ArticlePDF Available

A population genetics perspective on the evolutionary histories of three clonal, endemic, and dominant grass species of the Qinghai–Tibet Plateau: Orinus (Poaceae)

Wiley
Ecology and Evolution
Authors:

Abstract and Figures

We performed analyses of amplified fragment length polymorphism (AFLP) in order to characterize the evolutionary history of Orinus according to its population genetic structure, as well as to investigate putative hybrid origins of O. intermedius and to provide additional insights into relationships among species. The genus Orinus comprises three clonal grasses that are dominant species within xeric alpine grasslands of the Qinghai–Tibet Plateau (QTP). Here, we used eight selectively obtained primer pairs of EcoRI/MseI to perform amplifications in 231 individuals of Orinus representing 48 populations and all three species. We compared our resulting data to genetic models of hybridization using a Bayesian algorithm within NewHybrids software. We determined that genetic variation in Orinus was 56.65% within populations while the among‐species component was 30.04% using standard population genetics statistics. Nevertheless, we detected that species of Orinus were clustered into three highly distinct genetic groups corresponding to classic species identities. Our results suggest that there is some introgression among species. Thus, we tested explicit models of hybridization using a Bayesian approach within NewHybrids software. However, O. intermedius likely derives from a common ancestor with O. kokonoricus and is probably not the result of hybrid speciation between O. kokonoricus and O. thoroldii. We suspect that recent isolation of species of Orinus in allopatry via vicariance may explain the patterns in diversity that we observed, and this is corroborated by a Mantel test that showed significant positive correlation between geographic and genetic distance (r = 0.05, p < 0.05). Recent isolation may explain why Orinus differs from many other clonal species by exhibiting the highest diversity within populations rather than among them.
This content is subject to copyright. Terms and conditions apply.
6014
|
Ecology and Evolution. 2019;9:6014–6037.
www.ecolevol.org
Received: 20 February 2019 
|
Revised: 26 March 2019 
|
Accepted: 26 March 2019
DOI: 10.1002/ece 3.5186
ORIGINAL RESEARCH
A population genetics perspective on the evolutionary histories
of three clonal, endemic, and dominant grass species of the
Qinghai–Tibet Plateau: Orinus (Poaceae)
Yuping Liu1,2,3| AJ Harris4| Qingbo Gao5| Xu Su1,2,3| Zhumei Ren6
1Key Laboratory of Medicinal Plant and Animal Resources of the Qinghai‐Tibet Plateau in Qinghai Province, School of Life Science, Qinghai Normal Univer sity,
Xining, China
2Key Laboratory of Physical Geography and Environmental Process in Qinghai Province, School of Life Science, Qinghai Normal University, Xining, China
3Key Laboratory of Education Ministr y of Environments and Resource s in the Qinghai‐Tibet Plateau, School of Life Science, Qinghai Normal Universit y, Xining,
China
4Depar tment of Biolog y, Oberlin College and Cons ervatory, Oberlin, O hio
5Qinghai Provincia l Key Laboratory of Crop Molecul ar Breeding, Nor thwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China
6School of Life Science, Shanxi Uni versit y, Taiyuan, China
This is an op en access arti cle under the ter ms of the Creative Commons Attribution L icense, which pe rmits use, dis tribution and reproduction in any medium,
provide d the original wor k is properly cited.
© 2019 The Authors. Eco logy an d Evolution published by John W iley & Sons Ltd.
Yuping Liu a nd AJ Harris co ntributed equ ally to this work .
Correspondence
Xu Su, Key Laboratory of Medicinal Plant
and Animal Resource s of the Qinghai‐Tibet
Plateau in Qinghai Province, School of Life
Science , Qinghai No rmal Universit y, No. 38
Wusixi Road, Xining 81000 8, China.
Email: xusu8527972@126.com
and
Zhumei Ren, Scho ol of Life Science, Shanxi
University, No. 92 Wucheng Road, Taiyuan
030006, C hina.
Email: zmren@sxu.edu.cn
Funding information
Open Project of Qinghai Provincial Key
Labor atory of Crop Molecular Breeding,
Grant/Award Number: 2017‐ZJ‐Y14; Natural
Science Foundation of Qinghai Province,
Grant/Award Number: 2017‐ZJ‐904; High‐
end Innovative Talent s Thousands of Pe ople
Plan; National Nat ural Science Foundation
of China, G rant/Award Numbe r: 31260 052
and 41761009; 135 High‐level Personnel
Training Project
Abstract
We performed analyses of amplified fragment length polymorphism (AFLP) in order
to characterize the evolutionary history of Orinus according to its population genetic
structure, as well as to investigate putative hybrid origins of O. intermedius and to
provide additional insights into relationships among species. The genus Orinus com‐
prises three clonal grasses that are dominant species within xeric alpine grasslands of
the Qinghai–Tibet Plateau (QTP). Here, we used eight selectively obtained primer
pairs of EcoRI/MseI to perform amplifications in 231 individuals of Orinus represent
ing 48 populations and all three species. We compared our resulting data to genetic
models of hybridization using a Bayesian algorithm within NewHybrids software. We
determined that genetic variation in Orinus was 56.65% within populations while the
among‐species component was 30.04% using standard population genetics statis‐
tics. Nevertheless, we detected that species of Orinus were clustered into three
highly distinct genetic groups corresponding to classic species identities. Our results
suggest that there is some introgression among species. Thus, we tested explicit
models of hybridization using a Bayesian approach within NewHybrids software.
However, O. intermedius likely derives from a common ancestor with O. kokonoricus
and is probably not the result of hybrid speciation between O. kokonoricus and O.
thoroldii. We suspect that recent isolation of species of Orinus in allopatry via vicari
ance may explain the patterns in diversity that we observed, and this is corroborated
    
|
 6015
LIU et aL .
1 | INTRODUCTION
Genetic diversity is a particularly significant factor in the long‐term
stability of plant populations (Hedrick, 2001; Jump, Marchant,
& Peñuelas, 2009; Rahimmalek, Tabatabaei, Arzani, & Etemadi,
2009; Wang et al., 2007). For example, low genetic diversity of a
population may both represent critical local adaptation and, simul‐
taneously, limit overall evolutionary potential in the face of environ‐
mental disturbances (Cortés et al., 2014; Jump et al., 2009; Sedlacek
et al., 2016, 2015). Therefore, knowledge of population genetic di‐
versity is extremely important for recognizing conservation needs
and developing sustainable strategies (Gordon, Sloop, Davis, &
Cushman, 2012; Kaljund & Jaaska, 2010). Conservation of species is
an urgent global issue, especially within biodiversity hotspots, such
as the Qinghai–Tibet Plateau (QTP) and surrounding mountainous
areas, which represent some of the highest priorities within tem‐
perate zones for conservation research and implementations (Beger
et al., 2015; Maréchaux, Rodrigues, & Charpentier, 2016; Myers,
Mittermeier, Mittermeier, Da Fonseca, & Kent, 2000).
The biodiversit y of the QTP appears to be correlated with its
complex, recent history of environmental change and its present‐
day heterogeneous landscape. Environmental change and landscape
heterogeneity are well‐known drivers of biodiversity according to
classic ecological theory (Risser, 1987). In the present, the QTP ex‐
hibits substantial landscape heterogeneity; for example, its elevation
range is from 3,000 to 5,000 m and represents a steep ecological
gradient comprising diverse niches for a rich composition of species
(Feng et al., 2017; Feng et al., 2017; Liu, Luo, Li, & Gao, 2017). With
respect to environmental change, the QTP has undergone extreme
ecological disturbances on an evolutionary timescale, especially
rapid uplifts since the Miocene–Pliocene or Miocene–Quaternary
epochs and subsequent climatic oscillations in the Quaternary (Liu,
2004; Liu, Gao, Chen, & Lu, 2002; Liu, Wang, Geng, et al., 2006;
Liu, Wang, Wang, Hideaki, & Abbot t, 2006; Liu et al., 2018, 2015;
Shi, 20 02; Shi, Li, & Li, 1998; Wen, Zhang, Nie, Zhong, & Sun, 2014;
Zheng & Nat, 1998). The biodiversity within the QTP is reflected
within its flora, which harbors ca. 9,000 vascular plant species of
which more than 18% are endemic (Wu, 2008), including at least 20
endemic genera (Wu, Yang, & Fei, 1995).
Many recent studies have sought to address evolutionary diver‐
sification of plant species within the QTP and have especially used
population genetics methods to elucidate patterns of diversity and
distributions and better understand the underlying mechanisms
(Liu, Wang, Geng, et al., 2006; Ren, Conti, & Salamin, 2015; Wen
et al., 2014). Recently, Wen et al. (2014) reviewed current evidence
of mechanisms of speciation on the QTP using exemplar species
within diverse vascular plant families, especially of Asteraceae,
Crassulaceae, Ericaceae, Orobanchaceae, and Papaveraceae.
However, the mechanisms of speciation within alpine areas of the
QTP (and beyond) remain poorly understood. These mechanisms
likely include allopatric processes and, possibly, rapid genetic isola
tion due to increased mutation rates under high levels of ultravio‐
let light exposure (Davies, Savolainen, Chase, Moat, & Barraclough,
2004; Madriñán, Cortés, & Richardson, 2013; Willis, Bennett, &
Birks, 20 09). Within the QTP, studies of many plant species are
needed to serve as models for diversification and speciation pat‐
terns and processes, especially to represent the numerous habits,
life histories, environmental preferences, and other features of the
rich botanical diversity of the region. Such studies are particularly
urgent for regions, such as the alpine grasslands (Bowman, 2000;
Li et al., 2014; Yi et al., 2011), that have become imperiled during
the Anthropocene (Crutzen & Stoermer, 2000) especially due to cli
mate change and pressures from intensive grazing by livestock (Han,
Brierley, Cullum, & Li, 2016; Wilcox, Sorice, & Young, 2011).
Within the alpine grasslands of the QTP, the dominant vascu
lar plants are three endemic species comprising the entirety of the
genus, Orinus Hitchcock (Figure 1; Poaceae; Liu et al., 2018; Su, Wu,
Li, & Liu, 2015). Orinus consists of clonal grasses and was estab
lished in 1933 by Hitchcock based on the type species O. arenicola
Hitchc. [=O. thoroldii (Stapf ex Hemsl.) Bor] collected in the Kashmir
region. The genus is sister to Cleistogenes Keng in subtribe Orininae
P. M. Peterson, Romasch. & Y. Herrera from the QTP (Peterson,
Romaschenko, & Arrieta, 2016; Soreng et al., 2017). The species
of Orinus occur especially in high‐elevation, xeric areas of the QTP.
Among the three species, Orinus thoroldii is primarily distributed in
the western QTP, O. kokonoricus (K. S. Hao) Tzvelev occurs in the
eastern QTP, and O. intermedius X. Su & J. Quan Liu is native to the
southeastern QTP.
Orinus is especially characterized by long scaly rhizomes with nu
merous nodes, which serve as the basis for its clonal reproduction.
It also reproduces sexually via seeds borne on sparse panicles within
pedicelled and laterally compressed spikelets that have 3‐ to 5‐veined
lemmas with short awns (Su, Liu, Wu, Luo, & Liu, 2017). Orinus thor
oldii is distinguished from O. kokonoricus by having pubescent leaf
by a Mantel test that showed significant positive correlation between geographic and
genetic distance (r = 0.05, p < 0.05). Recent isolation may explain why Orinus differs
from many other clonal species by exhibiting the highest diversity within populations
rather than among them.
KEYWORDS
alpine grassland, amplified fragment length polymorphism, genetic variation, hybridization,
population biology
6016 
|
   LIU et aL.
blades and dark brown or pu rple spikelet s with two to six flower s (Su
et al., 2017). Leaf blades in O. kokonoricus are glabrous and spikelets
are yellow or white and bear one to three flowers (Su et al., 2017). In
a recent taxonomic revision of the genus, Su et al. (2017) described
O. intermedius, a new species, as most similar to O. kokonoricus but
bearing intermediate features between O. kokonoricus and O. thorol
dii, such as having caryopses and stamen of intermediate lengths. Su
et al. (2017), Su et al. (2015) recognized O. intermedius as distinct on
account of its rhizomes bearing sparse small scales compared to O.
kokonoricus and O. thoroldii, which have many larger scales. However,
Su et al. (2015) suspected that O. intermedius may ha ve a hybr id or igi n
with the other two species as progenitors. Nevertheless, O. interme
dius appeared more likely to be an incompletely isolated sister of O.
kokonoricus than a hybrid based on a population‐level phylogenetic
study comprising chloroplast and nuclear ribosomal internal tran
scribed spacer (ITS; Liu et al., 2018). At present, the putative hybrid
status of O. intermedius remains incompletely resolved.
Orinus represents an important model for evolution and biodi
versity of vascular plants within the grasslands of the QTP for sev
eral reasons. As the dominant vascular plant species within the xeric,
alpine grasslands, Orinus can provide a representative first glimpse
into evolutionary diversification and diversity within this threatened
habitat type (Ma et al., 2017; Sedlacek et al., 2016; Yang et al., 200 4).
Moreover, few population genetics studies have targeted clonal spe
cies, which may exhibit different patterns of diversification than spe
cies that most often reproduce sexually. Finally, Orinus possesses an
extensive system of roots and rhizomes (Cai, 2004; Su et al., 2015;
Su, Yue, & Liu, 2013) that limit soil loss within the wind‐swept alpine
gr as sland s of th e QT P (Figu re 1; Yang et al., 2004). Th us , the diver sity
and di ve rsi fic ation of th e gen us can al so yiel d insig ht s into the timi ng ,
mechanisms, and ecological consequences of regional desertification
(Guo et al ., 2002; Ha n, Fan g, & Berg er, 2012; see also Liu et al ., 2018).
In this report, we investigated diversity and diversification in
Orinus using analyses of amplified fragment length polymorphism
(AFLP) markers. We specifically sought to address the following
questions: (a) Are there three distinct species of Orinus, and do these
exhibit recent or ongoing gene flow? and (b) Does O. intermedius
have a hybrid origin? Additionally, we used our data to compare pat‐
terns of diversity and diversification in Orinus to other clonal plants,
especially of alpine regions.
2 | MATERIALS AND METHODS
2.1 | Taxonomic sampling strategy and obtaining
AFLPs
The AFLPs analyzed in this study were previously published in Liu
et al. (2018) where they were used in a distance‐based phylogenetic
analysis complementar y to phylogenetic reconstructions based on
chloroplast and nuclear gene sequences. Here, we analyzed the
AFLPs for the first time using population genetics methods and ap‐
plied them to perform the first explicit test of the hybrid origin hy‐
pothesis for O. intermedius. Below, we describe obtaining the AFLPs,
FIGURE 1 Photographs showing the species of Orinus in their
habitat s: (a) O. kokonoricus, (b) O. intermedius, and (c) O. thoroldii
    
|
 6017
LIU et aL .
including taxonomic sampling, in brief, and refer to our prior work for
greater detail (Liu et al., 2018).
We sampled a total of 231 individuals of the genus Orinus from
48 natural populations from 28°21′51.0 to N and 79°48′9.0 to
102°30′59.7E representing the distributional ranges of the species
and including the type localities of each (Figures 1 and 2, Table 1).
As species of Orinus are do min ant wi thi n the gra ssl a nds of the QT P,
the boundaries among populations can be difficult to determine.
Thus, we sampled from localities at least 30 km apar t to ensure, to
the best of our abilities, the genetic independence of the sampling
localities except via dispersal of pollen, seeds, or propagules. Per
population, we collected fresh leaf blades from three to five veg
etative units spaced at least 20 m apart in order to try and sample
genetically unique individuals of this clonal species. Our sampling
protocol was designed to detect the diversity of genotypes within
and among populations covering a vast region, especially to cap
ture rare alleles (e.g., as in Pluess & Stöcklin, 2004), and, notably,
our objectives do not include determining the abundance of clonal
genotypes within populations at this time. Nevertheless, we re
gard our within‐population sampling as preliminar y and acknowl
edge that greater depth of sampling will yield deeper insights into
some aspect s of diversity and diversification in the genus in future
studies. We dried the leaf samples in silica gel. For each popula
tion, voucher specimens and geolocations are reported in Liu et
al. (2018).
For the AFLP analyses of all individuals, we per formed DNA
digestion with DNAs obtained using standard methods (Doyle
& Doyle, 1987; see Liu et al., 2018) and the restriction enzymes
PstI and MseI (40 U/μl; Beijing Dingguo Biotechnology Co., Ltd).
We performed two rounds of PCR on the digestion products com
prising preamplification and selective amplification (Table 2). We
carried out selective amplification (Zuo, Wen, Ma, & Zhou, 2015)
in 25 μl volume of reaction mixture containing of 2.0 μl PstI/MseI
primer combinations (GAA/CAA, GAC/CAC, GAC/CAG, GAC/
CTA, GAG/CAA, GAG/CAG, GAG/CTG, and GAT/CAG; Table 2).
Subsequently, we separated and analyzed the fluorescently‐la
be led am pli f i c a tion pro duc ts on an AB I PRISM 377 DNA Sequ enc e r
(Applied Biosystems) using GeneScan ROX‐500 with an internal
size standard. We scored the presence or absence of the resulting
AF L P prod u c t s (Fig ure 3) usin g Ge neSc an 3. 1 (A ppli e d Bios y s tem s).
We imported the scored data into Binthere (Garnhart, 2001) and
MG (Zhou & Qian, 2003) to generate a presence/absence, or 0/1
binary, matrix (data available from the Dryad Digital Repository:
https://doi.org/10.5061/dryad.403j5s4) for downstream analyses.
2.2 | Genetic diversity and population
genetic structure
For each population, we calculated the average standard deviation
among markers. Thus, a population with all 1s or 0s for a particular
FIGURE 2 Localities of O. thoroldii (green), O. kokonoricus (blue), and O. intermedius (red) sampled in this study
6018 
|
   LIU et aL.
TABLE 1 Localities for samples of Orinus collected for this study
Population code Species name Locality NLatitude (N) Longitude (E) Altitude (m) Voucher specimens
1O. kokonoricus Xiahe, Gansu 535°11′9.2″ 102°30′59.7″ 3 ,007 X. Su, 11,295
2Gonghe, Qinghai 536° 11′ 3.0 101°59′16.9″ 2, 826 X. Su, 12,040
3Xining, Qinghai 536°37′10.8 101°4 4′1 .7 2,547 X. Su, 12,042
4Haiyan, Qinghai 536°50 ′8. 3″ 10 0 °50′6 . 1″ 3,305 X. Su, 11,005
5Gonghe, Qinghai 536°6′0.5 100°24′16.0″ 2,998 X. Su, 11,016
6Gonghe, Qinghai 536°2′21.8 10 0°18′55. 6″ 3,072 X. Su, 12,038
7Yushu, Qinghai 532°58′55.6″ 97°1 4′ 17.6″ 3,493 X . Su, 13,095
8Nangqian, Qinghai 532°32′50.6″ 96 ° 11′45. 2 4,119 X. Su, 11,075
9Nangqian, Qinghai 532°29′24.4″ 9 16′ 7. 5″ 3,728 X. Su, 11,080
10 Jiangda, Xizang 531°20′20.8″ 98°8′2.2″ 3,818 X. Su, 12,032
11 Changdu, Xizang 531°15′20.0″ 97 ° 9 ′4 2 . 4″ 3,298 X. Su, 12,025
12 Changdu, Xizang 531°29′36.7″ 97°12′21.1″ 3,354 X. Su, 12,027
13 Dingqing, Xizang 531 °15′57. 4 95 °4 9′5 7. 0 3,603 X. Su, 11,152
14 Luolong, Xizang 530°4 6′1 . 2″ 95°3 4′27.7″ 3,76 2 X. Su, 13,081
15 Leiwuqi, Xizang 431°45′12 .8″ 96°19 ′51 . 2″ 3 ,624 X . Su, 13,090
16 Dingqing, Xizang 531° 36′18 .9 95°6′53 .8″ 3,786 X. Su, 13,087
17 Bianba, Xizang 530 °49 ′19. 1″ 94 °51′3 0.7 3,999 X. Su, 13,082
18 Bianba, Xizang 530 ° 58′40 . 3 94°43′35.3″ 3,597 X . Su, 13,083
19 Biru, Xizang 531°31′7.8″ 9 3 1′59.7 3,991 X. Su, 13,085
20 O. intermedius Aba, Sichuan 532°45′26.7″ 102°3′33.8″ 3,319 X. Su, 12,003
21 Banma, Qinghai 433°1′28.9″ 100°41′52. 3″ 3,852 X . Su, 13,032
22 Aba, Sichuan 432°54′45.0″ 101°46′59.3″ 3,379 X. Su, 11,285
23 Aba, Sichuan 532°54′28.2″ 101°46′25.5 3,358 X. Su, 12,0 01
24 Aba, Sichuan 431°46′16.2″ 1 0 0 °5 8 ′5 7.1″ 3,478 X. Su, 12,007
25 Luhuo, Sichuan 531°38′35. 0″ 10 0 °17′15.9 3,534 X. Su, 13,058
26 Daofu, Sichuan 330 °37′17.7″ 101°24′15 .5″ 3,573 X. Su, 12,0 08
27 Mangkang, Xizang 529°32′28.8″ 98 °15′18.5″ 3 ,522 X. Su, 13,075
28 Mangkang, Xizang 429°32′27.2″ 98°15′3.3″ 3,507 X. Su, 12,016
29 O. thoroldii Zhanang, Xizang 429°15′23 .9 91°22′7.1 3,586 X. Su, 11,195
30 Qushui, Xizang 529°29′46.0″ 90°5 6′14.6″ 3 ,617 X. Su, 11,010
31 Rikaze, Xizang 529 °18′0.4″ 89°46′7.3″ 3,767 X. Su, 11,018
32 Kangma, Xizang 528°33′20.0″ 89°41′2.0″ 4,412 X. Su, 11,132
33 Lazi, Xizang 529°9′28.3″ 8 10′16 .9″ 4,060 X. Su, 11,033
34 Dingjie, Xizang 528° 21′ 51. 0 87 °45′57. 0 4,324 X. Su, 11,120
35 Dingri, Xizang 528°39′34.2″ 8 7 ° 7 ′45.6″ 3, 852 X. Su, 11,123
36 Dingri, Xizang 528°39′34.2″ 8 7 ° 7 ′45.6″ 3, 852 X. Su, 11,119
37 Angren, Xizang 52 9°26′24 .0″ 86°39′52 .6″ 4, 593 X. Su, 11,034
38 Jilong, Xizang 528°46′6.3″ 85°32′14.3″ 4,614 X . Su, 11,100
39 Shaga, Xizang 429°23′31. 5″ 8 3 0 57.4 4, 677 X. Su, 11,039
40 Shaga, Xizang 529°0′27.0″ 85°26′48.8″ 4,687 X. Su, 11,078
41 Shaga, Xizang 529° 30 ′1.4″ 84°33′39.6″ 4,578 X. Su, 11,0 43
42 Zhongba, Xizang 529°41′7.9″ 8 4 ° 8 ′4 8 .1″ 4,563 X . Su, 11,0 44
43 Zhongba, Xizang 529°59′45.6″ 83° 31′4 3. 1″ 4,582 X. Su, 11,045
44 Pulan, Xizang 530°48′35.8″ 81°34′22 .5″ 4, 610 X . Su, 11,0 49
45 Pulan, Xizang 53 0°2 1′5 8.5 81°9 ′8.3 4,260 X. Su, 11,050
46 Pulan, Xizang 53 1 0′42 .6″ 80°45′26.8″ 4,427 X. Su, 11,054
47 Ali, Xizang 532 ° 3 4 17.9 80 °3′10.7 4, 451 X . Su, 11,056
48 Zhada, Xizang 531°28′46.0″ 79 °4 8 9.0 4,434 X . Su, 11,070
Abbreviation: N, number of individuals sampled for amplified fragment leng th polymorphism experiments.
    
|
 6019
LIU et aL .
marker would have a standard deviation of zero for the marker, and
clonal individuals should have an average deviation of zero. However,
clonal individuals may vary in AFLP analyses due to errors in obtain
ing or processing the data or due to somatic mutations. Thus, we
regarded any population with less than 0.05 average deviation as
being comprised exclusively of clones, and we sought to exclude
these populations from downstream analyses.
We assessed genetic diversity in Orinus, including natural
breaks potentially corresponding to species, by analyzing binary
matrix of AFLP bands. We analyzed the matrix in POPGENE 1.32
(Yeh, Yang, & Boyle, 1999) to calculate the following summary
statistics: percentage of polymorphic loci (PPL), observed number
of alleles (Na), effective number of alleles (Ne), expected hetero
zygosity (He; Kimura & Crow, 1964), and Shannon's information
inde x (I; Le wo ntin, 1972 ). We also analy zed the bi nar y mat rix usin g
the NTSYS‐pc 2.l statistical package (Rohlf, 200 0). Specifically, in
NTSYS, we generated a pair wise similarit y matrix with a simple
matching coefficient according to the SIMQUAL algorithm. We
also used SAHN in NTSYS package to construct a UPGMA tree
based on Nei's genetic distance for assessment of relationships
among individuals and populations of Orinus, and we estimated
support for the UPGMA tree using 2000 bootstrap replicates in
Winboot software (Yap & Nelson, 1996; see also Liu et al., 2018).
We calculated a genetic similarity matrix from the AFLP data ac
cording to the method of Nei and Li (1979) and visualized genetic
variation among individuals with a principal coordinate analysis
(PCoA) performed in GENALEX 6.5 (Peakall & Smouse, 2012).
In addition, we constructed a similarity‐based network using
the Neighbor‐Net algorithm based on Jaccard's distances within
SplitsTree 4.13 (Huson & Br yant, 2006) to further depic t relation
ships among individuals and populations and species based on the
AFLP datasets.
We also sought to evaluate the genetic differentiation between
and within populations of the three species of Orinus using average
FST, analysis of molecular variance (AMOVA; Excoffier, Smouse, &
Quattro, 1992), and a Mantel test. We calculated FST using Arlequin
3.11 (Excoffier, Laval, & Schneider, 2005) and determined sig‐
nificance of the pairwise FST comparisons via permutation tests
(n = 1,000) with a sequential Bonferroni correction. For the AMOVA,
we tested significance with nonparametric permutation using 9,999
replications. We performed Mantel tests on the distance matrix of
Jaccard's coefficients calculated in GENALEX 6.5 (Peakall & Smouse,
2012) in order to detect the correlations between genetic distances
generated from each of the AFLP primer pairs, and geographic dis‐
tances of populations derived from geographic coordinates using
AFLP datasets (Ehrich, 2006). For the Mantel tests, we computed
correlation coefficients and assessed the significance with 1,00 0
permutations.
We conducted a Bayesian analysis of the population structure in
Orinus using STRUC TURE 2.3 (Falush, Stephens, & Pritchard, 2007;
Hubisz, Falush, Stephens, & Pritchard, 2009; Pritchard, Stephens, &
Donnelly, 2000) to determine whether the structure was consistent
with species boundaries and to infer the relative amounts of gene
flow between each species. We performed the analyses using an
admixture model with independent allele frequencies for 10 inde
pendent runs for the number of clusters (K) ranging from 1 to 10.
We applied 1 × 106 Markov chain Monte Carlo repetitions with a
burn‐in rate of 25%. We summarized the outputs of all runs with the
Web‐based software Structure Harvester (Earl & von, 2012), and we
calculated the average similarity coefficients among runs for each
K. We determined the optimal K using two methods: the point of
diminishing returns for adding additional K (i.e., elbow method) and
the value representing the greatest change from the previous value
(i.e., ΔK; Evanno, Regnaut, & Goudet, 2005; Pritchard et al., 20 00).
2.3 | Testing AFLP data against explicit genetic
models of hybridization
We tested the hybrid status of O. intermedius using the Bayesian im
plementation in NewHybrids (Anderson & Thompson, 2002) ver
sion 2.0+ Developmental (https://github.com/eriqande/newhybrids).
Specifically, we tested the 231 sampled individuals for their compat
ibility with five genetic models: that each is genetically (a) O. kokonori
cus, (b) O. thoroldii, (c) a true hybrid of O. kokonoricus and O. thoroldii, (d)
TABLE 2 Adapters and primer combination sequences used in
this study
Primer Name Sequence
Adapters
P‐L Pst I‐adapter 5′‐CTCGTAGACTGCGTACATGCA‐3′
P‐R Pst I‐adapter 5′‐TGTACGCAGTCTAC‐3′
M‐L Mse I‐adapter 5′‐GACGATGAGTCCTGAG‐3
M‐R Mse I‐adapter 5′‐TACTCAGGACTC AT‐3′
Preamplification primer
P01 Pst I 5′‐GACTGCGTACATGCAG‐3′
P02 Mse I 5′‐GATGAGTCCTGAGTAAC‐3′
Selective amplification primer
A‐1 Pst I‐GAA 5′‐GACTGCGTACATGCAGA A‐3′
Mse I‐CA A 5′‐GATGAGTCCTGAGTAACAA‐3′
B‐2 Pst I‐GAC 5′‐GACTGCGTACATGCAGAC‐3′
Mse I‐CAC 5′‐GATGAGTCCTGAGTAACAC‐3′
B‐3 Pst I‐GAC 5′‐GACTGCGTACATGCAGAC‐3′
Mse I‐CAG 5′‐GATGAGTCCTGAGTAACAG‐3′
B‐5 Pst I‐GAC 5′‐GACTGCGTACATGCAGAC‐3′
Mse I‐ C TA 5′‐GATGAGTCCTGAGTAACTA‐3
C‐1 Pst I‐GAG 5′‐GACTGCGTACATGCAGAG‐3′
Mse I‐CA A 5′‐GATGAGTCCTGAGTAACAA‐3′
C‐3 Pst I‐GAG 5′‐GACTGCGTACATGCAGAG‐3′
Mse I‐CAG 5′‐GATGAGTCCTGAGTAACAG‐3′
C‐7 Pst I‐GAG 5′‐GACTGCGTACATGCAGAG‐3′
Mse I‐CTG 5′‐GATGAGTCCTGAGTAACTG‐3′
D‐3 Pst I‐ GAT 5′‐GACTGCGTACATGCAGAT‐3′
Mse I‐CAG 5′‐GATGAGTCCTGAGTAACAG‐3′
6020 
|
   LIU et aL.
a hybrid of O. kokonoricus and O. thoroldii backcrossed with O. kokonori
cus, and (e) a hybrid of O. kokonoricus and O. thoroldii backcrossed with
O. thoroldii. These models cannot explicitly test the possibility that O.
intermedius is an independent species not derived from hybrid origins.
However, O. intermedius individuals should be resolved under model 1
or 2 if the species is not a hybrid but, instead, shared a common ances
tor with either O. kokonoricus or O. thoroldii that does not include the
other species. Additionally, models 4 and 5 cannot be differentiated
from low levels of int rogression that may occur among species that are
differentiating in allopatry, but we interpret these results within the
context of our other statistical analyses. For individuals within popu
lations, we averaged the posterior probabilities of compatibility with
each model. Thus, our results represent the average posterior prob
ability for the best genetic model for each population. We also present
the results for each individual in Appendix A.
3 | RESULTS
3.1 | Genetic diversity
Among 64 pairs of EcoR I/MseI primer combinations, we success
fully obtained eight pairs of selective AFLP primers that could
amplify fragments with good coverage in the 231 individuals rep
resenting 48 populations of the three species of Orinus (Table 1,
Figure 3). For the eight primer pairs, all summary and genetic sta
tistics for the primer pairs are presented in Table 3. The eight
pairs produced a total of 1,324 unambiguous and repetitious AFLP
amplification bands across all the samples from O. thoroldii and
O. kokonoricus, and 1,261 in O. intermedius. The total number of
AFL P amplifi cation bands fo r each pr im er pair range d from 15 4 (P‐
GAC/M‐CAC) to 185 (P‐GAT/M‐CAG) with an average of 166, 150
(P‐GAA/M‐C AA) to 179 (P‐GAC/M‐CAC) with an average of 166,
and 143 (P‐GAA/M‐CA A) to 171 (P‐GAG/M‐CAA) with an average
of 158. Among the AFLP amplification bands, 1,313 (99.17%) were
polymorphic in O. thoroldii, 1,315 (99.32%) in O. kokonoricus, and
1,242 (98.49%) in O. intermedius. The total number of polymor
phic bands for each primer pair varied from 152 (P‐GAC/M‐CAC)
to 185 (P‐GAT/M‐CAG) with an average of 164, 150 (P‐GAA/M‐
CAA) to 179 (P‐GAC/M‐CAC) with an average of 164, and 142
(P‐GAA/M‐C AA) to 171 (P‐GAG/M‐CA A) with an average of 155.
Each primer pair yielded rich and clear patterns among the three
species of Orinus. The allele size of O. thoroldii and O. intermedius
ranged from 70 to 500 bp, while that of O. kokonoricus ranged
from 60 to 500 bp. In addition, the percentage polymorphism of
FIGURE 3 Fluorescently‐labeled
AFLPs generated using different primer
combinations. (a) P‐GA A/M‐CA A, (b)
P‐GAC/M‐C AC, (c) P‐GAC/M‐CTG, (d)
P‐GAG/M‐CTA, (e) P‐GAG/M‐CAA , (f)
P‐GAG/M‐CAG, (g) P‐GAG/M‐CTG, and
(h) P‐GAT/M‐CAG
    
|
 6021
LIU et aL .
each species of Orinus varied from 98.11% to 100% with an aver
age of 99.15% in O. thoroldii, 95.78% to 100% with an average of
99.32% in O. kokonoricus, and 96.27% to 100% with an average of
98.26% in O. intermedius among the primer pairs.
The mean Na of O. thoroldii was 1.99, which varied from 1.98
to 2.00, while the mean Ne and He varied from 1.27 to 1.34 with a
mean value of 1.32 and from 0.17 to 0.21 with the mean value of
0.20, respectively. The mean value of I was 0.31 and ranged from
0.27 to 0.34. For Orinus kokonoricus, the Na, Ne, He, and I ranged,
respectively, from 1.96 to 2.00, 1.29 to 1.37, 0.18 to 0.23, and 0.29
to 0.35. The mean values were 1.99, 1.32, 0.20, and 0.32, also re
spectively. Similarly, the mean values of Na, Ne, He, and I for O. inter
medius were 1.98, 1.33, 0.21, and 0.33, and the variation of these
ranged from 1.96 to 2.00, 1.29 to 1.38, 0.19 to 0.23, and 0.30 to
0.37, all respectively. All measures revealed high levels of genetic
diversit y among the three species of Orinus. In particular, O. inter
medius showed the highest level of genetic diversity among the
three species according to Shannon's information index (I = 0.33).
3.2 | Population genetic structure
Analysis of molecular variance (AMOVA) based on AFLP datasets
and inbreeding coefficients (FST; Table 4) indicated significant
interspecific genetic differentiation across the natural distribu
tion of the three species of Orinus (FST = 0.19, p < 0.01). Variation
within populations represented 56.65% of the total genetic varia
tion, while variation among species comprised 30.04%, and varia
tion among populations within each species was 13.31%. Among
TABLE 3 Summary Statistics for eight amplified fragment length polymorphism selective primer combinations in the present study
Species name Selective nuclear Polymorphism bands Amplification bands PPL (%) Size range (bp) NaNeHeI
O. thoroldii P‐GAA/M‐CAA 161 164 98.17 70–5 00 1.98 1.33 0.20 0.32
P‐GAC/M‐CAC 152 154 98.70 70 –500 1.99 1.33 0.20 0.31
P‐GAC/M‐CAG 167 17 0 98. 24 70 –50 0 1.98 1.27 0 .17 0.27
P‐GAC/M‐CTA 156 159 98.11 71–4 98 1.98 1.30 0 .19 0.30
P‐GAG/M‐CAA 174 174 100 70 –499 2.00 1.30 0.19 0.31
P‐GAG/M‐CAG 159 159 100 70–500 2.0 0 1.34 0.21 0.33
P‐GAG/M‐CTG 159 159 100 70– 494 2.00 1.33 0. 21 0.33
P‐GAT/M‐CAG 185 185 100 71– 498 2.00 1.33 0.21 0.34
Tot al 1,313 1 ,324 9 9.17 560–3,988
Mean 164 166 99.1 5 70–499 1 .99 1.32 0. 20 0.31
O. kokonoricus P‐GAA/M‐CAA 150 150 100 70 –500 2.0 0 1.37 0.23 0.35
P‐GAC/M‐CAC 17 9 179 10 0 70–498 2.00 1.29 0.19 0.31
P‐GAC/M‐CAG 159 166 95.78 7 1– 49 8 1.96 1.29 0.18 0.29
P‐GAC/M‐CTA 161 163 98.77 70– 499 1.99 1.32 0.20 0. 31
P‐GAG/M‐CAA 170 170 100 70–499 2.00 1.33 0. 20 0.33
P‐GAG/M‐CAG 16 4 164 100 60–497 2.00 1.32 0.20 0.32
P‐GAG/M‐CTG 174 174 100 70–493 2.00 1. 31 0.20 0.37
P‐GAT/M‐CAG 158 158 100 71–5 0 0 2.00 1.34 0.21 0.33
Tot al 1,315 1 ,324 99. 32 551–3,984
Average 164 166 99.3 2 69–498 1.99 1.32 0.20 0. 32
O. intermedius P‐GAA/M‐CAA 142 14 3 99.3 0 70–499 1.99 1.38 0.23 0.37
P‐GAC/M‐CAC 16 3 163 100 71– 49 8 2.00 1.33 0.21 0.34
P‐GAC/M‐CAG 155 161 96. 27 70–499 1.96 1.29 0 .19 0.30
P‐GAC/M‐CTA 152 154 98.70 70–50 0 1.99 1.36 0.22 0.35
P‐GAG/M‐CAA 171 171 98.28 70–489 1.98 1.31 0.20 0.32
P‐GAG/M‐CAG 142 146 9 7. 2 6 70–490 1.97 1.34 0 .21 0.33
P‐GAG/M‐CTG 152 155 98.06 70–498 1.98 1.31 0.20 0.33
P‐GAT/M‐CAG 165 168 98.21 71–497 1.98 1.32 0.21 0.33
Tot al 1,242 1, 261 98 .49 562–3,969
Average 155 158 98.26 70–496 1 .98 1.33 0. 21 0.33
Note. PPL, percentage of polymorphic loci; Na, observed number of alleles; Ne, effective number of alleles; He, expected heterozygosity; I, Shannon's
information index.
6022 
|
   LIU et aL.
the three species of Orinus, the genetic variation between O.
thoroldii and O. kokonoricus was the highest (FST = 0.46, p < 0.01),
with 33.67% of the variation between species and 54.34% within
populations. For O. thoroldii and O. intermedius, the genetic varia
tion was also high (FST = 0.44, p < 0.01), and 31.21% of the total
variation was interspecific while 55.91% was within populations.
Genetic variation between O. kokonoricus and O. intermedius was
lower, at 18.00% with a corresponding average FST value of 0.35,
while 65.04% of the variation was within populations. In all spe
cies, intrapopulational genetic variation was much higher than
interpopulational.
The UPGMA tree indicated that the 231 individuals from 48
populations of Orinus comprised three clades (Figure 4) corre
sponding to three geographically clustered groups of populations
within the QTP and consistent with species identities. Thus, the
UPGMA tree revealed geographic structure within the genus
Orinus with three independent clades consisting of O. thoroldii,
O. kokonoricus, and O. intermedius, which is sister to O. kokonori
cus (Figure 4). Similarly, the Mantel tests agreed that geography is
positively correlated with genetic divergence (r = 0.05, p < 0.05).
Discre te clus ter corre sponding to specie s an d geograp hy was sup
ported by the principal coordinate analysis (PCoA; Figure 5). The
first two axes in the PCoA plot explained 23.31% and 18.20% of
variation, respectively (data not shown). The PCoA axis 1 sepa
rated O. thoroldii from the other two species, while axis 2 yielded
greater separation for O. intermedius. Additionally, the split
network revealed three splits, corresponding to the three species
of Orinus (Figure 6). According to STRUCTURE (Figu re 7 ), t he opti
mum K value was K = 3 and the highest peak of ΔK values also ap
peared at K = 3. The three clusters predicted by the STRUCTURE
analysis corresponded to the three recognized species of Orinus
(Figure 7d). In a separate analysis with K = 2, O. kokonoricus and O.
intermedius were clustered together (Figure 7d).
3.3 | Results of genetic models of hybridization
The results of NewHybrids show that models of a single genetic
origin are best suited to most populations (Figure 8; Appendix
A). All populations of O. kokonoricus correspond to O. kokonoricus
origins with posterior probability (pp) of 1.0 except populations
14 and 17 (Figure 2), in which one individual each (Appendix A)
showed trivial pp (<0.01) support for hybrid backcrossing into O.
kokonoricus. Most populations of O. thoroldii had 1.0 pp of having
a genetic origin of solely O. thoroldii stock. For population 33 of
O. thoroldii, one individual showed a trivial pp of representing a
hybrid with backcrossing into O. thoroldii. In contrast, populations
29 and 30 had nontrivial pp for representing hybrid backcrosses
to O. thoroldii (0.48 and 0.21, respectively). Nevertheless, these
support values were lower than for an origin from exclusively O.
thoroldii genetic stock. Among populations of O. intermedius, four
populations (20, 21, 25, and 26) showed 1.0 pp for exclusive ori
gins from O. kokonoricus stock, while three populations (22, 23,
TABLE 4 Results of analyses of molecular variance (AMOVAs) based on amplified fragment length polymorphism markers for the three
species of Orinus
Grouping regions Source of variation df SS VC Percent variation (%) Fixation index
O. thoroldii Among populations 19 4,692.26 25.25 16. 86 FST = 0.17*
Within populations 77 9,5 8 9.10 124. 53 83.14
O. kokonoricus Among populations 18 4,905.54 29.99 19.4 5 FST = 0.20*
Within populations 75 9,3 13 .95 124.19 80.55
O. intermedius Among populations 82,340.80 38.79 23.68 FST = 0.24*
Within populations 30 3, 749.92 124. 80 76 . 32
O. thoroldii and O.
kokonoricus
Among species 17,6 6 4. 9 8 7 7.1 7 33 .67 FST = 0.46*
Among populations within species 37 9,6 0 9. 03 27. 4 6 11.98 FSC = 0.18*
Within populations 153 19,05 3 . 35 124.53 54.34 FCT = 0.34*
O. thoroldii and O.
intermedius
Among species 14, 147. 07 69. 73 31.21 FST = 0.44*
Among populations within species 27 7,0 4 4 . 29 28.77 12.88 FSC = 0.19*
Within populations 108 13, 4 89.3 2 124 .90 55.91 FCT = 0.31*
O. kokonoricus and
O. intermedius
Among species 12,171.07 34.42 18.00 FST = 0.35*
Among populations within species 26 7,246.34 32.45 16.97 FSC = 0.21*
Within populations 105 13,063.87 124.42 65.04 FCT = 0.18*
Tot al Among species 210,080.42 66.08 30.04 FST = 0.19*
Among populations within species 45 11,949. 83 29. 2 7 13.31 FSC = 0.43*
Within populations 183 22,803.27 124.61 56.65 FCT = 0.30*
Note. df, degrees of freedom; SS, sum of squares; VC, variance components; FST, variance among populations; FSC, variance among populations within
species; FCT, variance among groups relative to total variance. Significant level:
*p < 0.01.
    
|
 6023
LIU et aL .
and 24) showed high pp for O. kokonoricus origins and trivial pp
for representing hybrid backcrosses with O. kokonoricus. Notably,
two populations of O. intermedius, 27 and 28, had 1.0 pp and
0.77 pp, respectively, for representing hybrid backcrosses with O.
kokonoricus.
4 | DISCUSSION
4.1 | The hybrid origin of Orinus intermedius
In our prior work, we have hypothesized that Orinus intermedius (Su et
al., 2017) may be either a hybrid of O. kokonoricus and O. thoroldii or an
FIGURE 4 Dendrogram of the three species of Orinus generated by unweighted pair group method analysis (UPGMA) cluster analysis
from the similarit y matrix obtained using amplified fragment length polymorphism genetic distance
FIGURE 5 A two‐dimensional plot of
the principal coordinate analysis (PCoA)‐
based variation of amplified fragment
length polymorphism markers within the
three species of Orinus. Tick marks on
axes are in increment s of 1.0, and 0.0 on
each axis is indicated by a gray line
PC1 (23.31%)
PC2 (18.20%)
O. thoroldii
O. intermedius
O. kokonoricus
6024 
|
   LIU et aL.
incompletely diverged sister of O. kokonoricus. Here, our AFL P da ta are
consistent with most populations of O. kokonoricus and O. intermedius
sharing a common ancestor, and, thus, a common genetic stock, that
is not shared with O. thoroldii. Therefore, our data do not support a
hybrid origin for O. intermedius. However, we observed that two pop
ulations of O. intermedius are consistent with a backcrossing model.
However, this likely represents a level of introgression occurring con
temporaneously with speciation processes, rather than backcrossing,
as we did not detect any true hybrid individuals or populations.
4.2 | Species limits in Orinus and introgression
Previously, we suggested that Orinus represents three species and
noted that genetic isolation among all species of Orinus is nearly, but
not entirely, complete (Liu et al., 2018; Su et al., 2017, 2015). The
present study is congruent with our prior work in showing that the
three species of Orinus are largely distinct, especially according to
the UPGMA (Figure 4), STRUC TURE (Figure 7), AMOVA (Table 4),
and SplitsTree (Figure 6). However, some gene flow does continue
to occur among all species based on the result s of these same analy
ses and may also explain the nonzero probabilities of backcrosses
within some populations of O. kokonoricus and O. thoroldii according
to NewHybrids (Figure 8; Appendix A).
Gene flow between O. intermedius and O. kokonoricus may en
able them to maintain the higher levels of genetic diversit y that we
detected, compared with O. thoroldii, which is more genetically iso
lated. In contrast to our results, it is relatively common that more
widely spread species, such as O. thoroldii, maintain greater genetic
diversit y than more geographically restricted species (Hamrick &
Godt, 1989; Karron, 1987; Xue, Wang, Korpelainen, & Li, 2005), such
as O. intermedius and O. kokonoricus. High diversity within O. inter
medius and O. kokonoricus is likely due to their ongoing speciation
(Liu et al., 2018), in which barriers to gene flow remain incomplete.
Relatedly, due to earlier divergence time of O. thoroldii, it may have
had more time in isolation to undergo some degree of genetic drift.
Orinus thoroldii is not only more genetically distant from its conge
ners (Figure 5), but also more geographically distant. Thus, genetic
differentiation in Orinus may be mediated by reduced gene flow ov er
greater geographic distances as is consistent with an allopatric mode
of speciation as has been observed in other plant species of the QTP
(Ge, Zhang, Yuan, Hao, & Chiang, 2005; Hu et al., 2016; Liu, Wang,
Geng, et al., 2006; Zhang, Chiang, George, Liu, & Abbott, 20 05).
4.3 | Population and species diversification history
in Orinus compared to other clonal species
Many clonal species exhibit a common pattern of diversity, which is
low or intermediate within populations and very high among them
(Ellst r and & Roo se, 1987; Li & Ge, 20 01). This pat ter n has been docu
mented in other clonal grasses, such as Psammochloa villosa Hitchc.
(Poaceae; Li & Ge, 2001; Yu, Dong, & Krüsi, 2004). Overall, for
clonal species, this pattern suggests that interpopulation movement
of propagules is rare and that diversity within populations may be
largely explained by the founder genotypes and, in some cases, out
crossing among genotypes (e.g., Carex curvula, Dryas octopetala L.,
Salix herbacea L., and Vaccinium uliginosum L.; de Witte, Armbruster,
Gielly, Taberlet, & Stöcklin, 2012).
Orinus differs from other clonal plants by showing the highest
diversity within populations and limited diversity among them, in‐
cluding populations within and among species. This is an uncommon
pattern of diversity for clonal species, but one which has been pre
viously observed (Pluess & Stöcklin, 2004). In particular, Geum rep
tans L. (Rosaceae), a clonal alpine species of the Swiss Alps, exhibits
FIGURE 6 Neighbor‐Net split network of the three species
of Orinus based on amplified fragment length polymorphism data
using Jaccard's distances. Lines of green, blue and red represent O.
thoroldii, O. kokonoricus, and O. intermedius, respectively
10.0
100
O. thoroldii
O. kokonoricus
O. intermedius
98.7
FIGURE 7 Results of the Bayesian clustering analysis in STRUC TURE of the 231 individuals representing three species of Orinus. (a) The
probability of the data Ln P(D) (±SD) against the number of K cluster, and increase of Ln P(D) given K, calculated as (Ln P(D)k−Ln P(D)k−1). (b)
K values from the mean log‐likelihood probabilities from STRUCTURE runs where inferred cluster (K) ranged from one to ten. (c) Bayesian
inference of the number of clusters (K) for the three species of Orinus. (d) Estimated genetic clustering for K = 2 and 3, where unique colors
correspond to assignment to dif ferent clusters
    
|
 6025
LIU et aL .
012345678910
K
LnPD
-5E+4
-45E+4
-15E+4
-25E+4
-35E+4
12345678910
K
Delta K
0
300
100
200
123456789
K
Delta K
0
350
50
150
250
O. kokonoricus O. intermediusO. thoroldii
O. kokonoricus O. intermediusO. thoroldii
K = 2
K = 3
(a) (b)
(c)
(d)
6026 
|
   LIU et aL.
this pattern of diversity probably due to ongoing gene flow, despite
geographic isolation of populations on sky islands (Pluess & Stöcklin,
2004; see also sky islands in Hughes & Atchison, 2015; Körner, 2004).
In Orinus, gene flow is unlikely to account for this pattern of diversity,
especially among species, because the species are, overall, distinct,
and because the species probably experience limited gene flow by
rare dispersals of rhizome sections and occasional pollen movement
by wind, water, and animal visitors. Within Orinus, there is no obvi
ous mechanism for seed dispersal. Therefore, alternatively to ongo
ing, regular gene flow, recency of isolation of species and populations
of Orinus within the QTP may explain the limited genetic diversity at
the interspecific and interpopulational levels, respectively (e.g., as in
Cruickshank & Hahn, 2014). Indeed, Orinus may have begun diversify
ing within the QTP during the latter part of the Pliocene (2.85 million
years ago; Liu et al., 2018), which rep resents the end of a global period
of evol ution of mode rn alpin e species (Hu ghes & Atchison, 2015). This
alternative also requires that the original populations possessed high
genetic diversity that has been preserved, at least partially, to present
times. High diversity within ancestral populations often results from
isolation by vicariance, rather than dispersal, events (Mayr, 1942; see
also Harr is , Icker t‐Bond , & Ro dgu ez, 2018; Kropf, Com es, & Kad ere it,
2006). Vicariance within the QTP is often invoked to explain com
monly observed patterns in the diversification of plant populations or
species (e.g., Yang, Li, Ding, & Wang, 2008), especially the divergence
of western lineages, such as O. thoroldii, from eastern ones, such as O.
kokonoricus and O. intermedius. Moreover, vicariance in the region may
be attributed to either the topographic or climatic effects of recent
geomorphism (Jia, Liu, Wang, Zhou, & Liu, 2011; Liu et al., 2013; Wen
et al., 2014; Yang et al., 2008), and topology may be a better explana
tion for divergence in the case of Orinus, because the ecological niches
of species are similar (Su et al., 2015). Overall, the pattern of genetic
diversity within Orinus could eventually come to resemble patterns
overserved for other clonal species (Ellstrand & Roose, 1987; Li & Ge,
2001) given sufficient evolutionary time. However, as a caveat of the
pre sent stud y, we also cannot rule out that our li mited sam pling within
populations accounts for some parts of the patterns in diversity that
we observed, and expanded sampling is needed in the future.
ACKNOWLEDGMENTS
We thank Prof. Jianquan Liu for allowing us to use the molecular
laboratory facility in Lanzhou Univer sity (Lanzhou, China) and Paul
M. Peterson for improving the manuscript. This work was finan
cially supported by the National Natural Science Foundation of
China (Grant Nos. 31260052 and 41761009), the Natural Science
Foundation of Qinghai Province (Grant No. 2017‐ZJ‐904), the Open
Project of Qinghai Provincial Key Laboratory of Crop Molecular
Breeding (Grant No. 2017‐ZJ‐Y14), the “High‐end Innovative
Talents Thousands of People Plan” in Qinghai Province, and the
“135 High‐level Personnel Training Project” in Qinghai Province.
CONFLICT OF INTEREST
None declared.
AUTHOR CONTRIBUTIONS
XS conceived and designed the study. XS, YL, and QG performed the
laboratory work. YL, AJ‐H, QG, XS, and ZR contributed to perform
ing data analyses, interpreting results, and writing the manuscript.
All authors approved the manuscript as written.
DATA ACCESSIBILITY
All data are provided within the text, tables, appendix, and figures,
except for the binary scoring of AFLP bands, which we have sub‐
mitted to the Dryad Digital Repository (https://doi.org/10.5061/
dryad.403j5s4).
ORCID
AJ Harris https://orcid.org/0000‐0003‐3215‐1201
REFERENCES
Anderson, E. C., & Thompson, E. A. (2002). A model‐based method for
identifying species hybrids using multilocus genetic data. Genetics,
160 (3), 1217–1229.
FIGURE 8 Results of testing explicit genetic models in
NewHybrids. Posterior probabilit y of models shown on the y‐axis,
averaged for populations shown on the x‐axis. We tested five
models, but the true hybrid model is not shown, because it received
0.0 pp for all individuals and, thus, all populations. Bars represent
populations 1‐48 consecutively
1.000/0.000/0.000/0.000
[O. kokonoricus]
[O. thoroldii]
0.000/0.000/0.000/1.000
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1357911131517192123252729313335373941434547
0.000/0.250/0.250/0.500
Posterior Probability
Population Number
Legend
[Hybrid backcross with O. thoroldii]
0.500/0.250/0.250/0.000
[Hybrid backcross with O. kokonoricus]
    
|
 6027
LIU et aL .
Beger, M., McGowan, J., Treml, E., Green, A., White, A., Wolff, N.,
Possingham, H. (2015). Integrating regional conservation priorities
for multiple objectives into national policy. Nature Communications,
6, 8208. ht tps://doi.org/10.1038/ncomms9208
Bowman, W. D. (20 00). Bi otic controls ove r ecosys tem response to envi
ronment al change in alpine tundra of the Rocky Mountains. Aliso, 29,
396–400. https://doi.org/10.1579/0044‐7447‐29.7.396
Cai, L. B. (200 4). Two new recorded species of Orinus from Qinghai
Province. Bulletin of Botanical Research, 24, 394–395.
Cortés, A. J., Waeber, S., Lexer, C., Sedlacek , J., Wheeler, J. A., van
Kleunen, M ., … Karrenberg, S. (2014). Small‐scale pat terns in snow‐
melt timing affect gene flow and the distribution of genetic diver‐
sity in the alpine dwar f shrub Salix herbacea. Heredity, 113, 233 –239.
https://doi.org/10.1038/hdy.2014.19
Cruickshank, T. E., & Hahn, M. W. (2014). Reanalysis suggests that ge‐
nomic islands of speciation are due to reduced diversit y, not re‐
duced gene flow. Molecular Ecology, 23, 3133–3157. https://doi.
org /10.1111/me c.12796
Crutzen, P. J., & Stoermer, E. (2000). The “Anthropocene”. Global Change
Newsletter, 41, 12–14.
Davies, T. J., Savolainen, V., Chase, M. W., Moat, J., & Barraclough, T.
G. (2004). Environment al energy and evolutionary rates in flowering
plants. Proceedi ngs of the Royal Society of London B Biological Science s,
271, 2195–2200. https://doi.org/10.1098/rspb.20 04.2849
de Witte, L. C., Armbruster, G. F. J., Gielly, L., Taberlet, P., & Stöcklin, J.
(2012). AFLP markers reveal high clonal diversity and extreme lon‐
gevity in four key arctic‐alpine species. Molecular Ecology, 21, 1081
1097. ht tps://doi.or g/10.1111/j.1365‐294X .2011.05326 .x
Doyle, J. J., & Doyle, J. L. (1987). A rapid DNA isolation procedure for
small quantities of fresh leaf material. Phytochemical Bulletin, 19,
11–1 5 .
Earl, D. A., & von, H. B. M. (2012). Structure Har vester: A website and
program for visualizing Structure output and implementing the
Evanno method. Conservation Genetic Resources, 4, 359–361. ht tps://
doi.org/10.10 07/s12686 ‐011‐9548‐7
Ehrich, D. (2006). AFLPDAT: A collection of R functions for convenient
handling of AFLP data. Molecular Ecology Notes, 6, 603–604. https://
doi.org/10.1111/j.1471‐8286.2006.01380.x
Ellstrand, N. C., & Roose, M. L. (1987). Patterns of genotypic diversity in
clonal plant species. Ame rican Journal of B otany, 74, 123–131. ht tps://
doi.org/10.1002/j.15372197.1987.tb08586.x
Evanno, G., Regnaut, S., & Goudet , J. (2005). Detecting the num‐
ber of clusters of individuals using the software STRUCTURE: A
simulation study. Molecular Ecology, 14, 2611–2620. https://doi.
org/10.1111/j.1365‐294X.2005.02553.x
Excoffier, L., Laval, G., & Schneider, S. (2005). Arlequin (version 3.0):
An integrated software package for population genetics data
analysis. Evolutionary Bioinformatics Online, 1, 47–50. https://doi.
org /10.117 7/11769343050010 00 03
Excoffier, L., Smouse, P. E., & Quattro, J. M. (1992). Analysis of molecu‐
lar variance inferred from metric distances among DNA haplotypes:
Applic ation to human mitochondrial DNA restriction data. Genetics,
131, 479–491.
Falush, D., Stephens, M., & Pritchard, J. K. (2007). Inference of popu‐
lation structure using multilocus genotype data: Dominant markers
and null alleles. Molecular Ecology Notes, 7, 574–578. https://doi.
org /10.1111/j .1471‐8286 .2 007.01758 .x
Feng, C., Tong, C., Zhang, R., Li, G., Wanghe, K., Tang, Y., … Zhao, K.
(2017). Biodiversity and distribution patterns of Triplophysa spe
cies in the northeastern margin of the Tibetan Plateau. Biodiversity
Science, 25, 53–61. ht tps://doi.o rg/10.17520/biods. 20162 59
Garnhart, N. (2001). Binthere V1.0, a program to bin AFLP data. Durham,
NH: University of New Hampshire.
Ge, X. J., Zhang, L. B., Yuan, Y. M., Hao, G., & Chiang, T. Y. (2005). Strong
genetic differentiation of the East Himalayan Megacodon stylophorus
(Gentianaceae) detected by inter‐simple sequence repeats (ISSR).
Biodiversity Conservation, 14, 849–861. https://doi.org/10.1007/
s10531‐004‐0655‐6
Gordon, S. P., Sloop, C . M., Davis, H. G ., & Cushman, J. H. (2012).
Population genetic diversity and structure of two r are vernal pool
grasses in central California. Conservation Genetics, 13 , 117–130.
htt ps://doi.org/10.10 07/s10592‐011‐0269‐y
Guo, Z. T., Ruddiman, W. F., Hao, Q. Z., Wu, H. B., Qiao, Y. S., Zhu, R. X.,
… Liu, T. S. (2002). Onset of Asian desertification by 22 Myr ago in
ferred from loess deposits in China. Nature, 416 , 159–163.
Hamrick, J., & Godt, M. (1989). Allozyme diversity in plant species. In A .
Brown, M. Clegg, A. Kahler, & B. Weir (Eds.), Plant population genetics,
breeding and genetic resources (pp. 43–63). Sunderland, MA: Sinauer
Associates Publishers.
Han, M., Brierley, G. J., Cullum, C., & Li, X. (2016). Climate, vegetation
and human land‐use interactions on the Qinghai–Tibet Plateau
through the Holocene. In G. J. Brierley, X. Li, C. Cullum, & J. Gao
(Eds.), Landscape and ecosystem diversity, dynamics and management in
the Yellow River Source Zone (pp . 253–274) . Be rlin, Ger ma ny : Springer.
Han, W. X., Fang, X. M., & Berger, A. (2012). Tibet forcing of mid‐
Pleistocene synchronous enhancement of East Asian winter and
summer monsoons revealed by Chinese loess record. Quaternary
Research, 78, 174–184. https://doi.org/10.1016/j.yqres.2012.05.
001
Harris, AJ, Ickert‐Bond, S., & Rodríguez, A. (2018). Long distance disper
sal in the assembly of flor as: A review of progress and prospect s in
North America. Journal of System atics and Evolution, 56 , 430–448.
Hedrick, P. (2001). Conservation genetics: Where are we now? Trend s
in Ecology and Evolution, 16 , 629–6 36. h ttps://doi.org/10.1016/
s0169‐5347(01)02282‐0
Hu, Q. J., Peng, H. C., Bi, H., Lu, Z. Q., Wan, D. S., Wang, Q., & Mao, K.
S. (2016). Genetic homogenization of the nuclear ITS loci across two
morphologically distinct gentians in their overlapping distributions
in the Qinghai‐Tibet Plateau. Scientific Reports, 6, 34244. https://doi.
org/10.1038/srep34244
Hubisz, M. J., Falush, D., Stephens, M., & Pritchard, J. K. (2009). Inferring
weak population structure with the assistance of sample group in‐
formation. Molecular Ecology Resources, 9, 1322–1332. https://doi.
org /10.1111/j .1755‐0998 .2009.02591 .x
Hug he s, C. E., & At chiso n, G. W. (2 015). The ubiqui ty of al pine plant ra di
ations: From the Andes to the Hengduan Mountains. New Phytologist,
207, 275–282. https://doi.org /10.1111/nph.13230
Huson, D. H ., & Bryant, D. (2006). Application of phylogenetic net works
in evolutionary studies. Molecula r Biolog y and Evolution, 23, 254–267.
https://doi.org/10.1093/molbev/msj030
Jia, D. R., Liu, T. L., Wang, L. Y., Zhou, D. W., & Liu, J. Q. (2011).
Evolutionary histor y of an alpine shrub Hippophae tibetana
(Elaeagnaceae): Allopatric divergence and regional expansion.
Biological Journal of the Linnean Society, 102, 37–50. https://doi.
org /10.1111/j .1095‐8 312.2010 .01553 .x
Jump, A. S., Marchant, R., & Peñuelas, J. (2009). Environmental change
and the option value of genetic diversity. Trends Plant Science, 14,
51–58. https://doi.org/10.1016/j.tplants.2008.10.002
Kaljund, K., & Jaaska, V. (2010). No loss of genetic diversity in small and
isolated populations of Medicago sativa subsp. falcata. Biochemical
Systematic s and Ecology, 38, 510–520. ht tps://doi.org /10.1016/j.
bse.2010.05.007
Karron, J. (1987). A comparison of levels of genetic polymorphism and
self‐compatibility in geographically restricted and widespread plant
congeners. Evolutionary Ecolog y, 1, 47–58. http s://doi .org/10.10 07/
BF02067268
Kimura, M., & Crow, J. F. (1964). The number of alleles that can be main
tained in a finite population. Genetics, 49, 725–738.
Körner, C. (20 04). Mountain biodiversity, its causes and function. Ambio,
13, 11–17.
6028 
|
   LIU et aL.
Kropf, M., Comes, H. P., & Kadereit, J. W. (2006). Long‐distance dispersal
vs vicariance: The origin and genetic diversit y of alpine plants in the
Spanish Sierra Nevada. New Phytologist, 172, 169–18 4. https://doi.
org /10.1111/j .1469‐8137.20 06 .0 1795.x
Lewontin, R. C. (1972). Testing the theory of natural selection. Nature,
236, 181–182. https://doi.org/10.1038/236181a0
Li, A ., & Ge, S. (2001). Genetic variation and clonal diversity of
Psammochloa villosa (Poaceae) detected by ISSR markers. Annals of
Botany, 87, 585–590. https://doi.org/10.1006/anbo.2001.1390
Li, Y., Wen, L., Dong, S., Liu, S., Wang, X., & Wu, Y. (2014). The interaction
between poisonous plants and soil quality in response to grassland
degradation in the alpine region of the Qinghai‐Tibetan Plateau. Plant
Biology, 215, 809–819. https://doi.org/10.1007/s11258‐014‐0333‐z
Liu, J. Q. (2004). Uniformity of karyotypes in Ligularia (Asteraceae:
Senecioneae), a highly diversified genus of the eastern
Qinghai–Tibet Plateau highlands and adjacent areas. Botanical
Journal of the Linnean Society, 14 4, 329–342. https://doi.
org /10.1111/j .1095‐8 33 9.20 03.00 225.x
Liu, J. Q., Gao, T. G., Chen, Z. D., & Lu, A. M. (2002). Molecular phylogeny
and biogeography of the Qinghai‐Tibet Plateau endemic Nannoglottis
(Asteraceae). Molecular Phylogenetics and Evolution, 23, 3 07–325.
htt ps://doi.org/10.1016/S1055‐790 3(02) 00 039‐8
Liu, J., Luo, Y. H., Li, D. Z., & Gao, L . M. (2017). Evolution and mainte‐
nance mechanisms of plant diversity in the Qinghai‐Tibet Plateau and
adjacent regions: Retrospect and prospect. Biodiversity Science, 25,
163–174. https://doi.org/10.17520/biods.2016293
Liu, J., Möller, M., Provan, J., Gao, L. M., Poudel, R . C., & Li, D. Z. (2013).
Geological and ecological factors drive cryptic speciation of yews in
a biodiversity hotspot. New Phytologist, 199, 1093–1108. https://doi.
org /10.1111/np h.1 2336
Liu, J. M., Wang, L., Geng, Y. P., Wang, Q. B., Luo, L. J., & Zhong, Y. (2006).
Genetic diversity and population structure of Lamiophlomis rotata
(Lamiaceae), an endemic species of Qinghai–Tibet Plateau. Genetica,
128, 385–394. https://doi.org/10.1007/s10709‐006‐7517‐y
Liu, J. Q., Wang, Y. J., Wang, A. L., Hideaki, O., & Abbott , R. J. (2006). Radiation
and diversification within the LigulariaCremanthodiumParasenecio
complex (Asteraceae) triggered by uplift of the Qinghai‐Tibetan
Plateau. Molecular Phyloge netics and Evolution, 38, 31–49. https://doi.
org /10.1016/j.ympev.2005.09.010
Liu, Y. P., Ren, Z. M., Harris, AJ, Peterson, P. M., Wen, J., & Su, X. (2018).
Phylogeography of Orinus (Poaceae), a dominant grass genus on the
Qinghai‐Tibet Plateau. Botanical Journal of the Linnean Society, 186,
202–223. https://doi.org/10.1093/botlinnean/box091
Liu, Y. P., Su, X., He, Y. H., Han, L. M., Huang, Y. Y., & Wang, Z. Z. (2015).
Evolutionary histor y of Orinus thoroldii (Poaceae), endemic to the
western Qinghai‐Tibetan Plateau in China. Biochemical Systematics
and Ecology, 59, 159–167. https://doi.org/10.1016/j.bse.2015.01.014
Ma, Z., Liu, H., Mi, Z., Zhang, Z., Wang, Y., Xu, W., He, J.‐S. (2017).
Climate warming reduces the temporal stabilit y of plant community
biomass production. Nature Communications, 8, 15378. https://doi.
org/10.1038/ncomms15378
Madriñán, S., Cortés, A. J., & Richardson, J. E. (2013). Páramo is the
world's fastest evolving and coolest biodiversity hotspot. Frontiers in
Genetics, 4, 192. https://doi.org/10.3389/fgene.2013.00192
Maréchaux, I., Rodrigues, A. S. L., & Charpentier, A. (2016). The value
of coarse species range maps to inform local biodiversit y conser‐
vation in a global context. Ecography, 40, 1166–1176. ht tps://doi.
org /10.1111/ecog.02 598
Mayr, E. (1942). Systematics a nd the origin of species, from the viewpoint of
a zoologist. New York, NY: Columbia University Press.
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A., &
Kent, J. (2000). Biodiversity hot spots for conser vation priorities.
Nature, 403(6772), 853–858.
Nei, M., & Li, W. H. (1979). Mathematical model for studying geneti‐
cal variation in terms of restriction endonucleases. Proceedings of
the National Academy of Science of the United States of America, 76,
5269–5273.
Peakall, R., & Smouse, P. (2012). GenAIEx 6.5: Genetic analysis in Excel:
Population genetic software for teaching and research – An update.
Bioinformatics, 28, 2 537–2 539.
Peterson, P. M., Romaschenko, K., & Arriet a, Y. H. (2016). A molec‐
ular phylogeny and classification of the Cynodonteae (Poaceae:
Chloridoideae) with four new genera: Orthacanthus, Triplasiella,
Tripogonella, and Zaqiqah; three new subtribes: Dac tylocteniinae,
Orininae, and Zaqiqahinae; and a subgeneric classification of
Distichlis. Tax on, 65, 1263–1287.
Pl u es s , A. R ., & St öc k li n , J. (2 0 04 ). Po pu la t io n ge ne t ic di ve r si t y of th e cl on a l
plant Geum reptans (Rosaceae) in the Swiss Alps. American Journal of
Botany, 91, 2013–2021. https://doi.org/10.3732/ajb.91.12.2013
Pritchard, J. K., Stephens, M., & Donnelly, P. (2000). Inference of pop‐
ulation structure using multilocus genotype data. Genetics, 155,
945–9 59.
Rahimmalek, M., Tabatabaei, B. E. S., Arzani, A., & Etemadi, N. (2009).
Assessment of genetic diversity among and within Achillea species
using amplified fragment length polymorphism (AFLP). Biochemical
Systematic s and Ecology, 37, 354–361. htt ps://doi.org/10.1016/j.
bse.2009.06.002
Ren, G. P., Conti, E., & Salamin, N. (2015). Phylogeny and biogeography of
Primula sect . Armerina: Implications for plant evolution under climate
change and the uplift of the Qinghai‐Tibet Plateau. BMC Evolutiona ry
Biology, 15, 161. https://doi.org/10.1186/s12862‐015‐04 45‐7
Risser, P. (1987). Landscape ecology: State of the art. In M. Turner (Ed.),
Landscape heterogeneity and disturbance (pp. 3–14). New York, NY:
Springer.
Rohlf, F. (200 0). NTSYS‐pc version 2.1: Numerical Taxonomy and
Multivariance Analysis System.
Sedlacek, J., Cortés, A. J., Wheeler, J., Bossdorf, O., Hoch, G ., Klápště,
J., … van Kleunen, M. (2016). Evolutionary potential in the Alpine:
Trait heritabilities and performance variation of the dwarf willow
Salix herbacea from different elevations and microhabitats. Ecology
and Evolution, 6, 3940–3952.
Sedlacek, J., Wheeler, J. A., Cortés, A. J., Bossdorf, O., Hoch, G., Lexer,
C., … Rixen, C. (2015). The response of the alpine dwarf shrub Salix
herbacea to altered snowmelt timing: Lessons from a multi‐site
transplant experiment. PLoS ONE, 10 (4), e0122395. ht tps://doi.
org/10.1371/journal.pone.0122395
Shi, Y. F. (2002). Characteristics of late Quaternar y monsoonal glaciation
on the Tibetan Plateau and in East Asia. Quaternary International, 97,
79–91. ht tps://doi.org /10.1016/S1040‐6182(02)0 0053‐8
Shi, Y., Li, J., & Li, B. (1998). Uplift and environmental changes of Qinghai‐
Tibetan Plateau in the late Cenozoic. Guangzhou, China: Guangdong
Science and Technolog y Press.
Soreng, R. J., Peterson, P. M., Romaschenko, K., Davidse, G., Zuloaga, F.
O., Judziewicz, E. J., … Morrone, O. (2017). A worldwide phylogenetic
classification of the Poaceae (Gramineae) II: An update and a compar
ison of two 2015 classifications. Journal of Systematics and Evolution,
55, 259–290. https://doi.org/10.1111/jse.12262
Su, X., Liu, Y. P., Wu, G. L., Luo, W. C ., & Liu, J. Q. (2017). A taxonomic
revision of Orinus (Poaceae) with a new species, O. intermedius, from
the Qinghai‐Tibet Plateau. Novon, 25, 206–213.
Su, X., Wu, G . L., Li, L. L., & Liu, J. Q. (2015). Species delimitation in
plants using the Qinghai‐Tibetan Plateau endemic Orinus (Poaceae:
Tridentinae) as an example. Anna ls of Botany, 116 , 35–48.
Su, X ., Yue, W., & Liu, J. Q. (2013). Germplasm collection and preser va‐
tion of Orinus (Poaceae) in the Qinghai‐Tibet Plateau. Plant Diversity
Research, 35, 343–347.
Wang, W., Chen, L., Yang, P., Hou, L., He, C ., Gu, Z., & Liu, Z. (2007).
Assessing genetic diversity of populations of topmouth culter (Culter
alburnus) in China using AFLP markers. Biochemical Systematics and
Ecology, 35, 662–669. https://doi.org/10.1016/j.bse.2007.04.008
    
|
 6029
LIU et aL .
Wen, J., Zhang, J. Q., Nie, Z. L ., Zhong, Y., & Sun, H. (2014). Evolutionar y
diversifications of plants on the Qinghai‐Tibetan Plateau. Frontiers in
Genetics, 5, 4. ht tps://doi.org/10.3389/fgene.2014.000 04
Wilcox, B. P., Sorice, M. G., & Young, M. H. (2011). Dryland ecohy‐
drology in the Anthropocene: Taking stock of human–ecologi
cal interactions. Geography Compass, 5(3), 112–127. https://doi.
org /10.1111/j .1749‐8198.2011. 00 413 .x
Willis, K. J., Bennett, K . D., & Birks, H. J. B. (2009). Variability in thermal
and UV‐B energy fluxes through time and their influence on plant
diversity and speciation. Journal of B iogeography, 36, 1630–1644.
https://doi.org/10.1111/j.1365‐2699.2009.02102.x
Wu, S. G., Yang, Y. P., & Fei, Y. (1995). On the flora of the alpine region
in the Qinghai‐Xizang (Tibet) plateau. Acta Botanica Yunnanica, 17,
233–250.
Wu, Y. (2008). The vascula r plants and their eco‐geograph ical distribution of
the Qinghai‐Tibetan Plateau. Beijing, China: Science Press.
Xue, X., Wang, Y., Korpelainen, H., & Li, C. (2005). Assessment of AFLP‐
based genetic variation in the populations of Picea asperata. Silvae
Genetica, 54, 24–30. https://doi.org/10.1515/sg‐2005‐0004
Yang, F. S., Li, Y. F., Ding, X., & Wang, X. Q. (2008). Extensive population
expansion of Pedicularis longiflora (Orobanchaceae) on the Qinghai‐
Tibetan Plateau and its correlation with the Quaternary climate
change. Molecular Ecology, 17, 5135–5145.
Ya ng , M. X. , Wa ng , S. L ., Ya o , T. D. , Go u, X . H . , L u, A. X. , & Gu o, X. J. (2 00 4) .
Desertification and its relationship with permafrost degradation in
Qinghai‐Xizang (Tibet) Plateau. Cold Region Science and Technology,
39, 47–53. https://doi.org/10.1016/j.coldregions.2004.01.002
Yap, I., & Nelson, R. (1996). Winboot: A program for performing boot‐
strap analysis of binary data to determine the confidence limits of
UPGMA‐based dendrograms. International Rice Research Institute
Discussion Paper Series, 14, 1–22.
Yeh, F., Yang, R ., & Boyle, T. (1999). POPGENE: Microsoft Windows‐based
freeware for population genetic analysis. Version 1.31. Edmonton,
Canada: University of Alberta.
Yi, S. H., Zhou, Z. Y., Ren, S. L., Xu, M., Qin, Y., Chen, S. Y., & Ye, B.
S. (2011). Effects of permafrost degradation on alpine grass
land in a semi‐arid basin on the Qinghai‐Tibetan Plateau.
Environmental Research Letters, 6, 45403–45409. https://doi.
org /10.1088/1748‐9326/6/4/0 45 40 3
Yu, F., Dong, M., & Krüsi, B. (2004). Clonal integration helps Psammochloa
villosa survive sand burial in an inland dune. New Phytologist, 162 (3),
697–704. h tt ps ://doi.or g/10.1111/ j.14 69‐8137.200 4.01073 .x
Zhang, Q., Chiang, T. Y., G eorge, M., Liu, J. Q., & Abbott, R. J. (2005).
Phylogeography of the Qinghai‐Tibetan Plateau endemic Juniperus
przewalskii (Cupressaceae) inferred from chloroplast DNA se
quence variation. Molecular Evolution, 14, 3513–3524. https://doi.
org /10.1111/j .136 5‐294X. 20 05.0 2677.x
Zheng, B., & Nat, R. (1998). On the problem of Quaternar y glaciations,
and the extent and patterns of Pleistocene ice cover in the Qinghai‐
Xizang ( Tibet) Plateau. Quaternary International, 45, 109–122.
Zhou, S. L., & Qian, P. (2003). Matrix Generator (MG): A program for
creating 0/1 matrix from DNA fragments. Acta Botanica Sinica, 45,
766–769.
Zuo, Y. J., Wen, J., Ma, J. S., & Zhou, S. L. (2015). Evolutionary radiation
of the Panax bipinnatifidus species complex (Araliaceae) in the Sino
Himalayan region of eastern Asia as inferred from AFLP analysis.
Journal of Systematic s and Evolution, 53, 210–220.
How to cite this article: Liu Y, Harris AJ, Gao Q, Su X, Ren Z.
A population genetics perspective on the evolutionar y
histories of three clonal, endemic, and dominant grass
species of the Qinghai–Tibet Plateau: Orinus (Poaceae). Ecol
Evol. 2019;9:6014–6037. https://doi.org/10.1002/ece3.5186
6030 
|
   LIU et aL.
APPENDIX A
TABLE A1 Posterior probabilities for five genetic models tested in NewHybrids for individual samples of species of Orinus
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. kokonoricus 4 0 1 0 0 0
O. kokonoricus 4 0 1 0 0 0
O. kokonoricus 4 0 1 0 0 0
O. kokonoricus 4 0 1 0 0 0
O. kokonoricus 4 0 1 0 0 0
O. kokonoricus 5 0 1 0 0 0
O. kokonoricus 5 0 1 0 0 0
O. kokonoricus 5 0 1 0 0 0
O. kokonoricus 5 0 1 0 0 0
O. kokonoricus 5 0 1 0 0 0
O. kokonoricus 8 0 1 0 0 0
O. kokonoricus 8 0 1 0 0 0
O. kokonoricus 8 0 1 0 0 0
O. kokonoricus 8 0 1 0 0 0
O. kokonoricus 8 0 1 0 0 0
O. kokonoricus 9 0 1 0 0 0
O. kokonoricus 9 0 1 0 0 0
O. kokonoricus 9 0 1 0 0 0
O. kokonoricus 9 0 1 0 0 0
O. kokonoricus 9 0 1 0 0 0
O. kokonoricus 13 0 1 0 0 0
O. kokonoricus 13 0 1 0 0 0
O. kokonoricus 13 0 1 0 0 0
O. kokonoricus 13 0 1 0 0 0
O. kokonoricus 13 0 1 0 0 0
O. kokonoricus 1 0 1 0 0 0
O. kokonoricus 1 0 1 0 0 0
O. kokonoricus 1 0 1 0 0 0
O. kokonoricus 1 0 1 0 0 0
O. kokonoricus 1 0 1 0 0 0
O. kokonoricus 12 0 1 0 0 0
(Connues)
    
|
 6031
LIU et aL .
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. kokonoricus 12 0 1 0 0 0
O. kokonoricus 12 0 1 0 0 0
O. kokonoricus 12 0 1 0 0 0
O. kokonoricus 12 0 1 0 0 0
O. kokonoricus 11 0 1 0 0 0
O. kokonoricus 11 0 1 0 0 0
O. kokonoricus 11 0 1 0 0 0
O. kokonoricus 11 0 1 0 0 0
O. kokonoricus 11 0 1 0 0 0
O. kokonoricus 10 0 1 0 0 0
O. kokonoricus 10 0 1 0 0 0
O. kokonoricus 10 0 1 0 0 0
O. kokonoricus 10 0 1 0 0 0
O. kokonoricus 10 0 1 0 0 0
O. kokonoricus 6 0 1 0 0 0
O. kokonoricus 6 0 1 0 0 0
O. kokonoricus 6 0 1 0 0 0
O. kokonoricus 6 0 1 0 0 0
O. kokonoricus 6 0 1 0 0 0
O. kokonoricus 2 0 1 0 0 0
O. kokonoricus 2 0 1 0 0 0
O. kokonoricus 2 0 1 0 0 0
O. kokonoricus 2 0 1 0 0 0
O. kokonoricus 2 0 1 0 0 0
O. kokonoricus 3 0 1 0 0 0
O. kokonoricus 3 0 1 0 0 0
O. kokonoricus 3 0 1 0 0 0
O. kokonoricus 3 0 1 0 0 0
O. kokonoricus 3 0 1 0 0 0
O. kokonoricus 14 0 1 0 0 0
(Connues)
TABLE A1 (Continued)
6032 
|
   LIU et aL.
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. kokonoricus 14 00.99999 0 0 0.00001
O. kokonoricus 14 0 1 0 0 0
O. kokonoricus 14 0 1 0 0 0
O. kokonoricus 14 0 1 0 0 0
O. kokonoricus 17 0 1 0 0 0
O. kokonoricus 17 0 1 0 0 0
O. kokonoricus 17 00 .99735 0 0 0.0 0265
O. kokonoricus 17 0 1 0 0 0
O. kokonoricus 17 0 1 0 0 0
O. kokonoricus 18 0 1 0 0 0
O. kokonoricus 18 0 1 0 0 0
O. kokonoricus 18 0 1 0 0 0
O. kokonoricus 18 0 1 0 0 0
O. kokonoricus 18 0 1 0 0 0
O. kokonoricus 19 0 1 0 0 0
O. kokonoricus 19 0 1 0 0 0
O. kokonoricus 19 0 1 0 0 0
O. kokonoricus 19 0 1 0 0 0
O. kokonoricus 19 0 1 0 0 0
O. kokonoricus 16 0 1 0 0 0
O. kokonoricus 16 0 1 0 0 0
O. kokonoricus 16 0 1 0 0 0
O. kokonoricus 16 0 1 0 0 0
O. kokonoricus 16 0 1 0 0 0
O. kokonoricus 15 0 1 0 0 0
O. kokonoricus 15 0 1 0 0 0
O. kokonoricus 15 0 1 0 0 0
O. kokonoricus 15 0 1 0 0 0
O. kokonoricus 7 0 1 0 0 0
O. kokonoricus 7 0 1 0 0 0
O. kokonoricus 7 0 1 0 0 0
TABLE A1 (Continued)
(Connues)
    
|
 6033
LIU et aL .
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. kokonoricus 7 0 1 0 0 0
O. kokonoricus 7 0 1 0 0 0
O. intermedius 22 00.99999 0 0 0.00001
O. intermedius 22 0 1 0 0 0
O. intermedius 22 0 1 0 0 0
O. intermedius 22 0 1 0 0 0
O. intermedius 23 0 1 0 0 0
O. intermedius 23 00.99918 0 0 0.00082
O. intermedius 23 0 1 0 0 0
O. intermedius 23 0 1 0 0 0
O. intermedius 23 00.99999 0 0 0.00001
O. intermedius 20 0 1 0 0 0
O. intermedius 20 0 1 0 0 0
O. intermedius 20 0 1 0 0 0
O. intermedius 20 0 1 0 0 0
O. intermedius 25 0 1 0 0 0
O. intermedius 25 0 1 0 0 0
O. intermedius 25 0 1 0 0 0
O. intermedius 25 0 1 0 0 0
O. intermedius 25 0 1 0 0 0
O. intermedius 26 0 1 0 0 0
O. intermedius 26 0 1 0 0 0
O. intermedius 26 0 1 0 0 0
O. intermedius 26 0 1 0 0 0
O. intermedius 26 0 1 0 0 0
O. intermedius 28 00.88592 0 0 0.1140 8
O. intermedius 28 0 0 0 0 1
O. intermedius 28 00.00 012 0 0 0.99988
O. intermedius 28 0 0 0 0 1
O. intermedius 21 0 1 0 0 0
(Connues)
TABLE A1 (Continued)
6034 
|
   LIU et aL.
(Connues)
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. intermedius 21 0 1 0 0 0
O. intermedius 21 0 1 0 0 0
O. intermedius 24 00 .9 974 3 0 0 0.00257
O. intermedius 24 0 1 0 0 0
O. intermedius 24 0 1 0 0 0
O. intermedius 24 0 1 0 0 0
O. intermedius 27 0 0 0 0 1
O. intermedius 27 0 0 0 0 1
O. intermedius 27 0 0 0 0 1
O. intermedius 27 0 0 0 0 1
O. intermedius 27 0 0 0 0 1
O. thoroldii 29 0.11855 0 0 0.88145 0
O. thoroldii 29 1 0 0 0 0
O. thoroldii 29 0.00002 0 0 0.99998 0
O. thoroldii 29 0.95236 0 0 0.04764 0
O. thoroldii 30 0.986 88 0 0 0.01312 0
O. thoroldii 30 1 0 0 0 0
O. thoroldii 30 0.00092 0 0 0.99908 0
O. thoroldii 30 0.99997 0 0 0.00003 0
O. thoroldii 30 0.94228 0 0 0.05772 0
O. thoroldii 31 1 0 0 0 0
O. thoroldii 31 1 0 0 0 0
O. thoroldii 31 1 0 0 0 0
O. thoroldii 31 1 0 0 0 0
O. thoroldii 31 1 0 0 0 0
O. thoroldii 33 1 0 0 0 0
O. thoroldii 33 1 0 0 0 0
O. thoroldii 33 0.99999 0 0 0.00001 0
O. thoroldii 33 1 0 0 0 0
O. thoroldii 33 1 0 0 0 0
TABLE A1 (Continued)
    
|
 6035
LIU et aL .
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. thoroldii 37 1 0 0 0 0
O. thoroldii 37 1 0 0 0 0
O. thoroldii 37 1 0 0 0 0
O. thoroldii 37 1 0 0 0 0
O. thoroldii 37 1 0 0 0 0
O. thoroldii 39 1 0 0 0 0
O. thoroldii 39 1 0 0 0 0
O. thoroldii 39 1 0 0 0 0
O. thoroldii 39 1 0 0 0 0
O. thoroldii 41 1 0 0 0 0
O. thoroldii 41 1 0 0 0 0
O. thoroldii 41 1 0 0 0 0
O. thoroldii 41 1 0 0 0 0
O. thoroldii 41 1 0 0 0 0
O. thoroldii 42 1 0 0 0 0
O. thoroldii 42 1 0 0 0 0
O. thoroldii 42 1 0 0 0 0
O. thoroldii 42 1 0 0 0 0
O. thoroldii 42 1 0 0 0 0
O. thoroldii 43 1 0 0 0 0
O. thoroldii 43 1 0 0 0 0
O. thoroldii 43 1 0 0 0 0
O. thoroldii 43 1 0 0 0 0
O. thoroldii 43 1 0 0 0 0
O. thoroldii 44 1 0 0 0 0
O. thoroldii 44 1 0 0 0 0
O. thoroldii 44 1 0 0 0 0
O. thoroldii 44 1 0 0 0 0
O. thoroldii 44 1 0 0 0 0
O. thoroldii 45 1 0 0 0 0
O. thoroldii 45 1 0 0 0 0
(Connues)
TABLE A1 (Continued)
6036 
|
   LIU et aL.
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. thoroldii 45 1 0 0 0 0
O. thoroldii 45 1 0 0 0 0
O. thoroldii 45 1 0 0 0 0
O. thoroldii 46 1 0 0 0 0
O. thoroldii 46 1 0 0 0 0
O. thoroldii 46 1 0 0 0 0
O. thoroldii 46 1 0 0 0 0
O. thoroldii 46 1 0 0 0 0
O. thoroldii 47 1 0 0 0 0
O. thoroldii 47 1 0 0 0 0
O. thoroldii 47 1 0 0 0 0
O. thoroldii 47 1 0 0 0 0
O. thoroldii 47 1 0 0 0 0
O. thoroldii 48 1 0 0 0 0
O. thoroldii 48 1 0 0 0 0
O. thoroldii 48 1 0 0 0 0
O. thoroldii 48 1 0 0 0 0
O. thoroldii 48 1 0 0 0 0
O. thoroldii 40 1 0 0 0 0
O. thoroldii 40 1 0 0 0 0
O. thoroldii 40 1 0 0 0 0
O. thoroldii 40 1 0 0 0 0
O. thoroldii 40 1 0 0 0 0
O. thoroldii 38 1 0 0 0 0
O. thoroldii 38 1 0 0 0 0
O. thoroldii 38 1 0 0 0 0
O. thoroldii 38 1 0 0 0 0
O. thoroldii 38 1 0 0 0 0
O. thoroldii 36 1 0 0 0 0
O. thoroldii 36 1 0 0 0 0
(Connues)
TABLE A1 (Continued)
    
|
 6037
LIU et aL .
Putative Species
Population
Number (Figure 2)
1.000/0.000/0.000/0.000
(O. thoroldii)
0.000/0.000/0.000/1.000
(O. kokonoricus)
0.000/0.500/0.500/0.000
(true hybrid)
0.500/0.250/0.250/0.000
(backcross into O. thoroldii)
0.000/0.250/0.250/0.500
(backcross into O. kokonoricus)
O. thoroldii 36 1 0 0 0 0
O. thoroldii 36 1 0 0 0 0
O. thoroldii 36 1 0 0 0 0
O. thoroldii 34 1 0 0 0 0
O. thoroldii 34 1 0 0 0 0
O. thoroldii 34 1 0 0 0 0
O. thoroldii 34 1 0 0 0 0
O. thoroldii 34 1 0 0 0 0
O. thoroldii 35 1 0 0 0 0
O. thoroldii 35 1 0 0 0 0
O. thoroldii 35 1 0 0 0 0
O. thoroldii 35 1 0 0 0 0
O. thoroldii 35 1 0 0 0 0
O. thoroldii 32 1 0 0 0 0
O. thoroldii 32 1 0 0 0 0
O. thoroldii 32 1 0 0 0 0
O. thoroldii 32 1 0 0 0 0
O. thoroldii 32 1 0 0 0 0
TABLE A1 (Continued)
... This valuable forage resource exhibits high stress resistance that is used to generate high-quality agricultural varieties and improve forage utilisation by livestock [5,6]. On the QTP, Orinus contributes to soil stabilisation and sand fixation, which are pivotal in ecological and conservation contexts, due to its prolific root system and high drought, cold, and alkali resistance [4,7,8]. There have been numerous recent reports on the adaptation of high-altitude species to extreme habitats, including cold and drought conditions [9][10][11]. ...
... Phylogenetic trees generated using the Orinus and wheat AP2/ERF, bHLH, C2H2, GRAS, HD-ZIP, MADSbox, R2R3-MYB, NAC, TALE, and WRKY TF family members were divided into 13,24,5,10,4,12,9,8,6, and 7 subfamilies, respectively, with most family members assigned to known subfamilies. During evolution, however, the AP2/ERF and C2H2 TF families in Orinus developed new subfamily branches, while the GRAS and MADS-box TF families were found to exhibit subfamily loss, and the bHLH gene family exhibits both above phenomena. ...
Article
Full-text available
Background Transcription factors (TFs) are crucial regulators of plant growth, development, and resistance to environmental stresses. However, comprehensive understanding of the roles of TFs in speciation of Orinus, an extreme-habitat plant on the Qinghai-Xizang (Tibet) Plateau, is limited. Results Here, we identified 52 TF families, including 2125 members in Orinus, by methodically analysing domain findings, gene structures, chromosome locations, conserved motifs, and phylogenetic relationships. Phylogenetic trees were produced for each Orinus TF family using protein sequences together with wheat (Triticum aestivum L.) TFs to indicate the subgroups. The differences between Orinus and wheat species in terms of TF family size implies that both Orinus- and wheat-specific subfamily contractions (and expansions) contributed to the high adaptability of Orinus. Based on deep mining of RNA-Seq data between two species of Orinus, O. thoroldii and O. kokonoricus, we obtained differentially expressed TFs (DETFs) in 20 families, most of which were expressed higher in O. thoroldii than in O. kokonoricus. In addition, Cis-element analysis shows that MYC and G-box elements are enriched in the promoter region of DETFs, suggesting that jasmonic acid (JA) and abscisic acid (ABA) act synergistically in Orinus to enhance the signalling of related abiotic stress responses, ultimately leading to an improvement in the stress tolerance and speciation adaptation of Orinus. Conclusions Our data serve as a genetic resource for Orinus, not only filling the gap in studies of TF families within this genus but also providing preliminary insights into the molecular mechanisms underlying speciation in Orinus.
... We used AFLPs because they remain extremely efficient for investigating genetic diversity, genetic structure, and population demography due to their high levels of polymorphism (Wang, Wang, Liu, Yang, & Chen, 2008), their reproducible, reliable re-sults that are unaffected by the developmental stage of plant materials, and their universality among plant species. In addition, they have been used to resolve genetic structures and population demography in many diverse grass species such as Oryza sativa , Leymus racemosus , Orinus thoroldii and O. kokonoricus (Zhang & Jia, 2002;Sim, 2005;Li, 2015;Cai, 2017;Liu, Harris, Gao, Su, & Ren, 2019). Our main objectives were to (1) analyze the genetic structure from 43 populations of P. villosa from Inner Mongolian Plateau using an AFLP dataset, (2) test whether historical genetic divergence occurred among populations in response to Quaternary climate oscillations, and (3) evaluate the abiotic factors that are most influential in driving the distributions of P. villosa . ...
... The selective amplification was conducted in 25 μl volume of reaction mixture containing of 1.0 μl EcoR I/Mse I primer combinations (AAC/CAA, AAG/CAC, ACA/CAG, ACT/CAT, ACC/CTA, ACG/CTC, AGC/CTG, AGG/CTT; Table 1). Subsequently, we separated the fluorescently-labeled fragments on an ABI PRISM 377 DNA Calibrator (Applied Biosystems) using GeneScan ROX-500 with an internal size standard, allowing visual inspection of all individual sites (Liu, Harris, Gao, Su, & Ren, 2019). We recorded the presence or absence of AFLP amplification bands ( Figure S2) in a binary matrix as 1 or 0, respectively, based on interpretations from GeneScan 3.1 (Applied Biosystems). ...
Preprint
We sought to generate a preliminary demographic framework for Psammochloa villosa to support of future studies of this ecologically important desert grass species, its conservation, and sustainable utilization. Psammochloa villosa occurs in the Inner Mongolian Plateau where it is frequently the dominant species and is involved in sand stabilization and wind breaking. Here, we characterized the genetic diversity and structure of 210 individuals from 43 natural populations of P. villosa using amplified fragment length polymorphism (AFLP) markers. We obtained 1728 well-defined amplified bands from eight pairs of primers, of which 1654 bands (95.72%) were polymorphic.All these values indicate that there is abundant genetic diversity, but limited gene flow in P. villosa. However, an analysis of molecular variance (AMOVA) showed that genetic variation mainly exists within 43 populations of the species (64.16%), and we found that the most genetically similar populations were often not geographically adjacent. Thus, this suggests that the mechanisms of gene flow are surprisingly complex in the species and may occur over long distances. In addition, we predicted the distribution dynamics of P. villosa based on the spatial distribution modeling and found that its range has contracted continuously since the last inter-glacial period. We speculate that dry, cold climates have been critical in determining the geographic distribution of P. villosa during the Quaternary period. Our study provides new insights into the population genetics and evolutionary history of P. villosa in the Inner Mongolian Plateau, which can be used to design in-situ conservation actions and to prioritize sustainable utilization of germplasm resources.
... In addition, they have been used to resolve genetic structures and population demography in many diverse grass species such as Oryza sativa, Leymus racemosus, Orinus thoroldii, and O. kokonoricus (Cai et al., 2017;Liu et al., 2019;Zhang & Jia, 2002 We believe that, taken together, our results can provide a scientific basis for improved protection and sustainable utilization (e.g., as forage) of P. villosa within the fragile desert grassland ecosystems where the species occurs. ...
Article
Full-text available
Psammochloa villosa is an ecologically important desert grass that occurs in the Inner Mongolian Plateau where it is frequently the dominant species and is involved in sand stabilization and wind breaking. We sought to generate a preliminary demographic framework for P. villosa to support the future studies of this species, its conservation, and sustainable utilization. To accomplish this, we characterized the genetic diversity and structure of 210 individuals from 43 natural populations of P. villosa using amplified fragment length polymorphism (AFLP) markers. We obtained 1,728 well-defined amplified bands from eight pairs of primers, of which 1,654 bands (95.7%) were polymorphic. Results obtained from the AFLPs suggested effective alleles among populations of 1.32, a Nei's standard genetic distance value of 0.206, a Shannon index of 0.332, a coefficient of gene differentiation (GST) of 0.469, and a gene flow parameter (Nm) of 0.576. All these values indicate that there is abundant genetic diversity in P. villosa, but limited gene flow. An analysis of molecular variance (AMOVA) showed that genetic variation mainly exists within populations (64.2%), and we found that the most genetically similar populations were often not geographically adjacent. Thus, this suggests that the mechanisms of gene flow are surprisingly complex in this species and may occur over long distances. In addition, we predicted the distribution dynamics of P. villosa based on the spatial distribution modeling and found that its range has contracted continuously since the last interglacial period. We speculate that dry, cold climates have been critical in determining the geographic distribution of P. villosa during the Quaternary period. Our study provides new insights into the population genetics and evolutionary history of P. villosa in the Inner Mongolian Plateau and provides a resource that can be used to design in situ conservation actions and prioritize sustainable utilization.
... Therefore, we tested 25 alternative hypotheses for parental contribution, ranging from none, to the existence of F1 hybrids, to very small contributions from potential donors involving only 5% of loci (Supplementary File 1). Within an analysis, hybridization can be evaluated between only two lineages or species (see also Liu et al., 2019). Thus, we performed the tests of the 25 hypotheses on three datasets: a dataset of all sampled accessions of the three species of Lilium, a dataset comprising only LG and LS (in total 49 individuals with population codes ...
Article
Full-text available
We studied hybrid interactions of Lilium meleagrinum, Lilium gongshanense, and Lilium saluenense using an integrative approach combining population genetics, fieldwork, and phenological research. These three species occur along an elevational gradient, with L. meleagrinum occurring at lower elevations, L. saluenense at higher elevations, and L. gongshanense between them. The species show strong morphological differentiation despite there being no clear environmental barriers to gene flow among them. Lilium gongshanense is likely to have a hybrid origin based on our prior work, but its progenitors remain uncertain. We sought to determine whether gene flow occurs among these three parapatric species, and, if so, whether L. gongshanense is a hybrid of L. meleagrinum and/or L. saluenense. We analyzed data from multiple chloroplast genes and spacers, nuclear internal transcribed spacer (ITS), and 18 nuclear Expressed Sequence Tag-Simple Sequence Repeat (EST-SSR) microsatellites for accessions of the three species representing dense population-level sampling. We also inferred phenology by examining species in the field and using herbarium specimens. We found that there are only two types of chloroplast genomes shared among the three species and that L. gongshanense forms two distinct groups with closest links to other species of Lilium based on ITS. Taken together, L. gongshanense is unlikely to be a hybrid species resulting from a cross between L. meleagrinum and L. saluenense, but gene flow is occurring among the three species. The gene flow is likely to be rare according to evidence from all molecular datasets, and this is corroborated by detection of only one putative hybrid individual in the field and asynchronous phenology. We suspect that the rarity of hybridization events among the species facilitates their continued genetic separation.
Article
The species of Orinus (Poaceae) are important alpine plants with a variety of phenotypic traits and potential usages in molecular breeding toward drought-tolerant forage crops. However, the genetic basis of evolutionary adaption and diversification in the genus is still unclear. In the present study, we obtained transcriptomes for the two most divergent species, O. thoroldii and O. kokonoricus, using the Illumina platform and de novo assembly. In total, we generated 23,029 and 24,086 unigenes with N50 values of 1188 and 1203 for O. thoroldii and O. kokonoricus respectively, and identified 19,005 pairs of putative orthologs between the two species of Orinus. For these orthologs, estimations of non-synonymous/synonymous substitution rate ratios indicated that 568 pairs may be under strongly positive selection (Ka/Ks > 1), and Gene Ontogeny (GO) enrichment analysis revealed that significantly enriched pathways were in DNA repair and resistance to abiotic stress. Meanwhile, the divergence times of species between O. thoroldii and O. kokonoricus occurred 3.2 million years ago (Mya), and the recent evolutionary branch is an allotetraploid species, Cleistogenes songorica. We also detected a Ks peak of ∼0.60 for Orinus. Additionally, we identified 188 pairs of differentially expressed genes (DEGs) between the two species of Orinus, which were significantly enrich in stress resistance and lateral root development. Thus, we considered that the species diversification and evolutionary adaption of this genus was initiated by environmental selection, followed by phenotypic differentiation, finally leading to niche separation in the Qinghai-Tibet Plateau.
Article
Full-text available
We present a new worldwide phylogenetic classification of 11 506 grass species in 768 genera, 12 subfamilies, seven supertribes, 52 tribes, five supersubtribes, and 90 subtribes; and compare two phylogenetic classifications of the grass family published in 2015 (Soreng et al. and Kellogg). The subfamilies (in descending order based on the number of species) are Pooideae with 3968 species in 202 genera, 15 tribes, and 30 subtribes; Panicoideae with 3241 species in 247 genera, 13 tribes, and 19 subtribes; Bambusoideae with 1670 species in 125 genera, three tribes, and 15 subtribes; Chloridoideae with 1602 species in 124 genera, five tribes, and 26 subtribes; Aristidoideae with 367 species in three genera, and one tribe; Danthonioideae with 292 species in 19 genera, and one tribe; Micrairoideae with 184 species in eight genera, and three tribes; Oryzoideae with 115 species in 19 genera, four tribes, and two subtribes; Arundinoideae with 40 species in 14 genera, two tribes, and two subtribes; Pharoideae with 12 species in three genera, and one tribe; Puelioideae with 11 species in two genera, and two tribes; and the Anomochlooideae with four species in two genera, and two tribes. We also include a radial tree illustrating the hierarchical relationships among the subtribes, tribes, and subfamilies. Newly described taxa include: supertribes Melicodae and Nardodae; supersubtribes Agrostidodinae, Boutelouodinae, Gouiniodinae, Loliodinae, and Poodinae; and subtribes Echinopogoninae and Ventenatinae.
Article
Full-text available
Anthropogenic climate change has emerged as a critical environmental problem, prompting frequent investigations into its consequences for various ecological systems. Few studies, however, have explored the effect of climate change on ecological stability and the underlying mechanisms. We conduct a field experiment to assess the influence of warming and altered precipitation on the temporal stability of plant community biomass in an alpine grassland located on the Tibetan Plateau. We find that whereas precipitation alteration does not influence biomass temporal stability, warming lowers stability through reducing the degree of species asynchrony. Importantly, biomass temporal stability is not influenced by plant species diversity, but is largely determined by the temporal stability of dominant species and asynchronous population dynamics among the coexisting species. Our findings suggest that ongoing and future climate change may alter stability properties of ecological communities, potentially hindering their ability to provide ecosystem services for humanity.
Article
Full-text available
The evolution and maintenance of biodiversity is largely determined by the interaction of genetics and environmental factors. Geological and climatic histories, which played pivotal roles in the evolution and maintenance of plant diversity in the Qinghai-Tibet Plateau (QTP) and adjacent regions, are the most important environmental aspects. We review the major effects of QTP environmental changes associated with geological uplift, Asian monsoon evolution, and Pleistocene climatic oscillation on the origin, evolution, population demography, and maintenance mechanisms of plant diversity in the QTP and adjacent regions across spatiotemporal scales. Furthermore, we summarize the current progress and knowledge gaps on mechanisms of diversification and maintenance of plant diversity, and outline the effect of climate change on plant genetic diversity, hybrid zone dynamics, plant diversity patterns, the effect of Asian Monsoon evolution on plant diversity maintenance, and mechanisms of community assembly, the five additional future research hotspots.
Article
Full-text available
The northeastern region of the Tibetan Plateau is a region with high genetic diversity for endemic species. To comprehensively document the patterns of diversity and the distribution of Triplophysa species in this area, we probed the allocation of Triplophysa species using field surveys from 2012 to 2015. We found that areal shrinkage and fragmentation had occurred in some species. Species richness in this area was uneven. But the middle to upper reaches of the Heihe River, Datong River and Taohe River were uncommon areas with high species-richness and high biodiversity. Along altitudinal gradients, species richness presented a unimodal pattern and peaked at mid-elevations (2,200–2,400 m), which was the transition area between two community zones with high species richness. The unimodal pattern fit Lomolino’s prediction regarding species density and altitude. Biodiversity indices displayed uniform patterns with species richness and elevation. Consistent with most studies, the unimodal shape may be the universal pattern of biodiversity distribution along elevational gradients in the Tibetan Plateau and its adjacent highlands. The intermediate elevational regions should be conservation priorities.
Article
We present a statistical method for identifying species hybrids using data on multiple, unlinked markers. The method does not require that allele frequencies be known in the parental species nor that separate, pure samples of the parental species be available. The method is suitable for both markers with fixed allelic differences between the species and markers without fixed differences. The probability model used is one in which parentals and various classes of hybrids (F1's, F2's, and various backcrosses) form a mixture from which the sample is drawn. Using the framework of Bayesian model-based clustering allows us to compute, by Markov chain Monte Carlo, the posterior probability that each individual belongs to each of the distinct hybrid classes. We demonstrate the method on allozyme data from two species of hybridizing trout, as well as on two simulated data sets.
Article
To better understand the responses of arid-adapted, alpine plants to Quaternary climatic oscillations, we investigated 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 psbAtrnH), 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 differentiation 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 boundaries. 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.
Article
We compile and analyze data on the population genetic structure of broad-sense clonal plant populations where sexual recruitment is rare or absent. The data from 27 studies show a common theme: multiclonal populations of intermediate diversity and evenness tend to be the rule, most clones are restricted to one or a few populations, and widespread clones are exceptional. While a few studies have demonstrated that ecological differences among sympatric clones do occur, more experimental and theoretical studies are necessary to determine the role of selection and other evolutionary forces in maintaining clonal polymorphism.
Article
Six species have been described for the genus Orinus Hitchc. (Poaceae). Our analyses of morphological and genetic variation at the population level indicate that the genus should be reduced to three species, one of which, O. intermedius X. Su & J. Quan Liu, we describe as new from the Qinghai-Tibet Plateau. We include a complete taxonomic revision of the genus, a key to distinguish the three species, and geographic distribution and habitat data for each species.