POPULATION GENETIC STRUCTURE IN JAPANESE HARE 765
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
Table 1. Continued
Population
number
Sample
name
Locality
number District Prefecture City (Gun) Latitude Longitude
5 LbSZOK02 24 Chubu Shizuoka Fujinomiya 138.62 35.22
LbSZOK04 24 Chubu Shizuoka Fujinomiya 138.62 35.22
LbSZOK07 25 Chubu Shizuoka Susono 138.91 35.17
LbSZOK09 25 Chubu Shizuoka Susono 138.91 35.17
LbYMN130 26 Chubu Yamanashi Fujiyoshida 138.81 35.49
LbYMN131 27 Chubu Yamanashi Minamitsuru 138.80 35.48
LbYMN134 27 Chubu Yamanashi Minamitsuru 138.80 35.48
6 LbMIE_68 28 Kinki Mie Inabe 136.56 35.12
LbMIE_69 29 Kinki Mie Tsu 136.51 34.72
LbMIE_70 30 Kinki Mie – 136.51 34.73
LbNARA12 31 Kinki Nara Odaigahara 135.88 34.39
LbNARA57 32 Kinki Nara Katsuragi 135.71 34.51
LbNARA59 33 Kinki Nara Nara 135.81 34.69
LbNARA84 33 Kinki Nara Nara 135.81 34.69
LbSHIG97 34 Kinki Shiga Otsu 135.85 35.02
7 LbAWJ_17 35 Chugoku Hyogo Awaji 134.92 34.44
LbAWJ_18 35 Chugoku Hyogo Awaji 134.92 34.44
LbAWJ_19 35 Chugoku Hyogo Awaji 134.92 34.44
LbAWJ_20 35 Chugoku Hyogo Awaji 134.92 34.44
LbAWJ_21 35 Chugoku Hyogo Awaji 134.92 34.44
8 LbHRSM25 36 Chugoku Hiroshima Mihara 133.08 34.40
LbHRSM26 36 Chugoku Hiroshima Mihara 133.08 34.40
LbHRSM27 36 Chugoku Hiroshima Mihara 133.08 34.40
LbHRSM28 36 Chugoku Hiroshima Mihara 133.08 34.40
LbHRSM32 37 Chugoku Hiroshima Onomichi 133.20 34.41
LbHRSM34 37 Chugoku Hiroshima Onomichi 133.20 34.41
LbSHMN36 38 Chugoku Shimane Nita 133.05 35.18
LbSHMN37 38 Chugoku Shimane Nita 133.05 35.18
LbSHMN39 38 Chugoku Shimane Nita 133.05 35.18
9 LbOKI_42 39 Oki isl. Shimane Nishinoshima 132.98 36.10
LbOKI_43 39 Oki isl. Shimane Nishinoshima 132.98 36.10
LbOKI_44 39 Oki isl. Shimane Nishinoshima 132.98 36.10
LbOKI_46 40 Oki isl. Shimane Dogo 133.28 36.25
LbOKI_47 40 Oki isl. Shimane Dogo 133.28 36.25
LbOKI_49 40 Oki isl. Shimane Dogo 133.28 36.25
LbOKI_53 40 Oki isl. Shimane Dogo 133.28 36.25
LbOKI_54 40 Oki isl. Shimane Dogo 133.28 36.25
10 LbKCH136 41 Shikoku Kochi Nagaoka 133.65 33.77
LbKCH138 42 Shikoku Kochi Tosa (gun) 133.53 33.74
LbKCH140 42 Shikoku Kochi Tosa (gun) 133.53 33.74
LbKCH229 43 Shikoku Kochi Kami 133.69 33.60
LbKCH230 44 Shikoku Kochi Tosa (city) 133.43 33.50
11 LbFKO163 45 Kyushu Fukuoka Kama 130.77 33.56
LbFKOK85 46 Kyushu Fukuoka KitaKyushu 130.88 33.88
LbOITA86 47 Kyushu Oita Beppu 131.49 33.28
LbOITA88 47 Kyushu Oita Beppu 131.49 33.28
LbOITA92 48 Kyushu Oita Usa 131.33 33.53
LbOITA87 49 Kyushu Oita Yufu 131.43 33.18
LbOITA91 49 Kyushu Oita Yufu 131.43 33.18
LbOITA93 49 Kyushu Oita Yufu 131.43 33.18
LbKGS233 50 Kyushu Kagoshima Satsumasendai 130.30 31.81
LbKGS234 50 Kyushu Kagoshima Satsumasendai 130.30 31.81
Sampling locations are represented by the city or area where the samples were collected. The longitude and latitude of
each sampling location were determined using Google Earth 6.02; (Google, Inc.).
766 M. NUNOME ET AL.
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
portions without recombination signals were used in
the present study. We subdivided the MC1R sequence
into two parts (MC1R-a and MC1R-b) based on the
results of the recombination test. Tajima’s neutrality
tests (Tajima’s D; Tajima, 1989) and linkage disequi-
librium tests were performed with 10 000 permuta-
tions using ARLEQUIN, version 3.5 (Excoffier &
Lischer, 2010). We subdivided the samples into 11
populations according to their geographical locations
and phylogenetic data of previous CYT B sequences
and the SRY sequences from this study (populations
1–11; Fig. 1). First, samples were partitioned accord-
ing to the three main islands of the Japanese archi-
pelago (Honshu, Shikoku, and Kyushu). Samples from
the Oki Islands were treated as one population. Then,
samples from Honshu were further subdivided based
on the borders of the two mitochondrial lineages
(population 8 and the others), the two SRY lineages
(such as populations 2 and 3), the two morphotypes
(such as populations 3 and 5) and geographical dis-
tances (such as populations 1 and 2). Geographical
variations in the six genes were surveyed by examin-
ing haplotype frequencies in 11 populations. Isolation-
by-distance (IBD) was evaluated for each gene dataset
using a Mantel test with 1000 replicates using
ALLELE IN SPACE (Miller, 2005). Genetic diversity
[expected heterozygosity (HE) and pairwise nucleotide
differences (pi)] within populations for each locus were
examined using ARLEQUIN, verison 3.5.
POPULATION NETWORK CONSTRUCTION AND
POPULATION GENETIC STRUCTURE ANALYSIS
To infer genetic differences between the two morpho-
types, exact tests (Raymond & Rousset, 1995) were
performed using ARLEQUIN, version 3.5, for two
representative groups of populations (populations 1–3
and 4–11), based on the distributions of Lba and Lbb.
In addition, according to two CYT B lineages, an
exact test was performed for two other population
groupings (populations 1–6 and 7–11).
Genetic differences among populations were also
examined through two independent analyses. First,
we constructed population network trees to determine
the genetic relationships among the 11 populations,
with a special focus on significant differences in
the pairwise fixation index (FST) among populations.
Second, population genetic structure was inferred
using STRUCTURE, version 2.3 (Pritchard, Stephens
& Donnelly, 2000) to determine the genetic back-
grounds of the 11 populations. Genetic relationships
among populations have commonly been constructed
as unrooted trees based on pairwise FST (Wright,
1951) or Nei’s genetic distance (Nei’s DA; Nei & Li,
1979). However, these trees are rectilinear and cannot
present significant genetic differences among popula-
tions. Thus, to survey population genetic relation-
ships and identify significant genetic differences, we
used significant FST distances in network reconstruc-
tion in addition to performing conventional network
reconstruction using pairwise FST distances. First,
pairwise FST differences between populations and
their corresponding Pvalues were calculated for the
six nuclear genes using ARLEQUIN, version 3.5, with
1000 permutation replicates. Then, a conventional
FST network based on the NJ method was recon-
structed using TREEFIT (Kalinowski, 2009). Second,
we assigned values of ‘1’ or ‘0’ to Pvalues in the
resulting data matrix according to their significance
(P<0.05) or nonsignificance (P≥0.05), respectively.
We used ‘0’ (meaning nonsignificant difference) for
within-population values, which were diagonal blank
elements in the Pvalue matrix. Finally, a binary
alignment of 0 and 1 for each population was gener-
ated. Then, for the binary data, reduced median net-
works were constructed using NETWORK, version
4.6.1.0 (http://www.fluxus-engineering.com; Bandelt,
Forster & Rohl, 1999). The network analyses and
subsequent Bayesian clustering analysis were per-
formed for each locus and for the combined dataset
that included all six loci. MC1R-a and -b were
included in combined data A and combined data B,
respectively.
Population genetic structure was inferred by Bayes-
ian clustering analysis using STRUCTURE, version
2.3. This analysis estimates the number of genetic
clusters (K) based on allelic frequencies of loci in the
dataset and survey proportions of genetic clusters
in the populations. Kwas estimated from 5 000 000
Markov chain Monte Carlo (MCMC) generations,
with data sampled every 10 000 generations after a
burn-in period of 2 000 000 generations. Convergence
of MCMC chains was checked based on the similarity
of estimated log probability values for data [lnP(D)]
and the variance of log likelihood {Var [lnP(D)]}
in an independent analysis. Admixture and allele
frequency-correlated models were assumed in the
analyses. To determine an appropriate K, we used
Evanno’s method in STRUCTURE HARVESTER
(Earl & vonHoldt, 2012).
RESULTS
PHYLOGENETIC ANALYSIS OF SRY SEQUENCES
In total, 1002 bp from the SRY region were obtained
from 30 samples (see Supporting information,
Table S2), except for a simple tandem repeat of (GT)n
that was approximately 36 bp in length. The dataset
comprised four haplotypes with six variable sites,
including one base indel. The four haplotypes were
divided into two major lineages (N and S) by five of
POPULATION GENETIC STRUCTURE IN JAPANESE HARE 767
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
the six variable sites. The two lineages showed a
clear allopatric distribution with the border located
approximately halfway between Kanto and Chubu
districts (Fig. 2). The bootstrap value of lineage S
(95%) was substantially high, although the value for
lineage N (62%) was not. Lineage N was composed
of two haplotypes (Haps N1 and N2) from 13 samples
from populations 1, 2, and 4. For lineage S, two
haplotypes (Haps S1 and S2) were found from 17
samples from populations 3 and 5–11. The divergence
time between the two lineages was estimated to
be 1.07 Mya, with 95% highest-probability density
ranging from 0.95 to 2.99 Mya.
GENETIC VARIATIONS IN SIX NUCLEAR
GENE SEQUENCES
For six nuclear loci, 104 samples were used in the
subsequent analyses, including missing loci for which
amplification failed. The sequence lengths for the
six nuclear genes ranged from 316 bp for SPTBN1
to 668 bp for TSHB (see Supporting information,
Table S3; accession number in Table S2). Because the
MC1R gene was estimated to have a recombination
point halfway along the fragment, we partitioned
the sequences into the first 456 bp (MC1R-a) and the
last 375 bp (MC1R-b) and used them separately in
the analyses. The number of polymorphic sites ranged
from two (TYR) to nine (ASIP). The number of alleles
ranged from four (TYR)to12(ASIP). Although MC1R
had five nonsynonymous substitutions at V95I,
A101V, V154M, A179T, and V199I (site numbers
for substitutions refer to the MC1R sequence for
O. cuniculus), in 11 substitutions within sequences
that totalled 831 bp, the geographical distributions
of the variations were restricted to a few populations
and did not appear to match the distributions of
the two morphotypes (see Supporting information,
Table S4). The significance of IBD varied among
genes, and the r-values of the Mantel tests were
generally very small (see Supporting information,
Table S3). SPTBN1 and TSHB exhibited lower
genetic diversity than the other genes, especially in
northern populations. In addition, TSHB had a sig-
nificantly negative Tajima’s D.
GENETIC DIFFERENCES AMONG POPULATIONS BASED
ON SIX NUCLEAR GENES
For the exact test, we also examined allelic differ-
ences between groups that represented the two SRY
lineages discovered in the present study (Table 2).
Almost all genes exhibited significant differences
between the two winter coat groups, between the two
CYT B lineage groups, and between the two SRY
lineage groups (P<0.05). TYR and MC1R did not
differ significantly between Lba and Lbb.
Population networks were constructed using the NJ
method (Saitou & Nei, 1987), pairwise FST distances,
and the significance levels of FST values for the six
autosomal genes (Fig. 3). Here, we describe networks
based on pairwise FST distances (Fig. 3A) and the
significance of FST (Fig. 3B) as ‘distance-based’ and
‘significance-based’ networks, respectively. The rela-
tionships among populations estimated by the two
types of network were generally similar. For example,
population 5 was placed at one end of both TYR
networks. Populations 4, 7, 2, 6, 8, 10, and 11 pro-
ceeded in sequence from the other end of the distance-
based network for TYR (Fig. 3A) and were clu-
stered together in one node in the significance-based
network (Fig. 3B). However, some points differed
between the two types of network for TYR. Popu-
lation 9 was closely related to population 4 in the
Table 2. Summary of nondifferentiation exact Pvalues between two putative groups based on winter coat colour: CYT
B(previous study) and the results for SRY
Gene fragment
Exact Pvalue
Colour (Lba
versus Lbb)
North versus
South of CYT B
North versus
South of SRY
ASIP <0.01 0.01 0.01
TYR 0.13 0.06 0.43
MC1R-a 0.08 0.06 0.01
MC1R-b 0.23 <0.01 <0.01
MC1R (full length) 0.11 <0.01 <0.01
APOB <0.01 <0.01 <0.01
SPTBN1 <0.01 <0.01 <0.01
TSHB <0.01 <0.01 0.03
Significant Pvalues are shown in bold.
768 M. NUNOME ET AL.
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
distance-based network, whereas it was assigned to
the node of populations 1 and 3 and was separated
from population 4 in the significance-based network.
In the networks for ASIP, population 3 was located
near population 11 in the distance-based network,
whereas the significance-based network placed popu-
lation 3 at the same node as population 9, which was
very far from population 11. Similar partial discrep-
ancies were observed between networks for APOB,
in which the relationship between populations 2 and
10 differed. Remarkable differences were found
between networks for combined data B, which con-
sisted of MC1R-b and the other five genes (without
MC1R-a). The significance-based network showed
0.1
pop8
pop7
pop10
pop9
pop11
pop6
pop4
pop3
pop1
pop2
pop5
0.1
pop4
pop1
pop2
pop3
pop5
pop6
pop8
pop7
pop10
pop9
pop11
0.1
pop6
pop9
pop4
pop1
pop2
pop8
pop3
pop11
pop7
pop5
pop10
0.1
pop4
pop9
pop1
pop3
pop5
pop7
pop2
pop6
pop8
pop10, 11
0.1
pop2
pop4
pop5
pop1
pop8
pop11
pop9
pop6
pop3, 7, 10
0.1
pop3
pop10
pop2
pop9
pop11
pop8
pop7
pop5
pop1
pop4
pop6
0.1
pop6
pop8
pop11
pop7, 9
pop10
pop5
pop2, 3, 4 pop1
0.1
pop7
pop2
pop5
pop1
pop6
pop11
pop10
pop3
pop4
pop8
pop9
0.1
pop7
pop11
pop2
p
op1, 4
pop8
pop10
pop6
pop9
pop3
pop5
ASIP TYR MC1R-a
MC1R-b APOB SPTBN1
TSHB Combined (MC1R-a) Combined (MC1R-b)
A
Figure 3. Population networks for six nuclear genes and combined data for all loci. A, networks calculated based on
pairwise FST distance. B, networks constructed based on significance of FST. Numbers on branches of networks in (B) are
population numbers and indicate the cut-off point for significant differences for a certain population. Combined data A
includes all sequences except MC1R-b (the latter half of MC1R) and combined data B includes all sequences except
MC1R-a (the first half of MC1R).
POPULATION GENETIC STRUCTURE IN JAPANESE HARE 769
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
close connections among populations 1, 2, 9, and 11,
despite large genetic and geographical distances
among these populations in the distance-based
network. Although several differences were observed
between the two types of population network, popu-
lations 1, 2, 9, and 11 tended to be located at external
nodes of the networks for all six genes. Combined
data A and B subdivided the other populations (popu-
lations 3–8 and 10) into two similar groups: popula-
tions 3–6 and populations 7, 8, and 10.
Bayesian clustering analysis indicated that the
Japanese hare population is composed of four genetic
clusters (N1 and S1–S3), the geographical distri-
butions of which show a north–south cline (Fig. 4).
STRUCTURE HARVESTER indicated that K= 4 was
the most appropriate parameter for combined data A
and B. Because these datasets produced very similar
results, we used only the results from combined data A.
FST genetic distances among the four clusters indicated
that cluster N was very distant from the other three.
B
pop6
pop4
pop1
pop2
pop8
p
op3, 9
pop11
pop7
pop5
pop10
9
3
41
2
1
2
7
11
4
4
8
8
8
8
10
10
2
211
11
7
ASIP
pop1, 3, 9
pop5
pop2, 4, 6, 7, 8, 10, 11
5
11
10
8
7
6
4
2
pop1
11
pop2
pop8
pop4, 5, 9
pop6, 11
pop7, 10
6
10
7
3
1
2
8
pop3
pop9
7
pop6
pop2, 3, 7, 8, 10
pop11
8
10
11
3
1
2
8
pop1, 4
2
3
pop5
pop9
8
pop2
11 pop11
pop10
pop4, 6
pop3, 7, 8
pop5
pop1
3
4
7
9
5
11
1
10
3
7
8
2
2
1
11
4
6
6
pop1, 2, 3, 4
6
pop6, 7, 9, 11
pop5, 10
pop8
7
9
11 4
2
3
1
4
2
3
16
7
9
11
5
8
10
pop9
6
pop8
pop3,5,6,7,10
pop4
7
10
4
1
9
11
2
pop1, 11
3
5
pop2
8
4
pop2
pop1
pop8
pop7, 10
pop9, 11
pop6
pop3
pop4, 5
1
6
10
7
9
11
9
11
10
7
2
6
6
6
4
5
4
5
10
7
2
8
6
6
8
8
pop4, 5
pop3 pop6
pop2
pop11
pop1
pop9
pop7 pop8
pop10
7
10 2
8
4
56
3
7
10
19
8
3
11
2
2
711
TYR MC1R-a
MC1R-b APOB SPTBN1
TSHB Combined (MC1R-a) Combined (MC1R-b)
Figure 3. Continued.
770 M. NUNOME ET AL.
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
Clusters S2 and S3 branched off from cluster S1, with
a relatively shorter FST distance compared to that
observed between S1 and N. Cluster N prevailed in the
northernmost population (population 1). Populations 2
and 4 also had relatively high frequencies for cluster N
relative to the other populations. The S clusters were
broadly observed in populations 2–11. Cluster S1 gen-
erally included individuals from populations 8 and 11
(Fig. 4A), and clusters S2 and S3 were equally distrib-
uted over all populations, except population 1.
DISCUSSION
USEFULNESS OF A POPULATION NETWORK BASED ON
THE SIGNIFICANCE OF FST VALUES FOR DEPICTING
POPULATION GENETIC STRUCTURE
Population networks based on the (non)significance
of pairwise FST distances proved rather effective for
clustering populations compared to conventional net-
works of FST distance. Significance-based networks
had almost the same topologies as conventional net-
works of FST distance for every gene and combined
data A; in combined data B, populations 1, 2, 9, and
11 were placed near one another (Fig. 3B). Although
populations 1 and 2 and populations 9 and 11 showed
substantial genetic differences from one another,
they were similar in that they also had significant
genetic differences from the other populations in com-
bined data B. Although the distance-based network
could recognize the large genetic differences between
populations 1 and 2 and populations 9 and 11, the
significance-based network treated all significant
genetic differences among populations as having
the same value of ‘1’, which did not reflect genetic
distance. For this reason, distance- and significance-
based networks of combined data B produced differ-
ent topologies. Thus, combined data A provided a
more reasonable significance-based network, in which
the four groups of populations could be recognized
more easily than in the conventional FST network: (1)
populations 1 and 2; (2) populations 3–6; (3) popula-
tions 7, 8, and 10; and (4) populations 9 and 11. The
significance-based network with combined data A
appeared to reflect the results of the population clus-
tering analyses (Fig. 4). For example, the primary
genetic component in populations 1 and 2 was cluster
N1, and populations 3–6 contained the four genetic
clusters with similar proportions. Although simula-
tion studies would be needed to evaluate the efficiency
of the significance-based network, this may provide
an easy method for surveying clusters of populations
that showed significant genetic differences.
TWO DIVERGENT GENETIC GROUPS IN
L. BRACHYURUS AS A RESULT OF PAST VICARIANCE
The SRY and nuclear genes showed two genetically
divergent groups in L. brachyurus, as demonstrated
pop. 1 pop. 2 pop. 3 pop. 11pop. 10pop. 9pop. 8pop. 7pop. 6pop. 5pop. 4
N1S1
S2
S3
0.01
Cluster N1
Cluster S1
Cluster S2
Cluster S3
A
B
Figure 4. Results of genetic structuring analyses using STRUCTURE, version 2.3. A, genetic component proportions of
individuals (upper) and populations (lower) are represented by thin horizontal bars composed of four coloured clusters.
The component proportions of a cluster indicate the proportions of assignment of the individual (population) into each of
the four subgroups. B, genetic relationships among clusters are illustrated using networks based on FST genetic distance.
POPULATION GENETIC STRUCTURE IN JAPANESE HARE 771
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
previously using mitochondrial data (Nunome et al.,
2010), even though genetic differences between the
two morphotypes were obscure in our molecular data
(Figs 2, 4). A geographical border between the two
divergent lineages in SRY was clearly located across
the eastern part of Honshu Island, running from
north to south, although the location did not match
the distribution of either morphotype. Interestingly,
the border did not even match the two CYT B lineages
in Chugoku district on the western part of Honshu
Island (Fig. 2). The presence of two lineages within
the species was well supported by nuclear genes, with
two divergent genetic clusters (N and S) alternately
in the northern and southern areas (Fig. 4). When
STRUCTURE analysis was performed on the basis
of the K= 2 model, clusters S1, S2, and S3 were
combined into one cluster ‘S’ and then only two clus-
ters ‘N’ and ‘S’ were exhibited without any changes
in frequency in populations (data not shown). The
existence of two SRY lineages and the presence of
two genetic clusters in the nuclear genes could be
explained by past vicariance in the species, as hypoth-
esized in a previous mitochondrial study (Nunome
et al., 2010). In addition, the timing of the vicariance
in the two SRY lineages was estimated to be approxi-
mately 1 Mya, which is similar to the estimate of
1.2 Mya for the two CYT B lineages, although the
evolutionary rate of the SRY sequences used in the
present study would have been slow, given the small
numbers of substitutions observed in the sequences.
Genetic subdivisions in morphology, karyotype, and
DNA sequences have been found commonly at inter-
or intraspecific levels in various Japanese mammals
(Nagata et al., 1999; Tsuchiya et al., 2000; Iwasa &
Abe, 2006; Kawamoto et al., 2007; Tomozawa &
Suzuki, 2008; Oshida, Masuda & Ikeda, 2009; Yasuda
et al., 2012). One possible explanation for these diver-
gences is repeated habitat fragmentation during
glacial periods in the Late Pleistocene. The four SRY
haplotypes (Fig. 2) and three subclusters of cluster S
(S1–S3; Fig. 4) would also be products of fragmenta-
tion during a more recent period. Although we could
not determine a relationship between past vicariance
and morphological divergence in L. brachyurus,a
vestige of the vicariance would remain in the strong
genetic population structure.
NUCLEAR GENES IMPLY A GENETIC MIXTURE
BETWEEN TWO MORPHOTYPES
The results of the present study suggest that Lba
and Lbb were genetically indistinguishable from each
other, in contrast to our initial expectation that the
two morphotypes with different winter coat colours
would be genetically differentiated as a result of dif-
ferent evolutionary trajectories. The topologies of the
population networks were not consistent among the
six genes. The absence of consistency among the
networks for the six genes implies that the popula-
tions are not genetically structured, as is evident in
the mixing states of the four genetic clusters in the
nuclear genes among the populations. Similar findings
were reported in willow grouse and Arctic fox, which
also showed little genetic divergence between popula-
tions with different winter coat colours (Meinke et al.,
2001; Skoglund & Hoglund, 2010). Genetic variation
at neutral loci that are not correlated with a colour
polymorphism or genes involved in a polymorphism
have been commonly observed in other mammals,
such as the oldfield mouse (Peromyscus polionotus)
(Mullen & Hoekstra, 2008), the rock pocket mouse
(Chaetodipus intermedius) (Hoekstra, Drumm &
Nachman, 2004), and the grey wolf (Canis lupus)
(Anderson et al., 2009). The two morphotypes of
L. brachyurus may be only differentiated at genes
involved in the differences in seasonal changes in
coat colour. Thus, genome-wide surveys using abun-
dant genetic markers, such as microsatellites or
single-nucleotide polymorphism analyses, in individu-
als around the boundary between Lba and Lbb are
required to fully appreciate gene flow between the two
morphotypes and to determine which loci show affini-
ties with the morphotypes.
GENETIC VARIATION OF COAT COLOUR-RELATED
GENES AND NEUTRAL GENES AMONG POPULATIONS
Initially, we expected that genes involved in differ-
ences in winter coat colour would show particular
geographical differences in genetic diversity. None of
the markers, including the three coat colour-related
genes, exhibited genetic differentiation between the
two morphotypes. Tajima’s neutrality tests did not
suggest that natural selection was affecting the genes
(Fig. 3; see also Supporting information, Table S3).
No differences in genetic diversity (HEor pi) among
populations were observed in the three genes. The
results did not suggest that environmental differences
between locations were affecting the genes. We found
five amino acid variants of MC1R (V154M, A101V,
V95I, V199I, and A179T) (see Supporting informa-
tion, Table S4). One of the variants, A101V, is placed
in the region where the jaguar (Panthera onca) has
a 15-bp deletion related to its coat colour variation
(Eizirik et al., 2003). The remaining four amino acid
variants did not correspond to any of the amino acid
changes related to coat colour variations of other
animals (Majerus & Mundy, 2003). However, all five
mutations appeared to be distributed without any
relation to the areas of Lba and Lbb. Similar findings
were reported in the Japanese marten (Hosoda
et al., 2005; Sato et al., 2009) and the willow grouse
772 M. NUNOME ET AL.
© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111, 761–776
(Skoglund & Hoglund, 2010). MC1R and other
neutral markers showed no clear genetic differences
between the two morphotypes in the Japanese
marten. In addition, genetic variation in TYR was not
related to differences in winter colour in the willow
grouse. Although a study of the Arctic fox found a
relationship between substitutions in MC1R and vari-
ation in winter coat colour (Vage et al., 2005), MC1R,
as well as ASIP and TYR, are involved in lifetime
coat-colour variations in other mammals (Klungland
& Vage, 2003; Nachman et al., 2003; Fontanesi et al.,
2006; Kambe et al., 2011). Thus, the seasonal change
in coat colour in L. brachyurus may be controlled by
other regulatory genes and not by melanogenesis-
related genes such as MC1R and ASIP.
The negative value of Tajima’s Dfor TSHB and
its lower genetic variation in northern populations
suggested that the locus is under natural selection.
Although TSHB has been used as a neutral marker
for phylogenetic analyses (Matthee et al., 2004;
Hoofer et al., 2008; Stoffberg et al., 2010), it has
recently been reported to regulate seasonal reproduc-
tion through photoperiodic signalling in birds and
mammals (Nakao et al., 2008; Ono et al., 2008). Wild
stickleback populations showed differences in gene
expression for TSHβ2, a paralogue of TSHB, between
marine and stream ecotypes, especially under short-
photoperiod conditions (Kitano et al., 2010). Genetic
variation in photoperiod-related genes could vary
with latitude, as was shown in European populations
of Drosophila melanogaster (Tauber et al., 2007)
and Alaskan populations of Chinook salmon
(Oncorhynchus tshawytscha) (O’Malley & Banks,
2008). Because L.brachyurus is known to show
seasonal changes in reproductive activity with
photoperiodic signals (Otsu, 1971), TSHB could be
subject to the latitudinal cline in seasonal photo-
period in the Japanese archipelago. To further
examine this issue, studies of the seasonal and geo-
graphical expression patterns of the gene in wild
mammals that show seasonal changes in breeding
activity or coat colour, such as Lepus and Martes
species, are needed.
CONCLUSIONS
The results of the present study suggest that genetic
diversity in the Japanese hare is attributable to
vicariance events, which may have occurred approxi-
mately 1 Mya, rather than to differences in winter
coat colour. Although the two morphotypes of Japa-
nese hare have been considered to be different sub-
species, the difference in winter coat colour did not
appear to restrain gene flow. However, some func-
tional genes related to seasonal changes in coat colour
and reproductive status may vary geographically
according to environmental differences within the
Japanese archipelago. In this case, we can carry out
population genetic surveys of the Japanese hare
across its range because the Japanese hare inhabits a
restricted area: the Japanese archipelago. In addition,
the accumulation of genomic information for rabbit
(O. cuniculus) would facilitate genome-wide research
on the Japanese hare, although these two species are
not closely related. Indeed, several primers used in
the present study were designed based on the pub-
lished genome sequences of the rabbit. Many rabbit
microsatellite markers have been applied for popula-
tion genetic studies of Lepus species (Hamill, Doyle &
Duke, 2006; Thulin, Fang & Averianov, 2006) and
a high karyotype similarity was revealed between
Lepus and Oryctolagus (Robinson, Yang & Harrison,
2002). Thus, to detect a candidate gene for seasonal
changes in coat colour and to survey gene flow
between populations that show differences in winter
coat colour, the Japanese hare represents an appro-
priate model species.
ACKNOWLEDGEMENTS
We thank Kimiyuki Tsuchiya, Shimane Prefecture
Mountainous Region Research Centre and Toyama
Family Park, for providing tissue specimens. We also
express our appreciation to our colleagues for their
valuable advice during the present study. This study
was supported in part by a Grant-in-Aid for Fellows
and for Research Activity Start-Up of the Japan
Society for the Promotion of Science from the Minis-
try of Education, Culture, Sports, Science and Tech-
nology, Japan.
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:
Table S1. Primer information.
Table S2. List of accession numbers of samples. Alleles of heterozygous individuals have two accession
numbers. Samples that could not be amplified are represented by hyphens.
Table S3. Molecular indices for loci.
Table S4. Geographical distribution of nonsynonymous substitutions of MC1R.
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