historical vicariance and male-mediated gene ﬂow in the...

Molecular Ecology (2009) 18, 3714–3729 doi: 10.1111/j.1365-294X.2009.04310.x

Historical vicariance and male-mediated gene flow inthe toad-headed lizards Phrynocephalus przewalskii

JOHN URQUHART,* YUEZHAO WANG† and JINZHONG FU*

*Department of Integrative Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada, †Chengdu Institute of Biology,

Chinese Academy of Sciences, Chengdu, Sichuan 610041, China

Corresponde

E-mail: jfu@u

Abstract

Using mitochondrial and microsatellite DNA data and a population genetic approach, we

tested male-mediated gene flow in the toad-headed lizards Phrynocephalus przewalskii.The mitochondrial DNA (ND2 gene), on the one hand, revealed two major lineages and a

strong population genetic structure (FST = 0.692; FST¢ = 0.995). The pairwise differences

between the two lineages ranged from 2.1% to 6.4% and the geographical division of the

two lineages coincided with a mountain chain consisting of the Helan and Yin

Mountains, suggesting a historical vicariant pattern. On the other hand, the nuclear

microsatellite DNA revealed a significant but small population genetic structure

(FST = 0.017; FST¢ = 0.372). The pairwise FST among the nine populations examined with

seven microsatellite DNA loci ranged from 0.0062 to 0.0266; the assignment test failed to

detect any naturally occurring population clusters. Furthermore, the populations

demonstrated a weak isolation by distance and a northeast to southwest clinal variation,

rather than a vicariant pattern. A historical vicariant event followed by male-mediated

gene flow appears to be the best explanation for the data. Approximately 2–5 Ma,

climatic change may have created an uninhabitable zone along the Helan-Yin mountain

chain and initiated the divergence between the two mitochondrial lineages. With further

climatic changes, males were able to disperse across the mountain chain, causing

sufficient gene flow that eventually erased the vicariant pattern and drastically reduced

the population genetic structure, while females remained philopatric and maintained the

mitochondrial DNA (mtDNA) divergence. Although polygyny mating system and female

philopatry may partially contribute to the reduced movement of females, other

hypotheses, such as female intrasexual aggression, should also be explored.

Keywords: male-mediated gene flow, microsatellite DNA, mtDNA, Phrynocephalus, population

genetic structure, vicariance

Received 12 March 2009; revision received 24 June 2009; accepted 29 June 2009

Introduction

Sex-biased dispersal is a common phenomenon in

mammals and birds; whereas male-biased dispersal pre-

vails in mammals, female-biased dispersal dominates in

birds (Greenwood 1980; Wolff 1994; Clarke et al. 1997).

Several nonmutually exclusive hypotheses have been

proposed and tested, including competition between

related females for resources, competition between

related males for mates, different fecundity costs of

nce: Jinzhong Fu, Fax: 1-519-767 1656;

oguelph.ca

dispersal between sexes, avoidance of inbreeding and

kin competition (Greenwood 1980; Dobson 1982; Pusey

1987; Perrin & Mazalov 2000; Devillard et al. 2004).

Most of these hypotheses linked the biased dispersal to

a species’ mating system: male-biased dispersal with

polygyny and female-biased dispersal with monogamy

(e.g. Greenwood 1980). However, these hypotheses are

primarily derived from studies of birds and mammals,

which are endothermic and generally have extensive

parental care. Whether ectothermic species without

extensive parental care, which comprise the majority of

animal species, follow the same rules is largely unex-

plored. Ectotherms have very different energy allocation

� 2009 Blackwell Publishing Ltd

MALE-MED IATED GENE FLOW IN PHRYNOCEPHALUS 3 71 5

from endotherms, and may have very different fecun-

dity costs of dispersal. Furthermore, parental care

increases the parental investment, which is a leading

factor in determining sexual selection. Species without

parental care probably have different intra- and inter-

sexual competition patterns. So far, studies on ecto-

therms are limited and revealed patterns are equivocal

(Johansson et al. 2008 and reference therein).

Besides birds and mammals, lizards as a group are

probably the most commonly used model organisms for

ecological and evolutionary studies. They are ecto-

therms and generally lack parental care. Extensive work

has been conducted on lizard foraging mode, mating

behaviour and community structure (Vitt & Pianka

1994; Reilly et al. 2007). A few cases of sex-biased dis-

persals have been reported in lizards. For example,

using mark and re-capture, Clobert et al. (1994)

reported male-biased dispersals in the common lizard

(Lacerta vivipara) and Olsson et al. (1996) found female-

biased dispersal in sand lizards (Lacerta agilis). Most

recently, using population genetic methods, Stenson

et al. (2002), Johansson et al. (2008) and Ujvari et al.

(2008) reported male-biased dispersal in the Dominican

anole (Anolis oculatus), the Caribbean lizard (Anolis ro-

quet) and the Frillneck lizard (Chlamydosaurus kingii),

respectively. With a wealth of background knowledge,

lizards provide us the best opportunity to test the

hypotheses derived from mammals and birds, and per-

haps to generate new ones for ectothermic species.

Due to difficulties associated with directly measuring

the dispersal rates by tracking individual animals, such

as mark and re-capture (e.g. Baker et al. 1995; Koenig

et al. 1996; Berry et al. 2004), ‘indirect’ methods to infer

sex-biased dispersal from population genetic tools pres-

ent attractive alternatives (Goudet et al. 2002; Prugnolle

& de Meeus 2002). In addition, sex-biased dispersal

may not necessarily lead to sex-biased gene flow, which

makes genetic-based methods more appealing if the

research focus is on the genetic consequence of the dis-

persal, not the dispersal itself (Riley et al. 2006). Two

groups of genetic methods have been established. One

group uses bi-parentally inherited markers and com-

pares differences in genetic structure between males

and females, and the other group compares markers

with different modes of inheritance (Prugnolle & de

Meeus 2002). Interestingly, of the two most recent stud-

ies on lizards, each used a different population genetic

method (Johansson et al. 2008; Ujvari et al. 2008).

Toad-headed lizards of the genus Phrynocephalus are

common species in central Asian desert. Similar to other

desert lizards, they can reach very high population den-

sity, which makes them excellent model systems for

ecological and evolutionary studies. One species,

Phrynocephalus przewalskii, has a large distribution range


in northern China and the adjacent Mongolia, and has

been subjected to extensive systematic and ecological

studies (e.g. Liu et al. 1993; Xu & Yang 1993, 1995).

Juveniles of this species may reach sexual maturity

within a year from birth and a large number of individ-

uals may reach five years of age (Xu & Yang 1993; Zhao

et al. 1999). Recently, Gozdzik & Fu (2009) compared

their morphology as well as their mitochondrial DNA

(mtDNA) data. Although two deeply diverged mtDNA

lineages were found, a principle component analysis of

24 morphological characters revealed no significant dif-

ference between the two lineages. The observed contra-

diction between the mtDNA and the morphological

data provides an opportunity for further investigating

the potential male-mediated gene flow in this species.

In this study, we used an ‘indirect’ population genetic

approach to examine the potential male-mediated gene

flow in the species Phrynocephalus przewalskii. Of the

two groups of population genetic methods, Goudet

et al. (2002) found that methods using only bi-paren-

tally inherited markers and comparing female and male

differences in genetic structure were very conservative

and were limited to animals where dispersal occurs

mostly at the juvenile stage. Considering its long adult

life, this group of methods may not be suitable for

P. przewalskii. Therefore, we used both maternally

inherited mtDNA and bi-parentally inherited microsat-

ellite DNA data to detect potential male-biased gene

flow. If gene flow in P. przewalskii is dominantly male-

mediated, we would expect mtDNA data to show a

strong genetic structure and the microsatellite DNA

data to demonstrate a high level of gene flow across

populations.

Materials and methods

Sampling

Samples were collected throughout the range of P. prze-

walskii, including the Gobi, Tengger and Ordos deserts

(Fig. 1). A total of 694 specimens were collected from

55 sites in 2002, 2005 and 2006. The most distant sites

were separated by approximately 1000 km. To maxi-

mize the sensitivity of detecting genetic structure, we

used two different sampling strategies for mtDNA and

microsatellite DNA. For mtDNA, we sequenced sam-

ples from all 55 sites but only a few samples (1–21)

from each site. The microsatellite DNA analysis requires

large sample sizes from each site, so we examined nine

sites with sample sizes of 38–48. The nine populations

were chosen based on the results of Gozdzik & Fu

(2009); representatives from both mtDNA lineages and

the overlap zone were sampled (Fig. 1). All samples

used for microsatellite DNA analysis were collected

Fig. 1 Distribution map and sampling

sites of Phrynocephalus przewalskii. The

black, dashed line outlines the species

distribution. The red, dashed line indi-

cates the division between the two mito-

chondrial lineages. Solid circle represents

population with all members from mito-

chondrial clade I and empty circles rep-

resent populations with all members

from mitochondrial clade II. Half solid

circles represent mixed populations.

Populations 5, 12, 20, 29, 31, 32, 35, 50

and 54 (in bold) were subjected to micro-

satellite DNA analysis.

3716 J . URQUHART, Y . WANG and J . FU

between 2005 and 2006. We assumed that annual varia-

tion in population genetic makeup was minimal. Sam-

pling site and sample size information are presented in

Appendix I and depicted in Fig. 1. Six additional

sequences from three closely related species, P. guttatus,

P. versicolor and an undescribed species (as of Wang &

Fu 2004), were obtained from Wang & Fu (2004), which

were used as outgroup taxa for the phylogenetic analy-

sis of the mtDNA.

Laboratory protocols

Genomic DNA was extracted from muscle or liver tis-

sue using a standard phenol–chloroform protocol

(Palumbi 1996). Extracted DNA was re-suspended

in 200 ll TE buffer (10 mM Tris-HCl, pH 8.0, 1 mM

EDTA).

An 850 base pair (bp) fragment of the ND2 gene from

the mitochondrial genome was targeted for sequencing

with primers L4447 (5¢-AAGCAGTTGGGCCCATGCCC-

CAAAAACGG-3¢) and H5622 (5¢-TATTTTAATTAAA

ATATCTGAGTTGCA-3¢; Wang & Fu 2004). Standard

polymerase chain reactions (PCR) were performed with

annealing temperature optimized at 50 �C. PCR prod-

ucts were purified using the QIAquick PCR purification

kits with the manufacturer’s protocol (Qiagen). DNA

sequencing was conducted with BigDye terminator

sequencing chemistry (Applied Biosystems) in conjunc-

tion with an ABI 3730. Sequences were checked and

edited with Sequencher version 4.5 (Genecode Corp)

and imported into MacClade version 4.08 (Maddison &

Maddison 2003), where they were aligned.

Twelve polymorphic microsatellite DNA loci from

Urquhart et al. (2005) were examined. PCR optimization

generally followed the procedures described by Urqu-

hart et al. (2005). One primer pair was modified; the

reverse primer of locus Phry75 was changed to 5¢-AG-

TTGTAAAAGGTCCAGGTGCTC-3¢ to reduce the length

of the PCR products. One primer from each pair was

labelled with tetrachloro-6-carboxy-fluorescein (TET).

The labelled PCR products and TAMRA� size standard

marker (GeneScan� 350; Applied Biosystems) were elec-

trophoresed on 6% denaturing polyacrylamide gels.

The gels were then visualized on a FMBIO II laser scan-

ner (Hitachi) to determine the lengths of the microsatel-

lite DNA fragments.

mtDNA analysis

A phylogenetic tree was used to represent the diver-

gence patterns among the mtDNA and a Bayesian infer-

ence with computer program MrBayes version 3.2

(Ronquist & Huelsenbeck 2003) was employed. The

best-fit model (GTR+I+G) was selected by hLRT in

MrModelTest version 2.1 (Nylander 2004) and a flat

‘prior’ setting was used. Four Markov chains were exe-

cuted and the data set was run for ten million genera-

tions to allow adequate time for convergence. Tracer

version 1.4 (Rambaut & Drummond 2007) was used to

plot the resulting likelihood values and to determine

when the Markov chains reached convergence. Trees

were sampled every 500 generations and we used the

last 10 000 sample trees to estimate the consensus tree

and the Bayesian posterior probabilities. All other sam-

pled trees were designated as ‘burn-in’. Two separate

runs, which included a total of four independent tree

searches, were conducted and the resulting trees were

compared and pooled.



An analysis of molecular variance (AMOVA) using Arle-

quin version 3.1 (Excoffier et al. 2005) was conducted.

Populations were divided into two groups following

the designation of the phylogenetic tree and their geo-

graphical distribution. Permutation tests were per-

formed at three hierarchical levels: among groups,

among sites within groups and among individuals

within sites.

Pairwise percentage differences (uncorrected p-dis-

tance) were used to represent the magnitude of the

mtDNA divergence. The distances were calculated

using PAUP* version b10 (Swofford 2002). A divergence

time estimate was also carried out. Studies of ND2 gene

divergence in other agamid lizards (genus Laudakia)

provided an estimate of approximately 0.65% change

per lineage per million years (Macey et al. 1998). We

used this clock rate to estimate approximate divergence

time. We did not pursue a more elaborated test because

of the lack of appropriate calibration points.

Microsatellite DNA analysis

All loci were screened using Micro-Checker version 2.2

(Van Oosterhout et al. 2004) for large allele dropout

and the presence of null alleles. All loci were tested for

linkage equilibrium and Hardy–Weinberg equilibrium

(HWE) using Arlequin.

Pairwise FST was used to evaluate the degree of pop-

ulation subdivision. Weir & Cockerham’s (1984) h was

calculated using Arlequin. As an estimator of FST, hprobably has a smaller variance than Slatkin’s (1995)

RST when the number of loci is small (Balloux & Gou-

det 2002), and it does not require that all loci follow a

single stepwise mutation model. Significance tests for

pairwise h were performed by permutation of multi-

locus genotype data among pairs of samples. A total of

10 000 permutations were performed to allow for the

significance at the 1% nominal level after Bonferroni

corrections. Exact tests of population differentiation

based on allele frequencies (Raymond & Rousset 1995)

were also conducted with Arlequin. A total of 100 000

Markov chain steps and a burn-in of 10 000 were used.

A locus by locus analysis of molecular variance

(AMOVA) using Arlequin was conducted. The nine popu-

lations were divided into two groups, following the

designation of the mtDNA. Permutation tests with

10 000 replicates were performed at four hierarchical

levels: among groups, among sites within groups,

among individuals within sites and within individuals.

Patterns of isolation by distance (IBD) were evaluated

by examining the correlation between Rousset’s (1997)

FST ⁄ (1)FST) and geographical distance. A Mantel test

was conducted using Genepop web version (Raymond

& Rousset 2003). The linear distances between sampling


sites were estimated from their coordinates using a web

service at http://jan.ucc.nau.edu/~cvm/latlongdist.

html. For testing of statistical significance, 10 000 per-

mutations in Mantel tests were used to test the null

hypothesis that genetic distance is not associated with

geographical distance.

An assignment test was also applied to the data with

the computer program Structure version 2.2 (Pritchard

et al. 2007), which does not assume a drift-migration

equilibrium. The admixture model was used and the

number of clusters (k) was varied from 1 to 6. For each

k, 50 runs were executed with 100 000 iterations after

100 000 iterations as ‘burn-in’. An average over the ten

highest likelihood values [lnP(D)] was obtained for each

k. The lnP(D) values were plotted against the k value to

determine the best k.

Comparison between mtDNA and microsatellite DNA

As a result of the different modes of inheritance of

mtDNA (haploid and uniparental) and microsatellite

DNA (diploid and bi-parental), a fourfold greater level

of genetic structure in the mtDNA is expected (e.g. Pa-

lumbi et al. 2001; but see Hudson & Turelli 2003). The

ratio of mtDNA divergence to microsatellite DNA

divergence should be approximately four, all else being

equal. Crease et al. (1990) presented a formula for

calculating the ratio of mtDNA divergence to micro-

satellite DNA divergence (k). The parameter

k = ln(1)N) ⁄ ln(1)G), where N is the genetic divergence

in mtDNA genes and G is the genetic divergence in

microsatellite DNA. We used FST¢ (Meirmans 2006), a

standardized FST, to represent the genetic divergence

of the markers. Thus, k = ln[1) FST¢(mtDNA)] ⁄ ln[1)FST¢(microsatelliteDNA)]. FST¢ is derived from AMOVA and

standardized (FST¢ = FST ⁄ FST(max); Meirmans 2006). FST¢for microsatellite DNA was calculated with GenoDive

version 2.0b14 (Meirmans 2009) and FST¢ for mtDNA

was calculated with Arlequin, following the recommen-

dation of Meirmans (2006).

Results

mtDNA sequence data

A total of 370 sequences of P. przewalskii were gathered,

including 154 new sequences from this study. The other

216 sequences of P. przewalskii and 6 sequences of three

outgroup taxa were from two previous studies (Wang

& Fu 2004; Gozdzik & Fu 2009). All new sequences are

deposited in GenBank (accession no. GQ302988–

GQ303142). A total of 850 bp of DNA sequences of the

ND2 gene were confidently resolved and 176 haplo-

types were identified, including 6 outgroup taxa. Of the


850 nucleotide sites, 196 were variable across the

ingroup members.

Figure 2 presents the Bayesian tree along with the

Bayesian posterior probabilities. The tree resolved two

major clades; whereas clade I spanned from the south-

west to the northeast of the distribution, clade II was

mostly restricted to the Ordos Desert. The geographi-

cal division of the two clades coincided with a moun-

tain chain including the Helan and Yin Mountains

(Fig. 1). At the contact zone, several populations had

haplotypes from both clades (e.g. 11, 12, 32–37 and

39–42; Fig. 1).

There was a clear population genetic structure within

both clades. Within clade I, there were several groups.

At the top, clade (Ia+Ib) included haplotypes from sites

1–11, 13–15 and 17–20 (Fig. 2). All members of these

populations were in this clade except one specimen of

population 11, which was grouped in clade II, and sev-

eral specimens of population 20. The phylogenetic posi-

tion of each haplotype displayed a clear association

with its geographical location. At the base of the clade,

all haplotypes were from the western sites (17–20) and

the eastern most populations were all located at the tip

of the clade. An accelerated rate of molecular evolution

was also observed (Fig. 2). At the base of clade I, there

were H105 from population 34 and H104 from popula-

tion 42. Both populations were located at the contact

zone, and most of their co-habitants were from clade II.

The last group, Ic, was a paraphyletic assemblage com-

prising most samples from the southwestern popula-

tions. Within this group, haplotypes from different

populations were intertwined, and had no clear associa-

tion with their geographical locations.

Within clade II, there were several deeply diverged

clades. Some of the clades demonstrated relationships

with the geographical locations of the haplotypes. For

example, samples in clade IId (exclusively populations

42–44) were restricted to the northern end of the Helan

Mountains.

For AMOVA, populations were divided into two

groups, following the division of the Helan and Yin

Mountains and the division of the mtDNA gene tree.

Group 1 included populations from clade I (1–11, 13–

15, 17–31 and 38–41), and group 2 included populations

from clade II (12, 16, 32–37 and 42–55). Several popula-

tions from the contact zone had haplotypes from both

clades I and II (e.g. 32–37, 39–42; Fig. 1), and the group-

ing of these populations was determined by their

majority. All three levels were statistically significant,

and the largest component of variation was among the

groups (46.56%; Table 1). This is not surprising because

the grouping was based on the divergence patterns

revealed by the tree. The among-populations-within-

groups and within-populations components each

accounted for approximately half of the remaining vari-

ation (27.41% and 26.02%).

Pairwise differences between clade I and II ranged

from 2.1% to 6.4%, while the majority was 4–5%.

Applying the molecular clock hypothesis and Macey

et al.’s (1998) calibration that 0.65% sequence diver-

gence is expected to accumulate over 1 Myr within each

lineage (1.3% between lineages), the divergence

between clade I and II is found to have occurred

approximately 2–5 Ma, placing this divergence in the

Pliocene.

Microsatellite DNA data

Of the 12 loci published in Urquhart et al. (2005), only

seven were used in the analysis. The other five loci suf-

fered from either inconsistent PCR amplification after

optimization, or significant large allele dropout or pres-

ence of null alleles detected by Micro-Checker.

A majority of the HWE tests significantly deviated

from expectation. In all cases, there was significant het-

erozygote deficiency (Table 2). This deficiency did not

appear to correlate with the location of contact zones

between mtDNA clades. While some linkage disequilib-

rium tests were significant, there were no two loci that

were consistently associated across populations. There-

fore, all loci were included in the subsequent analyses.

Other indices, the average number of alleles (A), the

observed heterozygosity (HO) and the expected hetero-

zygosity (HE) across populations for each locus, are also

presented in Table 2.

Pairwise FST values are presented in Table 3. The val-

ues varied from 0.0062 to 0.0266 and all except one

were statistically significant after Bonferroni correction

for multiple comparisons (P < 0.01). The low FST values

indicated that there was a small population genetic

structure among the populations, despite geographical

distances between some of the populations being

1000 km. Exact tests of population differentiation based

on haplotype frequencies showed nondifferentiation

both globally and pairwisely (P = 1.000). This was con-

cordant with the observation that not a single unique

allele existed in any populations.

The isolation by distance test revealed a significant

but weak correlation (R2 = 0.1672, PMantel = 0.0307). This

was not surprising considering the low FST values. A

linear correlation best-fit line is presented in Fig. 3.

Following the mtDNA data, the nine populations

examined for microsatellite DNA were also divided into

two groups. Group 1 included populations 5, 20, 29 and

31; group 2 included populations 12, 32, 35, 50 and 54.

The AMOVA results of the microsatellite DNA data are

presented in Table 1. Most of the variation was allo-

cated to the within-individual component (81.7%),


H6H7H8H9H10

H5H4

H3

H1H2

H11H12

H13H14

H15H16

H17H18

H19H20

H21H22

H23H24

H25H26H27

H28H29

H30H31

H32H33

H34H35

H36H37H38

H39H40

H41H42H43

H44H45

H46H47H48

H49H50

H51H52

H53H54

H55H56

H57H58

H59H60

H61H62H63

H64H65

H66H67

H68H69

H70H71

H72H73

H74H75

H76H77

H78H79H80

H81H82

H83H84

H85H86

H87H88H89

H90H91H92

H93H94

H95H96

H97H98

H99H100H101

H102H103

H104H105

0.001 substitutions/site

100

100

100

100

100

98

72

Gro

up

Ia

Group Ibpopulations 17–20

Gro

up

Ic

populations33,35

populations20,21,22,23,24

populations 32

populations30,31

populations 27,28

populations20,21,24,25,27,29,30,31,32,36,37,39,40,41

populations24,25

populations12,24,25,26,29,31,42

pop. 42 Group Idpop. 34 Group Ie

86

98

100

94

94

95

94

100

97

po

pul

atio

ns 1

3–

15

po

pul

atio

ns 1

–1

1

Ic Id

H106H107

H108H109

H110H111

H112H113

H114H115

H116H117

H118H119

H120H121

H122H123H124

H125H126

H127H128H129

H130H131

H132H133

H134H135

H136H137H138H139H140

H141H142

H143H144

H145H146

H147H148

H149H150

H151H152

H153H154

H155H156

H157H158

H159H160

H161H162

H163H164

H165H166

H167H168

H169H170

P. versicolor -1P. versicolor -2

P. sp. -1P. sp. -2

Phrynocephalus guttatus -1Phrynocephalus guttatus -2

IbIa

100

100

100100

98

100

98

99

100

100

100

96

po

pul

atio

ns

32

–4

1,4

3–

46

,48

–5

1p

op

ulat

ions

1

2,1

6,4

5,4

6,4

8,5

1,5

3,5

4,5

5

po

ps.

4

5–

48

,52

,5

4,5

5p

op

ulat

ions

4

2,4

3,4

4

Ie

Gro

up

IIa

Gro

up

IIb

Gro

up

IIc

Gro

up

IId

Clade I

Clade II

100

Fig. 2 A gene tree derived from mtDNA sequence data using Bayesian inference. Numbers above the branches are Bayesian poster-

ior probabilities. Taxa are haplotypes; all haplotype designations are listed in Appendix I.



Table 1 Results of the analysis of molecular variance (AMOVA)

for microsatellite DNA data (A) and mitochondrial DNA

(ND2) sequence data (B)

Source of variation

Sum of

squares

Variance

components

Percentage

variation

A: Microsatellite DNA

Among groups 8.579 )0.0031 )0.03

Among populations

within groups

62.154 0.05762 1.70*

Among individuals

within populations

1499.481 0.56358 16.59*

Within individuals 1093.000 2.77743 81.75*

Total 2663.214 3.39750

B: Mitochondrial DNA

Among groups 1183.725 6.29099 46.56*

Among populations

within groups

1476.732 3.70409 27.41*

Among individuals

within populations

1107.643 3.51633 26.02*

Total 3768.100 13.51141

*P < 0.01.


while the among-groups component was not statisti-

cally significant, which strongly contrasted the mtDNA

results (Table 1).

Figure 4 presents the plot between the resulting like-

lihood values [lnP(D)] and numbers of population clus-

ters [k] from the Structure analysis. As expected, the

lnP(D) values increased along with the increase in the k

values. If the Helan-Yin mountain chain formed a sig-

nificant genetic barrier to the nuclear gene flow, we

would expect two naturally occurring population clus-

ters; therefore, we would expect the lnP(D) to approach

a plateau when k = 2. However, the lnP(D) values

showed no sign of stationarity even when k = 6, sug-

gesting no distinct population clusters. The high lnP(D)

values when k = 6 were probably a reflection of a more

subtle population structure. From the bar plot of vari-

ous k values (Fig. 5), the majority of individuals

revealed low probabilities of being assigned to any par-

ticular clusters. Only individuals from population 5 at

the very northeast demonstrated high probabilities of

being assigned to a cluster. Population 20 at the very

southwest also demonstrated a similar pattern, although

to a lesser degree. Overall, there appeared to be a clinal

variation from northeast to southwest. This was particu-

larly apparent when k = 2 (Fig. 5).

Compared with mtDNA, the nuclear microsatellite

DNA has much less population genetic structure. The

FST of the mtDNA was 0.692 and the standardized FST¢was 0.995; the FST of microsatellite DNA was 0.017 and

standardized FST¢ was 0.372. Therefore, the k = ln[1)FST¢(mtDNA)] ⁄ ln[1) FST¢(microsatelliteDNA)] = 11. This value

greatly exceeded the ratio of 4, suggesting that these

differences were not caused purely by their mode of

inheritance.

Discussion

All analyses indicate well-structured mitochondrial

DNA and minimum structure of nuclear loci among

populations of Phrynocephalus przewalskii. Considering

all evidences, a historical vicariant event followed by

male-mediated gene flow appears to be the best expla-

nation of the data.

A vicariant pattern and strong population geneticstructure of mtDNA

There are clearly two mtDNA lineages within P. prze-

walskii (clades I and II), and the geographical division

of the two lineages coincides with the location of the

Helan-Yin mountain chain (Fig. 1). The Yin Mountains

run west-east in the middle of Inner Mongolia and rise

to elevations of 1500–2200 m, with many low-lying

areas with salt pans and small ponds (Zhao et al. 1990).

This mountain chain creates a major climatic division in

this region. The Helan Mountain range lies to the west

of the Yellow River, where the river flows north across

the Yinchuan Plain and reaches a maximum elevation

of 3556 m, extending over 180 km north of the Tibetan

Plateau (Zhao et al. 1990). Both mountains experienced

episodic uplifts and erosions since their formation.

Despite the coincidence of locations, the formation of

these mountains is unlikely the cause of this vicariant

pattern. The Yin Mountains were first formed during

the late Palaeozoic 386–257 Ma and the Helan Moun-

tains were first formed during the Mesozoic 205–

135 Ma (Zhu 1984). Their formation well-preceded the

divergence of the mtDNA lineages, estimated to have

occurred 2–5 Ma. The Yellow River does not appear to

have any significant impact on the distribution of this

species. Seasonal change of water flow and frequent

historical changes of routes may all contribute to this

observation.

We postulate that Pliocene climatic changes might

have been a major factor generating the divergence

between the two mitochondrial lineages. The time of

the divergence (2–5 Ma) concurs with the time of

major geomorphological changes around the Tibetan

Plateau (Liu et al. 1998). Our study region has repeat-

edly experienced a dry climate and the landscape has

changed from subtropical to desert conditions multiple

times (Liu et al. 1998). The Yin and Helan mountain

chain probably has been a major climatic barrier of the

region. For example, presently southeast of the Helan-

Yin mountain chain is much wetter than the northwest


Table 2 Allelic diversity at seven microsatellite DNA loci in nine populations of Phrynocephalus przewalskii

Population Phr27 Phr51 Phr54 Phr63 Phr72 Phr75s Phr81 Average

#5 (N = 48)

A 20 14 34 31 34 33 24 27

HE 0.942 0.820 0.964 0.961 0.970 0.955 0.952 0.938

HO 0.944 0.674 0.938 0.913 0.857 0.875 0.723 0.846

PHW 0.330 0.151 0.357 0.118 0.000 0.004 0.000

#12 (N = 37)

A 22 26 31 24 24 20 22 24

HE 0.950 0.957 0.967 0.950 0.933 0.923 0.923 0.943

HO 0.639 0.969 0.778 0.914 0.543 0.676 0.657 0.739

PHW 0.000 0.817 0.000 0.220 0.000 0.000 0.000

#54 (N = 48)

A 29 20 33 34 25 32 30 29

HE 0.958 0.948 0.963 0.972 0.956 0.952 0.959 0.958

HO 0.813 0.864 0.875 1.000 0.867 0.938 0.841 0.885

PHW 0.022 0.082 0.014 0.862 0.004 0.044 0.069

#50 (N = 47)

A 26 23 35 32 34 27 32 30

HE 0.948 0.935 0.964 0.967 0.968 0.955 0.967 0.958

HO 0.886 0.800 0.721 0.872 0.851 0.907 0.826 0.838

PHW 0.014 0.005 0.002 0.014 0.006 0.368 0.000

#35 (N = 48)

A 27 31 36 35 35 30 34 33

HE 0.948 0.956 0.974 0.973 0.972 0.941 0.965 0.961

HO 0.511 0.841 0.851 0.875 0.771 0.875 0.809 0.790

PHW 0.000 0.000 0.001 0.038 0.000 0.295 0.002

#31 (N = 48)

A 27 23 37 38 28 16 29 28

HE 0.952 0.937 0.975 0.974 0.956 0.932 0.960 0.955

HO 0.771 0.702 0.854 0.896 0.681 0.771 0.688 0.766

PHW 0.002 0.000 0.004 0.001 0.000 0.010 0.000

#32 (N = 47)

A 21 28 32 32 24 25 32 28

HE 0.915 0.952 0.962 0.959 0.929 0.944 0.959 0.946

HO 0.561 0.756 0.766 0.894 0.696 0.761 0.745 0.740

PHW 0.000 0.000 0.000 0.006 0.002 0.003 0.000

#29 (N = 44)

A 22 28 32 27 24 28 34 28

HE 0.946 0.955 0.969 0.953 0.940 0.956 0.966 0.955

HO 0.442 0.821 0.850 0.761 0.694 0.854 0.750 0.739

PHW 0.000 0.010 0.010 0.000 0.001 0.043 0.000

#20 (N = 45)

A 23 30 34 27 28 27 25 28

HE 0.954 0.941 0.969 0.956 0.938 0.946 0.948 0.950

HO 0.791 0.721 0.822 0.636 0.822 0.867 0.667 0.761

PHW 0.027 0.007 0.002 0.001 0.047 0.013 0.000

A, number of alleles; HO, observed heterozygosity; HE, the expected heterozygosity; PHW, P-value of Hardy–Weinberg equilibrium

test.


of the mountains. It is not difficult to envision that

during wet periods of climatic cycles since the Plio-

cene, the wet side of the mountain would be forested.

Phrynocephalus przewalskii lives only in sandy substrate

and a green belt along the mountain chain would cre-

ate an effective barrier to their dispersal and gene

flow, and a lasting barrier would initiate the vicariant


divergence. Subsequent dry climatic cycle might have

reduced the barrier effect and enabled males to cross

the mountain chain. Future work with co-distributed

groups could lead to corroboration of similar patterns

of divergence to determine if Pliocene climatic changes

influenced the evolutionary history of the region and

its inhabitants.

Fig. 3 Correlation between geographical distance in kilometre

(x-axis) and genetic distance given as FST ⁄ (1 ) FST) values

(y-axis). R2 = 0.1672, PMantel = 0.0307

–21 200

–20 400

–20 600

–20 800

–21 000

1 6 5 4 3 2

Ln P

(D

)

k

Fig. 4 A plot of average log likelihood values against k values.

All data are obtained from analysis of the microsatellite DNA

loci using assignment program Structure.

Table 3 Population pairwise FST for microsatellite data from nine sampling locations

Population 5 12 20 29 31 32 35 50 54

5 0

12 0.0194 0

20 0.0135 0.0206 0

29 0.0168 0.0219 0.0158 0

31 0.0184 0.0216 0.0182 0.0105 0

32 0.0221 0.0266 0.0247 0.0135 0.0136 0

35 0.0146 0.0188 0.0138 0.0089 0.0143 0.0130 0

50 0.0119 0.0160 0.0115 0.0089 0.0102 0.0129 0.0064 0

54 0.0149 0.0207 0.0151 0.0119 0.0159 0.0162 0.0093 0.0062 0

All values except one (bold) are significant at P = 0.01 level after Bonferroni correction.


The mtDNA remains well-structured after the initial

vicariant event. AMOVA assigned 46.56% of the total vari-

ation to the differences between the two lineages.

Within each lineage, there is geographical structure

among the mtDNA haplotypes as well. AMOVA assigned

27.41% of the total variation to the among-populations-

within-groups component (Table 1), suggesting a sub-

stantial amount of structure within both clade I and

clade II. The structure is most apparent within clade I.

All members of clade Ia are exclusively found in the

northeastern sites (1–11, 13–15), and all members of

clade Ib are exclusively found in populations (17–20) in

the northwest (Figs 1 and 2). The strong population

genetic structure of the mtDNA suggests that females

have had limited dispersal, particularly crossing the

Helan-Yin mountain chain.

Although limited, female dispersal did occur. It is

noteworthy that, within both clades I and II, there is a

substantial amount of mtDNA exchange among the

populations. For example, within assemblages Ic, IIa,

IIb and IIc, there is no clear association between the

clade and geographical distribution. Haplotypes from

the same location are often distributed in different

clades on the tree, and there are many haplotypes that

occur in multiple locations, i.e., H125 is shared by 33

individuals from sites 35, 36, 41, 43, 44, 45, 46, 50 and

51, and H158 is shared by 15 individuals from sites 45,

46, 47, 48, 54 and 55 (Appendix I). Furthermore, at both

ends of the Helan Mountains, there are several popula-

tions with haplotypes from both clade I and clade II.

These are probably secondary contact zones. The mix-

ing of the two clades also occurs at the eastern part of

the Yin Mountains (sites 11 and 12; Fig. 1).

A weak population genetic structure of nuclear genesand male-mediated gene flow

The microsatellite DNA data reveal little genetic struc-

ture among the populations, despite the large distance


Fig. 5 Bar plot of the individual assign-

ment results. Each vertical bar represents

one individual and its probabilities of

being assigned to clusters. Only individ-

uals from populations 5 and 20, which

represent the northeastern most and

southwestern most populations, revealed

high probability of being assigned to a

cluster. The results suggest weak popula-

tion genetic structure with some north-

east to southwest clinal variation.


between the eastern and western populations. The exact

tests of population differentiation show no significant

difference among any populations; the assignment test

fails to detect any naturally occurring population clus-

ters; and AMOVA reveals no detectable difference

between the two groups and only 1.70% of variation

at the among-populations-within-groups component

(Table 1). Although the pairwise FST is mostly signifi-

cant, the values obtained are small (Table 3). Further-

more, the small variation among populations can be

mostly explained by isolation by distance and a north-

east to southwest clinal variation.

The divergence patterns revealed by the microsatellite

DNA data are strikingly different from those of the

mtDNA. First, the Helan-Yin mountain chain divides

the mtDNA into two distinct groups, although it has no

detectable impact on the nuclear genes. The AMOVA

assigned 46.56% of all mtDNA variation to difference

between the two groups, but did not find any signifi-

cant amount of microsatellite DNA variation between

the two groups (Table 1). Instead, the microsatellite

DNA demonstrated a weak clinal variation and isola-

tion-by-distance pattern. Second, mtDNA has much

more population genetic structure than the nuclear

DNA. The mtDNA has a FST of 0.692 and a standard-

ized FST¢ of 0.995, which are strongly in contrast with a


FST of 0.017 and a standardized FST¢ of 0.372 for the mi-

crosatellite DNA data. As a result of their differences in

modes of inheritance and effective population size, a

fourfold greater level of genetic structure in the mtDNA

is expected. However, the k value (Crease et al. 1990) of

11 is much greater than the expected value of 4.

Although Hudson & Turelli (2003) questioned the four-

fold role based on the stochasticity of mtDNA, all tests

and indices (e.g. pairwise FST, AMOVA, Structure) suggest

that the mtDNA is well-structured, whereas the nuclear

DNA has a minimum amount of variation among

populations.

Male-mediated gene flow may best explain the dis-

crepancy between mtDNA and nuclear DNA. For the

past 2–5 Myr, females have more or less remained on

the same side of the Helan-Yin mountain chain,

although limited dispersal has occurred. In contrast,

extensive male movement has reduced the amount of

nuclear genes structure to a minimum. Several lizard

species with reported male-mediated gene flow demon-

strated a similar pattern: highly structured mtDNA and

high levels of gene flow of nuclear genes (e.g. Stenson

et al. 2002; Johansson et al. 2008). Male-mediated gene

flow in lizards has generally been associated with

polygynous mating systems and female philopatry (Jo-

hansson et al. 2008; Ujvari et al. 2008). Both factors may


well-contribute to the observed patterns in Phrynocepha-

lus przewalskii. Currently, we do not have much data on

the mating strategy and territorial behaviour of P. prze-

walskii. However, preliminary data from a closely

related species, P. vlangalii, revealed that floater males

have a much larger home range than that of females

(Yin Qi, personal communication).

Male-mediated gene flow in P. przewalskii spans a

very large spatial and temporal scale, compared with

other studies that have found evidence for male-medi-

ated gene flow or male-biased dispersal in lizards. For

example, sampling sites of both Johansson et al. (2008)

and Ujvari et al. (2008) were within 50 km of each

other. Both were also focused on short-term migra-

tion ⁄ dispersal within one generation. Compared with

direct measurements of dispersal, ‘indirect’ genetic

methods can be applied to small and large spatial and

temporal scales. They are probably more sensitive as

well, because of the benefits of accumulation of differ-

ences between different types of markers over long time

and large distance.

Several microsatellite DNA loci in multiple popula-

tions deviated significantly from HWE, and heterozy-

gote deficiency was detected in all cases (Table 2). The

increased homozygosity is probably a consequence of

the biology of these lizards rather than the presence of

null alleles. First, we screened all microsatellite loci

using Micro-Checker before analysis. All loci with sig-

nificant long allele drop-out or null alleles were

excluded from analysis. Second, we found that the fre-

quency of individuals that failed to amplify for popula-

tions ⁄ loci significantly deviating from HWE is lower

than that of populations ⁄ loci not significantly deviating

from HWE. Higher frequency of the former would sug-

gest the presence of null alleles. Several authors adver-

tised this null allele detecting method under the

assumption that some of the observed homozygotes

were actually heterozygous for the null allele and indi-

viduals that failed to amplify were homozygous for the

null allele (e.g. Magalon et al. 2005). Although the sig-

nificant heterozygote deficiency may violate assump-

tions of some methods, it has unlikely compromised

our overall conclusion as their presence typically

inflates the estimates of FST (Chapuis & Estoup 2007).

In contrast, we find no evidence for such inflation.

Although male-mediated gene flow may sufficiently

explain the minimum amount of structure at the

nuclear loci, one question remains: what evolutionary

forces have been keeping females of P. przewalskii from

crossing the mountain chain for the last 2–5 Myr?

Polygyny and female philopatry may explain part of

the genetic structure in mtDNA, particularly the struc-

ture within clades I and II (Fig. 2), but they may not be

sufficient to explain the separation of the two clades

along the mountain chain. Physical (size) difference

between males and females is unlikely the reason. The

sexual size dimorphism of this species is rather small;

males reach snout to vent length (SVL) of 47–63 mm,

whereas females reach SVL of 42–60 mm. If males are

capable of crossing the mountains, females are likely

capable too. In addition, there is one large gap between

the Yin and Helan Mountains (Fig. 1). Females appear

to have used the corridor to cross the mountain chain;

several populations nearby the corridor (39–42) have

haplotypes from both clades I and II. However, they

have not dispersed far (Fig. 1). Behavioural data on this

species are lacking, and we can only speculate that this

is probably associated with female-specific behaviour,

such as female intrasexual aggression (Jenssen et al.

2000). Females may defend territories against distantly

related females, such as the ones from different, deeply

diverged clades (e.g. clades I and II). Such hypothesis

can be tested in manipulative field studies.

Concluding remarks

mtDNA sequence data revealed a clear vicariant history

of P. przewalskii. However, this pattern has been gradu-

ally erased by male-mediated gene flow for the nuclear

genes. Limited migration maintains a small amount of

population genetic structure, with a weak isolation-by-

distance pattern.

Strong mtDNA structure is common in lizards (e.g.

Clark et al. 1999; Stenson & Thorpe 2003; Jin et al.

2008), although the nuclear gene structure is unknown

in most cases. Male-mediated gene flow is perhaps

much more common than we currently know. Although

polygynous mating systems and female philopatry may

significantly contribute to male-biased dispersal, other

alternative hypotheses should be explored. Studying

sex-biased dispersal in lizards may prove to be a very

fertile ground and more novel hypotheses will probably

be generated.

Acknowledgements

We thank Z. Liu, Y. Zheng, Q. Li and F. Feng for field assis-

tance, and A. Gozdzik and K. Bi for laboratory assistance. T.

Crease, R. Danzmann, D. Noble and K. Bi provided many

valuable comments for this manuscript. This project is sup-

ported by an NSFC (China) grant (NSFC30470252) to YW and

an NSERC (Canada) discovery grant to JF.

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Appendix I

Sample localities, voucher numbers and haplotype designation of

the University of Guelph (UG) and the Chengdu Institute of Biolog

examination (bold)

Population Locality Latitude Longitude

Phrynocephalus przewalskii

1 W of Abag 43�56.19¢N 114�33.24¢E2 Sonid Zuoqi 43�47.86¢N 113�36.63¢E3 E of Erenhot 43�20.46¢N 112�11.12¢E4 N of Sonid Youqi 43�07.47¢N 112�25.20¢E5 E of Sonid Youqi 42�48.094¢N 112�40.033¢E

6 S of Sonid Youqi 42�05.100¢N 112�09.577¢E7 Wu Lan Hua 41�51.219¢N 111�12.685¢E8 Wei Jing 42�36.609¢N 111�02.695¢E9 Ba Yin Ta La 42�28.070¢N 110�26.501¢

10 S of Bai Ling Miao 41�37.216¢N E110�30.690¢

11 S of Bai Ling Miao 41�31.64¢N 110�32.89¢E

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specimens examined. All voucher specimens are preserved at

y (CIB). Samples in [ ] were subjected to microsatellite DNA

Haplotype assignment and Voucher numbers

Sample

size

H1(CIB-XM01340) H2(CIB-XM01341) 2

H3(CIB-XM01244) 1

H5(CIB-XM01261) H4(CIB-XM01262) 2

H13(CIB-XM01240) 1

H6(UG-37461, UG-37479) H10(UG-37473)

H8(UG-37467, UG-37504) H7(UG-37470)

H5(UG-37462, UG-37464, UG-37476)

H9(UG-37482) micro[UG-37459-82,

UG-37492-509, UG-37513-8]

10 [48]

H5(UG-37523, UG-37538) 2

H11(UG-37555, UG-37560-4) 6

H13(UG-37593, UG-37611) 2

H13(UG-37649, UG-37662) 2

H14(UG-2003, UG-2017) H13(UG-1015-6,

UG-2019-22, UG-2027) H12(UG-2018)

10

H15(CIB-W01308) H16(CIB-W01309)

H17(CIB-XM01242) H159(CIB-XM01246)

4


Appendix I Continued

Population Locality Latitude Longitude Haplotype assignment and Voucher numbers

Sample

size

12 Hai Liu Tu 41�21.633¢N 109�06.031¢E H103(UG-2045) H146(UG-2036) H151(UG-2039,

UG-2049, UG-2051) H152(UG-2042, UG-2048)

micro[UG-2035-44, UG-2046-53, UG-2055,

UG-2057-8, UG-2060-75]

7 [37]

13 Chuan Jing 41�52.944¢N 108�10.058¢E H18(UG-2078, UG-2117) H26(UG-2081)

H27(UG-2082-83) H28(UG-2077, UG-2118)

H29(UG-2084)

8

14 Bao Yin Tu 41�44.686¢N 107�04.317¢E H19(UG-2127, UG-2129) H22(UG-2130)

H24(UG-2128)

4

15 Sai Wu Su 41�28.530¢N 106�57.053¢E H20(UG-2169) H21(UG-2170) H23(UG-2168)

H25(UG-2171)

4

16 Tai Yang Miao 40�47.354¢N 106�32.700¢E H157(UG-2193) 1

17 Tu Ke Mu 40�42.567¢N 105�53.678¢E H30(UG-2215) H34(UG-2217-9) 4

18 Wu Li Ji 40�52.515¢N 104�26.242¢E H31(UG-2223) H32(UG-2224, UG-2226)

H34(UG-2225)

4

19 Meng Geng Bu

La Ge

40�00.153¢N 103�49.810¢E H33(UG-2474) H34(UG-2473) 2

20 E Keng Hu Du Ge 39�16.125¢N 101�45.591¢E H35(UG-2424-5, UG-2437) H42(UG-2422)

H43(UG-2440, UG-2443) H44(UG-2428)

H88(UG-2431) micro[UG-2421, UG-2425-55,

UG-2458-65, UG-2467-71]

8 [45]

21 Shang Dan 39�00.217¢N 101�11.805¢E H43(UG-2405) H88(UG-2406) 2

22 Jinchang(Hexibao), 38�41¢N 102�06¢E H42(CIB-W0729) 1

23 Jinchang, 38�23.60¢N 102�05.60¢E H42(CIB-W0239) 1

24 N of Wu Wei 38�06.298¢N 102�42.803¢E H39(UG-839) H40(UG-840) H100(UG-847-8,

UG-853) H41(UG-849, UG-851) H85(UG-852)

H94(UG-850) H92(UG-846)

10

25 Wu Wei 37�53.063¢N 102�56.190¢E H86(UG-863, UG-854) H89(UG-862) H93(UG-857,

UG-860) H95(UG-858-9) H100(UG-856, UG-861,)

H102(UG-855)

10

26 Gu Lang 37�31.115¢N 103�23.597¢E H98(UG-824) H99(UG-825) 2

27 Jing Tai 37�22.446¢N 104�09.934¢E H60(UG-815) H57(UG-816) 2

28 Zhong Wei 37�26.191¢N 104�21.208¢E H56(UG-809-10) 2

29 Gan Tang 37�26.750¢N 104�32.007¢E H58(UG-797, UG-801-2) H59(UG-805)

H62(UG-4506) H63(UG-799) H64(UG-806)

H96(UG-798, UG-803-4) H97(UG-4497)

H101(UG-800) micro[UG-4472-84, UG-4486-97,

UG-4500-09, UG-4511-9]

12 [44]

30 Alxa Zouqi 37�49.609¢N 104�58.150¢E H47(UG-893) H48(UG-897) H49(UG-892)

H50(UG-888-91, UG-904) H51(UG-900)

H52(UG-895) H53(UG-896, UG-899)

H54(UG-902) H55(UG-901) H79(UG-898)

H90(UG-894)

16

31 Zhong Wei 37�35.140¢N 105�01.256¢E H46(UG-881) H47(UG-4576, UG-4582, UG-4585)

H50(UG-887) H63(UG-886, UG-4591)

H77(UG-4588) H90(UG-883-5, UG-4574)

H103(UG-882, UG-4569, UG-4579)

micro[UG-4568-70, UG-4572-98, UG-4600-17]

15 [48]

32 Zhong Wei

(S of

the Yellow R.)

37�27.270¢N 104�59.534¢E H45(UG-869) H58(UG-878) H59(UG-870)

H61(UG-877) H134(UG-868, UG-872, UG-874)

H135(UG-879) H114(UG-866-7) H118(UG-876)

H123(UG-873) H128(UG-875) micro[UG-866-79,

UG-4535-67]

13 [47]

33 E of Zhong Wei 37�30.688¢N 105�27.672¢E H36(UG-790) H37(UG-792) H106(UG-789)

H107(UG-794) H110(UG-791) H112(UG-793,

UG-795, UG-796)

8





Sample

size

34 En He 37�29.611¢N 105�45.663¢E H105(UG-4565-6) H112(UG-4655)

H115(UG-4656-8) H118(UG-4660)

7


H113(UG-912) H125(UG-911) H136(UG-908,

UG-910) micro[UG-906-12, UG-4459-71,

UG-4625-52]

7 [48]

36 Alxa Zouqi 37�50.389¢N 105�24.191¢E H83(UG-925, UG-927) H85(UG-933)

H122(UG-923) H123(UG-931) H125(UG-926,

UG-928-30) H136(UG-924)

10

37 Alxa Zouqi 38�21.124¢N 105�42.030¢E H76(UG-938) H78(UG-939, UG-941)

H114(UG-935, UG-950, UG-951) H116(UG-946)

H117(UG-949) H121(UG-942) H123(UG-937)

H125(UG-934, UG-936, UG-940, UG-944,

UG-952) H130(UG-943) H137(UG-948)

17

38 Alxa Zouqi 38�32.722¢N 105�38.849¢E H114(UG-955) H125(UG-953-4) 3

39 Alxa Zouqi 38�47.317¢N 105�40.359¢E H65(UG-958) H73(UG-964) H78(UG-959, UG-966,

UG-968-70, UG-972-4) H82(UG-957)

H123(UG-977-8) H124(UG-961) H125(UG-960,

UG-962-3, UG-967, UG-975-6, UG-979)

H129(UG-971) H130(UG-956) H138(UG-965)

24


H74(UG-982) H78(UG-983, UG-986-8, UG-992)

H80(UG-991) H81(UG-989) H114 (UG-985)

12

41 Alxa Zouqi 39�01.318¢N 105�52.651¢E H65(UG-1001, UG-1003, UG-1005-6, UG-1008-14)

H66(UG-997, UG-1000) H70(UG-993)

H71(UG-994) H72(UG-1015) H74(UG-995)

H75(UG-998) H84(UG-1004) H91(UG-1007)

H125(UG-996, UG-999) H130(UG-1002)

23

42 Ba Yan Nuo

Ni Gong

39�33.206¢N 105�24.322¢E H103(UG-2538) H104(UG-2544) H163(UG-2532)

H168(UG-2533, UG-2541) H169(UG-2547)

H170(UG-2550)

7

43 Alxa Zouqi 39�22.076¢N 106�26.193¢E H125(UG-1019) H141(UG-1020-1) H162(UG-1016)

H163(UG-1017, UG-1022-3) H166(UG-1018)

8

44 Wuhai 39�26.687¢N 106�43.192¢E H125(UG-1024, UG-1028, UG-1031)

H126(UG-1025) H127(UG-1030, UG-1035)

H164(UG-1029, UG-1034) H165(UG-1032)

H167(UG-1026-7)

11

45 Otog Qi 39�13.716¢N 107�10.340¢E H111(UG-1039) H125(UG-1045, UG-1047)

H131(UG-1040) H142(UG-1043) H143(UG-1046)

H144(UG-1048) H158(UG-1038, UG-1041-2)

10

46 Otog Qi 39�08.841¢N 107�53.763¢E H120(UG-1055) H123(UG-1054) H125(UG-1066-7)

H140(UG-1056) H144(UG-1051, UG-1061)

H148(UG-1053, UG-1063) H149(UG-1062)

H150(UG-1058) H158(UG-1052)

12

47 Otog Qi 39�00.187¢N 108�09.676¢E H158(UG-1073, UG-1084) H160(UG-1072,

UG-1078, UG-1081-3, UG-1085)

8

48 Otog Qi 38�55.481¢N 107�34.146¢E H132(UG-1092) H158(UG-1093) H144(UG-1094) 3

49 Otog Qianqi 38�38.876¢N 107�19.772¢E H132(UG-1110-2) 3

50 Ling Wu 38�05.033¢N 106�27.831¢E H125(UG-4686, UG-4688-9) H133(UG-4685,

UG-4687, UG-4690) micro[UG-4685-4718,

UG-4720-32]

6 [47]

51 Otog Qianqi 38�08.359¢N 107�31.097¢E H125(UG-1126) H132(UG-1125) H139(UG-1127)

H145(UG-1128)

4

52 Yulin 38�21.32¢N 109�41.50¢E H161(CIB-W01286) 1

53 W of Dongsheng City 39�21.47¢N; 109�49.75¢E H155(CIB-W01243), H156(CIB-W01247) 2





Sample

size

54 Hang Jin Qi 39�59.130¢N 108�32.368¢E H145(UG-2590) H147(UG-2589, UG-2592)

H153(UG-2610) H158(UG-2588, UG-2595,

UG-2598, UG-2601, UG-2604, UG-2607)

micro[UG-2588-2635]

10 [48]

55 Ao Bao Liang 39�56.732¢N 110�17.105¢E H154(UG-2645) H158(UG-2642-4) 4

Outgroup

Phrynocephalus sp.

Jiayuguan, Gansu 39�42¢N 98�11¢E CIB-W0984 1

Xingxingxia, Gansu 41�37.19¢N 95�14.31¢E UG-JF1415 1

Phrynocephalus versicolor

Ejin Qi, Inner Mongolia 41�58¢N 101�06¢E CIB-W1082 1

Hami, Xinjiang 43�04.19¢N 93�34.93¢E CIB-W01450 1

Phrynocephalus guttatus

Kuytun, Xinjiang 44�24.96¢N 84�47.12¢E CIB-W0887 1

Burqin, Xinjiang 47�18.70¢N 86�46.11¢E UG-JF1294 1



historical vicariance and male-mediated gene ﬂow in the...

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