Study on inter-taxon population structure and diversity variation of hosta inferring from trnG-trnS regional cpDNA

Abstract

Diversity studies are now a key tool in genetic conservation work. The perennial herb genus Hosta showed a complex radiation of numerous species in mountains and riversides around the Shikoku Island, Japan. The purpose of this study was to evaluate trnS-trnG regional genetic structure and the genetic divergence within hosta taxa populations in this area. We sequenced trnS-trnG regional (chloroplast DNA) cpDNA in 81 populations comprising 399 individuals of 11 Hosta taxa collected from Shikoku area. The different numbers of haplotypes were found in different taxon. The divergences of population of Hosta genus and individual taxon were shown in NJ phylogenetic tree. The highest number of haplotypes (14) was found in H. longipes var. gracillima. H. sieboldiana and H. kiyosumiensis populations showed the maximum haplotype diversity (1.0), and H. alismifolia showed maximum nucleotide diversity (π: 0.012). The genetic structures of the H. tardiva with H. kikutii var. caput-avis (FST divergence: 52.7%) and H. sieboldiana with H. tardiva (FST divergence: 52.2%) populations were greatly differentiated from each other (FST value: >0.15 to 0.25). We found maximum evolutionary divergence (0.009) between H. alismifolia and H. kikutii var. polyneuron populations. The significant negative neutrality test values are the evidence of expansion of the total population. H. sieboldiana and H. kiyosumiensis are more widely distributed than other taxa. H. sieboldiana, H. alismifolia, H. longipes var. gracillima and H. kikutii var. polyneuron showed the excessive low frequency variants.

Full text

HOSTED BY
Contents lists available at ScienceDirect
Annals of Agricultural Sciences
journal homepage: www.elsevier.com/locate/aoas
Study on inter-taxon population structure and diversity variation of hosta
inferring from trnG-trnS regional cpDNA
Hasan Mehraj
a,c,⁎
, Subarna Sharma
a,c
, Kouhei Ohnishi
b
, Kazuhiko Shimasaki
c
a
The United Graduate School of Agricultural Sciences, Ehime University, Ehime 790-8556, Japan
b
Research Institute of Molecular Genetics, Kochi University, B200 Monobe, Nankoku, Kochi 783-8502, Japan
c
Laboratory of Vegetable and Floricultural Science, Faculty of Agriculture and Marine Science, Kochi University, Kochi 783-8502, Japan
ARTICLE INFO
Keywords:
Giboshi
Plantain lily
Shikoku Island
Taxa
Haplotype network
Phylogenetic tree
ABSTRACT
Diversity studies are now a key tool in genetic conservation work. The perennial herb genus Hosta showed a
complex radiation of numerous species in mountains and riversides around the Shikoku Island, Japan. The
purpose of this study was to evaluate trnS-trnG regional genetic structure and the genetic divergence within hosta
taxa populations in this area. We sequenced trnS-trnG regional (chloroplast DNA) cpDNA in 81 populations
comprising 399 individuals of 11 Hosta taxa collected from Shikoku area. The different numbers of haplotypes
were found in different taxon. The divergences of population of Hosta genus and individual taxon were shown in
NJ phylogenetic tree. The highest number of haplotypes (14) was found in H. longipes var. gracillima.H. sie-
boldiana and H. kiyosumiensis populations showed the maximum haplotype diversity (1.0), and H. alismifolia
showed maximum nucleotide diversity (π: 0.012). The genetic structures of the H. tardiva with H. kikutii var.
caput-avis (F
ST
divergence: 52.7%) and H. sieboldiana with H. tardiva (F
ST
divergence: 52.2%) populations were
greatly differentiated from each other (F
ST
value: > 0.15 to 0.25). We found maximum evolutionary divergence
(0.009) between H. alismifolia and H. kikutii var. polyneuron populations. The significant negative neutrality test
values are the evidence of expansion of the total population. H. sieboldiana and H. kiyosumiensis are more widely
distributed than other taxa. H. sieboldiana,H. alismifolia,H. longipes var. gracillima and H. kikutii var. polyneuron
showed the excessive low frequency variants.
Introduction
Genus Hosta, a member of the Asparagaceae family, is a shade-tol-
erant perennial garden plant. It is also known as plantain lily (giboshi in
Japan). It is preferred by gardeners for its striking foliage, and creation
of a landscape focal point. Islands are unique but have not been pro-
tected from human activities. Evolutionary processes works differently
in any island thus results faster species variation in an island archipe-
lago than on the larger continuous landmass of a larger continent. Hosta
has approximately 43 species which was originated in Japan, Korea and
China (Schmid, 1991). Fujita (1976) identified 18 species and 7 vari-
eties of the Hosta genus in Japan. The Japanese archipelago has many
islands; Hokkaido, Honshu, Shikoku, and Kyushu are the main four
(Millien-Parra and Jaeger, 1999). Hosta taxa are widely distributed
throughout all of these four islands in Japan. Though Shikoku is the
smallest among these major islands, but it is a major center for the
distribution of genus Hosta. Shikoku is considered as the home of some
taxa, including H. shikokiana and H. kikutii var. polyneuron (Fujita,
1976). H. shikokiana had already been placed on the endangered species
list in this area (Schmid, 1991). Among the habitats around Shikoku,
hosta plants show numerous numbers of taxa with phenotypic varia-
tions which has not been studied yet at genetical level. Hosta plants are
frequently found in this area; but a number of taxa are placed under the
list of extinction. It may be caused by the continuous changes of allelic
frequency through adaptation to locality that resulted from selection
potency, quantity of gene flow, efficient population size (Andre et al.,
2011) and ecological factors as well (Pilot et al., 2006). Neutrality tests
are generally indicated the abuses of mutation equilibrium flow caused
by selection or alter in population size (Tajima, 1989; Fu and Li, 1993)
and Fu’s test is done for the past population expansion (Fu, 1997). F
ST
matrix provides the insights the genetic structure variation (Holsinger
and Weir, 2009) and searches the associations between allele fre-
quencies with particular habitats (Bierne et al., 2011).
Molecular markers have been used as effective and dominant tools
for inference of the current and previous demographic progression of
plant species (Maki et al., 2008). Genetic structure, diversity, and
https://doi.org/10.1016/j.aoas.2017.12.003
Received 26 February 2017; Received in revised form 7 December 2017; Accepted 8 December 2017
Peer review under responsibility of Faculty of Agriculture, Ain-Shams University.
⁎
Corresponding author at: Laboratory of Vegetable and Floricultural Science, Faculty of Agriculture and Marine Science, Kochi University, Kochi 783-8502, Japan.
E-mail addresses: hmehraj02@yahoo.com (H. Mehraj), subarnaplantbreeding@gmail.com (S. Sharma), kouheio@kochi-u.ac.jp (K. Ohnishi), shim@kochi-u.ac.jp (K. Shimasaki).
Annals of Agricultural Sciences 62 (2017) 211–220
Available online 19 December 2017
0570-1783/ 2018Production and hosting by Elsevier B.V. on behalf of Faculty of Agriculture, Ain Shams University. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T

interspecific or intraspecific genetic relationship of plant species can be
determined through study of their cpDNA sequences (Ayele et al., 2009;
Taberlet et al., 1991). The low evolutionary rate of this molecule is a
serious limitation at the intraspecific level. The non-coding regions
display the highest frequency of mutations. Therefore, sequencing of
the non-coding regions, the resolution of cpDNA can be increased both
for evolutionary studies, and for identifying intraspecific genetic mar-
kers. Non-coding regions of chloroplast such as the intergenic spacer
[between the trnL-trnF or, rpl20-rps12 gene] can be used for successful
variation and relationships among closely related species or genera
(Van Ham et al., 1994; Gielly and Taberlet, 1994; Cros et al., 1998;
Khan and Azim, 2011). The key idea in the current study was to place
the primers for the polymerase chain reaction (PCR) in a conserved
region. The succession of conserved trn genes and several hundred base
pairs of non-coding regions have a higher rate of nucleotide substitution
of the single-copy regions (Wolfe et al., 1987). We selected an inter-
genic spacer (trnS-trnG) from the cpDNA sequences for tobacco
(Hamilton, 1999). It was hypothesized that region between the trnS-
trnG genes was suitable for the genetic structure and diversity variation.
Concerning the hypotheses, we estimated the trnS-trnG regional cpDNA
structure and diversity with a view to evaluate the genetic structure
within taxa; and the genetic divergence among taxa of the genus Hosta
in Shikoku, Japan.
Materials and methods
Plant materials
Leaves of hosta plant (1–12 individuals) were collected from dif-
ferent locations around Shikoku Island, Kochi prefecture, Japan
(Table 1 and supplementary Fig. S1) between October 2014 and June
2015. The locations data were recorded using Garmin eTrex20J.
Sample within one meter wasn’t collected from each location to avoid
the collection error as much as possible. The collected leaves were
preserved in ziplock plastic bags and stored them in deep freezer
(−80 °C) until DNA extraction. In total, 399 individuals of 11 taxa
[identified morphologically (Schmid, 1991)] of Hosta genus were se-
quenced (Table 1).
Table 1
Hosta genus sample collection locality around Shikoku, Japan with geographical data and accession number.
P
code
N
Ind
Locality N E Accession number
Hosta sieboldiana
A1 3 Shiozuka highland roadside, Tairano, Yamashiro-cho, Miyoshi-shi, Tokushima 33.9900 133.8800 LC152207
A2 5 Shiozuka highland roadside, Tairano, Yamashiro-cho, Miyoshi-shi, Tokushima 33.9300 133.8500 LC152208
A3 3 Yamashiro-cho, Miyoshi-shi, Tokushima 34.0500 134.5200 LC152209
A4 6 Yamashiro-cho, Miyoshi-shi, Tokushima 34.0700 134.5200 LC152210
Hosta alismifolia
B1 12 Itachino, Nankoku-shi, Kochi 33.5600 133.6300 LC152211
B2 2 Mihara-mura, Hata-gun, Kochi 32.8800 132.9100 LC152212
B3 3 Sakawa-cho, Takaoka-gun, Kochi 33.5200 133.2200 LC152213
B4 5 Sakawa-cho, Takaoka-gun, Kochi 33.5000 133.2300 LC152214
B5 6 Sakawa-cho, Takaoka-gun, Kochi 33.5100 133.2300 LC152215
B6 5 Koda, Kochi-shi, Kochi 33.5200 133.5100 LC152216
B7 4 Koda, Kochi-shi, Kochi 33.5100 133.5100 LC152217
Hosta sieboldii
C1 6 Otoyo-cho, Nagaoka-gun, Kochi 33.4147 133.4130 LC152218
C2 4 Yoshiuno Otsu, Tsuno-cho, Takaoka-gun, Kochi 33.2726 133.0170 LC152219
C3 5 Yoshiuno Otsu, Tsuno-cho, Takaoka-gun, Kochi 33.2715 133.0140 LC152220
C4 5 Yoshiuno Otsu, Tsuno-cho, Takaoka-gun, Kochi 33.2735 133.0370 LC152221
C5 5 Nagatake, Kamo, Sakawa-cho, Takaoka-gun, Kochi 33.3060 133.1940 LC152222
C6 4 Higashi Iya, Higashimiyoshi-cho, Miyoshi-gun, Tokushima 34.0870 134.5586 LC152223
C7 6 Sedo (Akutagawa), Tosa-cho, Tosa-gun, Kochi 33.7100 133.4100 LC152224
Hosta longissima
D1 4 Kochi kada (Warei shrine), Ino-cho, Agawa-gun, Kochi 33.5358 133.5141 LC152225
D2 6 Kochi koda dais, Kochi-shi, Kochi 33.5339 133.0879 LC152226
D3 2 Tengu highland, Tsuno-cho, Takaoka-gun, Kochi 33.4707 132.9780 LC152227
Hosta tardiva
E1 5 Sedo, Tosa-cho, Tosa-gun, Kochi 33.3902 133.2584 LC152228
E2 7 Higashiishihara, Tosa-cho, Tosa-gun, Kochi 33.4145 133.2773 LC152229
E3 6 Higashiishihara, Tosa-cho, Tosa-gun, Kochi 33.4029 133.2695 LC152230
E4 5 Higashiishihara, Tosa-cho, Tosa-gun, Kochi 33.4168 133.2789 LC152231
E5 4 Nishiyamagumi, Sakawa-cho, Takaoka-gun, Kochi 33.2853 133.1540 LC152232
E6 4 Oishi, Motoyama-cho, Nagaoka-gun, Kochi 33.4517 133.3550 LC152233
E7 8 Itachino, Nankoku-shi, Kochi 33.5637 133.3749 LC152234
E8 4 Itachino, Nankoku-shi, Kochi 33.5648 133.3749 LC152235
E9 5 Itachino, Nankoku-shi, Kochi 33.5666 133.3748 LC152236
E10 4 Kochi koda dais, Kochi-shi, Kochi 33.5308 133.5250 LC152237
Hosta longipes var. gracillima
F1 5 Tosayama-mura, Kochi-shi, Kochi 33.3758 133.2981 LC152238
F2 3 Tosayama-mura, Kochi-shi, Kochi 33.3799 133.2965 LC152239
F3 6 Kagamiogachi, Kochi-shi, Kochi 33.5789 133.4730 LC152240
F4 4 Kagamiogachi, Kochi-shi, Kochi 33.5798 133.4730 LC152241
F5 5 Kagamikariyama, Kochi-shi, Kochi 33.5994 133.4704 LC152242
F6 6 Kagamikariyama, Kochi-shi, Kochi 33.5994 133.4707 LC152243
F7 1 Kuroson valley, Shimanto-shi, Kochi 33.1317 132.8970 LC152244
F8 3 Kuroson valley, Shimanto-shi, Kochi 33.1389 132.8910 LC152245
F9 6 Nametoko valley, Uwajima-shi, Ehime 33.1275 132.4840 LC152246
(continued on next page)
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
212

DNA extraction and amplification
Young leaves were used for DNA extraction. Leaves (40–80 mg)
were washed in 70% ethanol, kept in microcentrifuge tube with a
Zirconia bead and Nuclei Lysis solution (600 µl); and disrupted at
3500 rpm for 3 min by Micro Smash MS-100 bead beater (Tomy Seiko,
Tokyo,Japan). The genomic DNA was purified in accordance with the
manufacture’s instructions (Wizard®Genomic DNA Purification Kit,
Promega, Wisconsin, USA). Finally, DNA was dehydrated with 100 µl
DNA Rehydration solution. We amplified chloroplast intergenic regions
with a pair of primers trnS (GCU) (GCCGCTTTAGTCCACTCAGC) and
trnG (UCC) (GAACGAATCACACTTTTACCAC) (Hamilton, 1999) with
following conditions: 95 °C (incubation) for 1 min, then 30 cycles of
incubation at 95 °C for 30 s, 60 °C for 60 s, 68 °C for 60 s and finally
extension at 68 °C for 5 min. The reaction volume for the cpDNA am-
plification was 40 µl [27 µl distilled water, 4 µl thermo reaction buffer,
4 µl dNTPs, 2 µl trn S (GCU) primer, 2 µl trn G (UCC) primer, 1 µl DNA
and 0.2 µl Taq DNA polymerase].
DNA sequencing and repositories
Amplified PCR products were purified using Wizard®SV Gel and
PCR Clean-Up System (Promega, Wisconsin, USA). Nucleotides were
sequenced using BigDye™Terminator Cycle Sequencing Ready Reaction
Kit (Applied Biosystems, California, USA), and analyzed on Genetic
Analyzer Models 3100 and 3130 (Applied Biosystems). For all variants,
sequencing was performed at least twice to verify the variations. After
sequencing, sequence data chromatograms were edited using SeqEd
(Applied Biosystems, Foster City, CA) version 1.0.3 (Hagemann and
Kwan, 1997) and deposited in DNA Data Bank of Japan (DDBJ) under
the accession number LC152207 to LC152287.
Table 1 (continued)
P
code
N
Ind
Locality N E Accession number
F10 3 Kankakedori, Shodoshima-cho, Shozu-gun, Kagawa 34.5173 134.3201 LC152247
F11 4 Kozukushi-cho, Sukumo-shi, Kochi 32.9407 132.7510 LC152248
F12 4 Kozukushi-cho, Sukumo-shi, Kochi 32.8307 132.7610 LC152249
F13 9 Onaro, Shimanto-cho, Takaoka-gun, Kochi 33.2309 132.9831 LC152250
F14 7 Shimotsui, Shimanto-cho, Takaoka-gun, Kochi 33.2996 132.9449 LC152251
F15 4 Shimotsui, Shimanto-cho, Takaoka-gun, Kochi 33.2936 132.9559 LC152252
F16 8 Hashikami, Hashikami-cho, Sukumo-shi, Kochi 33.0400 132.7200 LC152253
Hosta nakaiana
G1 4 Hongawa-Erimon, Ino-cho, Agawa-gun, Kochi 33.7269 133.2398 LC152254
G2 2 Omorikawa valley, Hongawa, Ino-cho, Agawa-gun, Kochi 33.4248 133.1780 LC152255
G3 2 Omorikawa valley, Hongawa, Ino-cho, Agawa-gun, Kochi 33.4136 133.1810 LC152256
Hosta kikutii var. caput-avis
H1 5 Tosayamahirose, Kochi-shi, Kochi 33.4734 133.3520 LC152257
H2 5 Tosayamahirose, Kochi-shi, Kochi 33.4634 133.3620 LC152258
H3 7 Hibihara, Tosayamahirose, Kochi-shi, Kochi 33.4791 133.3830 LC152259
H4 3 Hibihara, Tosayamahirose, Kochi-shi, Kochi 33.4841 133.3530 LC152260
H5 6 Tosayama, Kochi-shi, Kochi 33.3816 133.3031 LC152261
H6 4 Hibihara, Tosayamahirose, Kochi-shi, Kochi 33.5324 133.7682 LC152262
Hosta kikutii var. polyneuron
I1 7 Nishitosanakaba, Shimanto-shi, Kochi 33.0997 132.8218 LC152263
I2 4 Nishitosanakaba, Shimanto-shi, Kochi 33.1997 132.8399 LC152264
I3 6 Nishitosanakaba, Shimanto-shi, Kochi 33.0527 132.8669 LC152265
I4 10 Hidaka-mura, Takaoka-gun, Kochi 33.3354 133.2150 LC152266
I5 5 Hidaka-mura, Takaoka-gun, Kochi 33.3924 133.2030 LC152267
I6 5 Kuwagauchi, Tsuno-cho, Takaoka-gun, Kochi 33.2273 133.2010 LC152268
I7 4 Kuwagauchi, Tsuno-cho, Takaoka-gun, Kochi 33.2114 133.1910 LC152269
I8 2 Kuwagauchi, Tsuno-cho, Takaoka-gun, Kochi 33.2414 133.1710 LC152270
I9 9 Kuwagauchi, Tsuno-cho, Takaoka-gun, Kochi 33.2614 133.1410 LC152271
I10 10 Kuwagauchi, Tsuno-cho, Takaoka-gun, Kochi 33.2114 133.1810 LC152272
I11 5 Kuwagauchi, Tsuno-cho, Takaoka-gun, Kochi 33.2675 133.1610 LC152273
I12 5 Hidaka-mura, Takaoka-gun, Kochi 33.2400 132.9800 LC152274
I13 2 Hidaka-mura, Takaoka-gun, Kochi 33.9210 133.3670 LC152275
I14 4 Hidaka-mura, Takaoka-gun, Kochi 33.7000 133.5270 LC152276
I15 3 Oboke, Yamashiro-cho, Miyoshi-shi, Tokushima 33.8783 133.76.04 LC152277
I16 5 Oboke, Yamashiro-cho, Miyoshi-shi, Tokushima 33.8851 133.76.04 LC152278
Hosta longipes var. caduca
J1 10 Besshi, Niyodogawa-cho, Agawa-gun, Kochi 33.5300 133.0500 LC152279
J2 2 Tengu highland, Tsuno-cho, Takaoka-gun, Kochi 33.2756 133.1520 LC152280
J3 2 Tengu highland, Tsuno-cho, Takaoka-gun, Kochi 33.4653 133.0050 LC152281
J4 4 Besshi, Niyodogawa-cho, Agawa-gun, Kochi 33.3985 133.1350 LC152282
J5 4 Shimonanokawa, Niyodogawa-cho, Agawa-gun, Kochi 33.5800 133.0980 LC152283
Hosta kiyosumiensis
K1 5 Taniuchi, Naka-cho, Naka-gun, Tokushima 33.9800 134.4900 LC152284
K2 5 Taniuchi, Naka-cho, Naka-gun, Tokushima 33.8900 134.5500 LC152285
K3 6 Taniuchi, Naka-cho, Naka-gun, Tokushima 33.8100 134.4700 LC152286
K4 6 Ousakayama, Ikku, Kochi 33.5200 133.5900 LC152287
P
code
= Population code; N
Ind
= No. of individuals, N = Latitude, E = Longitude and RS = River system.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
213

Data analysis
Alignment was done by ClustalW process (Thompson et al., 1994)
using MEGA7 (Kumar et al., 2016) and the aligned regions were cor-
rected manually. Evolutionary analyses for whole population were
analyzed by MEGA7. DnaSP v5 (Librado and Rozas, 2009) was used to
estimate the number of segregating sites (S) for the dataset of whole
genus; number of haplotypes and number of polymorphic sites (N
PS
)
and haplotype diversity (h) for the dataset of each taxon; nucleotide
diversity (π) and neutrality test (Tajima’s D, Fu and Li’sD∗and F∗) for
the dataset of whole genus and each individual taxon. Neutrality test
(Fu's FS) (intra-population methods) for individual taxon and pairwise
F
ST
difference (distance method) for the population of among taxa were
estimated using Arlequin ver. 3.11 (Excoffier et al., 2005). Evolutionary
divergence both for individual taxa and whole genus was estimated by
MEGA7. Population relationships i.e. phylogenetic tree was constructed
as NJ tree (Saitou and Nei, 1987) using MEGA7, and bootstrap values
were reconfirmed by PAUP 4.0a147 (Swofford, 2003). PopART was
used for TCS statistical parsimony haplotypes networks for the dataset
of whole genus and each individual taxon to determine the relationship
among the haplotypes (Clement et al., 2000).
Results
The trnS-trnG intergenic regions of cpDNA were analyzed for 81
hosta plant populations containing up to 982 bp and found 60 numbers
of segregating sites with 0.005 nucleotide diversity. The negative values
for Tajima’sD(−2.263), Fu and Li’sD(−5.181) and Fu and Li’sF
(−4.810) indicated an excess of low frequency variants caused by in-
creasing population size (Table 2).
Variation in neutrality and diversity test
The number of polymorphic sites was 4, 24, 8, 4, 6, 62, 7, 5, 39, 8
and 5 for all taxa in chronological order (Table 3) and the polymorphic
sites were shown in supplementary Table S1. The maximum haplotype
diversity was found from H. sieboldiana and H. kiyosumiensis popula-
tions (h: 1.000); maximum nucleotide diversity from H. alismifolia (π:
0.012) and the minimum haplotype diversity from H. sieboldii (h: 0.286)
(Table 3). It was found the higher value for haplotype diversity (h) than
that of nucleotide diversity (π) for all taxa (Table 3). Tajima’s D, Fu and
Li’s D and Fu and Li’s test were not significant at P > .10 level of
significance. It was found the negative values for Tajima’s D, Fu and Li’s
D and Fu and Li’s test from the population of H. sieboldiana, H. alismi-
folia, H. longipes var. gracillima and H. kikutii var. polyneuron.Negative
Tajima’s D signifies an excess of low frequency polymorphisms relative
to expectation while positive value refer low levels of both low and high
frequency polymorphisms. It was found negative values for Fu’s Fs test
in H. sieboldiana,H. longipes var. gracillima,H. kikutii var. polyneuron
and H. kiyosumiensis. The negative value of Fu’s Fs is the evidence for an
excess number of alleles than that expected from a recent population
expansion. On the other hand, positive value of Fu’s Fs is the evidence
for the deficiency of alleles, which would be expected from a recent
population bottleneck. The mean pairwise difference, locus wise nu-
cleotide diversity and gene diversity was varied from taxon to taxon
(supplementary Table S2).
Variation in genetic structure
We found different levels of genetic differentiation: little (F
ST
value: > 0 to 0.05); moderate (F
ST
value: > 0.05 to 0.15); high (F
ST
value: > 0.15 to 0.25); and very high (F
ST
value: > 0.25). However, we
found maximum F
ST
divergence (52.7%) between H. tardiva and H.
kikutii var. caput-avis populations i.e., these two taxa were greatly dif-
ferentiated, that were closely followed by the H. sieboldiana and H.
tardiva population (52.2%). It wasn’t found genetic differentiation
among some taxa (F
ST
value: ≤0) (Table 4). The highest evolutionary
divergence (0.009) was found between populations from H. alismifolia
and H. kikutii var. polyneuron (Table 5).
Haplotype network
Different numbers of haplotypes were found for each taxon from
different prefectures (Fig. 1a–k). Maximum fourteen haplotypes [Kochi:
Table 2
Neutrality test for whole population of Hosta genus.
mn S πD
T
Tajima
(1989)
Fu and Li’sDFu
and Li (1993)
Fu and Li’sFFu
and Li (1993)
81 982 60 0.00450 −2.26319** −5.18127** −4.81023**
Abbreviations: m = number of sequences, n = total number of sites, S = Number of
segregating sites, π= nucleotide diversity, D
T
= Tajima’s D test.
D
T
: **, P < .01.
Fu and Li’s D and F: **, P < .02.
NB: calculation was done for the whole data set.
Table 3
Estimation of the number of polymorphic sites (N
PS
), haplotype diversity (h), nucleotide diversity (π) and the neutrality test (Tajima's D test, Fu and Li’s D* and F* and Fu's FS test) for
eleven hosta taxa.
Statistics Gp_1 Gp_2 Gp_3 Gp_4 Gp_5 Gp_6 Gp_7 Gp_8 Gp_9 Gp_10 Gp_11
N
PS
4.0 24.0 8.0 4.0 6.0 62.0 7.0 5.0 39.0 8.0 5.0
h 1.0 0.714 0.286 0.667 0.533 0.975 0.667 0.8 0.967 0.9 1.0
π0.002 0.012 0.0 0.0 0.003 0.004 0.0 0.003 0.008 0.005 0.003
Tajima's D test Tajima (1989)
Tajima's D −0.065 −0.311 NA NA 0.956 −1.546 NA 1.541 −1.227 0.687 0.372
Fu and Li’s D* and F* Fu and Li (1993)
Fu and Li’sD −0.065 −0.312 NA NA 0.956 −1.742 NA 1.541 −1.271 0.687 0.372
Fu and Li’sF −0.060 −0.323 NA NA 0.904 −1.936 NA 1.456 −1.441 0.676 0.351
Fu's FS test Fu (1997)
FS −1.741 2.562 3.644 1.609 0.388 −1.963 0.000 0.067 −3.843 0.212 −1.322
N/A = not applicable and neutrality test were not significant at P > .10.
Gp_1: H. sieboldiana, Gp_2: H. alismifolia, Gp_3: H. sieboldii, Gp_4: H. longissima, Gp_5: H. tardiva, Gp_6: H. longipes var. gracillima, Gp_7: H. nakaiana, Gp_8: H. kikutii var. caput-avis, Gp_9: H.
kikutii var. polyneuron, Gp_10: H. longipes var. caduca and Gp_11: H. kiyosumiensis.
NB: calculation was done for each species independently; number of individuals sequenced and the sequence length for each species are presented in the supplementary Tables S1 and S2.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
214

12; Kagawa; 1 (haplotype 8); both Kochi and Ehime: 1 (haplotype 3: F3,
F7 and F9 populations) were detected for H. longipes var. gracillima
(Fig. 1f). H. kikutii var. polyneuron was the second highest haplotype
(13) providing taxon [Kochi: 11; Tokushima: 1 (haplotype 13); both
Kochi and Tokushima: (haplotype 4: I4, I13, and I15 populations)]
(Fig. 1i). For H. kiyosumiensis, in total four haplotypes were detected.
Only one haplotype was found from Kochi (haplotype 4) and rest three
from Tokushima (Fig. 1 k). The 81 sequences of hosta from four geo-
graphic locations (Kochi, Tokushima, Kagawa and Ehime prefectures)
showed 57 haplotypes around Shikoku. Fifty-seven haplotypes were
used for constructing haplotype networks (Fig. 2). However, the hap-
lotype network revealed 47 haplotypes without consideration of taxa,
i.e., some of the haplotypes from different taxa contained identical
genetic material. From the haplotype network, it was found that all
haplotypes were clustered in three major groups. The sequences of the
H. alismifolia haplotype 1 and H. longissima haplotype 1 were identical.
Similarly, some other haplotypes from different taxa also contained
identical genetic material [the following groups had identical genetic
material: H. kikutii var. polyneuron haplotype 3&H. kiyosumiensis hap-
lotype 3; H. longipes var. gracillima haplotype 3&H. kikutii var. caput-avis
haplotype 1; H. alismifolia haplotype 4, H. sieboldii haplotype 1, H. long-
issima haplotype 2, H. tardiva haplotype 1, H. kikutii var. polyneuron
haplotype 4and H. longipes var. caduca haplotype 4; and H. longipes var.
gracillima haplotype 5,H. kikutii var. polyneuron haplotype 5 and H.
longipes var. caduca haplotype 1]. Table 6 represents the number and
percentage of the haplotypes for each of the hosta taxa and prefectures
of Shikoku Island as well. It was found maximum 24.55% haplotypes
from H. longipes var. gracillima while 22.80% haplotypes from H. kikutii
var. polyneuron (Table 6). Maximum haplotypes were found from Kochi
prefecture (85.97%) (Table 6).
Phylogenetic tree
NJ phylogenetic tree was constructed to show the inherent re-
lationship among the indels of the populations for each taxon (Fig. 3)
and whole genus (Fig. 4). The topology of the NJ tree generally reflects
the divergence of population of each taxon. The phylogenetic tree was
constructed for the H. sieboldiana,H. alismifolia,H. sieboldii,H. tardiva,
H. longipes var. gracillima,H. kikutii var. caput-avis,H. kikutii var. poly-
neuron,H. longipes var. caduca and H. kiyosumiensis (Fig. 3). Due to less
than four operational taxonomic units phylogenetic tree was not con-
structed for H. longissima and H. nakaiana taxa. Hosta genus was greatly
influenced by those taxa and geographic locations (Fig. 4) but we did
not find any geographical clustering of the studied hosta population.
Variations were clearly observed among the single nucleotide poly-
morphisms (SNPs) of all studied taxa. The early divergence of long
branches of the populations [e.g., I8 and B3 (97%)] were supported by
considerable bootstrap value.
Table 5
Estimation of evolutionary divergence over sequence pairs between the hosta taxa population from cpDNA.
Gp_1 Gp_2 Gp_3 Gp_4 Gp_5 Gp_6 Gp_7 Gp_8 Gp_9 Gp_10 Gp_11
Gp_1 0.002 0.001 0.002 0.002 0.002 0.002 0.001 0.002 0.002 0.002
Gp_2 0.007 0.002 0.001 0.002 0.002 0.001 0.002 0.002 0.002 0.002
Gp_3 0.004 0.006 0.001 0.001 0.001 0.001 0.002 0.001 0.001 0.001
Gp_4 0.004 0.004 0.003 0.001 0.001 0.001 0.002 0.002 0.001 0.002
Gp_5 0.004 0.006 0.002 0.003 0.001 0.001 0.002 0.001 0.001 0.001
Gp_6 0.005 0.007 0.004 0.004 0.004 0.001 0.001 0.001 0.001 0.001
Gp_7 0.005 0.006 0.005 0.003 0.004 0.005 0.002 0.002 0.002 0.001
Gp_8 0.004 0.007 0.005 0.005 0.005 0.004 0.005 0.001 0.001 0.001
Gp_9 0.007 0.009 0.005 0.006 0.005 0.006 0.007 0.006 0.001 0.001
Gp_10 0.005 0.007 0.004 0.004 0.004 0.004 0.005 0.004 0.005 0.001
Gp_11 0.005 0.006 0.004 0.004 0.004 0.005 0.005 0.004 0.006 0.004
Gp_1: H. sieboldiana, Gp_2: H. alismifolia, Gp_3: H. sieboldii, Gp_4: H. longissima, Gp_5: H. tardiva, Gp_6: H. longipes var. gracillima, Gp_7: H. nakaiana, Gp_8: H. kikutii var. caput-avis, Gp_9: H.
kikutii var. polyneuron, Gp_10: H. longipes var. caduca and Gp_11: H. kiyosumiensis.
The numbers of base substitutions per site from averaging over all sequence pairs between groups are shown. Above the diagonal of the table represents Standard error estimate(s). The
analysis involved 81 nucleotide sequences. All positions with less than 95% site coverage were eliminated. That is, fewer than 5% alignment gaps, missing data, and ambiguous bases
were allowed at any position. There were a total of 982 positions in the final dataset. We used ML model for analysis (Tamura et al., 2004) where the differences in the composition bias
among sequences were considered in evolutionary comparisons (Tamura and Kumar, 2002).
Table 4
Assessment of population pairwise fixation index (F
ST
) (distance method) over sequence pairs from cpDNA for eleven hosta taxa.
Gp_1 Gp_2 Gp_3 Gp_4 Gp_5 Gp_6 Gp_7 Gp_8 Gp_9 Gp_10 Gp_11
Gp_1 0
Gp_2 0.208 0
Gp_3 0.450 0.206 0
Gp_4 0.465 −0.201 0.305 0
Gp_5 0.522 0.282 −0.007 0.374 0
Gp_6 0.076 0.113 0.089 −0.012 0.128 0
Gp_7 0.449 0.042 0.306 0.400 0.365 −0.066 0
Gp_8 0.364 0.269 0.468 0.450 0.527 0.044 0.381 0
Gp_9 0.233 0.176 0.038 0.121 0.106 0.100 0.082 0.118 0
Gp_10 0.376 0.145 0.135 0.223 0.229 0.006 0.170 0.163 −0.069 0
Gp_11 0.444 0.150 0.379 0.368 0.451 0.045 0.289 0.347 0.108 0.075 0
Gp_1: H. sieboldiana, Gp_2: H. alismifolia, Gp_3: H. sieboldii, Gp_4: H. longissima, Gp_5: H. tardiva, Gp_6: H. longipes var. gracillima, Gp_7: H. nakaiana, Gp_8: H. kikutii var. caput-avis, Gp_9: H.
kikutii var. polyneuron, Gp_10: H. longipes var. caduca and Gp_11: H. kiyosumiensis.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
215

Discussion
It was observed that results of Tajima’s D test, Fu and Li’s D and F
test had significant negative values for the whole population (Table 2),
which was evidence for purifying selection at this locus or for increase
in the population size. These negative values also indicated the pre-
sence of excess low frequency polymorphism/mutations and an excess
of rare mutations in these genes of hosta populations. Results of the
current study confirmed that Hosta genus around Shikoku area had rare
alleles at low frequencies due to recent discriminating sweep up, ex-
pansion of the population after a recent bottleneck or some linkage to a
swept gene. Our results indicated very high haplotype diversity (h) and
low nucleotide diversity (π) for the population of all taxa, and it means
all of the studied taxa have many haplotypes but very similar between
them (Table 3 and supplementary Table S1). It is also clear from the
haplotype network, which shows very low nucleotide differences be-
tween haplotypes (Figs. 1 and 2). From these results, we can say that
each of the studied hosta taxa expanded their population after a period
of low effective population size; and their rapid population growth
enhanced the retention of new mutations (Grant and Bowen, 1998;
Avise et al., 1984; Rogers and Harpending, 1992) interpretation of the
interrelation of gene vs. nucleotide diversity.
Though neutrality test for individual taxon didn’t show any sig-
nificant value (Table 3) but the results indicated (1) there was no evi-
dence for H. sieboldii, H. longissima, H. nakaiana regarding change in
population size or pattern for selection; (2) there was evidence of over
dominant selection at this locus or a recent population bottleneck for H.
tardiva,H. kikutii var. caput-avis,H. longipes var. caduca and H. kiyosu-
miensis (D
T
> 0 and Fu and Li’s D & F > 0); and (3) there was evi-
dence similar to that for the whole population in H. sieboldiana,H.
Fig. 1. SNP Haplotype network for eleven taxa of Hosta genus (a) H. sieboldiana, (b) H. alismifolia, (c) H. sieboldii, (d) H. longissima, (e) H. tardiva, (f) H. longipes var. gracillima, (g) H.
nakaiana, (h) H. kikutii var. caput-avis, (i) H. kikutii var. polyneuron, (j) H. longipes var. caduca, and (k) H. kiyosumiensis collected from Shikoku areas of Japan based on trnS-trnG regional
cpDNA sequences. Pie circles indicated the origin of haplotypes with proportional size of the number of records in different color and cross mark into the connecting line between pie
circles noted the number of nucleotide substitution. Here, Kochi, Tokushima, Kagawa and Ehime are the four prefectures in Shikoku Island, Japan.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
216

alismifolia,H. longipes var. gracillima,H. kikutii var. polyneuron (D
T
<0
and Fu and Li’s D & F < 0). The excessive low frequency variants re-
sulted from increasing population size in H. sieboldiana,H. alismifolia,
H. longipes var. gracillima and H. kikutii var. polyneuron. We found
limited samples for H. longissima and H. nakaiana here which have a
great possibility to quick reduction of population size. H. tardiva,H.
kikutii var. caput-avis,H. longipes var. caduca and H. kiyosumiensis taxa
need immediate recovery from extinction in this area. These genetic
differences could be inferred from differences in relative recruitment of
immigrant neutrality test (Oddou-Muratorio et al., 2004). Tajima’sD
test and Fu and Li’s D and F tests were used for neutrality testing
through cpDNA sequence in many plants, including rye (Li et al., 2011)
and pine species (Suharyanto and Shiraishi, 2011).
HighhaplotypeandlownucleotidediversitywasfoundintrnS-trnG
region of cpDNA for each Hosta taxon suggested the low difference be-
tween haplotypes. It might be an indication of recent population expan-
sion resulting from bottlenecks (González-Wangüemert et al., 2011)or
Fig. 2. SNP Haplotype network for 57 haplotypes from eleven Hosta species from Shikoku areas of Japan based on cpDNA sequences. Pie circles indicated the origin of haplotypes with
proportional size of the number of records in different color and cross mark into the connecting line between pie circles noted the number of nucleotide substitutions. Some of the node
level consisted identical sequences like Hap._5 (Hap._5, Hap._11); Hap._19 (Hap._19, Hap._33); Hap._39 (Hap._39, Hap._56); Hap._8 (Hap._8, Hap._9, Hap._12, Hap._13, Hap._40, Hap._53)
and Hap._21 (Hap._21, Hap._41, Hap._50).
Table 6
Number and percentage of haplotypes for each hosta taxa and prefecture.
Taxa Number of haplotypes % Prefectures Number of
haplotypes
%
Gp_1 4 (Kochi 4) 7.02
Gp_2 4 (Kochi 4) 7.02
Gp_3 2 (Kochi 1, Tokushima 1) 3.51
Gp_4 2 (Kochi 2) 3.51
Gp_5 4 (Kochi 4) 7.02
Gp_6 14 (Kochi 12, Kagawa 1,
Ehime 1)
24.55
Gp_7 2 (Kochi 2) 3.51 Kochi 49 85.97%
Gp_8 4 (Kochi 4) 7.02 Tokushima 6 10.53%
Gp_9 13 (Kochi 11, Tokushima 2) 22.80 Kagawa 1 1.75%
Gp_10 4 (Kochi 4) 7.02 Ehime 1 1.75%
Gp_11 4 (Kochi 1, Tokushima 3) 7.02
Gp_1: H. sieboldiana, Gp_2: H. alismifolia, Gp_3: H. sieboldii, Gp_4: H. longissima, Gp_5: H.
tardiva, Gp_6: H. longipes var. gracillima, Gp_7: H. nakaiana, Gp_8: H. kikutii var. caput-avis,
Gp_9: H. kikutii var. polyneuron, Gp_10: H. longipes var. caduca and Gp_11: H. kiyosumiensis.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
217

break-up of habitat (Zhou et al., 2010). It was clear that most of the
polymorphic sites had emerged during demographic expansion and that
SNP had been built up through mutations and failure to gather nucleotide
sequence diversity (Zhou et al., 2010). Nucleotide and haplotype diversity
were also examined in different cpDNA region in different plants (Li et al.,
2011; Lijavetzky et al., 2007; Kolkman et al., 2007). Different levels of
haplotype diversity (ranging from 0.286 to 1.000) were found (Table 3).
H. sieboldiana and H. kiyosumiensis (h: 1.0) were widely distributed
whereas H. sieboldii (h: 0.286) was narrowly distributed taxon. It was
confirmed that geographical distribution of the studied Hosta taxa was
restricted, in terms of chronological order for H. sieboldiana &H. kiyosu-
miensis, H. longipes var. gracillima, H. kikutii var. polyneuron,H. longipes var.
caduca,H. kikutii var. caput-avis,H. alismifolia,H. longissima &H. nakaiana,
H. tardiva, H. sieboldii around Shikoku (Table 3). Lee and Maki (2013)
stated that H. sieboldiana occupied a restricted habitat in Japan but this
taxon distributed widely in Shikoku area.
Maximum F
ST
value between H. tardiva and H. kikutii var. caput-avis
(Table 4) population noted the differences in their allelic frequency. H.
kikutii var. caput-avis originated from west-central Shikoku Island; while H.
tarvida originated from central part of Kochi Prefecture and southwestern
part of the Tokushima Prefecture of Shikoku Island, Japan. Less than zero
F
ST
value between H. alismifolia and H. longissima,H. sieboldii and H. tar-
vida,H. longissima and H. longipes var. gracillima,H. nakaiana and H.
longipes var. gracillima,H. kikutii var. polyneuron and H. longipes var. caduca
(Table 4) indicated that these taxon pairs had similar allelic frequency. F
ST
had been used for evaluating population genetic differentiation (Whitlock,
2011; Rousset, 2013)fordifferent plant species, including orchids (Pandey
and Sharma, 2015)andsunflower (Renaut et al., 2013).
Fig. 3. Inference of evolutionary history for individual taxon based on trnS-trnG regional cpDNA variations using NJ phylogenetic tree (500 bootstrap replicates). Evolutionary distance
computed by maximum composite likelihood. Bootstrap value ≤50 was not shown in the phylogenetic tree. The analysis involved all nucleotide sequences with 985 positions in the final
dataset. Codon position includes 1st +2nd+3rd + Noncoding position. Less than 5% alignment gaps, missing data, and ambiguous bases were allowed at any position. Series A to K in
the phylogenetic tree represents the hosta plant population as in Table 1. Note: H. longissima and H. nakaiana had less than four operational taxonomic units (OTUs) but for construction of
a tree it should be OTUs ≥4.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
218

Different numbers of haplotypes were found for each taxon but none
of these were widely distributed throughout the entire Shikoku (Fig. 1).
Most of the haplotypes were detected in Kochi areas. Mountains run-
ning east and west divide Shikoku into a narrow northern and southern
sub region. Kochi prefecture comprises the southwestern part of Shi-
koku, facing the Pacific Ocean. It is bordered by Ehime to the north-
west and Tokushima to the north-east. It is the largest but least popu-
lous of Shikoku's four prefectures. Most of this province is mountainous,
and in only a few areas is coastal plain. Numerous numbers of moun-
tains with least disturbance by human activities lead Kochi prefecture
as a great source of hosta plant. H. longissima and H. nakaiana showed
small population sizes in Shikoku, and it may lead to a secondary ge-
netic variation loss due to the result of bottleneck and genetic drift.
Identical genetic material was found in different taxa throughout
the haplotype identification. Sharing the haplotypes across the taxa is
the evidence for the occurrence of the natural mutation or hybridization
(Ley and Hardy, 2014) of hosta plant taxa. Hosta can fertilize by selfing
or cross pollination which can resulted this genetic variability. Our
study was restricted to the Shikoku area and trnS-trnG region of cpDNA,
which may be reason for the uniformity of the population throughout
the geographical distribution. We found that the phylogeographic re-
lationship for the population of a taxon was differentiated or
not to their geographical distribution. The previous study on
Cryptomeria japonica (not differentiated to geographical distribution)
(Kado et al., 2003) and hosta (showed wide geographical variation)
(Lee and Maki, 2013) were agreed our findings.
Conclusion
Complementary information was found for the population structure
of studied taxa. The negative values for Tajima’s D, Fu and Li’s D and Fu
and Li’s F test was found thus indicated the overall hosta plant popu-
lations are going to increase in Shikoku Island, Japan. All studied hosta
taxa have many haplotypes but very similar between them. The max-
imum F
ST
divergence was between H. tardiva and H. kikutii var. caput-
avis populations, and H. sieboldiana and H. tardiva populations as well,
which means these pairs were greatly differentiated from each other.
Identical haplotypes shared by two different taxa notified the occur-
rence of natural mutation or hybridization. We can conclude that single
source of information should not be used to determine variation or
relationships among the closely related but highly diversified Hosta
taxa; but can be used for the generic level.It needs further study of the
studied taxa using multiple markers (including marker used in this
study) for assessing the variations in the actual extent and evolutionary
significance of introgression between hosta taxa.
Acknowledgement
The authors are most grateful to the Research Institute of Molecular
Genetics (RIMG), Kochi University, for access to instrumental facilities
for the conduct of the research. We are highly indebted to the United
Graduate School of Agricultural Science of Ehime University, Japan;
and to the Japanese Ministry of Education, Culture, Sports, Science and
Technology to support the study. Special thanks go to Sultana Umma
Habiba. We are also most thankful to the lab mates who helped us with
the collection of the samples.
Appendix A. Supplementary material
Supplementary data associated with this article can be found, in the
online version, at http://dx.doi.org/10.1016/j.aoas.2017.12.003.
References
Andre, C., Larsson, L.C., Laikre, L., Bekkevold, D., Brigham, J., Carvalho, R., Dahlgren,
T.G., Hutchinson, W.F., Mariani, S., Mudde, K., Ruzzante, E., Ryman, N., 2011.
Detecting population structure in a high gene-flow species, Atlantic herring (Clupea
harengus): direct, simultaneous evaluation of neutral vs putatively selected loci.
Heredity 106, 270–280.
Avise, J.C., Neigel, J.E., Arnold, J., 1984. Demographic influences on mitochondrial DNA
lineage survivorship in animal populations. J. Mol. Evol. 20 (2), 99–105.
Ayele, T.B., Gailing, O., Umer, M., Finkeldey, R., 2009. Chloroplast DNA haplotype di-
versity and postglacial recolonization of Hagenia abyssinica (Bruce) J.F. Gmel. in
Ethiopia. Plant Syst. Evol. 280 (3), 175–185.
Bierne, N., Welch, J., Loire, E., Bonhomme, F., David, P., 2011. The coupling hypothesis:
why genome scans may fail to map local adaptation genes. Mol. Ecol. 20 (10),
2044–2072.
Clement, M., Posada, D., Crandall, K.A., 2000. TCS: a computer program to estimate gene
genealogies. Mol. Ecol. 9 (10), 1657–1659.
Cros, J., Combes, M.C., Trouslot, P., Anthony, F., Hamon, S., Charrier, A., Lashermes, P.,
1998. Phylogenetic analysis of chloroplast DNA variation in Coffea L. Mol.
Fig. 4. Inference of evolutionary history for 81 hosta individuals based on cpDNA var-
iations using NJ phylogenetic tree (500 bootstrap replicates), evolutionary distance
computed by maximum composite likelihood (ML) considering both transitional and
transversional nucleotide substitutions. The optimal tree with the sum of branch length is
0.09535407. Bootstrap value ≤50 was not shown in the phylogenetic tree. The analysis
involved 81 nucleotide sequences with 985 positions in the final dataset. Codon position
includes 1st + 2nd+3rd + Noncoding position. Less than 5% alignment gaps, missing
data, and ambiguous bases were allowed at any position. Series A to I in the phylogenetic
tree represents the hosta plant population represented as in Table 1.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
219

Phylogenet. Evol. 9 (1), 109–117.
Excoffier, L., Laval, G., Schneider, S., 2005. Arlequin ver. 3.0: an integrated software
package for population genetics data analysis. Evol. Bioinform. Online 1, 47–50.
Fu, Y.X., 1997. Statistical tests of neutrality of mutations against population growth,
hitchhiking and background selection. Genetics 147 (2), 915–925.
Fu, Y.X., Li, W.H., 1993. Statistical tests of neutrality of mutations. Genetics 133 (3),
693–709.
Fujita, N., 1976. The genus hosta (Liliaceae) in Japan (in Japanese). Acta Phytotax.
Geobot. 27 (3-4), 66–96.
Gielly, L., Taberlet, P., 1994. The use of chloroplast DNA to resolve plant phylogenies:
non-coding versus rbcL sequences. Mol. Biol. Evol. 11 (5), 769–777.
González-Wangüemert, M., Froufe, E., Pérez-Ruzafa, A., Alexandrino, P., 2011.
Phylogeographical history of the white seabream Diplodus sargus (Sparidae): im-
plications for insularity. Mar. Biol. Res. 7 (3), 250–260.
Grant, W.A.S., Bowen, B.W., 1998. Shallow population histories in deep evolutionary
lineages of marine fishes: insights from sardines and anchovies and lessons for con-
servation. J. Hered. 89 (5), 415–426.
Hagemann, T.L., Kwan, S.P., 1997. SeqEd: manipulation of sequence data and chroma-
tograms from the ABI DNA sequencer analysis files. Sequence Data Analysis
Guidebook Volume 70 of the series Methods in Molecular Medicine™Springer New
York. pp. 55–63.
Hamilton, M.B., 1999. Four primer pairs for the amplification of chloroplast intergenic
regions with intraspecific variation. Primer Notes. Mol. Ecol. 8 (3), 521–523.
Holsinger, K.E., Weir, B.S., 2009. Genetics in geographically structured populations: de-
fining, estimating and interpreting F
ST
. Nat. Rev. Genet. 10, 639–650.
Kado, T., Yoshimaru, H., Yoshihiko, T., Hidenori, H., 2003. DNA variation in a conifer,
Cryptomeria japonica (Cupressaceae sensu lato). Genet. 164 (4), 1547–1559.
Khan, I.A., Azim, M.K., 2011. Variations in intergenic spacer rpl20-rps12 of mango
(Mangifera indica) chloroplast DNA: implications for cultivar identification and
phylogenetic analysis. Plant Syst. Evol. 292 (3–4), 249–255.
Kolkman, J.M., Berry, S.T., Leon, A.J., Slabaugh, M.B., Tang, S., Gao, W., Shintani, D.K.,
Burke, J.M., Knapp, S.J., 2007. Single nucleotide polymorphisms and linkage dis-
equilibrium in sunflower. Genetics 177 (1), 457–468. http://dx.doi.org/10.1534/
genetics.107.074054.
Kumar, S., Stecher, G., Tamura, K., 2016. MEGA7: Molecular evolutionary genetics
analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33 (7), 1870–1874.
Lee, S., Maki, M., 2013. Comparative phylogeographic study of Hosta sieboldiana and
Hosta albomarginata (Asparagaceae) in Japan. Ecol. Evol. 3 (14), 4767–4785.
Ley, A.C., Hardy, O.J., 2014. Contrasting patterns of gene flow between sister plant
species in the understorey of African moist forests –The case of sympatric and
parapatric Marantaceae species. Mol. Phylogenet. Evol. 77, 264–274.
Li, Y., Haseneyer, G., Schön, C.C., Ankerst, D., Korzun, V., Wilde, P., Bauer, E., 2011. High
levels of nucleotide diversity and fast decline of linkage disequilibrium in rye (Secale
cereale L.) genes involved in frost response. BMC Plant Biol. 11, Article no. 6.
Librado, P., Rozas, J., 2009. DnaSP v5: a software for comprehensive analysis of DNA
polymorphism data. Bioinformatics 25 (11), 1451–1452.
Lijavetzky, D., Cabezas, J.A., Ibáñez, A., Rodríguez, V., Martínez-Zapater, J.M., 2007.
High throughput SNP discovery and genotyping in grapevine (Vitis vinifera L.) by
combining a re-sequencing approach and SNPlex technology. BMC Genomics 8, 424.
Maki, M., Matsumua, S., Yamashiro, T., 2008. Allozyme diversity and history of dis-
tribution expansion in the maritime perennial plant Hedyotis strigulosa (Rubiaceae),
distributed over the wide latitudes in the Japanese Archipelago. Boil. J. Linn. Soc. 93
(4), 679–688.
Millien-Parra, V., Jaeger, J.J., 1999. Island biogeography of the Japanese terrestrial
mammal assemblages: an example of a relict fauna. J. Biogeogr. 26 (5), 959–972.
Oddou-Muratorio, S., Demesure-Musch, B., Pelissier, R., Gouyon, P.H., 2004. Impacts of
gene flow and logging history on the local genetic structure of a scattered tree species
Sorbus torminalis L. Mol. Ecol. 13 (12), 3689–3702.
Pandey, M., Sharma, J., 2015. Disjunct populations of a locally common North American
orchid exhibit high genetic variation and restricted gene flow. Open J. Genet. 5,
159–175.
Pilot, M., Jedrzejewski, W., Branicki, W., Sidorovich, V.E., Jedrzejewska, B., Stachura, K.,
Funk, S.M., 2006. Ecological factors influence population genetic structure of
European grey wolves. Mol. Ecol. 15 (14), 4533–4553.
Renaut, S., Grassa, C.J., Yeaman, S., Moyers, B.T., Lai, Z., Kane, N.C., Bowers, J.E., Burke,
J.M., Rieseberg, L.H., 2013. Genomic islands of divergence are not affected by geo-
graphy of speciation in sunflowers. Nat. Commun. 4, Article no., 1827.
Rogers, A.R., Harpending, H., 1992. Population growth makes waves in the distribution of
pairwise genetic differences. Mol. Biol. Evol. 9 (3), 552–569.
Rousset, F., 2013. Exegeses on maximum genetic differentiation. Genetics 194 (3),
557–559.
Saitou, N., Nei, M., 1987. The neighbor-joining method: a new method for reconstructing
phylogenetic trees. Mol. Biol. Evol. 4 (4), 406–425.
Schmid, W.G., 1991. The genus Hosta –Giboshi Zoku (ギボウシ属). Batsford/Timber
Press, London and Portland.
Suharyanto, Shiraishi, S., 2011. Nucleotide Diversities and Genetic Relationship in the
Three Japanese Pine Species; Pinus thunbergii,Pinus densiflora, and Pinus luchuensis.
Diversity 3 (1), 121–135.
Swofford, D.L., 2003. PAUP*[Phylogenetic analysis using parsimony (and other
methods)]. Version 4.0a147. Sinauer Associates, Sunderland, Massachusetts, USA.
Taberlet, P., Gielly, L., Pautou, G., Bouvet, J., 1991. Universal primers for amplification of
three non-coding regions of chloroplast DNA. Plant Mol. Biol. 17 (5), 1105–1109.
Tajima, F., 1989. Statistical method for testing the neutral mutation hypothesis by DNA
polymorphism. Genetics 123 (3), 585–595.
Tamura, K., Kumar, S., 2002. Evolutionary distance estimation under heterogeneous
substitution pattern among lineages. Mol. Biol. Evol. 19 (10), 1727–1736.
Tamura, K., Nei, M., Kumar, S., 2004. Prospects for inferring very large phylogenies by
using the neighbor-joining method. Proc. Natl. Acad. Sci. USA 101 (30),
11030–11035.
Thompson, J.D., Higgins, D.G., Gibson, T.J., 1994. CLUSTAL W: improving the sensitivity
of progressive multiple sequence alignment through sequence weighting, position-
specific gap penalties and weight matrix choice. Nucl. Acids Res. 22 (22), 4673–4680.
Van Ham, R.C.H.J., Hart, H., Mes, T.H.M., Sandbrink, J.M., 1994. Molecular evolution of
noncoding regions of the chloroplast genome in the Crassulaceae and related species.
Curr. Genet. 25 (6), 558–566.
Whitlock, M.C., 2011. G′
ST
and Ddo not replace F
ST
. Mol. Ecol. 20 (6), 1083–1091.
Wolfe, K.H., Li, W.H., Sharp, P.M., 1987. Rates of nucleotide substitutions vary greatly
among plant mitochondrial, chloroplast, and nuclear DNAs. Proc. Natl. Acad. Sci.
USA 84 (24), 9054–9058.
Zhou, G., Yang, L., Li, C., Xu, W., Chen, G., 2010. Genetic diversity in endangered
Notopterygium forbesii Boissieu based on intraspecies sequence variation of chlor-
oplast DNA and implications for conservation. Biochem. Syst. Ecol. 38 (5), 911–916.
H. Mehraj et al. Annals of Agricultural Sciences 62 (2017) 211–220
220