© 2018 The Linnean Society of London, Botanical Journal of the Linnean Society, 2018, 186, 202–223 202
Botanical Journal of the Linnean Society, 2018, 186, 202–223. With 6 figures.
Phylogeography of Orinus (Poaceae), a dominant grass 
genus on the Qinghai-Tibet Plateau
YU-PING LIU1,2,3, ZHU-MEI REN4, AJ HARRIS5, PAUL M. PETERSON5, JUN WEN5* and 
XU SU1,2,3* 
1Key Laboratory of Medicinal Plant and Animal Resources in the Qinghai-Tibet Plateau, School of Life 
Science, Qinghai Normal University, Xining 810008, Qinghai, China
2Key Laboratory of Physical Geography and Environmental Process in Qinghai Province, School of Life 
Science, Qinghai Normal University, Xining 810008, Qinghai, China
3Key Laboratory of Education Ministry of Environments and Resources in the Qinghai-Tibet Plateau, 
School of Life Science, Qinghai Normal University, Xining 810008, Qinghai, China
4School of Life Science, Shanxi University, Taiyuan 030006, Shanxi, China
5Department of Botany, National Museum of Natural History, Smithsonian Institution, PO Box 37012, 
Washington, DC 20013-7012, USA
Received 12 July 2017; revised 26 September 2017; accepted for publication 2 November 2017
To better understand the responses of arid-adapted, alpine plants to Quaternary climatic oscillations, we investi-
gated the genetic variation and phylogeographic history of Orinus, an endemic genus of Poaceae comprising three 
species from the dry grasslands of the Qinghai-Tibet Plateau (QTP) in China. We measured the genetic variation of 
476 individuals from 88 populations using three maternally inherited plastid DNA markers (matK, rbcL and psbA-
trnH), the biparentally inherited nuclear ribosomal internal transcribed spacer (nrITS) and amplified fragment 
length polymorphisms (AFLPs). We found that the plastid DNA, nrITS and AFLPs show considerable, recent differ-
entiation among the species. We detected 14 plastid haplotypes (H1–H14), of which only three were shared among 
all species, and 30 nrITS ribotypes (S1–S30), of which one (S10) was shared between two species, O. kokonoricus and 
O. intermedius, but absent in O. thoroldii. The nrITS types formed clades that were inconsistent with species bounda-
ries. Based on these data, we propose and illustrate a complex hypothesis for the evolutionary history of Orinus 
involving lineage sorting and introgression, the latter of which may explain the shared S10 nrITS type. The AFLP 
results showed clades corresponding to current species delineation and suggest that lineage sorting in the genus 
is probably complete. We estimated the crown age of Orinus to be 2.85 (95% highest posterior density: 0.58–12.45) 
Mya (late Pliocene), and subsequent divergence occurred in the Quaternary. Early divergences were allopatric. More 
recently, Orinus probably underwent regional expansions corresponding to Quaternary climatic changes, especially 
glaciation, which is consistent with our divergence time estimates. These climatic changes could have facilitated the 
S10 event and other hybridization events. Our data also suggest that species of this small genus of grasses survived 
the Quaternary glacial period in the extremely adverse habitats of the QTP.
ADDITIONAL KEYWORDS: amplified fragment length polymorphism – internal transcribed spacer – 
phylogeography – plastid DNA – Orinus – Qinghai-Tibet Plateau.
INTRODUCTION
The Quaternary period began c. 2.58 Mya and has 
been characterized by climatic oscillations, especially 
glacial and interglacial cycles in the Northern 
Hemisphere (Shackleton & Opdyke, 1973). The glacial 
cycles co-varied with and probably profoundly affected 
other aspects of the climate, including the intensity of 
the Asian monsoon, even in unglaciated regions (An 
et al., 2001; Jiang et al., 2011). The Quaternary climatic 
changes caused changes in geographical distributions 
and population demography of plant species and 
consequently left lasting, detectable genetic imprints 
*Corresponding authors. E-mail : wenj@si .edu and 
xusu8527972@126.com
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PHYLOGEOGRAPHY OF ORINUS (POACEAE) 203
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within and among species (Abbott et al., 2000; Avise, 
2000; Hewitt, 2004, 2011; Qiu, Fu & Comes, 2011; Qiu 
et al., 2013; Wen et al., 2014, 2016).
In Europe and North America, the fossil records of 
plant species and phylogeographic analyses indicate 
that a common pattern of geographical range shift 
was to retreat southward and to lower elevations 
during glacial periods and then to rapidly recolonize 
the northern areas and higher elevations during the 
interglacial and postglacial periods (Nason, Hamrick 
& Fleming, 2002; Stewart et al., 2010; Sakaguchi et al., 
2011; Li et al., 2012; Segovia, Pérez & Hinojosa, 2012; 
Voss, Eckstein & Durka, 2012; Tzedakis, Emerson & 
Hewitt, 2013; de Lafontaine et al., 2014). In comparison 
with Europe and North America, the genetic structure 
and variation in Quaternary phylogeographic histories 
of plant species are much more pronounced in 
topographically complex regions of China, such as the 
Qinghai-Tibet Plateau (QTP) (e.g. Zhang et al., 2005; 
Meng et al., 2007; Wang et al., 2009a, 2014; Opgenoorth 
et al., 2010; Xu et al., 2010; Qiu et al., 2011; Zou et al., 
2012; Wen et al., 2014; Liu et al., 2015; Zhang et al., 
2015; Wan et al., 2016).
The QTP and adjacent mountain ranges, such 
as the Hengduan and the Hindu-Kush Mountains, 
(hereafter QTP) were formed by the collision of the 
Indian subcontinent with Eurasia and contain the 
world’s tallest mountain (Mount Everest) and have 
an average elevation of > 4000 m (Zheng, 1996). The 
QTP is regarded as a hotspot for global biodiversity 
and supports many endemic genera and species 
(Wu, 1988; Mittermeier et al., 2005). The exceptional 
biodiversity of the QTP has been attributed to 
Quaternary climatic oscillations and Miocene-Pliocene 
or Miocene-Quaternary phases of uplifts of the QTP 
(Liu et al., 2002, 2006; Liu, 2004; Wang et al., 2009c; 
Mao et al., 2010; Xu et al., 2010; Jia et al., 2012; Wen 
et al., 2014; Liu et al., 2015). Climatic oscillations and 
uplifts may lead to allopatric speciation, detectable as 
genetic imprints that date to the Miocene, Pliocene or 
Quaternary.
Recent studies have shown evidence for the 
importance of Quaternary climatic oscillations in 
explaining genetic variability, distributions and 
demographic patterns observed in modern populations 
of QTP species (Tang & Shen, 1996; Bawa et al., 2010; 
Jia et al., 2011; Liu et al., 2012, 2014b, 2015; Wan et al., 
2016). In particular, many alpine species retreated to 
eastern or south-eastern refugia during glacial periods 
and recolonized the central plateau platform during the 
interglacial or postglacial stages (e.g. Zhang et al., 2005; 
Meng et al., 2007; Chen et al., 2008; Yang et al., 2008; 
Wu et al., 2010; Tian et al., 2011; Jia et al., 2012; Liu 
et al., 2015; Wan et al., 2016). In contrast, some other 
cold-tolerant alpine species were able to survive in situ 
through glacial periods in multiple ice-free refugia or 
microrefugia (Wang et al., 2009b; Opgenoorth et al., 
2010; Jia et al., 2011; Ma et al., 2014). These two major 
types of evolutionary hypotheses about phylogeographic 
relationships between plant species and Quaternary 
climatic oscillations have been developed and tested by 
previous studies on the QTP (Wu et al., 2010; Jia et al., 
2011; Tian et al., 2011; Ma et al., 2014; Liu et al., 2015). 
Results show that there was a close relationship between 
geographical distribution patterns of plant species 
from the QTP and Quaternary climatic oscillations, 
and independent genetic lineages appear in different 
plateau regions due to isolations among developed 
ice sheets. Given the probable impacts of ongoing 
climatic change on biodiversity, phylogeographic 
investigations of plant species in diverse regions, such 
as the QTP, are increasingly important. Although many 
phylogeographic studies of QTP plants have been 
performed, these have mostly focused on woody plants 
or herbaceous dicot lineages that occur in forested areas 
(e.g. Zhang et al., 2005; Meng et al., 2007; Chen et al., 
2008; Tian et al., 2011; Jia et al., 2012; Wan et al., 2016). 
The grasslands comprise a significant portion of the 
QTP and are dominated by grasses (Poaceae). Therefore, 
disentangling the phylogeographic history of grasses is 
crucial to understanding the evolution of the QTP flora. 
In addition, these kind of grass-dominated landscapes 
are interesting since many of the vegetation types thus 
far studied are dominated by trees or shrubs. Grasses 
are cold-, warm- and arid-tolerant, making their study 
necessary to describe evolution in the QTP. Therefore, 
phylogeographic studies of grasses are needed to 
understand the past history of biogeographic and 
demographic change linked to past climatic oscillations 
and to make informed inferences about the future of the 
QTP grasslands (e.g. Qiu et al., 2011; Liu et al., 2012, 
2014b, 2015; Wen et al., 2014).
Here, we studied the phylogeographic history of the 
perennial grass genus, Orinus Hitchc., that is endemic 
to alpine, dry grasslands of the QTP and occurs in 
unusually sandy habitats (Chen & Phillips, 2006; Su 
& Cai, 2009; Su et al., 2015). Orinus  comprises three 
 morphologically and ecologically  distinct  species, 
O. thoroldii (Stapf ex Hemsl.) Bor, O.  kokonoricus 
(K.S.Hao) Keng and O. intermedius X. Su & J. Quan Liu 
(Su et al., 2015, 2017), that are distributed at elevations 
between 2200 and 4800 m. Recently, Orinus was 
placed in subtribe Orininae P.M.Peterson, Romasch. 
& Y.Herrera with Cleistogenes Keng (Peterson, 
Romaschenko & Arrieta, 2016; Soreng et al., 2017). 
Furthermore, Orinus reproduces mainly through clonal 
reproduction via root suckers. Orinus spp. are dominant 
in places where they occur and are an exceptional 
study system for understanding the effects of the 
Quaternary climatic oscillations on the  demography of 
QTP grassland species. Specifically, we investigated the 
biogeographic and phylogeographic history in Orinus 
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using robust sampling of the three species throughout 
their geographical ranges using molecular markers, 
 including plastid DNA, nuclear  ribosomal internal 
transcribed spacer (nrITS) and amplified fragment 
length polymorphism (AFLP) data sets. We address the 
following questions: (1) What is the phylogeographic 
pattern in Orinus? (2) Are the phylogeographic  patterns 
in Orinus consistent with southern glacial refugia and 
with other demographic patterns observed among 
diverse alpine plants on the QTP?
MATERIAL AND METHODS
PoPulation samPling
We sampled 476 individuals belonging to 88 
populations from the distributional area of the genus 
including the type localities of all three species (Fig. 1A; 
see also Supporting Information, Table S1). From each 
population, we collected fresh leaf blades from three 
to 12 individuals and preserved them in silica gel. In 
each population, we selected individuals that were 
at least 20 m away from each other to avoid clones, 
and we recorded the latitude, longitude and elevation 
of each population using an Etrex GIS (Garmin, 
Taiwan, China). We also prepared several voucher 
specimens from each population and deposited them 
at the Herbarium of the Northwest Plateau Institute 
of Biology (HNWP), the Chinese Academy of Science, 
Xining, Qinghai Province, China.
Dna extraction, amPlification,  
sequencing anD aflP fingerPrinting
We extracted total DNA from silica gel-dried leaves 
using a modified 2× CTAB procedure (Doyle & Doyle, 
1987). We used universal primers to amplify nuclear 
ITS and three plastid DNA regions: matK, rbcL and 
psbA-trnH (White et al., 1990; Sang, Crawford & 
Stuessy, 1997; Feng et al., 1998; Sun, McLewin & Fay, 
2001). We performed the amplification using PCR 
in 25 µL reaction volumes, containing 1 µL plant 
template DNA, 0.2 mM MgCl2, 0.25 mM dNTPs, 2 µM 
each primer, 2.50 µL 10× PCR buffer and 0.25 µL Taq 
DNA polymerase (5 U/µL; TakaRa, Dalian, China). 
Our PCR thermocycling protocol comprised an initial 
5-min denaturation period at 94 °C, followed by 
36 cycles of denaturation at 94 °C for 50 s, annealing 
Figure 1. Sampling sites and geographical distribution of plastid DNA haplotypes observed in three Orinus spp. A, sam-
pling region (dashed-line box). B, documented distribution range (dotted line), sampling sites and plastid DNA haplotype 
frequencies per population. Each pie graph represents a plastid DNA haplotype, and size of pie is proportional to the 
number of individuals bearing that haplotype. C, network for 14 plastid DNA haplotypes detected from three Orinus spp. 
Dinebra viscida was used as the outgroup. Sizes of network circles are proportional to haplotype frequencies. Numbers on 
the link lines between haplotypes represent the mutational sites. Colours for haplotypes are described in (B).
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at 49–58 °C for 50 s and extension at 72 °C for 1 min, 
with a final extension at 72 °C for 10 min. We purified 
the PCR products with a TIAN-quick Midi Purification 
Kit (Tiangen, Beijing, China) in accordance with the 
manufacturer’s instructions, and we sequenced the 
purified products using an ABI 3130XL DNA Analyzer 
(Applied Biosystems, Foster City, CA, USA). We 
aligned the sequences of the plastid DNA and nrITS 
separately in MUSCLE (Edgar, 2004) and refined the 
alignments manually in MEGA 5 (Tamura et al., 2011). 
We combined the three plastid DNA regions because 
we did not detect phylogenetic incongruence among 
them using an incongruence length difference test 
under the parsimony criterion with 1000 replicates, 
Tree Bisection and Reconnection branch swapping 
and the number of trees retained for each replicate 
limited to 1000 (Farris et al., 1995). All newly obtained 
sequences of Orinus have been submitted to GenBank 
under the accession numbers KP302391–KP303274.
We used a slightly modified protocol (Vos et al., 1995) 
to examine the AFLP of all the sampled populations 
(Supporting Information, Table S1) and used fluorescent 
primers for selective amplification (Zuo et al., 2015). 
DNA was digested with restriction enzymes PstI and 
MseI (40 U/µL, Beijing Dingguo Biotechnology Co., Ltd, 
China) for 5 h at 37 °C in a 20 µL volume, followed by 
ligation (40 units T4 DNA ligase, 4 h at 8 °C) to double-
stranded PstI and MseI adapters. Two rounds of PCR 
amplification followed. Of 15 tested PstI/MseI primer 
combinations, eight were selected to produce the most 
repeatable and unambiguously scorable profiles. 
Selective fluorescence-labelled amplification products 
were separated and analysed on an ABI PRISM 377 
DNA Sequencer (Applied Biosystems, Foster City, CA, 
USA) using GeneScan ROX-500, with an internal size 
standard. We used GeneScan 3.1 (Applied Biosystems, 
Foster City, CA, USA) to score the bands of AFLP 
amplification products. We imported the raw data into 
Binthere (Garnhart, 2001) and MG (Zhou & Qian, 
2003) to generate a 0/1 matrix for data analyses.
PoPulation DescriPtive statistics
We calculated the haplotype diversity (HE) of the plastid 
DNA for each population using DnasP 5.0 (Librado & 
Rozas, 2009), and we used Permut (Pons & Petit, 1996) 
to find the average genetic diversity within populations 
(HS), total genetic diversity (HT) and the coefficients of 
differentiation (GST, NST) for each species, separately and 
combined. For the plastid DNA, we used permutation 
of GST and NST with 1000 replicates to infer significant 
phylogeographic structure (Pons & Chaouche, 1995). 
To examine population genetic structure, we used an 
analysis of molecular variance (AMOVA) with 1000 
permutations (Excoffier, Smouse & Quattro, 1992) in 
Arlequin 3.11 (Excoffier, Laval & Schneider, 2005). We 
calculated plastid gene flow among populations (Nem) 
based on the equation Nem = ([1/FST] − 1)/2, where Ne was 
the effective population size of female individuals and m 
was the migration rate (Freeland, Kirk & Petersen, 2011). 
In nrITS, we assumed that a site was heterozygous if it 
had a double peak at the same position in both strands, 
and the weaker signal between base calls was at least 
25% of the strength of the stronger (Fuertes-Aguilar, 
Rosselló & Nieto-Feliner, 1999; Fuertes-Aguilar & Nieto-
Feliner, 2003). We also determined nrITS ribotypes with 
PHASE 1.0 for heterozygous individuals (Stephens, 
Smith & Donnelly, 2011).
We used the Bayesian implementation of the k-mean 
method in STRUCTURE 2.2 (Pritchard, Stephens & 
Donnelly, 2000) to estimate the most likely number 
of populations (K) in Orinus according to the plastid 
DNA and nrITS data sets. Specifically, we performed 
analyses for K values ranging from 2 to 7, with ten 
replicates for each value of K and a burn-in of 2 × 106. 
We applied the ‘no admixture model’ and independent 
allele frequencies for these analyses. The most likely 
number of clusters was estimated according to the 
K resulting in the best improvement in the global 
likelihood (Evanno, Regnaut & Goudet, 2005).
network anD Phylogenetic analyses
We performed network and phylogenetic analyses 
to reconstruct relationships among populations and 
species. We first distinguished plastid DNA haplotypes 
and nrITS ribotypes with DnasP 5.0 software package 
(Librado & Rozas, 2009). We constructed a median-
joining network of haplotypes of the plastid DNA and 
ribotypes of nrITS with NETWORK 4.5.0.0 (Weir, 
1996). In NETWORK, we set both site mutations 
and indels to evolve with equal likelihood, and we 
assumed that each indel originated independently 
of all other indels. For reconstructing phylogenetic 
relationships, we applied maximum parsimony (MP) 
and maximum likelihood (ML) to the plastid DNA 
haplotypes and nrITS ribotypes, independently in 
PAUP*4.0b10 (Swofford, 2002). We also reconstructed 
phylogenetic relationships with Bayesian inference 
(BI) in MrBayes 3.1 (Ronquist & Huelsenbeck, 2003). 
For the ML analyses and BI, we used a general-time-
reversible model (GTR) with a gamma distribution 
of rate variation among sites (+ G) based on results 
in PAUP*4.0b10 and jModelTest according to the 
Akaike information criterion (Posada, 1998; Swofford, 
2002). We approximated the gamma distribution 
using four rate categories. For other parameters, 
we used default settings. For the MP analyses, we 
performed heuristic searches with 1000 random 
addition sequence replicates with ten trees retained 
at each step during the stepwise additions and with 
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tree-bisection-reconnection for branch swapping. We 
set PAUP*4.0b10 to treat all characters as unordered 
and equally weighted, gaps as missing and multistate 
data as uncertain in the MP analyses. For MP and ML, 
we calculated bootstrap values from 1000 replicates 
(Felsenstein, 1985). The BI consisted of two parallel 
runs with four incrementally heated chains and three 
million generations sampled every 1000 generations. 
The output was assessed for convergence using Tracer 
v.1.3 (Rambaut & Drummond, 2007), and summary 
statistics and trees were generated using the last two 
million generations. For network and phylogenetic 
analyses of plastid DNA and nrITS, we used Dinebra 
viscida (Scribn.) P.M.Peterson & N.Snow and four 
samples of Cleistogenes as outgroups, respectively 
(Peterson et al., 2012, 2016). For the AFLP data, we 
analysed a rectangular binary 0/1 data matrix using 
the NTSYS-pc 2.l (Rohlf, 2000) statistical package, and 
we generated a pairwise similarity matrix with simple 
matching coefficient according to the SIMQUAL 
procedure in NTSYS-pc. We performed cluster analysis 
of the binary matrix using the unweighted pair-group 
method to build a UPGMA dendrogram by means of 
SAHN package in NTSYS-pc. We performed bootstrap 
analysis of the UPGMA tree with 2000 replicates using 
the winboot computer program (Yap & Nelson, 1996). 
We also calculated a genetic similarity matrix using 
AFLP data according to the method of Nei & Li (1979).
Dating the Divergence between lineages
We obtained the nrITS data set of Chloridoideae from 
Peterson et al. (2016) and used it to estimate the 
divergence times of Orinus. We verified equal base 
frequencies among accessions in PAUP*4.0b10 and 
tested a strict molecular clock hypothesis in MEGA 
5 (Tamura et al., 2011). The strict clock was rejected 
(2lnLR = 434.458, d.f. = 48, P < 0.01). We performed 
Bayesian divergence time estimation in BEAST 2.4.5 
(Bouckaert et al., 2014), which co-estimates topology 
and node ages. We prepared the nrITS data set for 
analysis in BEAST using Beauti and by directly 
editing the content of.xml files. We applied an HKY 
model of nucleotide substitutions because the more 
parameter-rich GTR model did not yield substantial 
gains according to the preliminary analyses. We 
approximated the gamma distribution of site-specific 
rates with ten rate categories and applied the ‘birth 
death’ tree prior process model with a standard, 
uniform prior. We set a ‘relaxed lognormal clock’ with 
a substitution rate prior of 6.85 × 10−9 based on Wolfe, 
Li & Sharp (1987). We calibrated the crown node age 
of Chloridoideae as 32.74 Mya, which was inferred 
in prior studies (Christin et al., 2008; Vicentini et al., 
2008) and is reasonable because no isotopic surveys 
to-date provided evidence of an older date for C4 grass 
(Osborne & Beerling, 2006). Our calibration comprised 
a normal distribution with an SD of 1.0, yielding a 95% 
highest posterior density (HPD) of 28.09–37.19 Mya. 
We constrained the monophyly of the Chloridoideae 
after preliminary analyses revealed that long branches 
(i.e. high evolutionary rates) resulted in placement 
of Sporobolus R.Br. with the outgroups. Sporobolus 
clearly belongs in Chloridoideae based on strong 
evidence from prior molecular and morphological 
studies (Peterson et al., 2016). We ran two independent 
analyses in BEAST with 5 × 108 Markov chain Monte 
Carlo generations. We compared the posterior and 
likelihood distributions from each run in Tracer 1.5.0 
to ensure convergence, and we selected one of two runs 
for downstream analyses (Rambaut & Drummond, 
2009). We performed a 10% burn-in and summarized 
trees by selecting the maximum clade credibility tree 
in TreeAnnotator 2.4.5, which is part of the BEAST 
2.4.5 package, and using median heights for branch 
lengths. We visualized the maximum clade credibility 
tree and other summary statistics in FigTree 1.3.1 
(Rambaut, 2009).
To calculate divergence times of species and 
populations in Orinus, we used nrITS and two methods: 
(1) a direct calculation from mutation rates using 
a strict molecular clock; and (2) a dating analysis in 
BEAST (Drummond & Rambaut, 2007). For the direct 
calculation, a strict molecular clock was appropriate, 
because it was not rejected by an analysis in MEGA 
5 (Tamura et al., 2011) (2lnLR = 54.524, d.f. = 29, 
P = 0.61), and performed a coalescent Bayesian 
skyline tree process prior suitable for intraspecific 
data. The strict molecular clock comprised mutation 
rates of 5.8–8.1 × 10−9 substitutions/site/year, which 
are well established as rates of evolution of nrITS in 
other perennial grass genera (Wolfe et al., 1987). For 
the analyses in BEAST, we analysed 476 sequences 
of Orinus, and we used four samples of Cleistogenes 
as outgroups. We applied an age calibration to the 
Orinus crown node based on our results from the tree 
for Chloridoideae (above). Specifically, the calibration 
comprised a uniform prior with using the median date 
from the tree for Chloridoideae ± 1 Mya. All other 
parameters of this analysis were the same as for the 
analysis of Chloridoideae (Peterson et al., 2016), except 
that we used a coalescent skyline model of diversification 
because it is appropriate for intraspecific taxa.
glacial refugia anD DemograPhic analyses
We inferred putative glacial refugia of Orinus based 
on occurrences of comparatively high genetic diversity 
among intraspecific populations and for the genus 
with plastid DNA and nrITS data sets. Genetic 
diversity is expected to be higher in refugial areas 
compared with surrounding areas (Hewitt, 1996, 1999, 
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2000) due especially to founder effects (Mayr, 1942). 
Although associating high diversity areas with glacial 
refugia may be overly simplistic (Petit et al., 2003), 
our intention is to generate a working hypothesis for 
future  testing. To visualize putative refugia based on 
diversity across geographical areas, we generated 
surface plots of the number of unique haplotypes, 
ribotypes and combined haplotypes and ribotypes 
within  populations using a triangulated irregular 
network (TIN) in ArcMap v.10 (ESRI, 2010). The from-
end of link points are used as the TIN uses triangles 
nodes points,  georeferenced populations in this case, 
and interpolate values, or number of genotypes in this 
case, between them. We trimmed the TINs according to 
the convex hulls of O. thoroldii and O. intermedius and 
for the geographically distinct northern and central 
metapopulations of O.  kokonoricus (Fig. 6A). The 
resulting surfaces facilitate inference and visualization 
of geographical areas of high diversity, which we take 
as possible glacial refugia. We deposited all GIS data 
online with ESRI, and it is available at https://www.
arcgis.com/home/item.html?id=d2f9770771ec4de58a83
73d85e3695ce.
We used several methods to detect demographic 
expansions based on plastid DNA data sets, such as 
from refugia, in the history of Orinus. We sought to 
detect recent demographic expansion in Orinus and in 
each species using a mismatch distribution analysis 
in Arlequin 3.5. The mismatch distribution analysis 
applies a model of computes the pairwise p-distances 
(absolute distances) between sequences and organizes 
the results in a histogram. A distribution of pairwise 
frequencies that is multimodal is the equilibrium 
state, showing expected differentiation among species 
or populations. In contrast, a unimodal distribution 
represents geneflow and a trend towards panmixia 
(Slatkin & Hudson, 1991; Rogers & Harpending, 1992). 
We analysed the results of the mismatch distribution 
by comparing the sum of squared deviations observed 
distributions and those expected following a recent 
demographic expansion. We also quantified modality of 
the distribution using Harpending’s raggedness index, 
where more ragged distributions are multimodal. 
We assessed recent demographic expansions using 
Tajima’s D (Tajima, 1989) or Fu’s FS (Fu, 1997) in 
Arlequin 3.5, with 10 000 parametric bootstrap 
replicates. Positive values for these statistics typically 
indicate demographic contractions or a recent 
bottleneck event (Tajima, 1989; Fu, 1997; Hamilton, 
2009). In addition, we estimated expansion times (t) 
using the relationship τ = 2ut (Rogers & Harpending, 
1992), where u is the mutation rate per generation for 
all sequences analysed and t is the expansion time in 
number of generations. Here, u = μkg, where μ is the 
substitution rate, k is the average sequence length 
of the analysed DNA region and g is the generation 
time in years. We assumed that g = 5 years based 
on data from the closely related genus Triodia R.Br. 
(Armstrong, 2011).
RESULTS
iDentification of PlastiD Dna haPlotyPes anD 
nrits ribotyPes, anD Dating Divergence times
Among the 476 individuals, the total alignment length 
of three plastid DNA sequences (matK, rbcL and 
psbA-trnH) was 2898 bp; for nrITS, it was 624 bp. 
Nucleotide substitutions occurred at 19 polymorphic 
sites in plastid DNA (0.66%), and 13 of these were 
potentially parsimony informative; there were no 
indels (see Supporting Information, Table S2). The 
aligned nrITS sequences had 46 variable sites, 45 of 
which were potentially parsimony informative (see 
Supporting Information, Table S3). We used sequence 
polymorphisms to identify haplotypes in plastid DNA 
and ribotypes in nrITS.
In plastid DNA, we identified 14 different haplotypes, 
H1–H14 (Fig. 1B; see Supporting Information, Table 
S1). Forty-nine populations (55.68%) were fixed for 
a single haplotype; the remaining 39 (44.32%) were 
polymorphic (Fig. 1B; see Supporting Information, Table 
S1). Two haplotypes, H4 and H6, were shared between 
O. kokonoricus and O. intermedius, and only one, H2, 
was fixed among all three Orinus spp. Of these shared 
haplotypes, H2 and H4 occurred in 67.05 and 17.05% of 
all populations, respectively, whereas H6 was limited to 
six populations (6.82%). H2 was widely distributed across 
the QTP, and H4 was widely distributed throughout 
the eastern and south-eastern QTP. Six haplotypes 
were found only in O. thoroldii, four were specific to 
O. kokonoricus and one was specific to O. intermedius 
(Fig. 1C; see Supporting Information, Fig. S1).
In nrITS, we identified 30 different ribotypes, 
S1–S30. Of these, ten were each limited to a single 
population, and all but one were restricted to one 
species (Fig. 2; see Supporting Information, Fig. S2, 
Table S1). The S10 ribotype was shared between 
O. kokonoricus and O. intermedius. Thirty-nine 
populations (44.32%) only possessed one haplotype; 
the remaining 49 (55.68%) were polymorphic (Fig. 2; 
see Supporting Information, Fig. S2, Table S1). 
Ribotypes S2, S19 and S26 were the most common 
nrITS sequences and were fixed or present in nearly 
all sampled populations from the three Orinus spp. 
Sequence S2 was discovered in 84.44% of all samples 
for O. kokonoricus, S19 was found in all populations 
from O. thoroldii and S26 also occurred in 86.67% 
of all sampled populations of O. intermedius. Ten 
ribotypes (S7–S9, S15–S18, S22, S23 and S25) were 
private to a single population (Fig. 2; see Supporting 
Information, Table S1).
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The divergence time estimation showed Orinus 
diverged from its closest relatives c. 12.06 Mya (95% 
HPD: 6.87–17.50) (Miocene) and diversified c. 2.85 Mya 
(node 1; 95% HPD: 0.78–5.05) in the Pliocene (Fig. 3; 
see Supporting Information, Table S4). In Orinus, 
modern ribotypes diversified in the Pleistocene, 0.31–
1.71 Mya (nodes 2–9) (see Supporting Information, Fig. 
S2, Table S4), according to the analysis using BEAST. 
When the divergence time of ribotypes was calculated 
using mutation rates, we found the similar results 
as the above, also in the Pleistocene (see Supporting 
Information, Table S4).
PoPulation variability, glacial refugia anD 
DemograPhy
Haplotype diversity (HE) from each population was 
calculated based on plastid DNA haplotype frequencies 
(see Supporting Information, Table S1). The average 
genetic diversity within populations (HS) was relatively 
low for O. thoroldii, O. kokonoricus and O. intermedius 
(0.16 ± 0.05, 0.23 ± 0.07 and 0.31 ± 0.10), and the total 
genetic diversity HT (0.74 ± 0.03) across the whole 
genus was much higher than HS (0.21 ± 0.04) based 
on the observed plastid DNA variations (Table 1). 
A permutation test suggested that population 
differentiation across the sampling range was high 
(NST = 0.83 ± 0.04) and was significantly higher than 
GST (0.72 ± 0.05) (0.01 < P < 0.05), indicating a strong 
phylogeographic structure across the entire sampling 
range (Table 1).
Hierarchical AMOVA based on the plastid DNA 
data set revealed that there was higher interspecific 
genetic differentiation across the whole distribution of 
this genus (FST = 0.82), and the interpopulation genetic 
differentiation in O. thoroldii and O. kokonoricus was 
much more pronounced (FST = 0.72, FST = 0.73), but 
there was a little interpopulation differentiation in 
O. intermedius (FST = 0.34) (Table 2). These results 
suggested that the grouping pattern of hierarchical 
AMOVA was basically consistent with relationships 
among plastid haplotypes and their geographical 
distribution (Fig. 1C, Table 2).
Our analyses revealed extensive gene flow among 
populations of Orinus across its geographical range. 
In the STRUCTURE analyses (Fig. 4A), the highest 
likelihood of the plastid DNA data was obtained when 
all samples were weakly clustered into three groups 
according to the recognized species (K = 3). However, 
this result did not correspond to separate geographical 
regions because there was strong gene flow across the 
range of Orinus. In addition, a Nem value of 0.61 also 
indicated extensive gene flow existed between groups 
based on plastid DNA data.
Figure 2. Sampling sites and geographical distribution of nrITS ribotypes observed in three Orinus species. A, sampling 
region (dashed-line box). B, documented distribution range (dotted line), sampling sites and nrITS ribotype frequencies per 
population. Each pie graph represents nrITS ribotypes; size of pie is proportional to number of individuals bearing that 
haplotype.
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Table 1. Estimates of genetic diversity for plastid DNA in three Orinus spp. on the Qinghai-Tibet Plateau
Groups HS HT GST NST
O. kokonoricus (P1–45) 0.23 (0.07) 0.74 (0.06) 0.69 (0.10) 0.60 (0.12)
O. thoroldii (P46–73) 0.16 (0.05) 0.56 (0.04) 0.72 (0.08) 0.81 (0.07)*
O. intermedius (P74–88) 0.31 (0.10) 0.59 (0.05) 0.48 (0.18) 0.33 (0.15)
All populations 0.21 (0.04) 0.74 (0.03) 0.72 (0.05) 0.83 (0.04)*
HS, estimate of average genetic diversity within populations; HT, total genetic diversity; GST, coefficient of genetic variation over all populations; NST, 
coefficient of genetic variation influenced by both haplotype frequencies and genetic distance between haplotypes.
*P < 0.05.
Figure 3. Bayesian divergence time estimate of Orinus (shaded) based on the nrITS data set of Chloridoideae from Peterson 
et al. (2016). Clade constraint is marked by the black circle. Numbers in parentheses indicate 95% highest posterior density 
intervals.
Table 2. Results of analysis of molecular variance for plastid DNA and nrITS sequence data from populations of Orinus 
on the Qinghai-Tibet Plateau
Groups Source of variation d.f. SS VC Variation (%) Fixation index
Plastid DNA
All samples Among groups 2 121.90 0.74 Va 44.78 FST = 0.82*
Among populations 
within groups
53 152.13 0.62 Vb 37.72 FSC = 0.68*
Within populations 420 52.46 0.29 Vc 17.50 FCT = 0.45*
Total 475 326.49 1.65
O. kokonoricus Among populations 20 50.09 0.54 Va 72.69 FST = 0.73*
Within populations 161 14.17 0.20 Vb 27.31
Total 181 64.26 0.74
O. thoroldii Among populations 26 92.52 0.92 Va 71.90 FST = 0.72*
Within populations 161 24.18 0.36 Vb 28.10
Total 187 116.70 1.28
O. intermedius Among populations 7 9.52 0.16 Va 34.27 FST = 0.34*
Within populations 98 14.10 0.32 Vb 65.73
Total 105 23.62 0.48
nrITS
All samples Among groups 2 1977.08 6.32 Va 81.90 FST = 0.96*
Among populations 
within groups
53 491.63 1.08 Vb 13.96 FSC = 0.77*
Within populations 420 134.40 0.32 Vc 4.15 FCT = 0.82*
Total 475 2603.11 7.72
O. kokonoricus Among populations 20 204.28 1.13 Va 67.89 FST = 0.68*
Within populations 161 86.25 0.54 Vb 32.11
Total 181 290.53 1.67
O. thoroldii Among populations 26 21.58 0.09 Va 30.17 FST = 0.30*
Within populations 161 33.48 0.21 Vb 69.83
Total 187 55.06 0.30
O. intermedius Among populations 7 265.77 2.95 Va 95.17 FST = 0.95*
Within populations 98 14.67 0.15 Vb 4.83
Total 105 280.43 3.10
d.f., degrees of freedom; SS, sum of squares; VC, variance components; FCT, correlation within populations relative to groups; FSC, correlation of 
haplotypes within groups relative to the total; FST, correlation within populations relative to the total.
*P < 0.001 (10 000 permutations).
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PHYLOGEOGRAPHY OF ORINUS (POACEAE) 211
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Figure 4. Estimated genetic structure for K = 2–3 obtained with the program STRUCTURE (Pritchard et al., 2000) for 56 
populations of Orinus based on plastid DNA (A) and nrITS (B) sequence variations. Each vertical bar represents an individ-
ual and its assignment proportion (not shown). Red, Orinus thoroldii; Green, O. kokonoricus; Blue-purple, O. intermedius.
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For nrITS, we found that 81.90% of the total genetic 
variation occurred between groups, 13.96% occurred 
among populations within groups and only 4.15% 
occurred within populations. The pairwise FST value 
between three groups was 0.96 (Table 2). It suggested 
that there was high interspecific differentiation among 
three species, and interpopulation differentiation of 
O. kokonoricus and O. intermedius was also extremely 
high (FST = 0.68, FST = 0.95). In contrast, O. thoroldii 
exhibited lower interpopulation variation (FST = 0.30). 
The grouping pattern of hierarchical AMOVA based 
on nrITS data was in accordance with relationships 
of ribotypes and their geographical distribution 
(Fig. 5, Table 2). Similarly, the STRUCTURE analyses 
indicated that almost all samples of O. intermedius 
and O. kokonoricus were clustered into a lineage, and 
there was only obscure gene flow between them and 
O.  thoroldii (K = 2) (Fig. 4B). However, all samples 
of this genus were clustered into three independent 
lineages when the highest likelihood of the data was 
obtained (K = 3), and there was prominent introgression 
between O. kokonoricus and O. intermedius (Fig. 4B). 
In addition, the gene flow between the three groups 
was low according to the Nem value was 0.11.
Our surface analysis in ArcMap revealed four 
centres of diversity for haplotypes, ribotypes and 
the combined diversity of haplotypes and ribotypes 
(Fig. 6). For O. thoroldii, the haplotype and ribotype 
data are congruent in showing a centre of diversity 
in the eastern part of the range (Fig. 6B, C). The 
haplotype and ribotype data also agree that the 
northern metapopulation of O. kokonoricus has a 
centre of diversity at the southern portion of its 
range (Fig. 6B, C). In contrast, the haplotypes show 
centres of diversity at the northern ends of the ranges 
of O. intermedius and the central metapopulation of 
O. kokonoricus, whereas the ribotypes show centres of 
diversity at the southern ends of these ranges (Fig. 6B, 
C). Overall, greater diversity among ribotypes than 
haplotypes (Figs 1, 2) yielded a geographical pattern in 
the combined analysis of genotypes (Fig. 6E) consistent 
with ribotypes alone.
The mismatch distributions of pairwise differences 
for all samples from the identified haplotypes of 
Orinus and O. thoroldii were close to bimodal, whereas 
those of O. kokonoricus and O. intermedius were close 
to be unimodal (see Supporting Information, Fig. S3), 
indicating that the former should experience recent 
bottlenecks and the latter should experience recent and 
rapid population expansion. However, further analyses 
using the non-significant variance and raggedness 
index tests indicated that none of the observed 
distributions differed significantly from those expected 
under a sudden expansion model (Table 3). Moreover, 
the significant negative calculated values for Tajima’s 
D (P < 0.01) and non-significant positive calculated 
values for Fu’s FS (P > 0.05) were also supported this 
earlier, rapid demographic or geographical expansion 
and subsequent population growth (Table 3). Besides, 
the mean expansion times were estimated to be c. 25, 
29, 40 and 53 kya for O. intermedius, O. kokonoricus, 
O. thoroldii and Orinus, respectively (Table 3). These 
results support a recent and rapid demographic 
population growth in the genus and each of the three 
species, and all expansions occurred before the Last 
Glacial Maximum (LGM; c. 20 kya). Possibly, Orinus 
and O. thoroldii have experienced recent bottlenecks.
DISCUSSION
PhylogeograPhic Patterns in Orinus
In recent years, many studies have focused on the 
early stages of speciation (Abbott et al., 2013; Liu et al., 
2014b). Some of these have shown that divergence 
among species can occur even in the presence of gene 
flow and that species boundaries are maintained by 
divergent selection (Hewitt, 1996; Petit & Excoffier, 
2009; Schluter, 2009; Nosil, 2012; Sousa & Hey, 2013). 
Our plastid DNA, nrITS and AFLP data suggest that 
Orinus may be at an advanced stage of speciation in 
which gene flow is limited, by geographical isolation or 
divergent selection, and fixation is underway so that 
most sequences form clades comprising only one species, 
but these species are paraphyletic (Fig. 5) (Funk & 
Omland, 2003) Population bottlenecks have also 
played a role in promoting divergence among closely 
related taxa but has rarely been studied (Butlin et al., 
2012; Bi et al., 2016).
Our results suggest a subtle but complex geographical 
pattern in the genetic diversity of Orinus. High levels of 
interspecific genetic variation occurred among samples 
of plastid DNA (44.78%) and nrITS (81.90%) (Table 2). 
In addition, the differentiation among species was 
high overall evidenced by significant FST of 0.86 and 
0.96 for plastid DNA and nrITS (Table 2), indicating 
nearly complete genetic isolation (Rieseberg, Church 
& Morjan, 2004; Hauquier et al., 2017). Moreover, 
only one plastid DNA haplotype and no nrITS types 
were shared among all populations (Figs 1, 2). 
However, the pattern is more complex than isolation 
by species; the eastern and south-eastern species, 
O. kokonoricus and O. intermedius, clearly have more 
gene flow between them than either does with the 
western species, O. thoroldii. Orinus kokonoricus and 
O. intermedius share two additional plastid DNA 
haplotypes in common (Fig. 1), exclusive of O. thoroldii, 
and one nrITS type (Fig. 2), strongly suggestive of 
recent or ongoing gene flow (Parchman, Benkman & 
Br i t ch , 2006) . Moreover, the  phy logenet i c 
reconstruction of nrITS sequences in O. kokonoricus 
and O. intermedius shows that the haplotypes unique 
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to each species do not form clades; they are intermixed 
in their phylogenetic positions, and this is highly 
consistent with genetic connectivity and subsequent 
isolation and fixation. In contrast, O. thoroldii does not 
share any additional haplotypes or nrITS ribotypes in 
common with O. kokonoricus or O. intermedius. Overall, 
the demographic pattern suggests greater and/or more 
frequent connectivity between the eastern and south-
eastern species than with the western one.
It is noteworthy that Orinus spp. are largely 
differentiated and possess few shared ribotypes or 
haplotypes, but the ribotypes or haplotypes do not form 
the same clades as the species (Fig. 5; see Supporting 
Information, Figs S1, S2). At least two, non-mutually 
Figure 6. The sampled populations and interpolated distribution of genetic diversity of plastid DNA and nrITS in three 
Orinus spp. A, the sampled populations and convex hulls drawn around them. B, the interpolated distribution of genetic 
diversity of plastid DNA. C, the interpolated distribution of genetic diversity of nrITS. D, the highest genetic diversity regions 
of plastid DNA and nrITS. E, the interpolated distribution of genetic diversity of plastid DNA and nrITS. F, the legend of the 
study area in China to provide the geographical context, and a–e correspond to the number of genotypes 1–5, respectively.
Figure 5. Hypothesis of incomplete lineage sorting and reticulation in nrITS of Orinus shown within a species tree of the 
genus. Lineage A is fixed in O. thoroldii, whereas descendent types from lineage B are incompletely sorted in O. kokonoricus 
and O. intermedius. nrITS type S10 evolved in lineage F of O. kokonoricus and was later shared with O. intermedius during 
a secondary contact event. Black nodes indicate divergence events among types that we can infer from our data, and extant 
types sampled in this study are numbered 1–30 at terminal nodes. Two particularly large clades of nrITS types in lineage 4 
are collapsed into single terminal nodes, and all types represented by those nodes are listed numerically.
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PHYLOGEOGRAPHY OF ORINUS (POACEAE) 215
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exclusive hypotheses may explain this phylogeographic 
pattern: (1) somewhat recent species divergence with 
incomplete lineage sorting (Choleva et al., 2014; Zhou 
et al., 2017) or (2) recent and/or repeated secondary 
contact and introgression (Avise, 2000; Sardell & Uy, 
2016). In Orinus, both mechanisms are needed to 
explain our results (Figs 1, 2, 4). Based on our nrITS 
data, we propose nrITS split into two lineages, A and 
B before or after the divergence of O. thoroldii from 
the rest of Orinus (Fig. 5). Lineage A became fixed 
in O. thoroldii, in which lineage sorting is complete 
(Fig. 5). Lineage B diversified into lineages C, D, E and 
F in an ancestor of O. kokonoricus and O.  intermedius 
(Fig. 5). Lineages C and E are limited to O.  intermedius, 
whereas D and F occur only in O. kokonoricus (Fig. 5). 
Thus, sorting of the descendent genotypes of lineage B is 
incomplete between O. kokonoricus and O.  intermedius. 
The S10 nrITS type is shared by both O. kokonoricus 
and O. intermedius, but is clearly derived in lineage 
F (Fig. 5). Therefore, it seems probable that the S10 
type was shared by O. kokonoricus with O.  intermedius 
during a secondary contact and hybridization event 
(Sardell & Uy, 2016; Zhou et al., 2017). The plastid 
DNA data and the AFLPs are not in conflict with 
this hypothesis. Plastid DNA loci sort and become 
fixed more slowly than nuclear markers (Wolfe et al., 
1987; de Villiers et al., 2013; Shaw et al., 2017), such 
as nrITS, and the shared haplotypes among all three 
species and between O. kokonoricus and O. intermedius 
may represent incomplete lineage sorting (Choleva 
et al., 2014; Yasuda et al., 2015; Kuritzin et al., 2016). 
Alternatively, the haplotype shared among all three 
species may represent an older secondary contact 
(Miraldo et al., 2011; Sardell & Uy, 2016), predating the 
S10 event and too old to be preserved in nrITS data. 
AFLPs revealed that species and populations within 
species comprise clades. Therefore, most but not all 
lineage sorting among species is complete (Choleva 
et al., 2014; Yasuda et al., 2015; Kuritzin et al., 2016).
The demographic pattern that we observed in 
Orinus seems highly consistent with the history 
of geomorphism in the QTP and adjacent areas. 
The evidence for QTP uplifts comes primarily from 
detecting its effects on regional aridity and the 
monsoon climatic using dust sedimentation and 
indicator fossils of marine foraminifera (e.g. An et al., 
2001; Sun & An, 2001; Guo et al., 2002; Zheng et al., 
2004). Although the exact timing of uplift events 
remains somewhat in question, the QTP probably 
underwent early orogenesis c. 40 Mya along its western 
margin as the Indian subcontinent collided with 
Eurasia and more extensive, rapid uplift 20–7 Mya 
(Harrison et al., 1992; Ruddiman, 1998). In addition, 
many geological and historical biogeographic studies 
infer that that additional uplifts occurred east of the 
QTP around c. 4.0–2.5 Mya in adjacent mountain T
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ranges, especially the Hengduan Mountains (Chen, 
1992, 1996; Zheng et al., 2004; Gao et al., 2013; 
Favre et al., 2015). Thus, the Hengduan Mountains 
and other adjacent ranges have experienced more 
recent, Pliocene geological changes and associated 
climatic perturbations than the QTP proper (Xing 
& Ree, 2017). Contemporaneously, glacial cycling 
also impacted the area, and its effects can be 
difficult to distinguish from the genetic signature of 
geomorphism (Shackleton & Opdyke, 1973; Liu et al., 
2014b). Nevertheless, it is possible that regional 
geomorphism to the east of the QTP facilitated the 
dynamic history of recent allopatric speciation and 
secondary contact suggested by our nrITS data for 
O. kokonoricus and O. intermedius. Similarly, the 
relatively recent geomorphism to the east of the QTP 
by comparison to the QTP may also be reflected in 
the evolutionary and demographic histories of other 
diverse plant groups. For example, Yang et al. (2012) 
found that species of Meconopsis Vig. (Papaveraceae) 
occurring in the QTP diverged earlier than species 
occurring in adjacent eastern areas.
alloPatric Divergence, glacial refugia anD 
historical DemograPhy
The role of climatic oscillations in shaping the regional 
biota is important and should not be ruled out as a 
driver of evolutionary events in Orinus. Other species 
in the region have histories affected by climatic 
change. For example, Anisodus tanguticus Pascher 
(Solanaceae) has western and eastern clades that 
diverged during the Pleistocene, probably a result 
of genetic isolation in glacial refugia, rather than a 
geological event (Wan et al., 2016). Similar patterns 
of intraspecific divergence due to Quaternary climatic 
change have also been found in other plant species 
in the QTP and adjacent regions, such as Aconitum 
gymnandrum Maxim. (Ranunculaceae) (Wang et al., 
2009a), Sophora davidii (Franch.) Skeels (Fabaceae) 
(Fan et al., 2013) and Oxyria sinensis Hemsl. 
(Polygonaceae) (Meng et al., 2015).
Based on the divergence time of 32.74 Mya for 
Chloridoideae, the crown age was dated to be 2.85 (95% 
HPD: 0.58–12.45) Mya, with interspecific divergences 
occurred in the range of 0.31–1.70 Mya (see Supporting 
Information, Fig. S2, Table S4). This relatively recent 
interspecific diversification atop an unbranched stem 
lineage is sometimes regarded as reflecting ancient 
extinctions (Harvey, May & Nee, 1994). Deep divergence 
in Orinus apparently began in the mid-Pleistocene (see 
Supporting Information, Fig. S2, Table S4). Although 
these estimated timescales for deep divergence must 
be interpreted with caution, they (the major nodes) 
correspond relatively well with recent QTP uplifts 
(0.01–1.80 Mya) (Li, Shi & Li, 1995; Shi, Li & Li, 1998; 
Zheng, Xu & Shen, 2002). Development of aridification 
in the QTP was a response to climatic change at the 
time, such as long-term cooling and drying trends. By 
the early Pleistocene, the QTP dramatically uplifted 
to present heights (Wu et al., 2008), which made 
the climate of this area become extremely cool and 
dry. Especially, strong episodic cooling resulted in 
sharp increases in aridity of the QTP regions (Fang 
et al., 2002). Aridification played a significant role 
in the increase of genetic diversity, and even species 
divergence and speciation of alpine plants. Habitat 
fragmentation, vicariance and population isolation 
on the QTP provided opportunities for allopatric 
speciation through the action of selection and/or 
genetic drift (Wang et al., 2013; Meng et al., 2014; Wen 
et al., 2014). Thus, deep intraspecific divergence in 
Orinus may be a result of adaptation to arid habitats, 
with the mechanisms probably being similar to those 
in other arid/desert species (Wang et al., 2013; Yu et al., 
2013; Liu et al., 2014b; Meng et al., 2014). Therefore, it 
is likely that the deep divergence in Orinus was caused 
by allopatric differentiation and reduction in gene flow 
following plateau uplifts and climatic oscillation.
Plant populations in refugia generally have high 
genetic divergence (Petit et al., 2003). Our surface 
analysis in ArcMap revealed four centres of diversity 
for haplotypes, ribotypes and the combined diversity of 
haplotypes and ribotypes, which were consistent with 
the result of glacial refugia based on both plastid DNA 
and nrITS data sets (Figs 1B, 2B, 6B–E). Among them, 
there were three areas with relatively high plastid DNA 
and nrITS genetic diversity and one region with unique 
plastid DNA haplotypes and high nrITS genotypes 
(Figs 1B, 2B, 6B–E). One region with plastid DNA 
haplotype uniqueness and high nrITS genetic diversity 
(O. intermedius) is located on the southern edge of the 
QTP, an area well known as an important refugium 
for other alpine plant species (Figs 1B, 2B, 6E) (Zhang 
et al., 2005; Meng et al., 2007; Chen et al., 2008; Yang 
et al., 2008; Wang et al., 2009a; Gao et al., 2012; Liu 
et al., 2012, 2014b; Ma et al., 2014), which was further 
supported by the result of surface analysis in ArcMap 
(Fig. 6C–E). Furthermore, three (S28–S30) of four 
(S10, S28–S30) nrITS ribotypes from this region were 
endemic, indicating a divergence centre for Orinus. 
Plastid and nrITS genetic diversities are higher in 
two regions (O. kokonoricus) in the north-eastern and 
eastern plateau (Figs 1B, 2B, 6E), which may represent 
two important refugia throughout the Quaternary. Our 
surface analysis in ArcMap also indicated the northern 
metapopulation of O. kokonoricus has a centre of 
diversity at the southern portion of its range (Fig. 6B, C), 
and the southern metapopulation of O. kokonoricus has 
another centre of diversity at the southern portion of its 
range (Fig. 6E). We have two alternative biogeographic 
hypotheses regarding high levels of genetic diversity 
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PHYLOGEOGRAPHY OF ORINUS (POACEAE) 217
© 2018 The Linnean Society of London, Botanical Journal of the Linnean Society, 2018, 186, 202–223
in O. kokonoricus. A glacial refugium allowed 
O. kokonoricus to survive climatic oscillations and to 
accumulate genetic diversity (Tzedakis et al., 2002) or 
this region was composed of a mixture of individuals 
with different origins, resulting in higher genetic 
diversity than the original source (Petit et al., 2003). If 
the latter hypothesis is true, then haplotypes detected 
in this region should form a subset of haplotypes of 
the multiple original sources, although four (H1, H3, 
H5 and H7) out of the seven plastid DNA haplotypes 
in these populations of O. kokonoricus are endemic. 
Furthermore, the majority of nrITS ribotypes (S1–S9 
and S11–S18) were restricted to this area, indicating 
other divergence centres of O. kokonoricus. In addition, 
widespread haplotypes (H2 and H4) and ribotypes (S2 
and S3) coexisting among the great number of plastid 
DNA haplotypes and nrITS ribotypes also occurred 
in these two regions. Thus, the most-parsimonious 
explanation is consequently the presence of glacial 
refugia for O. kokonoricus. A similar result was found 
in previous studies of endemics species from the QTP 
(e.g. Gao et al., 2012; Ma et al., 2014). In addition, 
the western region of the QTP was only occupied by 
O. thoroldii probably represent the fourth separate 
refugia during the large glaciation stage (Figs 1, 2, 
6B–E). The populations of O. thoroldii in eastern part 
of the range had relatively high plastid DNA and nrITS 
genetic diversity (Figs 1, 2), which were congruent in 
showing a centre of diversity according to the surface 
analysis in ArcMap (Fig. 6B–E). Therefore, we thought 
greater diversity among ribotypes than haplotypes 
yielded a geographical pattern in the combined analysis 
of genotypes consistent with ribotypes alone.
Based on the plastid DNA data set, the three Orinus 
spp. might have experienced recent and repeated 
population expansion after allopatric divergence (e.g. 
Avise, 2004; Wang et al., 2009b; Gao et al., 2012; Ma 
et al., 2014; Liu et al., 2015), and O. thoroldii might 
also have experienced recent bottlenecks due to its 
bimodal mismatch distribution (Fig. S3B). A star-like 
phylogeny pattern for O. thoroldii and O. kokonoricus 
is shown in the haplotype network (Fig. 1C), suggesting 
the haplotypes might have originated from a sudden 
expansion event (Hudson, 1990). This is supported 
by  significantly negative Tajima’s D  values (Table 3), 
as well as unimodal mismatch distributions for 
O.  kokonoricus and O. intermedius (see Supporting 
Information, Fig. S3C, D). Overall, these findings 
support expansions of Orinus in western, eastern and 
north-eastern regions, perhaps between 25.48 and 
52.77 kya, prior to the LGM (18–24 kya) (Shi et al., 
1998) (Table 3), but later than other  previously reported 
QTP endemic genera (Ma et al., 2014) and species (e.g. 
Yang et al., 2008; Jia et al., 2011; Li et al., 2012). Early 
expansion of Orinus would have yielded all haplotypes 
in the QTP region. However, some haplotypes are 
fixed in specific populations. For example, H3, H4 and 
H6 correspond to populations 3–5, 42–43 and 17–20, 
 respectively. Thus, the existence of multiple high-
elevation refugia that would have facilitated survival 
during the LGM (Wang et al., 2009c; Opgenoorth 
et al., 2010; Jia et al., 2011; Gao et al., 2012; Liu 
et al., 2012; Ma et al., 2014). Perhaps, only small and 
isolated populations, such as P87 and P88, survived 
in restricted ice-free regions, and range expansion in 
the refugia appears to be restricted during glacial and 
interglacial periods. However, another distinct genetic 
signature via large-scale range expansions, that is 
wide distribution of a single haplotype (Avise, 1987; 
Comes & Kadereit, 1998; Hewitt, 2000). In the present 
study, two widely distributed haplotypes (H2, H9) 
were found in Orinus. For instance, H2 was found as a 
single haplotype in 59 of the 88 populations of the QTP 
and fixed in 25 of them, whereas H9 was fixed in 11 
of the 28 populations in O. thoroldii from the western 
QTP (e.g. Jia et al., 2011; Li et al., 2012; Wang et al., 
2014; Liu et al., 2015). Therefore, Orinus might have 
experienced a second recent range expansion, probably 
after the LGM, which led to the wide distribution of 
the two haplotypes in the QTP region.
Orinus intermedius is a newly described species (Su 
et al., 2017) and is sister to O. kokonoricus (Figs 1C, 
3, 5). The morphological characters of O. intermedius 
are intermediate between its two congeners (Su et al., 
2017). We initially hypothesized that O.  intermedius 
may have formed via hybrid speciation on the QTP and 
its adjacent areas (Su et al., 2015, 2017) in a similar 
manner to Ostryopsis intermedia B.Tian & J.Q.Liu 
(Betulaceae) (Liu et al., 2014a), Picea purpurea Masters 
(Pinaceae) (Sun et al., 2014), Roscoea humeana Balf.f. 
& W.W.Sm. and R. cautleoides Gagnep. (Zingiberaceae) 
(Zhao et al., 2016). However, our plastid and nrITS data 
support recent divergences between O.  intermedius and 
O. kokonoricus, which may explain their morphological 
similarities. In addition, the AFLP data suggest that the 
three Orinus spp. each form a separate clade indicating 
phylogenetic distinctiveness (Supporting Information, 
Fig. S4). As the next steps, we plan to use more rapidly 
evolving markers, such as single- or low-copy nuclear 
genes, or even next- generation  sequencing approaches 
in Orinus (Zimmer & Wen, 2012, 2015) to unravel 
the genetic structure and phylogeographic patterns 
and to explore speciation mechanisms (Abbott, 2017; 
Crawford & Archibald, 2017).
ACKNOWLEDGEMENTS
We are grateful to Prof. Jianquan Liu for providing space 
and expendables in the laboratory and two anonym-
ous reviewers for their comments on the manuscript. 
This work was supported by grants from the National 
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218 Y.-P. LIU ET AL.
© 2018 The Linnean Society of London, Botanical Journal of the Linnean Society, 2018, 186, 202–223
Natural Science Foundation of China (31260052 
and 41761009), the Natural Science Foundation of 
Qinghai Province (2017-ZJ-904, 2016-ZJ-937Q and 
2014-ZJ-947Q) and the State Scholarship Fund of 
China Scholarship Council (201508635003).
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:
Figure S1. Strict MP consensus tree of 14 plastid DNA haplotypes of three Orinus spp. Each tree is topologically 
congruent with ML tree and Bayesian consensus tree based on same data set. Bootstrap support values from 
Bayesian and MP analyses, and corresponding posterior probabilities from MP analyses, are given above branches 
(values > 50%). Dinebra viscida was used as an outgroup.
Figure S2. Strict MP consensus tree of 30 nrITS ribotypes of three Orinus species. Each tree is topologically 
congruent with ML tree and Bayesian consensus tree based on same data set. Bootstrap support values from 
Bayesian and ML analyses, and corresponding posterior probabilities from MP analyses, are given above branches 
(values > 50%). Four Cleistogenes spp. (C. bulgarica, C. festucacea, C. mucronata and C. songorica) were used as 
outgroups.
Figure S3. Mismatch distributions for plastid DNA data in genus Orinus (A), O. thoroldii (B), O. kokonoricus (C) 
and O. intermedius (D). The thin line represents the expected (Exp) values, and the dashed line represents the 
observed (Obs) values.
Figure S4. UPGMA dendrograms for three Orinus spp. generated by cluster analysis based on AFLP data set.
Table S1. Sampling data, estimates of haplotype diversity (HE), and haplotype composition for plastid DNA and 
nrITS data sets from 88 populations of Orinus.
Table S2. Variable sites for 14 plastid DNA haplotypes of three Orinus spp. on the Qinghai-Tibet Plateau (QTP).
Table S3. Variable sites for 30 nrITS ribotypes of three Orinus spp. on the Qinghai-Tibet Plateau (QTP).
Table S4. Estimates of divergence times in Orinus for the major nodes based on nrITS data set.
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