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wileyonlinelibrary.com/journal/zsc Zoologica Scripta. 2018;47:630–644.
© 2018 Royal Swedish Academy of Sciences
1
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INTRODUCTION
Geographic isolation is commonly considered an important
step in allopatric speciation. Discontinuous landscapes have
important consequences for the evolution of the species within
them (Krystufek, Klenovsek, Amori, & Janzekovic, 2015).
Isolation of population fragments accelerates genetic and
morphologic divergence, which ultimately leads to the emer-
gence of new species (Wang, Wan, Lim, & Yue, 2016). The
mid‐latitude arid zone of Eurasia provides a good natural ex-
ample of this phenomenon (the topography of this area is de-
tailed in Supporting Information Figure S1). It encompasses
Received: 21 March 2018
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Revised: 25 April 2018
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Accepted: 10 June 2018
DOI: 10.1111/zsc.12303
ORIGINAL ARTICLE
Phylogeny and taxonomic reassessment of jerboa, Dipus
(Rodentia, Dipodinae), in inland Asia
Jilong Cheng1,2
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Deyan Ge1
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Lin Xia1
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Zhixin Wen1
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Qian Zhang1
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Liang Lu3
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Qisen Yang1
1Key Laboratory of Zoological Systematics
and Evolution,Institute of Zoology,Chinese
Academy of Sciences, Beijing, China
2University of the Chinese Academy of
Sciences, Beijing, China
3State Key Laboratory for
Infectious Disease Prevention and
Control,Collaborative Innovation
Centre for Diagnosis and Treatment of
Infectious Diseases,National Institute
for Communicable Disease Control and
Prevention,Chinese Centre for Disease
Control and Prevention, Beijing, China
Correspondence
Qisen Yang, Key Laboratory of Zoological
Systematics and Evolution, Institute of
Zoology, Chinese Academy of Sciences,
Beijing 100101, China.
Email: yangqs@ioz.ac.cn
Funding information
Grants of Key Laboratory of Zoological
Systematics and Evolution of the Chinese
Academy of Sciences, Grant/Award
Number: Y229YX5105
Abstract
Deserts and arid regions are perceived to have low biological and genetic diversity,
which has partially influenced the identification of psammophilic species, especially
taxonomic inferences based on morphology alone. Recent studies of Dipus sagitta
have revealed clear, deep genetic divergence beyond the species level within this
monotypic genus. To clarify the taxonomy of Dipus, we examined a morphometric
dataset consisting of 191 voucher specimens covering nearly the entire distribution
of the genus to explore skull variation using traditional morphological measurements
and geometric morphometric analysis. Phylogenetic relationships within Dipus using
two mitochondrial genes (n = 383) and six nuclear genes (n = 106) were assessed by
Bayesian inference and maximum‐likelihood procedures. We used a “candidate spe-
cies approach” with the divergent mtDNA phylogenetic groups and subspecies iden-
tified in previous studies as the starting point and analysed the candidates using five
species delimitation methods and two validation methods. Our findings indicate that
Dipus can be divided into four phylogenetic groups that include two species: the
Deasyi group (D. deasyi), Sagitta group, Sowerbyi group and Turanicus group
(D. sagitta). According to the morphological analyses and the examined specimens,
pelage colour varies significantly with season and age, making it unsuitable as a di-
agnostic characteristic of the subspecies. Furthermore, measurements of body size
and skull size require a large number of specimens to reach statistical significance
and obtain reliable results. Geographical distributions should be considered first
when identifying species or subspecies due to the disjunct habitats of Dipus. Our
molecular analyses revealed the long‐neglected potential diversity in arid regions
and improved the efficiency of species/subspecies identification. We also found that
individuals from more humid areas or higher altitudes were larger, whereas individu-
als from drier areas possessed longer appendages and larger tympanic bulla.
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CHENG Etal.
unique, complex landscapes with huge mountains and riv-
ers that partition the overall arid zone into several large
deserts (Cheng et al., 2017; Zhang, 2012). However, com-
pared to forest ecosystems, such as the Himalaya–Hengduan
Mountains in South‐west China (Wen et al., 2016), deserts
and arid regions are perceived as having low biological and
genetic diversity, which partially influences the identification
of psammophilic species (Brito et al., 2014; Durant et al.,
2012), especially taxonomic inferences based on morphology
alone (Petrova, Tesakov, Kowalskaya, & Abramson, 2016).
Molecular species delimitation, whose use has expanded in
recent years, offers an integrative taxonomic approach that
relies on both molecular data and morphology to identify and
describe species‐level diversity.
The genus Dipus is distributed in the desert, semi‐des-
ert and steppe of the Don River from south‐eastern Europe
through Central Asia to north‐eastern China, and it has the
largest geographical range among the Dipodinae, even among
Palaearctic desert rodents (Lebedev et al., 2018; Shenbrot,
Sokolov, Heptner, & Koval’skaya, 2008; Wilson & Reeder,
2005). Dipus has a specialized extended hind limb and sal-
tatorial locomotion, making them well adapted for the desert
environment. In addition, Dipus was found to have a male‐bi-
ased dispersal characteristic (Shenbrot et al., 2008) . The first
Dipus fossils were found from the middle of the Late Miocene
(7.50–9.10 Ma) in Central Inner Mongolia (Qiu & Li, 2005;
Qiu, Wang, & Li, 2006); similarly, Pisano et al. (2015) es-
timated the divergence time of Dipus at 8.66 Ma (7.67–
10.29 Ma) using molecular data. Dipus tended to spread from
eastern parts in China and Mongolia to the western parts in
Kazakhstan during its evolutionary history (Lebedev et al.,
2018). Dipus was long considered the least divergent in the
Dipodinae phylogenetic line and monotypic, including only
the northern three‐toed jerboa, Dipus sagitta Pallas, 1773
(Shenbrot et al., 2008; Wilson & Reeder, 2005). However,
the taxonomy within Dipus is still somewhat ambiguous.
Shenbrot et al. (2008) suggested that geographic variation in
the northern three‐toed jerboa was largely manifested in the
dimensions and proportions of the skull and the fur colour.
However, after examining specimens from the eastern half
of the range of the species, Ma, Wang, Jin, and Li (1987)
reported that morphological measurements and pelage colour
varied significantly with season and age due to wide distribu-
tion and unstable characteristics of the subspecies. Moreover,
the range of the variation within intra‐subspecies was even
greater than the average variation within inter‐subspecies.
Recent phylogeographic studies by Cheng et al. (2017)
and Lebedev et al. (2018) both revealed strong divergence
within the monotypic genus Dipus in both mitochondrial and
nuclear genes, as supported by well‐resolved Bayesian trees
and deep genetic distances in some clades (>10%). This dif-
ferentiation appears notably higher than that detected from
intraspecific studies of rodents (2.09% on average; Ben Faleh
et al., 2010) and greater than the average genetic distance
between sister rodent species (9.55% on average; Baker &
Bradley, 2006). Therefore, cryptic species diversity might
exist within Dipus. An integrative approach combining mor-
phology and molecular data is essential for identifying and
describing species‐level diversity because it avoids both the
underestimation of species richness and the camouflaging of
true phylogenetic relationships due to parallelisms and con-
vergence based on morphology alone as well as the increase
in species numbers due to over‐splitting based on molecular
data alone (Petrova et al., 2016).
To revise the taxonomy within Dipus in the present study,
we collected pictures of the skulls of specimens covering as
much of the entire distribution of the genus as possible to
explore intragenus skull variation by geometric morphomet-
rics (GM; Figure 1). We also collected morphological data of
body size and measured skull indices to understand morpho-
logical diversity. In addition to using molecular data from pre-
vious studies, we added three new nuclear genes and applied
different species delimitation methods to assess the stability
and congruence of the detected lineages. We attempted to (a)
reassess the taxonomy within the genus Dipus, (b) reassess the
taxonomic status of D. deasyi Barrett‐Hamilton, 1900 and (c)
reconstruct the phylogenetic relationship within Dipus.
2
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MATERIALS AND METHODS
2.1
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Molecular analyses
2.1.1
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DNA isolation,
amplification and sequencing
We collected 383 sequences of cytochrome b (Cytb), 148
sequences of cytochrome oxidase subunit I (COI), 53 se-
quences of breast cancer protein 1 (BRCA1), 57 sequences
of exon 10 of the growth hormone receptor (GHR), 106 se-
quences of exon 1 of the interphotoreceptor retinoid‐bind-
ing protein (IRBP) and 54 sequences of a portion of the
recombination‐activating protein 1 (RAG1) from GenBank
(accession numbers KX399483–KX399764, JX891491–
JX891500, JX891502–JX891511, JX891517–JX891524 and
MF535659–MF535907). All sequences came from 92 locali-
ties covering almost the entire distribution of Dipus (Cheng
et al., 2017; Lebedev et al., 2018; Liao et al., 2015). In addi-
tion, we added two new nuclear genes [cannabinoid receptor
1 (CNR1) and recombination‐activating protein 2 (RAG2)]
and more sequences of the BRCA1 gene from 35 localities.
The new sequence dataset generated here is available in the
GenBank repository with Accession numbers MG557704–
MG557728. Because of the shallow genetic divergence of
nuclear genes, we included only one or two specimens per
locality in the nuclear gene analyses. Detailed information on
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CHENG Etal.
the sampling localities is provided in Supporting Information
Table S1.
Total genomic DNA was extracted using a TIANamp
Genomic DNA Kit (DP304; Tiangen Biotech, Beijing, China)
according to the manufacturer’s instructions. All amplifica-
tions were conducted in 25‐μl reactions containing approxi-
mately 25 ng of extracted DNA, 200 μm each dNTP, 0.2 μm
each primer, 0.75 unit of LA Taq polymerase and 2.5 μl of
10× buffer. The amplifications were performed using the fol-
lowing PCR profiles: initial denaturation at 94°C for 3 min
followed by 35 cycles with denaturation at 94°C for 30 s,
annealing at 55–57°C (depending on the primers) for 30 s
and polymerization at 72°C for 1 min or 2 min (depending
on the length of the target), and a final extension at 72°C for
10 min. The primers and annealing temperatures along with
the corresponding primary references are listed in Supporting
Information Table S2.
2.1.2
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Phylogenetic analysis
Phylogenies were reconstructed using Bayesian inference
analysis (BI) and maximum likelihood (ML) approaches
with combined mitochondrial genes and separate and com-
bined nuclear genes. Each dataset was partitioned by gene,
allowing each one to evolve at different rates. The program
jmodeltest 2.1.7 (Darriba, Taboada, Doallo, & Posada, 2012)
was employed independently to select the best fit model of
base‐pair substitutions for each gene partition based on the
Bayesian information criterion (BIC), and we used MrBayes
v.3.2.5 (Ronquist et al., 2012) to estimate the topologies.
Two parallel runs, one cold and three heated, of Markov
chain Monte Carlo (MCMC) analyses were performed for
20 million generations or more, with trees sampled every
1,000 generations to produce convergence (SD < 0.01). The
first 25% of the Markov chain samples (N = 20,000) were
discarded as burn‐in, and the remaining samples were used
to generate majority rule consensus trees. Maximum like-
lihood phylogenies were inferred with RAxML v.8.2.10
(Stamatakis, 2014) using a GTRGAMMAI evolution model
and 1,000 bootstrapping replicates. Final trees were arranged
and formatted with FigTree v1.4.2 (available at http://tree.
bio.ed.ac.uk/software/fig-tree/).
2.2
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Species delimitation
To test species hypotheses for the clades of the northern three‐
toed jerboa, two different analyses were conducted using the
different datasets (Carstens, Pelletier, Reid, & Satler, 2013;
Razkin, Gomez‐Moliner, Vardinoyannis, Martinez‐Orti, &
Madeira, 2017). First, five different species discovery meth-
ods were used on the mitochondrial data to discover uncon-
firmed candidate species; species validation methods were
FIGURE 1 Sampling sites and extant distribution of Dipus, with major geographical features within the distribution area labelled. Locality
codes and coordinates are presented in supplementary Supporting Information Table S1. The shape of the symbol marking the sampling sites
represents the analyses used for each site. The colour of each sampling site indicates individuals belonging to corresponding subclades identified
by molecular analyses directly or deductively. The potential correspondences between subspecies and subclades are also labelled with different
colourful boxes. The red hollow hexagons indicate the typical localities of subspecies in a previous study: a, D. deasyi; b, D. s. aksuensis; c,
D. s. nogai; d, D. s. innae; e, D. s. austrouralensis; f, D. s. turanicus; g, D. s. ubsanensis; h, D. s. lagopus; I, D. s. megacranius; j, D. s. usuni; k,
D. s. sagitta; l, D. s. zaissanensis; m, D. s. bulganensis; n, D. s. halli; o, D. s. fuscocanus; p, D. s. sowerbyi
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CHENG Etal.
then used on all molecular datasets to validate the candidate
species.
2.2.1
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Molecular species discovery
As both genetic distances and P ID(Liberal) require a priori
species designation, we set 4–14 “candidate species” (i.e.
clades) based on a combination of phylogenetic topologies
from the gene trees (BI and ML trees; see the Results). To
analyse genetic distance, we examined the mean intraspe-
cific and interspecific Kimura two‐parameter (K2P) distance
and the p‐distance calculated for each “candidate species” in
MEGA 6.04 (Tamura, Stecher, Peterson, Filipski, & Kumar,
2013) and added Stylodipus telum sequences as a reference.
The species delimitation plugin (Masters, Fan, & Ross, 2011)
in GENEIOUS 9.1.4 (Kearse et al., 2012) was used to ob-
tain P ID(Liberal) statistical values and to calculate the mean
probability of the intra/inter genetic distance ratios for these
candidate species (Xu, Liu, Chen, Li, & Kuntner, 2015).
The following three methods do not require assigning
a priori information of candidate “species”. We first used
the Automatic Barcode Gap Discovery (ABGD) method
(Puillandre, Lambert, Brouillet, & Achaz, 2012) to calculate
all pairwise distances in the dataset, evaluate intraspecific di-
vergences and sort the terminals into candidate species based
on the calculated p values. We performed ABGD analyses
online (http://wwwabi.snv.jussieu.fr/public/abgd/) using three
different distance metrics: Jukes–Cantor (JC69; Jukes, Cantor,
& Munro, 1969), K2P (Kimura, 1980) and simple distance
(p‐distance; Nei & Kumar, 2000). We analysed the data using
Pmin: 0.001, Pmax: 0.1, Steps: 10, X (relative gap width): 1
or 1.5, with the other parameters set to default values. The
Generalized Mixed Yule Coalescent method (GMYC) uses a
ML framework to delimit species based on ultrametric tree,
and it estimates the transition point on a tree, before which
all nodes reflect species diversification events and after which
all nodes represent a population‐coalescent process (Pons
et al., 2006; Razkin et al., 2017). We recovered a new mito-
chondrial tree by BEAST 1.8.2 after removing identical se-
quences from the combined mitochondrial dataset because
zero‐length terminal branches hinder likelihood estimates
(Fujisawa & Barraclough, 2013; Razkin et al., 2017). All the
parameter settings were from a previous study (Cheng et al.,
2017). The GMYC tests were run using the web server (http://
species.h-its.org/gmyc/) under the single‐threshold model be-
cause prior studies have shown that the output of the multiple‐
threshold model is no better than that of the single‐threshold
model (Fujisawa & Barraclough, 2013). The Poisson tree
process (PTP) method (Zhang, Kapli, Pavlidis, & Stamatakis,
2013) is similar to the GMYC method in that it seeks to iden-
tify significant changes in the rate of branching in a phylo-
genetic tree, but rather than using time to estimate branching
rates as in the GMYC model, the PTP directly uses the number
of substitutions. We implemented the PTP method in the ma-
jority consensus tree from the above‐concatenated Bayesian
analysis of the final dataset in the bPTP web server (http://
species.h-its.org/ptp/) for 500,000 generations, with thin-
ning = 100 and burn‐in = 10%. The bPTP web server ran the
original ML version of the PTP as well as an updated version,
which adds Bayesian support to delimited species in the input
tree (Bayesian implementation of the PTP model or bPTP).
2.2.2
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Molecular species validation
We used the program bp&p version 3.2 (Yang & Rannala,
2010) and *BEAST (Heled & Drummond, 2010) to validate
the candidate species discovered with the mitochondrial
and nuclear sequence data. In bp&p, we used the A11 and
A01 algorithms to explore different species delimitation
models and species phylogenies. We ran reversible‐jump
MCMC (rjMCMC) analyses for 500,000 generations (with
a five generation sampling interval) with a burn‐in phase of
100,000. The priors were set to θ ~ G (20, 2, 000) and τ ~ G
(20, 1, 000), and the other divergence time parameters were
assigned to the Dirichlet prior (Yang & Rannala, 2014).
Each analysis was run twice with different starting seeds
to ensure consistency. Concatenated mtDNA and nDNA
sequences were analysed using *BEAST in BEAST 1.8.2
(Drummond, Suchard, Xie, & Rambaut, 2012), and the to-
pology was obtained from BI and ML trees. The substitu-
tion models were unlinked, and the substitution parameters
were set according to the jmodeltes t results. We chose the
Yule process tree priors model; the uncorrelated relaxed
log‐normal clock was set for all loci. The mtDNA muta-
tion rates were set to 2%, and nuclear genes were estimated
according to the mtDNA. The MCMC chains were run for
200 million generations with sampling every 5,000 genera-
tions. The convergence of the MCMC chains was examined
in Tracer 1.6, and the first 25% were discarded as burn‐in.
2.3
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Morphological analyses
2.3.1
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Taxon sampling
All the specimens for morphological analyses used in the present
study are preserved at the Institute of Zoology of the Chinese
Academy of Sciences (IOZCAS), the Zoological Museum of
Moscow State University (ZMMSU), the Zoological Institute
of the Russian Academy of Sciences in Saint Petersburg (ZISP)
and the Natural History Museum (London).
2.3.2
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Traditional morphometric methods
We explored differences in body size among four phyloge-
netic groups (see the Results). The morphological data in-
cluded the body mass (BM), body length (BL), tail length
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CHENG Etal.
(TL), hind foot length (FL) and ear length (EL) of 174
suitable voucher specimens from 46 localities. Juveniles
were excluded from the analysis; these were identified
based on the sutures on the cranium and the occlusal sur-
face of the tooth row (Lu et al., 2015). Eighteen measure-
ments (Supporting Information Table S3) were taken on
each skull from 152 suitable voucher specimens using cal-
lipers with an accuracy of 0.01 mm according to the guide
of measurement in Xia, Yang, Ma, Feng, and Zhou (2006)
and Yang, Xia, Ma, Feng, and Quan (2005).
To characterize the differences among the four phylo-
genetic groups, standard statistics including the mean and
standard error were applied. The pairwise differences in
body size and skull measurements between phylogenetic
groups were tested by single‐factor analysis of variance
(ANOVA) using both the least significant difference and
Tukey’s test. If the result of the homogeneity of variance
test for the measurement was not significant, Dunnett’s
test was used. All calculations were performed using log
10‐transformed measurements to linearize age variation
(Lissovsky, Yatsentyuk, & Ge, 2016). These analyses
were performed using SPSS Statistics version 21.0 (SPSS,
Chicago, IL, USA).
2.3.3
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Photography and digitization
A total of 191 skulls of the voucher specimens from 59
localities that covered most of the species distribution
(Figure 1) were included in the GM analyses (Adams,
Rohlf, & Slice, 2004). For each skull, 3 standardized 2D
images (Supporting Information Figure S2) were collected
using a Canon PowerShot S5IS (Japan) with a macro‐focus-
ing lens: the cranial dorsal view (including the nasal, fron-
tal and parietal bones), the cranial ventral view (including
the jugal, upper tooth row, auditory bulla and the palatine,
basisphenoid and basioccipital bones) and the mandible
lateral view (including the condylar, coronoid, and angular
processes and the lower tooth row). A scale was set in some
images using a ruler with cm as the unit of measure. Images
were standardized for specimen position, camera lens plane
and the distance between the lens of the camera and the
specimen.
2.3.4
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Geometric morphometrics
To digitize evenly distributed points along the contours
of structures, MakeFan8 (Sheets, Zelditch, & Swiderski,
2004) was used to establish guidelines before digitiza-
tion. Landmark digitization was conducted with tpsDig2
2.30 software (Rohlf, 2017). We selected and digitized 9
landmarks in the dorsal view of the cranium (DVC), 25
landmarks in the ventral view of the cranium (VVC) and
21 landmarks in the lateral view of the mandible (LVM).
These landmarks are showed in Supporting Information
Figure S2 and defined in Supporting Information
Table S4.
The raw datasets for each of the above three views were
examined to test whether specimens greatly deviated from
the average values. Morphological information (including
size and shape) was extracted from these three datasets
using a generalized full Procrustes fit (Goodall, 1991;
Rohlf & Slice, 1990), and all configurations were scaled
to the same size after variations in size and orientation
were removed. We later analysed the divergence in cra-
nium size and shape by defining phylogenetic groups ob-
tained from molecular phylogenetic analysis (see Results).
Principal component analysis (PCA) was conducted to
visualize shape differences between individuals, and we
used canonical variate analysis (CVA) to test the differ-
ences between different phylogenetic groups. All shape
analyses were performed in MorphoJ 1.06d (Klingenberg,
2011).
3
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RESULTS
3.1
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Molecular analyses
For the new nuclear DNA sequences, BRCA1 (808 bp), CNR1
(1,078 bp) and RAG2 (1,032 bp) were obtained from 41, 34
and 42 individuals, respectively. The best model accord-
ing to the BIC criterion was determined to be GTR+I+G,
GTR+G, HKY+I, HKY+G, GTR+G, HKY+G, and HKY+I
for mtDNA, BRCA1, CNR1, GHR, IRBP, RAG1 and RAG2,
respectively.
All pairs of trees resulting from Bayesian and ML
analyses of the mtDNA genes showed very similar to-
pological structures (Figure 2), but ML bootstrap values
(BS) were always lower than the corresponding Bayesian
posterior probability values (PP*100). The phylogenetic
topologies agreed on four highly supported (PP > 0.90,
BS > 60) phylogenetic groups, namely, the Deasyi
group, Turanicus group, Sagitta group and Sowerbyi
group (Figure 2). The Deasyi group was monophyletic
and placed as a sister to all other groups (PP = 1.00,
BS = 100). The Turanicus group was subdivided into
two subclades supported by PP = 0.89, BS = 73. The
phylogenetic relationships in the Sagitta group contained
subclades IIIb, IIIc, IIId and IIIe, which were solidly
supported (PP > 0.95, BS > 77). Subclade IIIa1+2 had
an extremely low support (PP = 0.59, BS = 36). The
Sowerbyi group was the most diversified group, with six
subclades, IVa–f, with intermediate to high support.
The tree for the combined six nuclear genes was not
completely in agreement with the mtDNA tree (Supporting
Information Figure S3). The Deasyi group had deep diver-
gence as a monophyly with PP = 1.00, BS = 100. The other
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CHENG Etal.
three groups showed significant paraphyly and clustered to-
gether with low support. However, it is notable that IIb and
IIIb clustered together, even though these two subclades
came from different groups. Similar clustering was ob-
served for subclades IIIa and IVc–f (Supporting Information
Figure S3).
636
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CHENG Etal.
3.2
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Species delimitation
3.2.1
|
Molecular species discovery
Based on our priori hypotheses, the four groups showed ap-
proximately 10% interspecific distance among each other
(Supporting Information Table S5). The lowest interspecific
distances were 9.06% (K2P) between the Sowerbyi group
and Turanicus group and 8.31% (p‐distance) between the
Sagitta+IIIa group and Turanicus group, whereas the highest
interspecific distance was 13.45/11.91% (K2P value on the
left of divide, p‐distance value on the right of divide, same
means of expression in following cases) between the Deasyi
group and Sagitta+IIIa group. In total, the Deasyi group
showed a higher mean interspecific distance (12.91/11.54%;
Figure 2) than the other phylogenetic groups; the Sowerbyi
group had shorter mean genetic distances (8.57–9.59/7.83–
8.69%). The results based on the BI tree indicated high P
ID(Liberal) values of ≥0.95 (0.85–1.00) with four phyloge-
netic groups or six subdivisions, which separated the Sagitta
group into two subclades (Supporting Information Table S6;
Figure 2). The intra/inter value for the Deasyi group was <0.1,
indicating shallow divergence within this group. However,
the Sagitta+IIIa group showed the highest intra/inter value
(0.49), clearly indicating deep genetic distance within this
group. The Turanicus and Sowerbyi groups showed interme-
diate intra/inter values of 0.23 and 0.22, respectively.
The ABGD results agreed on 5–7 candidate “species”
(Supporting Information Table S7) using different parame-
ter combinations and the initial 12–14 partition. The Deasyi,
Turanicus and Sowerbyi groups were considered independent
candidate “species”, whereas the Sagitta group was separated
into IIIb/IIIc+d+e or IIIb+c+d+e; IIIa was separated into IIIa1/
IIIa2 or not (Figure 2). Different numbers of groups were ob-
tained for recursive partition with differing prior maximal dis-
tances (P): 13–25 (P = 0.0010), 13–22 (P = 0.0017), 13–16
(P = 0.0028), 13–14 (P = 0.0046), 9–10 (P = 0.0077), 5–7
(P = 0.0129) and 5–7 (P = 0.0215). According to the sugges-
tions of Puillandre et al. (2012), initial and recursive partitions
were stable for P = 0.0129 (Razkin et al., 2017). We considered
the accurate result is 5–7 candidate “species” (P = 0.0129). The
following two analyses suggested more candidate “species” be-
cause they identified additional subclades within the four phy-
logenetic groups. The single‐threshold GMYC model resulted
in 11 clusters and 22 entities with different confidence inter-
vals of 7–17 and 16–30, respectively (Supporting Information
Table S8), 2 of which included only one or two specimens
(Figure 3). The ML obtained with the GMYC model was sig-
nificantly higher than the likelihood observed in the null model:
GYMC model = 884.1897, null model = 857.8582, likelihood
ratio = 52.6631 and LR test <0.0001. The ML and Bayesian
solution PTPs identified 29 and 30 “species”, respectively, 20
of which included only one or two specimens (Figure 3). The
PhyloMap visualization of the PTP species delimitation result
showed six distinct taxa (Figure 2), consistent with previous
analyses. Consensus delimitation for the discovery of 11 can-
didate species was obtained after grouping or removing candi-
date entities containing less than five specimens (Razkin et al.,
2017), except IIa and IIIc (Figure 3).
3.2.2
|
Molecular species validation
The BP&P analysis identified 14 candidate “species” as
distinct clades (A11: PP > 0.85). The species tree of the
combined mtDNA and nuclear genes showed an inconsist-
ent structure and low support compared to the mtDNA tree
(Figure 3). The Deasyi group was delimited with a posterior
probability of 1.00, whereas the other groups yielded different
results. However, the *BEAST tree showed a phylogenetic
tree similar to that of mtDNA tree, except for the position of
the Turanicus group (Figure 3). The Deasyi group was also
delimited with PP = 1.00. This relatively low support value
and variable topological structure in the two analyses is due
to the weak divergence and slow evolutionary rate of the nu-
clear genes. Only the Deasyi group could be differentiated
from the other taxa.
3.3
|
Morphological analyses
The general variation in the body size of the four groups
is given in Supporting Information Tables S9 and S10.
The Sagitta group had the largest body size, with an aver-
age BW of 86.64 ± 18.37 g (53–123 g, n = 48) and BL of
125.69±10.15 mm (100–145 mm, n = 49), whereas the
Deasyi group possessed the largest appendages, with an
average TL of 173.42±10.96 mm (144–201 mm, n = 31),
HL of 62.90±2.07 mm (58–67 mm, n = 31) and EL of
20.77±2.08 mm (17–25 mm, n = 31). Based on the ANOVA
FIGURE 2 Bayesian mtDNA gene tree for 217 terminals of Dipus, with the results of four different species delimitation approaches,
including morphology. Numbers below branches show posterior probabilities and bootstrap support. Values beside clades names show mean
interspecific genetic distances, calculated as Kimura two‐parameter/p‐distance. The correspondence between each subclade and geographical
distribution is as follows: I, Tarim Basin and south‐west of Qaidam; IIa, North Caucasus, IIb, Turan Plain and west Kazakhstan; IIIa, North‐west
Great Lake depression, IIIb, Aral Karakums and south Lake Balkhash, IIIc, Irtysh valley, IIId, West Zaisan depression, IIIe, Junggar Basin and
Mongolian Dzungaria; IVa, East Mongolian Plateau and north‐east China, IVb, Central Mongolia and East Gobi, IVc, Ordos Plateau, IVd, Turpan
Basin, IVe, Great Lake Basin, IVf, North‐east Qaidam, Hexi Corridor, Alashan, Transaltai Gobi
|
637
CHENG Etal.
results (Supporting Information Table S10), TL and EL of
the Deasyi group and HL of the Sowerbyi group were signifi-
cantly different (p < 0.05).
For the skulls, only specimens of the Deasyi, Sagitta
and Sowerbyi groups were measured. Six significantly vari-
able indices (LBBO, GMB, LPF, WPF, LTB and ALCT)
were screened out among the three groups (Supporting
Information Tables S11 and S12). The Sagitta group had
the largest LBBO of 10.81 ± 0.77 mm (9.48–12.23 mm,
n = 29) and GMB of 20.92 ± 0.66 mm (19.32–22.71 mm,
n = 29), but the smallest LPF of 5.16 ± 0.51 mm (4.18–
6.15 mm, n = 29). The Deasyi group had the smallest LBBO
of 10.30 ± 0.42 mm (9.19–11.24 mm, n = 36) and GMB of
19.06 ± 1.42 mm (16.85–21.52 mm, n = 36), but the largest
LTB 9.82 ± 0.39 mm (9.02–10.88 mm, n = 36) and ALCT
6.01 ± 0.30 mm (5.47–6.66 mm, n = 36). The ANOVA also
resulted in the most significant variation between Deasyi and
the other two groups (Supporting Information Table S12).
A total of 191 intact skull voucher specimens were
available for the four phylogenetic groups (Deasyi group,
n = 35; Sagitta group, n = 55; Sowerbyi group, n = 94;
and Turanicus group, n = 7). We analysed skull morpho-
logical divergence among the groups. No outliers were
identified in DVC, VVC and LVM. Mahalanobis distances
(MD) and Procrustes distances (PD) were detected in CVA.
Significant shape variation between the Deasyi group and
the other groups was observed in all views (p < 0.0001 in
MD and p < 0.05 in PD; Figure 4a–c). In the DVC view,
all shape variations were significant (p < 0.01 in MD and
p < 0.05 in PD), despite the partially overlapping area
(Figure 4a). The VVC view showed the most clear variation
among the phylogenetic groups (p < 0.0001 in MD and PD;
Figure 4b), except PD (p = 0.1670) between the Sagitta and
Turanicus groups. In the LVM view, the Turanicus group
showed a largely overlapping area with the Sowerbyi group
(Figure 4c), which was confirmed by PD (p = 0.1230).
4
|
DISCUSSION
4.1
|
Phylogenetic relationships and
taxonomic reassessment in Dipus
The northern three‐toed jerboa, Dipus, has long been con-
sidered the least diversified in the Dipodinae phylogenetic
line, which includes only one species, D. sagitta (Pallas,
1773). This species is highly specialized to desert habitat
and is highly distinct (both genetically and morphologically)
from its closest living relatives (Stylodipus). In part due to
its fragmented distribution and unstable characteristics for
partitioning subspecies, the traditional taxonomy of Dipus
has been problematic. In the current study, we used a “can-
didate species approach” with the divergent mtDNA clades
and subspecies identified in previous studies as the starting
point (Cheng et al., 2017; Lebedev et al., 2018; Shenbrot
et al., 2008). Because the nuclear and mitochondrial markers
should be in concordance to document the presence or ab-
sence of species and to avoid overestimation of species num-
ber caused using only molecular data (Bezerra et al., 2016),
morphometric analyses and molecular phylogenetic analyses
were combined.
FIGURE 3 Summary of the results of the species delimitation analyses (including both discovery and validation approaches) represented
on a phylogenetic tree of the concatenated dataset. Grey boxes represent resultant candidate species (identified in discovery analyses); consensus
discovery is in colourful boxes. Black lines along the GMYC and PTP indicate that less than four individuals were included in these candidate
groups. The ultrametric tree was based on mtDNA data. The coalescent species tree was estimated by BPP and *BEAST based on all sequences.
Posterior probabilities are shown at the nodes
638
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CHENG Etal.
Shenbrot et al. (2008) divided D. sagitta (i.e. Dipus)
into the “Sagitta” and “Lagopus” groups based on the
structure of the hind limbs (subdigital skin pad size and
lobe number), the colour of the inner hairs of the tuft on the
foot and the shape of the tail flag as well as the genitalia
and karyotype along the Irtysh River and boundary moun-
tains between China and Kazakhstan. Although karyosys-
tematic methods are particularly useful in the case of taxa
that lie between the species level and the subfamily‐family
level, karyosystematics is of little help in differentiating
intraspecific and higher taxa and karyotype variability is
a common phenomenon within rodent populations/species
(McKenna, 1986; Vorontsov, 1979). Furthermore, phylo-
geographic studies of D. sagitta (i.e. Dipus) have shown
that only continuously large mountains can act as genetic
barriers, but the average elevation of the boundary moun-
tains is approximately 1,000–2,000 m, which is not high
enough to obstruct genetic communication between the
two side areas (Cheng et al., 2017). The individuals dis-
tributed in the Junggar Basin also presented longer genetic
distances from the individuals from the eastern distribution
area (Figures 1 and 2). Therefore, this two‐group division
cannot reflect the true differentiation.
Based on the results of molecular and morphological
analyses, we proposed a new division method in which the
whole Dipus genus was clearly divided into four significant
phylogenetic groups (i.e. the Deasyi group, Sagitta group,
Sowerbyi group and Turanicus group; the origins of these
names are discussed in the next section; Figures 1, 2 and 4).
There is a clear segmentation of the geographic boundaries of
the four groups in the broad mid‐latitude arid zone of Eurasia
(Figure 1). The basic reason for the genetic barriers is that the
suitable habitats of Dipus are interrupted by the formation
of geographical boundaries (Cheng et al., 2017). Among the
four groups, the Deasyi group occupies the Tarim Basin and
the southern and western Qaidam Basin in China; the Sagitta
group is distributed from the Altay and Tianshan Mountains
westward to the Aral Sea; the Sowerbyi group occupies the
Mongolian Plateau and adjacent areas; and the Turanicus
group is distributed on most of the Turan Plain and lowland
around the Caspian Sea.
The BI and ML trees highly support the four groups
(PP > 0.93, BS > 61), and the K2P and p‐distance for each
group ranged from 9.06/8.31% to 13.06/11.91%. Notably,
this differentiation level has been observed in other inter-
specific studies of rodents (Ben Faleh et al., 2012; Petrova,
Zakharov, Samiya, & Abramson, 2015). Because of the large
differentiation within the Sagitta group, P ID(Liberal) and
ABGD yielded a more detailed partition method, with 6 (P
ID ≥ 0.95; 0.84–1.00) and 5–7 subdivisions, respectively. It
FIGURE 4 Variation in the shape and principal component analysis of the dorsal and ventral views of the cranium and lateral views of the
mandible in voucher specimens. Canonical variant plots of the dorsal, ventral and mandible cranium are given in a, b and c, respectively. Principal
component plots of the dorsal, ventral and mandible cranium are given in d, e and f, respectively. The data points on these plots are coloured
according to taxonomic status based on the phylogenetic tree as well as traditional subspecies delimitation. The ellipses give 90% confidence equal
frequencies for the four phylogenetic groups
|
639
CHENG Etal.
is not inconsistent with the four groups; on the contrary, these
two analyses supplemented additional information about the
divergence level. As it is suggested to choose delimitations
that are concordant among different species‐delimitation
analyses (Carstens et al., 2013), consensus delimitation of
GMYC and PTP eliminated candidate groups/entities with
few specimens and selected 11 candidate species (Figure 3).
However, the structure of the nuclear genes revealed some
paraphyletic subclades; only the Deasyi group was supported
as a monophyly with deep divergence. This might be caused
by the male‐biased dispersal characteristic. The nuclear gene
clades from neighbouring areas tended to cluster together,
rather than clades from the same phylogenetic group. For ex-
ample, IIb and IIIb, IIIa and IVe in bp&p and IIa, IIb and IIIb
in the *BEAST species tree clustered together (Figure 3).
Although Dipus appeared in the middle of the Late
Miocene (7.50–9.10 Ma) according to fossil records (Qiu &
Li, 2005; Qiu et al., 2006), compared to other rodent taxa that
experienced explosive radiation (Lv, Xia, Ge, Wu, & Yang,
2016; Parada, Pardinas, Salazar‐Bravo, D’Elia, & Palma,
2013), the extant Dipodidae species have a relatively low evo-
lutionary rate and a low level of diversification (Pisano et al.,
2015). In the fossil Dipus species, changes in tooth size and
tooth crown height have been found, whereas morphological
characteristics have remained similar since the late Miocene
(Liu, Zhang, Cui, & Fortelius, 2008). In the GM analysis,
the Turanicus group showed largely visualized overlap with
the others in all views in CVA. In addition, the terrain of this
arid zone is relatively simple compared to the mountains in
mid‐ or low‐latitude regions, which favours the male‐biased
dispersal and genetic communication that results in morpho-
logical conservatism and low divergence of nuclear genes
(Cheng et al., 2017; Shenbrot et al., 2008).
In summary, we suggest that the whole genus Dipus should
be divided into four phylogenetic groups including two spe-
cies: the Deasyi group (i.e. D. deasyi), with strong evidence
from mtDNA, nuclear DNA and morphological data (dis-
cussed in the next section) and the Sagitta group, Sowerbyi
group and Turanicus group (i.e. D. sagitta). The deep diver-
gence in mtDNA among groups in D. sagitta already reaches
the interspecies level in rodents. However, due to the limits
of morphological data (especially for the Turanicus group)
and the paraphyletic structure from the nuclear gene tree, we
conservatively regard the three groups as D. sagitta.
4.2
|
Genetic divergence and subspecies
taxonomy of Dipus
Previous taxonomic studies of Dipus mainly used traditional
morphological measurements and body shapes; nearly 17
names of subspecies, including synonyms, were established.
Detailed information on the subspecies with some modifica-
tions is provided in Table 1. Combined with the molecular
sequences covering nearly the whole distribution of Dipus,
we reviewed the taxonomy within Dipus, including species
and subspecies, particularly the relationship between genetic
clades and traditional subspecies.
4.2.1
|
Taxonomic status of Dipus deasyi,
Barrett‐Hamilton, 1900 and D.s. aksuensis in
Deasyi group
The Deasyi group showed robust differentiation from the
other groups in all analyses. Genetic variation of the Deasyi
group was highly supported in the BI and ML trees and the
genetic distance (11.54/12.91%) in mtDNA, consistent with
the acknowledged range of interspecific genetic variation
(Baker & Bradley, 2006). The nuclear gene tree and all spe-
cies delimitation and validation analyses suggested that the
Deasyi group is a monophyly with high support. Furthermore,
morphological measurements agreed that the appendages
were significantly longer in the Deasyi group than the other
groups; significant shape variation between the Deasyi group
and other groups was also observed in all views. It is reason-
able to regard the Deasyi group as a separate species from the
other groups in Dipus.
The Deasyi group mainly occupies the Tarim Basin and
the southern and western Qaidam Basin in China (Figure 1).
The type localities of Dipus deasyi, Barrett‐Hamilton, 1900;
D. s. aksuensis Wang, 1964 and D. s. fuscocanus Wang,
1964, are located in this area. We compared specimens from
these localities, including (a) the only holotype specimen of
D. s. fuscocanus without its skull; (b) six specimens, includ-
ing the holotype of D. s. aksuensis; and (c) type specimens
of D. s. deasyi. We found that the pelage colour of D. s. fus-
cocanus was more similar to that of D. s. sowerbyi, and the
body size of D. s. aksuensis was truly smaller than that of
D. s. deasyi. However, considering that the significant vari-
ation in pelage colour and skull size is influenced by several
factors, it would be hasty to describe a new subspecies based
on so few specimens. Furthermore, molecular data showed
that samples from Aksu (locality 51; type locality of D. s. ak-
suensis) do not cluster together as a monophyly in the Deasyi
group. Samples from Heshuo (locality 54), which is near Korla
(type locality of D. s. fuscocanus), clustered as a monophyly
in the Sowerbyi group in all molecular analyses. Therefore,
we considered that (a) D. deasyi Barrett‐Hamilton, 1900 is
the valid name for the new separate species and (b) D. s. ak-
suensis is conspecific and a junior synonym of D. deasyi.
Dipus deasyi was long considered a remarkably similar
external form with inconstant identification characteristics
from other taxa in Dipus. However, in the original descrip-
tion, Barrett‐Hamilton (1900) noted that “…the external
appearance resembles D. loftusi Blanford, but the colour of
the upper surface is richer and not so brown; the exact tint
being somewhere between ‘Ecru drab’ and ‘Fawn colour’.
640
|
CHENG Etal.
Skull resembles that of D. lagopus Licht., but the teeth
are more massive and their pattern less complicated….”
Wang and Yang (1983) also noted that “… in specimens
from South Xinjiang, the anterior fold of the first upper
molar is moved more to the lateral side, and the lingual
side of the anteriority concaves inward lightly, which re-
sults in three obtuse convex angles on the lateral side and
a total of five dental lamina…”. Ma et al. (1987) compared
D. deasyi to D. s. sowerbyi and D. s. bulganensis (regarded
as D. s. zaissanensis by the authors); according to their
TABLE 1 List of the distribution information and correspondence with subclades from the phylogenetic tree of taxa in Dipus, including
species and subspecies levels
Phylogenetic group
Subclade in
phylogenetic tree
Potential matching
species/subspecies Distribution Revision & comments
Deasyi group I D. deasyi Tarim Basin and southern and western
Qaidam Basin
Valid; syn. D. s. aksuen-
sis Wang, 1964
Turanicus group IIa D. s. nogai Dagestan, Kalmykia, Astrakhan region
(right bank Volga), left bank of North
Don
Valid; need more
sample
IIb D. s. austrouralensis Sandy deserts and semi‐deserts of
Ural‐E'mba interfluve
Need more sample
D. s. innae Sandy deserts and semi‐deserts of
Volga‐Ural interfluve
Need more sample; syn.
D. s. kalmikensis
Kazantseva, 1940
D. s. turanicus Turan Plain and west Kazakhstan Valid
Sagitta group IIIa1 D. s. ubsanensis Tuva Valid
IIIa2 D. s. ssp.1 North‐west Great Lake depression Need more samples
IIIb D. s. lagopus Sands of Greater and Lesser Barsuki,
Aral Karakums, sands of lower stream
of Turgai(Tosynkum) and Sarysu
(Sarysu Muyunkums, Zhetykonur)
Valid
D. s. megacranius Chui Muyunkums Need more samples
D. s. usuni Sandy massifs of southern Lake
Balkhash area and Ili basin
Need more samples
IIIc D. s. sagitta Winding pine forests of right bank of
Irtysh in semi‐palatinsk and Pavlodar
regions of Kazakhstan and south of
Altai territory
Valid
IIId D. s. zaissanensis North‐western part of Zaisan Hollow Valid
IIIe D. s. bulganensis Junggar Basin (North‐western China,
Dzhungaria) and Mongolian
Dzungaria
Valid
Sowerbyi group IVa D. s. halli Eastern Mongolia, North‐eastern China
(Sandy land of Horqin, Hulun Buir
and Hunshandake)
Valid
IVb D. s. ssp.2 China (north of the Yinshan Mountains
and Daqingshan Mnountains);
Mongolia (Central and Eastern Gobi)
Need more morphologi-
cal sample
IVc D. s. ssp.3 Erdos Plateau (Mu Us Sandy Land,
Kubuqi Desert)
Need more morphologi-
cal sample and
compare with
D. s. sowerbyi
IVd D. s. fuscocanus North‐eastern Kashgaria Need more sample
IVe D. s. ssp.4 Valley of great lakes, basin of Gobi
lakes, Gobi Altai
Need more morphologi-
cal sample
IVf D. s. sowerbyi North‐east Qaidam, Hexi Corridor,
Alashan, Transaltai Gobi
Need to compare with
D. s. ssp.3
|
641
CHENG Etal.
description, although the pelage colour showed variation,
all specimens of D. deasyi showed lighter pelage (sandy
colour) and longer tails.
After we reviewed a series of specimens, including
type specimens of D. deasyi and D. s. sowerbyi, we also
observed differences in the number of dental lamina in
the first upper molar, although this unique characteristic
can be influenced by tooth abrasion with age. In the skull,
D. deasyi has the smallest LBBO and GMB but the largest
LTB and ALCT, resulting in a sharper shape at the palate
(Supporting Information Table S11). A recent similar study
by Lebedev et al. (2018) also suggested the taxonomic sta-
tus of D. deasyi.
4.2.2
|
Taxonomic discussion in the
Turanicus group and Sagitta group
Two clades are separated within the Turanicus group and
correspond to the following subspecies: IIa – D. s. nogai,
western coast of the Caspian Sea; IIb – D. s. turanicus,
D. s. innae and D. s. austrouralensis, the Turan Plain and
west Kazakhstan. The Turanicus group was named after
the dominant taxon, D. s. turanicus. The Syr Darya ap-
pears to have acted as a potential genetic barrier between
the Turanicus and Sagitta groups (Figure 1); however, the
clustered nuclear genes of IIb and IIIb reject this hypoth-
esis (Figure 3 and Supporting Information Figure S3).
Morphological analyses also indicated no significant dif-
ferentiation between the Turanicus group and the other
groups. Therefore, we still regarded the group as D. sag-
itta, and more molecular samples and morphological speci-
mens are needed for analysis.
The Sagitta group is subdivided into four subclades,
including IIIb – D. s. lagopus, D. s. megacranius and
D. s. usuni, Aral Karakum and south coast of Lake Balkhash;
IIIc – D. s. sagitta, Irtysh valley; IIId – D. s. zaissanensis,
west Zaisan depression; IIIe – D. s. bulganensis, Junggar
Basin and Mongolian Dzungaria. The Sagitta group was
named after the nominate subspecies D. s. sagitta. IIIb shows
a large distribution area that includes the type localities of
three subspecies. The low divergence within IIIb is possible
due to the lack of obvious geographic barriers; the large mor-
phological variation among the three subspecies might be
caused by different climate factors (Supporting Information
Figure S1). IIIc and IIId are distributed in very narrow areas,
which may have acted as refugia during the Quaternary cli-
mate change. IIIe is widespread with high haplotype diver-
sity and low nucleotide diversity (Cheng et al., 2017), and
D. s. bulganensis matched this subclade.
Subclade IIIa includes IIIa1 – D. s. ubsanensis and
IIIa2 – D. s. ssp.1 distributed in the North‐west Great Lake
depression. The status of IIIa2 requires further investiga-
tion. It needs to be explained separately because of its low
support values of PP and BS in the phylogenetic tree. In ad-
dition, the phylogenetic position of IIIa was different from
that in a recent study by Lebedev et al. (2018). It is difficult
to attribute IIIa to Sagitta group or Sowerbyi group or in-
dependent phylogenetic group. To avoid the Sagitta group
being paraphyly, we temporarily do not process the position
of subclade IIIa, even if IIIa and Sagitta group presented
a monophyletic structure on the phylogenetic tree. Further
investigation and analysis need to be conducted to confirm
the position of IIIa and its relationship with Sagitta group
and Sowerbyi group.
4.2.3
|
Diversification and taxonomy
within the Sowerbyi group
The Sowerbyi group was the taxon with the highest ge-
netic divergence; only three subspecies were identified in
past research (Wilson & Reeder, 2005). The attributable
relationships between subclades and subspecies are IVa –
D. s. halli, East Mongolian Plateau and north‐east China;
IVb – D. s. ssp.2, Central Mongolia and East Gobi from
the north slope of Yinshan Mountains; IVc – D. s. ssp.3,
Ordos Plateau; IVd – D. s. fuscocanus, Turpan Basin; IVe –
D. s. ssp.4, Great Lake Basin; IVf – D. s. sowerbyi, North‐
east Qaidam, Hexi Corridor, Alashan, Transaltai Gobi. The
Sowerbyi group takes its name from D. s. sowerbyi, which
was named earlier than the other two subspecies.
In the present study, IVa showed robust position and high
support in most analyses; the mtDNA genetic distance be-
tween IVa and the other clades in the Sowerbyi group varied
from 3.08% to 3.46% (Cheng et al., 2017), consistent with the
acknowledged range of intraspecific genetic variation (Baker
& Bradley, 2006). Dipus sagitta halli is widely acknowledged
as a subspecies and is distributed in the easternmost areas of
the mid‐latitude arid zone of Eurasia (Shenbrot, 1991), con-
sistent with the distribution range of IVa. Furthermore, speci-
mens sampled from localities belonging to IVa had the largest
body size in our morphological data (not show), which is
also an important morphological diagnosis of D. s. halli.
The living environment of D. s. halli provides more food
and a moderate environment compared with areas further in-
land, which could support more species. Increased interspe-
cific competition could promote larger body size (Du et al.,
2017; Ochocinska & Taylor, 2003). Therefore, we consider
D. s. halli a valid subspecies.
Specimens from the areas where subclades IVb, IVc,
IVe and IVf are distributed have long been recognized as
the subspecies D. s. sowerbyi. Subclade IVd corresponds
to subspecies D. s. fuscocanus. However, the phylogenetic
analysis revealed surprising intraspecific diversification as
well as increased taxonomic doubt, especially the Central
Inner Mongolia region where three subclades coexisted
here (Figure 1). The primary problem is that there are two
642
|
CHENG Etal.
subclades, IVc and IVf, coexisting in the type locality of
D. s. sowerbyi. This subspecies was first described based
on specimens from Yulinfu, Shensi, China (now north of
Yulin City, Shaanxi, China; near locality 46). Second, sub-
clade IVf covers the widest ecological range with regard
to humidity and elevation, and the variation in elevation is
from below sea level to the Qinghai–Tibetan Plateau (over
3,000 m). Specimens coming from north and east Qaidam
Basin have larger bodies than those from Hexi Corridor.
This partly verifies the viewpoint that the measurements and
pelage colour show significant seasonal variation, and the
intra‐subspecies variations were even larger than the average
inter‐subspecies variations (Ma et al., 1987). Third, after we
checked the voucher specimens from the localities of IVb,
IVc, IVd and IVf, our preliminary morphological data indi-
cated unstable pelage colour and no significant divergence
in GM analysis. Therefore, we temporarily attributed IVb‐f
to D. s. ssp.2, D. s. ssp.3, D. s. fuscocanus, D. s. ssp.4, and
D. s. sowerbyi, respectively. The status of these subclades re-
quires additional sampling efforts in the future.
5
|
CONCLUSION
Through an objective species delimitation approach includ-
ing multilocus gene and morphological data, we propose
that Dipus can be divided into four phylogenetic groups in-
cluding two species: the Deasyi group (D. deasyi); Sagitta
group, Sowerbyi group and Turanicus group (D. sagitta).
According to the morphological analyses of the specimens
we examined, we suggested that pelage colour shows sig-
nificant variation with season and age and is therefore un-
suitable as a diagnostic characteristic of the subspecies.
Measurements of body and skull size require a large number
of specimens to achieve statistical significance and reliable
results. Geographical distributions should be considered first
when identifying Dipus species or subspecies due to the dis-
junct habitat of the genus. Our molecular analyses revealed
the long‐neglected potential diversity in arid regions and
facilitated more efficient species/subspecies identification,
but additional morphological data, particularly from Central
Asia, are needed to fully resolve the taxonomic status of the
Turanicus group, Sagitta group and Sowerbyi group within
this genus. We also found a tendency of individuals from
more humid areas or higher altitudes to be larger, whereas
individuals from drier areas possessed longer appendages
and larger tympanic bulla. Experimental studies are needed
to properly address issues related to adaptive evolution.
ACKNOWLEDGEMENTS
We thank the editors and anonymous reviewers for providing
valuable comments. We sincerely thank Xue Lv, Yuanbao
Du and Yongbin Chang for their help with both the fieldwork
and software analyses. We thank Gregory I. Shenbrot for his
suggestions and prior work on jerboas. We also thank the re-
searchers who submitted sequences from previous studies to
GenBank. This research was supported by grants from the
Key Laboratory of Zoological Systematics and Evolution of
the Chinese Academy of Sciences (No. Y229YX5105).
ORCID
Jilong Cheng https://orcid.org/0000-0003-0959-0521
Qisen Yang https://orcid.org/0000-0001-9843-2378
REFERENCES
Adams, D. C., Rohlf, F. J., & Slice, D. E. (2004). Geometric mor-
phometrics: ten years of progress following the ‘revolu-
tion’. Italian Journal of Zoology, 71, 5–16. https://doi.
org/10.1080/11250000409356545
Baker, R. J., & Bradley, R. D. (2006). Speciation in mammals and the
genetic species concept. Journal of Mammalogy, 87, 643–662.
https://doi.org/10.1644/06-MAMM-F-038R2.1
Barrett‐Hamilton, G. (1900). On a small collection of mammals obtained
by Captain Deasy in South Chinese Turkestan and Western Tibet.
Proceedings of the Zoological Society of London, 68, 196–197.
Ben Faleh, A., Cosson, J. F., Tatard, C., Ben Othmen, A., Said, K.,
& Granjon, L. (2010). Are there two cryptic species of the
lesser jerboa Jaculus jaculus (Rodentia: Dipodidae) in Tunisia?
Evidence from molecular, morphometric, and cytogenetic data.
Biological Journal of the Linnean Society, 99, 673–686. https://
doi.org/10.1111/j.1095-8312.2010.01374.x
Ben Faleh, A., Granjon, L., Tatard, C., Boratyński, Z., Cosson, J.
F., & Said, K. (2012). Phylogeography of two cryptic spe-
cies of African desert jerboas (Dipodidae: Jaculus). Biological
Journal of the Linnean Society, 107, 27–38. https://doi.
org/10.1111/j.1095-8312.2012.01920.x
Bezerra, A. M. R., Annesi, F., Aloise, G., Amori, G., Giustini, L., &
Castiglia, R. (2016). Integrative taxonomy of the Italian pine
voles, Microtus savii group (Cricetidae, Arvicolinae). Zoologica
Scripta, 45, 225–236. https://doi.org/10.1111/zsc.12155
Brito, J. C., Godinho, R., Martinez‐Freiria, F., Pleguezuelos, J. M.,
Rebelo, H., Santos, X., … Carranza, S. (2014). Unravelling bio-
diversity, evolution and threats to conservation in the Sahara‐
Sahel. Biological Reviews, 89, 215–231. https://doi.org/10.1111/
brv.12049
Carstens, B. C., Pelletier, T. A., Reid, N. M., & Satler, J. D. (2013).
How to fail at species delimitation. Molecular Ecology, 22, 4369–
4383. https://doi.org/10.1111/mec.12413
Cheng, J., Lv, X., Xia, L., Ge, D., Zhang, Q., Lu, L., & Yang, Q. (2017).
Impact of orogeny and environmental change on genetic diver-
gence and demographic history of Dipus sagitta (Dipodoidea,
Dipodinae) since the Pliocene in inland east Asia. Journal of
Mammalian Evolution, 000, 1–14. https://doi.org/10.1007/
s10914-017-9397-6
Darriba, D., Taboada, G. L., Doallo, R., & Posada, D. (2012). jmodeltest
2: more models, new heuristics and parallel computing. Nature
Methods, 9, 772. https://doi.org/10.1038/nmeth.2109
|
643
CHENG Etal.
Drummond, A. J., Suchard, M. A., Xie, D., & Rambaut, A. (2012).
Bayesian phylogenetics with BEAUti and the BEAST 1.7.
Molecular Biology and Evolution, 29, 1969–1973. https://doi.
org/10.1093/molbev/mss075
Du, Y., Wen, Z., Zhang, J., Lv, X., Cheng, J., Ge, D., … Yang, Q. (2017).
The roles of environment, space, and phylogeny in determining
functional dispersion of rodents (Rodentia) in the Hengduan
Mountains, China. Ecology and Evolution, 7, 10941–10951.
https://doi.org/10.1002/ece3.3613
Durant, S. M., Pettorelli, N., Bashir, S., Woodroffe, R., Wacher, T.,
De Ornellas, P., … Baillie, J.E.M. (2012). Forgotten biodiver-
sity in desert ecosystems. Science, 336, 1379–1380. https://doi.
org/10.1126/science.336.6087.1379
Fujisawa, T., & Barraclough, T. G. (2013). Delimiting species using
single‐locus data and the generalized mixed yule coalescent ap-
proach: a revised method and evaluation on simulated data sets.
Systematic Biology, 62, 707–724. https://doi.org/10.1093/sysbio/
syt033
Goodall, C. (1991). Procrustes methods in the statistical analy-
sis of shape. Journal of the Royal Statistical Society Series B
(Methodological), 53, 285–339.
Heled, J., & Drummond, A. J. (2010). Bayesian inference of species
trees from multilocus data. Molecular Biology and Evolution, 27,
570–580. https://doi.org/10.1093/molbev/msp274
Jukes, T. H., Cantor, C. R., & Munro, H. (1969). Evolution of protein
molecules. Mammalian Protein Metabolism, 3, 132.
Kearse, M., Moir, R., Wilson, A., Stones‐Havas, S., Cheung, M.,
Sturrock, S., … Drummond, A. (2012). Geneious basic: an in-
tegrated and extendable desktop software platform for the or-
ganization and analysis of sequence data. Bioinformatics, 28,
1647–1649. https://doi.org/10.1093/bioinformatics/bts199
Kimura, M. (1980). A simple method for estimating evolutionary rates
of base substitutions through comparative studies of nucleotide
sequences. Journal of Molecular Evolution, 16, 111–120. https://
doi.org/10.1007/BF01731581
Klingenberg, C. P. (2011). MorphoJ: an integrated software package
for geometric morphometrics. Molecular Ecology Resources, 11,
353–357. https://doi.org/10.1111/j.1755-0998.2010.02924.x
Krystufek, B., Klenovsek, T., Amori, G., & Janzekovic, F. (2015).
Captured in ‘continental archipelago’: phylogenetic and envi-
ronmental framework of cranial variation in the European snow
vole. Journal of Zoology, 297, 270–277. https://doi.org/10.1111/
jzo.12274
Lebedev, V. S., Bannikova, A. A., Lu, L., Snytnikov, E. A., Adiya, Y.,
Solovyeva, E. N., … Shenbrot, G. I. (2018). Phylogeographical
study reveals high genetic diversity in a widespread desert ro-
dent, Dipus sagitta (Dipodidae: Rodentia). Biological Journal
of the Linnean Society, 123, 445–462. https://doi.org/10.1093/
biolinnean/blx090
Liao, J., Jing, D., Luo, G., Wang, Y., Zhao, L., & Liu, N. (2015).
Comparative phylogeography of Meriones meridianus, Dipus
sagitta, and Allactaga sibirica: potential indicators of the
impact of the Qinghai‐Tibetan Plateau uplift. Mammalian
Biology‐Zeitschrift für Säugetierkunde, 81, 31–39. https://doi.
org/10.1016/j.mambio.2015.05.002
Lissovsky, A. A., Yatsentyuk, S. P., & Ge, D. (2016). Phylogeny and
taxonomic reassessment of pikas Ochotona pallasii and O.argen-
tata (Mammalia, Lagomorpha). Zoologica Scripta, 45, 583–594.
https://doi.org/10.1111/zsc.12180
Liu, L., Zhang, Z., Cui, N., & Fortelius, M. (2008). The Dipodidae (jer-
boas) from loc. 30 of baode and their environmental significance.
Vertebrata PalAsiatica, 46, 124–132.
Lu, L., Ge, D., Chesters, D., Ho, S. Y. W., Ma, Y., Li, G., … Liu, Q.
(2015). Molecular phylogeny and the underestimated species
diversity of the endemic white‐bellied rat (Rodentia: Muridae:
Niviventer) in Southeast Asia and China. Zoologica Scripta, 44,
475–494. https://doi.org/10.1111/zsc.12117
Lv, X., Xia, L., Ge, D., Wu, Y., & Yang, Q. (2016). Climatic niche con-
servatism and ecological opportunity in the explosive radiation
of arvicoline rodents (Arvicolinae, Cricetidae). Evolution, 70,
1094–1104. https://doi.org/10.1111/evo.12919
Ma, Y., Wang, F., Jin, S., & Li, S. (1987). Gliers (rodents and lago-
morphs) of northern Xinjiang and their zoogeographical distri-
bution. Beijing, China: Science Press.
Masters, B. C., Fan, V., & Ross, H. A. (2011). Species delimitation
‐ a geneious plugin for the exploration of species boundar-
ies. Molecular Ecology Resources, 11, 154–157. https://doi.
org/10.1111/j.1755-0998.2010.02896.x
McKenna, M. C. (1986). Evolutionary relationships among rodents: a
multidisciplinary analysis. Science, 231, 166–168. https://doi.
org/10.1126/science.231.4734.166
Nei, M., & Kumar, S. (2000). Molecular evolution and phylogenetics.
Oxford, UK: Oxford University Press.
Ochocinska, D., & Taylor, J. R. E. (2003). Bergmann's rule in shrews:
geographical variation of body size in Palearctic Sorex species.
Biological Journal of the Linnean Society, 78, 365–381. https://
doi.org/10.1046/j.1095-8312.2003.00150.x
Parada, A., Pardinas, U. F. J., Salazar‐Bravo, J., D'Elia, G., & Palma,
R. E. (2013). Dating an impressive Neotropical radiation: mo-
lecular time estimates for the Sigmodontinae (Rodentia) provide
insights into its historical biogeography. Molecular Phylogenetics
and Evolution, 66, 960–968. https://doi.org/10.1016/j.
ympev.2012.12.001
Petrova, T. V., Tesakov, A. S., Kowalskaya, Y. M., & Abramson,
N. I. (2016). Cryptic speciation in the narrow‐headed vole
Lasiopodomys (Stenocranius) gregalis (Rodentia: Cricetidae).
Zoologica Scripta, 45, 618–629. https://doi.org/10.1111/
zsc.12176
Petrova, T. V., Zakharov, E. S., Samiya, R., & Abramson, N. I. (2015).
Phylogeography of the narrow‐headed vole Lasiopodomys
(Stenocranius) gregalis (Cricetidae, Rodentia) inferred from
mitochondrial cytochrome b sequences: an echo of pleistocene
prosperity. Journal of Zoological Systematics and Evolutionary
Research, 53, 97–108. https://doi.org/10.1111/jzs.12082
Pisano, J., Condamine, F. L., Lebedev, V., Bannikova, A., Quere, J. P.,
Shenbrot, G. I., … Michaux, J. R. (2015). Out of Himalaya: the
impact of past Asian environmental changes on the evolutionary
and biogeographical history of Dipodoidea (Rodentia). Journal
of Biogeography, 42, 856–870. https://doi.org/10.1111/jbi.12476
Pons, J., Barraclough, T. G., Gomez‐Zurita, J., Cardoso, A.,
Duran, D. P., Hazell, S., … Vogler, A. P. (2006). Sequence‐
based species delimitation for the DNA taxonomy of unde-
scribed insects. Systematic Biology, 55, 595–609. https://doi.
org/10.1080/10635150600852011
Puillandre, N., Lambert, A., Brouillet, S., & Achaz, G. (2012).
ABGD, automatic barcode gap discovery for primary species
delimitation. Molecular Ecology, 21, 1864–1877. https://doi.
org/10.1111/j.1365-294X.2011.05239.x
644
|
CHENG Etal.
Qiu, Z., & Li, Q. (2005). Restudies in Sminthoides schlosser, a fossil
genus of three‐toed jerboa from China. Vertebrata PalAsiatica,
43, 24–35.
Qiu, Z., Wang, X., & Li, Q. (2006). Faunal succession and biochro-
nology of the Miocene through Pliocene in Nei Mongol (Inner
Mongolia). Vertebrata PalAsiatica, 44, 164–181.
Razkin, O., Gomez‐Moliner, B. J., Vardinoyannis, K., Martinez‐Orti, A.,
& Madeira, M. J. (2017). Species delimitation for cryptic species
complexes: case study of Pyramidula (Gastropoda, Pulmonata).
Zoologica Scripta, 46, 55–72. https://doi.org/10.1111/zsc.12192
Rohlf, F. J. (2017). Tps series. Department of Ecology and Evolution,
State University of New York, Stony Brook, NY. Retrieved from
http://life.bio.sunysb.edu/morph/.
Rohlf, F. J., & Slice, D. (1990). Extensions of the procrustes method for
the optimal superimposition of landmarks. Systematic Biology,
39, 40–59. https://doi.org/10.2307/2992207
Ronquist, F., Teslenko, M., van der Mark, P., Ayres, D. L., Darling,
A., Hohna, S., … Huelsenbeck, J. P. (2012). MrBayes 3.2: effi-
cient bayesian phylogenetic inference and model choice across a
large model space. Systematic Biology, 61, 539–542. https://doi.
org/10.1093/sysbio/sys029
Sheets, H. D., Zelditch, M., & Swiderski, D. (2004). Morphometrics
software: IMP‐integrated morphometrics package. Department
of physics, Canisius College, Buffalo, NY. Retrieved from http://
www3.canisius.edu/~sheets/morphsoft.html
Shenbrot, G. I. (1991). Geographical variation of the three‐toed
brush‐footed jerboa, Dipus sagitta (Rodentia, Dipodidae). II,
Subspecific differentiation in the eastern Kazakhstan, Touva and
Mongolia. Zoologichesky Zhurnal, 70, 91–97.
Shenbrot, G. I., Sokolov, V. E., Heptner, V. G., & Koval'skaya, Y. M.
(2008). Mammals of Russia and adjacent regions: jerboas. New
Delhi, India: Amerind Publishing Co., Pvt. Ltd.
Stamatakis, A. (2014). RAxML version 8: a tool for phylogenetic anal-
ysis and post‐analysis of large phylogenies. Bioinformatics, 30,
1312–1313. https://doi.org/10.1093/bioinformatics/btu033
Tamura, K., Stecher, G., Peterson, D., Filipski, A., & Kumar, S. (2013).
MEGA6: molecular evolutionary genetics analysis version 6.0.
Molecular Biology and Evolution, 30, 2725–2729. https://doi.
org/10.1093/molbev/mst197
Vorontsov, N. N. (1979). Karyosystematics. The Great Soviet encyclo-
pedia. Farmington Hills, MI: The Gale Group. Retrieved from
https://encyclopedia2.thefreedictionary.com/karyosystemati-cs.
Wang, L., Wan, Z. Y., Lim, H. S., & Yue, G. H. (2016). Genetic vari-
ability, local selection and demographic history: genomic evi-
dence of evolving towards allopatric speciation in Asian seabass.
Molecular Ecology, 25, 3605–3621. https://doi.org/10.1111/
mec.13714
Wang, S., & Yang, G. (1983). Fauna of rodent in Xinjiang. Urumqi,
China: Xinjiang People's Publishing House.
Wen, Z., Yang, Q., Quan, Q., Xia, L., Ge, D., & Lv, X. (2016). Multiscale
partitioning of small mammal β‐diversity provides novel insights
into the Quaternary faunal history of Qinghai‐Tibetan Plateau and
Hengduan Mountains. Journal of Biogeography, 43, 1412–1424.
https://doi.org/10.1111/jbi.12706
Wilson, D. E., & Reeder, D. M. (2005). Mammal species of the world:
a taxonomic and geographic reference. Baltimore, MD: Johns
Hopkins University Press.
Xia, L., Yang, Q., Ma, Y., Feng, Z., & Zhou, L. (2006). A guide to the
measurement of mammal skull III: Rodentia and Lagomorpha.
Chinese Journal of Zoology, 41, 68–71.
Xu, X., Liu, F. X., Chen, J., Li, D. Q., & Kuntner, M. (2015). Integrative
taxonomy of the primitively segmented spider genus Ganthela
(Araneae: Mesothelae: Liphistiidae): DNA barcoding gap agrees
with morphology. Zoological Journal of the Linnean Society,
175, 288–306. https://doi.org/10.1111/zoj.12280
Yang, Z., & Rannala, B. (2010). Bayesian species delimitation using
multilocus sequence data. Proceedings of the National Academy
of Sciences of the United States of America, 107, 9264–9269.
https://doi.org/10.1073/pnas.0913022107
Yang, Z., & Rannala, B. (2014). Unguided species delimitation using
DNA sequence data from multiple loci. Molecular Biology and
Evolution, 31, 3125–3135. https://doi.org/10.1093/molbev/
msu279
Yang, Q., Xia, L., Ma, Y., Feng, Z., & Quan, G. (2005). A guide to
the measurement of mammal skull I: basic measurement. Chinese
Journal of Zoology, 40, 50–56.
Zhang, L. (2012). Palaeogeography of China‐the formation of Chinese
natural evironment. Beijing, China: Science Press.
Zhang, J., Kapli, P., Pavlidis, P., & Stamatakis, A. (2013). A general spe-
cies delimitation method with applications to phylogenetic place-
ments. Bioinformatics, 29, 2869–2876. https://doi.org/10.1093/
bioinformatics/btt499
SUPPORTING INFORMATION
Additional supporting information may be found online in
the Supporting Information section at the end of the article.
How to cite this article: Cheng J, Ge D, Xia L, etal.
Phylogeny and taxonomic reassessment of jerboa,
Dipus (Rodentia, Dipodinae), in inland Asia. Zool Scr.
2018;47:630–644. https://doi.org/10.1111/zsc.12303
