Population genetics of two asexually and sexually reproducing psocids species inferred by the analysis of mitochondrial and nuclear DNA sequences.

Abstract

The psocids Liposcelis bostrychophila and L. entomophila (Psocoptera: Liposcelididae) are found throughout the world and are often associated with humans, food stores and habitations. These insects have developed high levels of resistance to various insecticides in grain storage systems. However, the population genetic structure and gene flow of psocids has not been well categorized, which is helpful to plan appropriate strategies for the control of these pests.
The two species were sampled from 15 localities in China and analyzed for polymorphisms at the mitochondrial DNA (Cytb) and ITS (ITS1-5.8S-ITS2) regions. In total, 177 individual L. bostrychophila and 272 individual L. entomophila were analysed. Both Cytb and ITS sequences showed high genetic diversity for the two species with haplotype diversities ranged from 0.154 ± 0.126 to 1.000 ± 0.045, and significant population differentiation (mean F(ST) = 0.358 for L. bostrychophila; mean F(ST) = 0.336 for L. entomophila) was also detected among populations investigated. A Mantel test indicated that for both species there was no evidence for isolation-by-distance (IBD). The neutrality test and mismatch distribution statistics revealed that the two species might have undergone population expansions in the past.
Both L. bostrychophila and L. entomophila displayed high genetic diversity and widespread population genetic differentiation within and between populations. The significant population differentiation detected for both psocids may be mainly due to other factors, such as genetic drift, inbreeding or control practices, and less by geographic distance since an IBD effect was not found.

Full text

Page 1

Population Genetics of Two Asexually and Sexually
Reproducing Psocids Species Inferred by the Analysis of
Mitochondrial and Nuclear DNA Sequences
Dan-Dan Wei, Ming-Long Yuan, Bao-Jun Wang, An-Wei Zhou, Wei Dou, Jin-Jun Wang*
Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, People’s Republic of China
Abstract
Background: The psocids Liposcelis bostrychophila and L. entomophila (Psocoptera: Liposcelididae) are found throughout
the world and are often associated with humans, food stores and habitations. These insects have developed high levels of
resistance to various insecticides in grain storage systems. However, the population genetic structure and gene flow of
psocids has not been well categorized, which is helpful to plan appropriate strategies for the control of these pests.
Methodology/Principal Findings: The two species were sampled from 15 localities in China and analyzed for
polymorphisms at the mitochondrial DNA (Cytb) and ITS (ITS1-5.8S-ITS2) regions. In total, 177 individual L. bostrychophila
and 272 individual L. entomophila were analysed. Both Cytb and ITS sequences showed high genetic diversity for the two
species with haplotype diversities ranged from 0.15460.126 to 1.00060.045, and significant population differentiation
(mean FST=0.358 for L. bostrychophila; mean FST=0.336 for L. entomophila) was also detected among populations
investigated. A Mantel test indicated that for both species there was no evidence for isolation-by-distance (IBD). The
neutrality test and mismatch distribution statistics revealed that the two species might have undergone population
expansions in the past.
Conclusion: Both L. bostrychophila and L. entomophila displayed high genetic diversity and widespread population genetic
differentiation within and between populations. The significant population differentiation detected for both psocids may be
mainly due to other factors, such as genetic drift, inbreeding or control practices, and less by geographic distance since an
IBD effect was not found.
Citation: Wei D-D, Yuan M-L, Wang B-J, Zhou A-W, Dou W, et al. (2012) Population Genetics of Two Asexually and Sexually Reproducing Psocids Species Inferred
by the Analysis of Mitochondrial and Nuclear DNA Sequences. PLoS ONE 7(3): e33883. doi:10.1371/journal.pone.0033883
Editor: Keith A. Crandall, Brigham Young University, United States of America
Received November 10, 2011; Accepted February 19, 2012; Published March 27, 2012
Copyright: ? 2012 Wei et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was funded in part by the National Natural Sciences Foundation (30871631, 31000860), the Program for Innovative Research Team in
University (IRT0976), the Natural Science Foundation of Chongqing (CSTC, 2009BA1042), and the Specialized Research Fund for the Doctoral Program of Higher
Education (200806350009) of China. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: jjwang7008@yahoo.com
Introduction
Genetic variability is considered to be the foundation of
evolution, and it can be affected by a variety of factors, such as
mutation rates, effective population size, and gene flow [1]. The
current distribution of genetic variation within a species is caused
by its demographic history and a combination of the factors
previously mentioned. Gene flow is constraint on local genetic
differentiation and the adaptation between populations, and low
gene flow between populations can lead to genetic subdivision of
populations [2]. Decreased genetic diversity in a population can
cause a reduction in individual fitness through the expression of
inbreeding depression-like effects and further reduce the effective
population size (Ne) [3]. Levels of genetic diversity in natural
populations primarily reflect long-term processes in which a
balance is achieved between the generation of diversity by new
mutations and loss of diversity by drift. Food resources, dispersal
ability (active or passive), geographic isolation, exposure to
pesticides and other environmental factors can influence and
shape a pest’s population structure [4]. A thorough understanding
of genetic diversity and population structure on both large and
local geographic scales are crucial. Different evolutionary forces
and environmental factors can provide us with important
information about population dynamics and help to develop
effective pest management strategies.
Mitochondrial DNA (mtDNA), due to its accelerated rate of
evolution, simple maternally inherited, and lacking of recombina-
tion, has been used as a powerful and efficient way to study genetic
diversity in insect populations at both the inter- and intra-specific
levels, especially for cytochrome b (Cytb) gene [5,6]. The ribosomal
internal transcribed spacer (ITS) region, have been widely used for
population genetic studies [7,8] and species identification [9,10]
due to its highly conserved flanking regions (and so ease of use in
PCR) and rapid evolution rates. However, pseudogenic ITS
regions must be critically considered in population level and
phylogenetic studies as their utility is controversial and sometimes
they may cause erroneous analyses [11]. Fortunately, the presence
of conserved 5.8 S motifs and secondary structure can provide a
useful and swift tool for the pseudogenic ITS regions identification,
thus easily to exclude these pseudogenes from analyses [12].
PLoS ONE | www.plosone.org1March 2012 | Volume 7 | Issue 3 | e33883

Page 2

The small, wingless psocids, Liposcelis bostrychophila Badonnel and
L. entomophila (Enderlein) are found throughout the world and are
often associated with humans, food stores and habitations [13].
There is a growing awareness of the important pest status of
psocids due to the economic losses suffered by psocid infestation of
stored grains, as well as from their contamination of food and
commodities [13–15]. Recently, they have become a new risk for
global food security and safety [16]. L. bostrychophila and L.
entomophila are similar in morphology and often commix within the
same ecosystems. As the closest free living relatives of parasitic lice,
these two species can also transmit harmful microorganisms,
including fungi and bacteria [17,18]. Compared to L. bostrychophila,
L. entomophila has been found to be more commonly and more
widely distributed in grain storage systems in China. Unlike the
sexual reproduction undertaken by L. entomophila, L. bostrychophila is
an obligatory parthenogenetic species and displays considerable
adaptability to deal with local or temporary situations [19]. In L.
bostrychophila, parthenogenesis can maintain heterozygosity but
with the loss of variation [20]. Asexual reproduction is commonly
thought to be associated with low genetic diversity in animals (due
to lacking of recombination) and such organisms have generally
been regarded as evolutionary dead ends [21,22]. However, the
apparent lower genetic diversity of asexual animals compared to
closely relate sexual species has been called into question [23,24].
Paradoxically, against the background of its parthenogenetic
characteristics, L. bostrychophila also shows a considerable degree of
morphological and physiological variation both between and
within clones [19,25].
On the other hand, numerous studies have been conducted on
psocid physiology, biochemistry, and molecular biology in China
and worldwide [26–29]; however, the population genetic structure
of psocids has not been well established. Population genetic
variation for L. bostrychophila has been investigated using allozymes
[19], and randomly amplified polymorphic DNA (RAPDs) [30].
Microsatellite markers have been characterised for L. decolor and
cross-amplified in five other Liposcelis species of economic
importance [31] and these same microsatellites have been used
to investigate the genetic structure and gene flow of L. decolor in
Australia [32]. To our knowledge, no information is available on
the population genetic structure of L. entomophila. As little is known
of the population genetics of L. bostrychophila or L. entomophila in
China, we undertook a genetic study to investigate the genetic
diversity, the population genetic structure and population
demographic history of the two psocids using mitochondrial Cytb
and ITS sequences.
Materials and Methods
Ethics Statement
No specific permits were required for the described field studies,
and no specific permissions were required for these locations/
activities. We confirm that these locations are not privately-owned
or protected in any way and the field studies did not involve
endangered or protected species.
Sampling and DNA extraction
Approximately nine populations of L. bostrychophila and 11
populations of L. entomophila were sampled at grain storage facilities
from 15 locations in eight provinces of China from 2008 to 2010,
covering three Chinese Animal Fauna Regions [Southwest China
Region (SWCR), Central China Region (CCR), and South China
Region (SCR)] (Table 1 and 2; Figure 1). All specimens were
identified to species initially using morphological characteristics
[33] and confirmed by genetic methods using internal transcribed
spacer 2 (ITS2) rDNA genes after DNA extraction [10]. The
samples were stored at 280uC until DNA extraction. Genomic
DNA was extracted from single adult females using the protocols
described by Jia et al. (2009) [34] with slight modifications and all
DNA samples were stored at 220uC for later use.
Molecular data
The Cytb and ITS regions were amplified by PCR. A 485 bp
fragment of the mitochondrial Cytb gene was amplified using the
primer pairs CBF1 (59-TATGTACTACCATGAGGACAAA-
TATC-39) and CBR1 (59- ATTACACCTCCTAATTTATTAG-
GAAT-39) [35]; the complete ITS1-5.8 S-ITS2 (ITS) region
(,778 bp) was amplified with 18SF1 (59-CCGATTGAACGATT-
TAGTGAGGTCTT-39)and
CAGCGGGTATTCTCG-39) [10]. All PCR reactions were
carried out in a total volume of 50 ml, utilizing 60 ng of the
extracted DNA, 0.4 mM each primer, 100 mM each dNTP, 4 mM
Mg2+, 106PCR reaction buffer, ddH2O and 2 unit of Taq DNA
polymerase (5 U/ml, Takara, China-Japan Joint Company,
Dalian, China). PCR reactions were performed on a Bio-RAD
S1000TMThermal Cycler (Bio-Rad Laboratories, Hercules, CA)
and consisted of an initial denaturation step at 94uC for 4 min,
followed by 35 cycles of 94uC for 30 s, with annealing
temperatures of 46uC (Cytb) or 60uC (ITS) for 50 s and 72uC for
1 min, with a final 10 min extension at 72uC. PCR products were
visualized on 1.0% agarose gels under UV light and purified using
a gel band purification kit (Watson, Shanghai, China).
Cytb genes were directly sequenced using PCR purified products
from both forward and reverse PCR primers. For ITS sequences,
the purified products were ligated into pGEM-T Easy vectors
(Promega, Madison, WI) followed by ampicillin selection. All the
sequences were read on an ABI 3730 automated DNA sequencer
(Applied Biosystems, Foster city, CA, USA). Sequences were
assembled using Bioedit 7.0.9.0 [36] and manually corrected by
eye. The conserved motifs and secondary structure of 5.8 S rRNA
genes allowed us to identify putative ITS pseudogenes [12]. The
secondary structure of 5.8 S rRNA gene was reconstructed using
Mfold Server [37] and helices were numbered in accordance with
Wuyts et al. (2001) [38]. The secondary structure and three
28SR1(59-TGCTTAAATT-
Table 1. Sampling sites for psocids studied in this study.
Locality (Code)LatitudeLongitudeYear
Beibei, Chongqing (BB)29u499N106u259E2008
Dazu, Chongqing (DZ)29u429N105u439E2008
Mianyang, Sichuan (MY)31u289N104u389E2008
Guanghan, Sichuan (GH)30u589N 104u179E2009
Tongliang, Chongqing (TL) 29u509N 106u39E2009
Fuzhou, Fujian (FZ)26u49N 119u199E2010
Suizhou, Hubei (SZ)31u409N 113u219E2009
Loudi, Hunan (LD) 27u429N 111u599E2010
Huaibei, Anhui (HB)33u579N 116u489E2009
Shangqiu, Henan (SQ) 34u259N 115u399E2010
Xiangfan, Hubei (XF) 32u19N 112u89E2009
Wuhan, Hubei (WH) 32u369N 114u199E2008
Kaifeng, Henan (KF)34u479N 114u199E2008
Bozhou, Anhui (BZ)34u509N115u479E 2010
Wanning, Hainan (WN)18u479N110u229E2010
doi:10.1371/journal.pone.0033883.t001
Population Genetics of Psocids
PLoS ONE | www.plosone.org2 March 2012 | Volume 7 | Issue 3 | e33883

Page 3

conserved motifs (M1, M2, and M3) of 5.8 S gene were checked to
exclude the putative ITS pseudogenes from our ITS datasets. The
unique sequences of both genes were deposited into GenBank
under accessionnumbersJF419805–JF419883
JN828813–JN828948 (ITS).
(Cytb),and
Population genetic analyses
The number of haplotypes (n), haplotype diversities (h), and
nucleotide diversities (p) for the populations of each species were
estimated using the software DnaSP 5.10.00 [39]. Pairwise mismatch
distributions and test statistics [the test statistic of raggedness (rg) and
sum of square deviations (SSD)] were performed using Arlequin 3.1
[40] for all the sampling locations combined to find evidence of past
demographic expansions. According to coalescent theory, a popula-
tion at demographic equilibrium usually exhibits a multimodal
mismatch distribution, but is usually unimodal following a recent
population demographic or range expansion [41]. A significant SSD
value is considered as evidence of departure from the estimated
demographic model of a sudden population expansion and small rg
value represents a population which has experienced sudden
expansion [42]. Tajima’s D [43] and Fu’s FS [44], were also
calculated by Arlequin 3.1 to investigate the historical population
demographics and to test whether the sequences conformed to the
expectations of neutrality. Expectations of Fu’s Fs, Tajima’s D are
nearly zero in a constant-size population; significantly negative values
signify a sudden expansion in population size, whereas significantly
positive values indicate processes such as a population subdivision or
recent population bottleneck [44].
Pairwise FSTand gene flow were calculated using Arlequin 3.1 [40].
Two-level and three-level hierarchical analyses of molecular variance
(AMOVA) were conducted to evaluate the possible population genetic
structure of L. bostrychophila and L. entomophila using Arlequin 3.1 with
10,000 permutations. In addition, the correlation between genetic and
geographic distances was investigated with a partial Mantel test
executed by the web-based program Isolation By Distance Web
Service (IBDWS) version 1.52 [45]. The spatial analysis of molecular
variance (SAMOVA) was also employed to detect genetic barriers and
defines groups of populations that are geographically homogeneous
and maximally differentiated from each other, and was performed
using SAMOVA 1.0 [46] with 10,000 permutations.
Phylogenetic analyses and haplotype network
construction
Phylogenetic relationships between the Cytb haplotypes and ITS
haplotypes of the two psocids, L. bostrychophila and L. entomophila,
were performed with a Bayesian phylogenetic inference frame-
work and maximum-likelihood (ML) method, respectively. L.
decolor (JF440956 and JF742536), was used as an outgroup due to
its close relationship with L. bostrychophila and L. entomophila. First,
the coding region Cytb sequences were translated into amino acids
for confirmation in MEGA 5.01 [47] and examined for the
presence of stop codons and other indicators that they were
nuclear copies. Cytb and ITS haplotypes sequence alignments were
conducted with Clustal X Multiple Alignment [48] using the
default options. For Cytb sequences, transversions and transitions
versus sequence divergence were plotted, to evaluate the possibility
of sequence saturation in DAMBE 5.2.34 [49]. The best-fit model
of nucleotide substitution for mitochondrial and nuclear DNA
sequences was determined using the Akaike Information Criterion
in jModelTest 0.1.1 [50]. For Cytb haplotypes, three partitioned
Table 2. Summary statistics observed in L. bostrychophila and L. entomophila populations in this study.
SpeciesRegionCode
CytbITS
nHNh±SD
p±SDn HNh±SD
p±SD
L. bostrychophilaSWCR BB1440.39660.159 0.0009960.00044980.97260.064 0.0503460.00604
DZ 10 101.00060.045 0.0215660.00347870.96460.077 0.0400460.00796
MY1340.42360.164 0.0010760.0004612 110.98560.040 0.0346960.00338
GH----540.90060.161 0.0287260.00701
CCRFZ 1550.56260.143 0.0021660.00071----
SZ1320.15460.126 0.0007160.000581090.97860.054 0.0464760.00485
LD1470.80260.094 0.0245260.00407980.97260.064 0.0467760.00610
HB1380.80860.1130.0099560.00599106 0.77860.1370.0220260.00564
SQ1160.72760.1440.0029460.00090 1190.96460.051 0.0372760.00294
L. entomophilaSWCR BB1540.37160.1530.0012360.00060 1080.95660.0590.0296360.00446
TL 1640.44260.1450.0024460.001231080.93360.0770.0200760.00282
GH1450.50560.158 0.0027760.00111 1060.84460.103 0.0177160.01003
MY16 30.49260.117 0.0017960.0007512 100.97060.044 0.0162160.00351
CCR SZ1530.25760.142 0.0006260.0003511 100.98260.046 0.0180960.00312
XF1430.62660.104 0.0075460.001811060.77860.137 0.0081160.00180
WH1530.25760.142 0.0018560.001061580.73360.124 0.0046960.00108
KF 1650.53360.1420.0038560.001741160.72760.144 0.0142160.00857
BZ----10 60.86760.085 0.0374660.00461
FZ 1090.97860.054 0.0158160.002421290.90960.079 0.0290260.00618
SCRWN1780.72860.1140.0026860.00068 13 110.97460.0390.0298460.00575
n, number of individuals sequenced; HN, number of different haplotype; h, haplotype diversity; p, nucleotide diversity.
doi:10.1371/journal.pone.0033883.t002
Population Genetics of Psocids
PLoS ONE | www.plosone.org3 March 2012 | Volume 7 | Issue 3 | e33883

Page 4

Bayesian analyses were carried out and the best-fit model for 1st,
2nd, and 3rd codon position was HKY+I, TPM3uf+G, HKY+G,
respectively. The TPM3uf+I+G substitution model was utilized for
the ITS haplotypes data set. Phylogenetic trees for Cytb haplotypes
data set were reconstructed using MrBayes v3.12 [51]. Four
independent Markov chains were simultaneously run for seven
million generations (ngen=7,000,000) with a heating scheme
(temp=0.1). Trees were sampled each 100th generation (sample-
freq=100) and the first 20% of the generations were discarded as
burn-in and the remaining samples were used to compute the
consensus tree. Stationarity was considered reached when the
average standard deviation of split frequencies was below 0.01
[52]. Phylogenetic trees for ITS haplotypes data set were
conducted byPhyML 3.0(http://www.atgc-montpellier.fr/
phyml/) [53] using ML algorithms with 100 times bootstrap
replications.
Figure 1. Collection sites of L. bostrychophila and L. entomophila. Population codes correspond to those in Table 1. The populations of two
psocids were divided into three population groups based on Chinese animal fauna. The coloured regions indicate psocid collection provinces. SWCR,
coloured gray, includes two provinces; CCR, coloured orange, includes five provinces and SCR, coloured yellow, includes just one province.
doi:10.1371/journal.pone.0033883.g001
Population Genetics of Psocids
PLoS ONE | www.plosone.org4March 2012 | Volume 7 | Issue 3 | e33883

Page 5

Traditional phylogenetic methods assume that ancestral nodes
are no longer present in the data set and that the evolution of the
data set follows a bifurcating pattern. Intraspecific data sets usually
have features, including the persistence of ancestral haplotypes, the
existence of multiple descendant haplotypes and often low levels of
sequence variation [54], which do not fulfil the assumptions of
traditional phylogenetic methods. In the present study, median-
joining networks of haplotypes of each of the two genes were
constructed using Network 4.5.1.6 [55] to describe relationships
among unique haplotypes.
Results
Mitochondrial Cytb analyses
Sequence Variation and Genetic Diversity.
fragment of the Cytb gene was aligned and analyzed from 251
individuals (including 103 L. bostrychophila and 148 L. entomophila)
and no insertions or deletions were detected in any of the
sequences. The aligned sequences of 10 populations of L.
entomophila contained 55 segregating sites with 60 different
polymorphisms representing 28 singleton sites and 27 parsimony
informative sites. In comparison, the aligned sequences of eight
populations of L. bostrychophila had 76 segregating sites with 78
different polymorphisms representing 37 singleton sites and 39
parsimony informative sites.
In total, 39 haplotypes were detected in L. entomophila populations
and 40 haplotypes in L. bostrychophila populations (Table 2). Among
L. entomophila haplotypes, LeH1, LeH3, LeH10, and LeH13 were
shared by several populations, and the highest haplotype diversity
was 0.978 (FZ) and the lowest was 0.257 (SZ, WH) (Table 2). The
overall population haplotype diversity for L. entomophila was 0.853.
Haplotypes LbH1, LbH6, LbH14 and LbH35 were also shared in
some of the L. bostrychophila populations. The haplotype diversity of
all the L. bostrychophila populations was 0.875, and the highest was
the DZ population (1.000) and the lowest was the SZ population
(0.154) (Table 2). The haplotype diversity was not significantly
different between these two psocid species (F1,
P=0.451), and the nucleotide diversity of L. bostrychophila
(p=0.0280160.00117) was higher than that of L. entomophila
(p=0.0077860.00071), but the difference was not significant
(F1, 16=1.281, P=0.274). However, the two clades (Clade Lb1
and Clade Lb2) (Figure 2A) were considerably divergent within L.
bostrychophila, which may affect the results of population genetic
diversity estimates.We compared the populationgenetic diversity of
thesetwopsocid speciesatthesame geographicregion scale. Forthe
SWCR, the haplotype diversity of L. bostrychophila was 0.685, which
wasnotsignificantlylower
(h=0.76060.033) (F1, 5=0.832, P=0.404). However, the nucleo-
tide diversity of L. bostrychophila (p=0.0087560.00341) was not
significantly higherthanthat
(p=0.0036060.00185) (F1, 5=1.027, P=0.357). For the CCR,
both the haplotype and nucleotide diversities of L. bostrychophila
(h=0.85060.036; p=0.0115160.00322) were higher than those of
L. entomophila (h=0.79560.035; p=0.0072060.00111), but not
significant (F1, 8=0.196, P=0.670; F1, 8=0.167, P=0.693).
Phylogenetic analyses.
Substitution saturation of sequences
was tested using the software DAMBE 5.0.59. A lack of evidence
of saturation means that the diversity was not underestimated and
that the sequences were suitable for phylogenetic reconstruction.
Therefore, a phylogenetic tree that used three partitioned
Bayesian analyses showed that all haplotypes corresponding to L.
bostrychophila formed to a single well-supported clade designated as
clade Lb, while all the haplotypes corresponding to L. entomophila
formed another single well-supported clade designated as clade Le
A 433 bp
16=0.598,
thanthatof
L.entomophila
of
L.entomophila
either
(Figure 2A). Clade Lb could be subdivided into two well-supported
clades (Clade Lb1 and Clade Lb2). Clade Le could also be
subdivided into two clades (Clade Le1 and Clade Le2) with low
Bayesian posterior probabilities (0.52 and 0.52) (Figure 2A). Clade
Lb1 contained five populations and if the haplotypes LbH19,
LbH32, LbH33, and LbH34 were excluded, it would correspond
with the SWCR (Figure 2A). Clade Lb2 contained five populations
which were all included in the CCR. For Clade Le, two clusters
were not arranged according to relatively geographic regions.
Clade Le1 consisted of six haplotypes (LeH18, LeH23, LeH28,
LeH29, LeH30, and LeH31) from two populations, XF and FZ,
which were included in the CCR regions. Clade Le2 was admixed
in all 10 populations and had no geographical specificity
(Figure 2A).
The median-joining network among haplotypes of the L.
bostrychophila populations, representing genealogical relationships
is shown in Figure 2B. The networks of related haplotypes were
almost clustered into two areas corresponding to SWCR and
CCR. Because LbH6 was shared by three populations belonging
to the two regions, the two areas of the network were not distinct.
The L. bostrychophila haplotype networks were very consistent with
the Bayesian phylogenetic tree Clade Lb. For L. entomophila, the
network suggested little or no association between haplotypes and
geography (Figure 2C) which was consistent with the Bayesian
phylogenetic tree. The haplotypes of the same population/region
did not cluster together. The highest frequency haplotype was
LeH10, followed by LeH3 and LeH13, which consisted of 37, 36,
and 23 individuals, respectively, and they occupied a central
position in the network (Figure 2C).
When the Bayesian tree and median-joining network for
haplotypes were combined, the 40 haplotypes of L. bostrychophila
were divided into two clades that coincided with our predefined
regions. The 39 haplotypes of L. entomophila were also divided into
two clades with low Bayesian posterior probabilities; however, no
population-specific clustering pattern was revealed by the Bayesian
analysis, buttheWN population clusteredinthehaplotypenetwork.
Populationstructureand
analyses.
AMOVA results showed that there was significant
genetic differentiation of L. bostrychophila and L. entomophila
populations at various hierarchical levels (among regions, among
populations within regions, and within populations) (Table 3). For
L. bostrychophila, high genetic structure was found (WST=0.751,
P,0.001). AMOVA showed that 75.14% of the variation was
among populations and only 24.86% was partitioned within
populations. When performing a three-level AMOVA to test for
structure between SWCR and CCR, we also detected a high
genetic structure (WCT=0.672, P,0.05) between these two groups
with a large portion of total genetic structure (67.15% was
partitioned among groups). A small portion of the total genetic
structure (15.88%) was apportioned among populations and was
also significant within a region (WSC=0.484, P,0.001). For L.
entomophila, a two-level AMOVA test for structure among
populationsshowedhigh genetic
P,0.001) with slightly more of the total genetic structure
apportioned among populations (56.65%). When performing a
three-level AMOVA to test for genetic structure among groups, we
foundthat populationgenetic
(WCT=0.368, P,0.05) with a little more portion (36.84%) of
total genetic structure. Thus, both of these two species had
significant geographic structure, but compared to L. entomophila, L.
bostrychophila had more significant geographic structure. For
SAMOVA analysis, the K value increased from 2 to 5 for L.
bostrychophila and L. entomophila, respectively. The FCT was
significant and highest at 5 groups for both species (Table S1).
Demographichistory
structure(WST=0.566,
structure wassignificant
Population Genetics of Psocids
PLoS ONE | www.plosone.org5 March 2012 | Volume 7 | Issue 3 | e33883