Ann. Limnol. - Int. J. Lim.
Volume 53, 2017
|Page(s)||401 - 410|
|Published online||03 November 2017|
Molecular phylogeny and population genetic differentiation patterns in Brachionus calyciflorus Pallas (Rotifera) complex from two lakes in China
College of Life Sciences, Anhui Normal University,
Anhui, PR China
2 Key Laboratory of Biotic Environment and Ecological Safety in Anhui Province, Wuhu, Anhui, PR China
* Corresponding author: email@example.com
Received in final form: 15 September 2017
Accepted: 22 September 2017
The spatio-temporal patterns of population genetic structures have been attracting increasing attention of late. Few of these efforts, however, have focused on the underlying mechanisms of the seasonal alterations of in rotifer clone groups. To gain insights into the seasonal variation patterns of genetic differentiation in rotifer populations, 158 clones of the Brachionus calyciflorus Pallas species complex, with seasonal sampling from Guangzhou and Wuhu in China, were sequenced and analyzed based on the nuclear internal transcribed spacer (ITS) region and the mitochondrial cytochrome c oxidase subunit I (COI) gene. DNA taxonomy provided estimates of evolving entities ranging from 3 to 21 by combining the mitochondrial and nuclear markers with the different ABGD, PTP, and GMYC models. The most conservative number of the three evolving entities was used for further phylogenetic and population structure analyses. The B. calyciflorus species complex was found to have extreme nucleotide diversity, revealing twice the diversity from the COI dataset than from ITS. The similar patterns of seasonal succession in B. calyciflorus were investigated in the two habitats of Guangzhou and Wuhu, and the clonal groups involved in seasonal succession were actually sibling or cryptic species within the B. calyciflorus complex. We assume that these cryptic species are specialized for their ecological niches, especially in terms of temperature preference. The spatio-temporal patterns of population genetic structure varied with cryptic species, e.g. cryptic species II (-COI/-ITS) had much greater genetic differentiation among sampling sites than among seasonal populations and cryptic species III (-COI/-ITS) displayed a reverse pattern.
Key words: rotifer / Brachionus calyciflorus / cryptic species / seasonal succession / DNA taxonomy
© EDP Sciences, 2017
Understanding the spatio-temporal patterns and processes of population genetic differentiation has been a major focus of population ecology. Until now, most of the empirical research in population genetic patterns has attempted to tear apart the dynamic consequences of spatial variation. Little attention has been paid, however, to furthering the understanding of how the genetic structure of the population changes over time, since most spatial studies implicitly assume temporal genetic stability (King, 1972; Lessios et al., 1994; Heath et al., 2002; Arnaud and Laval, 2004; Bousset et al., 2004; Lee and Boulding, 2009; Chan and Hadly, 2011). In water habitats, the progressive physical, chemical, and biological factors change with seasonal succession. Thus, many zooplankton species exposed to these changes often thrive during only a restricted period of the annual cycle (Gómez et al., 1995; Ortells et al., 2003; Vanderploeg et al., 2012). During this process, selection and migration can also influence allele frequencies due to genetic drift and gene flow between populations (Hartl and Clark, 1989). Accordingly, habitat conditions have been proven to be important for shaping population genetic structure and demography (Charbonnel et al., 2002; Bousset et al., 2004).
Rotifers, a group of globally widespread microscopic Metazoa, play an important role in nutrient recycling and the transfer of energy in continental aquatic ecosystems (Bonecker and Aoyagui, 2005). Since the pioneering studies of the genetic structure of rotifer populations in the 1970s, several investigations have suggested extensive temporal variation in these populations (King, 1972, 1977; Snell, 1979; King and Serra, 1998). The two genetic models proposed by King (1972, 1977) showed that different genotypes are maximally adapted to different parts of the environmental spectrum over time, and that the temporal variation in the genetic structure of the population occurs as the lake environment undergoes its seasonal changes. The existence of seasonally isolated populations has been shown in Euchlanis dilatata from a man-made lake in Illinois (King, 1972), Asplanchna girodi from a golf course pond in Florida, and A. brightwelli from Lake Thonotosassa in Florida (King, 1977; King and Snell, 1980), all of which lend support to the Nonoverlap Model (complete genetic discontinuity model). In addition, Brachionus plicatilis was found to support the Overlap Model (incomplete genetic discontinuity model) in Soda Lake in Nevada (King and Zhao, 1987; Zhao and King, 1989).
Cryptic speciation has become widely recognised in biodiversity analyses of rotifers (Ruttner-Kolisko, 1989; Knowlton, 1993), leading to the conclusion that the currently acknowledged level of rotifer biodiversity may even be an underestimate considering the occurrence of cryptic species (Segers, 2007, 2008), although many efforts have been made by taxonomists to obtain a comprehensive understanding (Pejler, 1977; Dumont, 1983; De Ridder and Segers, 1997). Previous studies have shown that the presence of cryptic species has been documented in many monogonont (well known in Brachionus, Keratella, and Lecane) (Ruttner-Kolisko, 1989; Gómez et al., 2002; Segers, 2008; Segers and De Smet, 2008; Xiang et al., 2011a, b; Mills et al., 2017) and bdelloid (Fontaneto et al., 2007, 2009, 2011) species complexes which have hitherto been difficult and unreliable to classify with traditional taxonomical methods, due to the intraspecific plasticity and interspecific similarity of morphological traits (Colbourne et al., 1997; Serra et al., 1997; Hebert, 1998). Nevertheless, the seasonal succession of sympatric cryptic rotifer species can be evaluated with temporal sampling. Gómez et al. (1995) provided evidence of seasonal succession among three groups of the B. plicatilis complex in a marsh along the Mediterranean coast of Spain. In contrast to the Overlap Model of B. plicatilis from Soda Lake in Nevada, this case provides strong support for the Nonoverlap Model with distinguished temporal heterogeneity. We now know that the clonal groups or genotypes involved in a seasonal succession are in fact sibling or cryptic species that are both genetically and ecologically isolated.
B. calyciflorus Pallas is a well-known complex of cryptic species (Gilbert and Walsh, 2005; Cheng et al., 2008; Li et al., 2008; Xiang et al., 2011a, b; Papakostas et al., 2016), although it has been considered to be a traditional cosmopolitan species for a long time (Segers, 2008). In previous studies, our research group demonstrated that this complex is composed of several cryptic species in eastern China, with different composition patterns at different sites (Xiang et al., 2011a), so we wanted to investigate whether the molecular phylogeny and patterns of population genetic differentiation in B. calyciflorus complexes were similar in two different climate zones when seasonally surveyed. To determine the constitution of cryptic species and identify the patterns of seasonal genetic variation in the B. calyciflorus complex, all 158 clones of this complex were sequenced and analyzed based on the nuclear internal transcribed spacer (ITS) region and mitochondrial cytochrome c oxidase subunit I (COI) gene, as obtained by seasonal sampling from Guangzhou and Wuhu (1300 km apart from each other). We then investigated the seasonal change mechanisms of the genetic structure of the B. calyciflorus complex and evaluated the effects of environmental water fluctuation on the seasonal succession in rotifers.
The rotifer B. calyciflorus complex was collected from Lake Liuhua in Guangzhou and Lake Jinghu in Wuhu at four different time points (representative of all four seasons) over the course of one year (Tab. 1). Guangzhou is located in the southern subtropical zone of China with an oceanic monsoon climate that is fairly warm in winter and rather cool in summer, with a higher annual average temperature (23 °C) and a small annual temperature range. Wuhu, on the other hand, is situated in the northern subtropical zone of China and has a humid continental climate, characterized by cold and snowy winters but humid and hot summers with a lower annual average temperature (17.3 °C) and a large annual temperature range. In this study, water temperature, pH, and NH4-N concentration were measured simultaneously with the sampling of rotifers (Tab. 1).
Stock rotifers were cultured clonally under natural light (approximately 130 lx) in a homothermal incubator with EPA medium (pH 7.4–7.8) (Peltier and Weber, 1985). The culture temperatures were set close to the sampling temperatures. The rotifers were fed daily with the algae Scenedesmus obliquus at 1.0–2.0 × 106 cells/ml, which was grown using HB-4 medium (Li et al., 1959) under a semi-continuous culture condition and daily replenishment at 20%. Rotifer clones were harvested after they achieved high densities (200–300 ind/ml) and were starved for 24 h to avoid any potential intracorporal food contamination. Finally, a total of 158 B. calyciflorus clones were successfully established, and the sample sizes for each season were listed in Table 1.
Summary information of sampling and characteristics of habitats for each seasonal population.
The Wizard® Genomic DNA Purification Kit (Promega, USA) was used to isolate and purify the total genomic DNA as follows. Each rotifer clone (about 500 individuals) was transferred to a 1.5 ml microcentrifuge tube containing 35 µl of chilled Nuclei Lysis Solution, and incubated at 56 °C for 2 h. The sample was allowed to cool to room temperature for 5 min, then 15 µl of chilled Protein Precipitation Solution was added and the mixture was vortexed vigorously at high speed for 10 s. The sample was chilled on ice for 5 min, before being centrifuged for 10 min at 18 °C and 15 000 rpm. Next, the supernatant containing the DNA was removed and transferred to a sterile 1.5 ml microcentrifuge tube containing 50 µl of isopropanol and 0.5 µl of glycogen (20 mg/ml). The solution was then mixed via inversion, the samples were incubated at room temperature for 30 min, and the solution was centrifuged for 10 min at 15 000 rpm. The supernatant was subsequently decanted and 30 µl of 70% ethanol was added and centrifuged for 5 min at 15 000 rpm. Next, the ethanol was aspirated using a pipette tip, the tube was inverted on clean absorbent paper, and the pellet was air-dried for 2 h. Finally, 30 µl of deionized H2O was added to rehydrate the DNA by incubating at 65 °C for 1 h. The DNA was then stored below −20 °C until ready to use.
Following the procedures detailed by Xiang et al. (2011a,b), the nuclear ITS region and mitochondrial COI gene were amplified and sequenced. All of the ITS and COI sequences derived from the samples in this study were deposited in GenBank (the accession nos. are listed in Tab. 1).
After mtCOI sequence alignment was performed with ClustalX 1.81 (Thompson et al., 1997) using default parameters and nuITS alignment was performed with MAFFT v6.814b using the Q-INS-I algorithm (Katoh et al., 2009), nucleotide diversity (π) and haplotype diversity (h) were calculated using DnaSP 5.10.1 (Librado and Rozas, 2009). The DNASTAR computer package (DNASTAR Inc., Madison, WI, USA) was used to test the percentage of sequence divergence among and within the main phylogenetic clades.
The phylogenetic relationships were reconstructed using four optimality criteria, Neighbor-Joining (NJ), Maximum Parsimony (MP), Maximum Likelihood (ML), and Bayesian Inference (BI). The most optimal sequence evolution parameters and models (TVM+G and GTR+G), as selected by Modeltest 3.7 (Posada and Crandall, 1998), were used as settings in PAUP and Bayesian phylogenetic analyses based on the ITS and COI partial sequences. NJ, MP, and ML trees were constructed with the program PAUP* 4.0b10 (Swofford, 2002). Support for each node was tested with standard bootstrap analysis with 1000 replications for the NJ and MP trees and 100 replications for the ML trees. Two independent Bayesian analyses with the Markov Chain Monte Carlo (MCMC) method were conducted in MrBayes 3.1.2 (Ronquist and Huelsenbeck, 2003), with four chains per analysis and randomly chosen starting trees. The Markov chains were run for 10 000 000 generations with trees being sampled every 100 generations. The first 25 0000 generations were discarded as burn-in, and the remaining trees were used to estimate Bayesian posterior probabilities. The sequences of B. forficula and B. plicatilis (GenBank Acc. Nos. DQ834362 and EF524553) were used as outgroups in the phylogenetic reconstruction based on the ITS and COI partial sequences.
Three DNA taxonomy methods were used to independently identify putative species with the COI and ITS alignments, including the Automatic Barcode Gap Discovery (ABGD), Poisson Tree Process (PTP), and Generalised Mixed Yule Coalescent (GMYC) models (Fontaneto et al., 2015; Mills et al., 2016). The ABGD model (available from http://wwwabi.snv.jussieu.fr/public/abgd/abgdweb.html) attempts to automatically discover the barcode gap instead of using one or several predefined distance thresholds for species delimitation. The identified groups were considered to be equivalent to species (Puillandre et al., 2012). The PTP model (Zhang et al., 2013) was applied to the input ML trees using coalescence theory to distinguish between the population- and species-levels. The PTP method was used through the online tool (http://species.h-its.org/) with default settings, and the output of the ML and BI optimisation algorithms was reported. For the identification of potential cryptic species representing independently evolving entities, an ultrametric tree was constructed based on Bayesian analysis using the penalized likelihood (PL) method and the truncated Newton (TN) algorithm on r8s software (Sanderson, 2002). A generalized mixed Yule coalescent (GMYC) model with multiple thresholds (Pons et al., 2006; Monaghan et al., 2009; Fontaneto et al., 2009, 2011) was run on the ultrametric gene tree with R software. In the case of discordance in the amount of splitting, we chose to keep the smallest number of entities, in order to avoid over-splitting the species complex; thus, if a mistake was made in the identification of taxa, it was made in the direction of being more conservative in the amount of cryptic diversity (Mills et al., 2016).
The population genetic differentiation was analyzed for the B. calyciflorus cryptic species, consisting of two or more populations. Based on the haplotype frequencies with gaps coded as missing data, the percentages of variation within and among populations were evaluated using Analyses of molecular variance (AMOVA) in Arlequin 3.1 (Excoffier and Schneider, 2005) by calculating pairwise Fst values. In order to assess the relative contribution of spatial partitioning vs. seasonal differentiation to the total genetic variation, the relative levels of fixation indices (FCT, among groups of populations; FSC, among populations within groups; FST, within populations) were detected for the different cryptic species based on two molecular markers using a hierarchical AMOVA. The P-values were determined using 1000 random permutations. Partial Pearson's correlations with two-tailed tests of significance were performed between water environment parameters (water temperature, pH, and NH4-N concentration) and genetic diversity (Fst values, haplotype diversity, and nucleotide diversity), all while controlling for the effects of seasons and coordinates using SPSS 15.0 (SPSS Inc., Chicago, IL, USA).
In this study, the ITS sequences from the B. calyciflorus complex ranged from 759 to 765 bp. A total of 158 clones were defined as 118 unique ITS haplotypes, of which 12 were shared, showed a wide geographical distribution. The assessment of genetic diversity showed that the Wuhu nucleotide diversity (0.0373 ± 0.0183) was higher than that of Guangzhou (0.0299 ± 0.0148), and the patterns of variation in nucleotide diversity among the four seasons were identical for both sampling sites, as follows: spring > summer > autumn > winter.
The length of the sequenced partial COI gene in the eight seasonal populations of Guangzhou and Wuhu was 712 bp. A total of 113 haplotypes were defined by the 158 sequences, including 9 shared haplotypes. The genetic diversity analyses indicated that the nucleotide diversity (π) of Wuhu (0.0966 ± 0.0465) was also higher than that of Guangzhou (0.0680 ± 0.0330), based on the COI sequences, confirming the results discovered with the ITS sequences. The changes in nucleotide diversity (π) at the two sites were similar to each other, and the change in the order of nucleotide diversity in Wuhu was spring > summer > autumn > winter, with spring and winter also corresponding to the highest and lowest levels in Guangzhou.
DNA taxonomy tools based on the nuITS and mtCOI sequences provided estimates of evolving entities, ranging from 3 to 21. Based on nuITS dataset, the minimum estimate of 3 groups was provided by the ABGD model with 1.2% prior maximal distance, yet the estimated number of putative species was between 3 and 16 (mean 4.96) using the PTP method with an acceptance rate of 0.47, where the most supported partition found with a simple heuristic search was 3 species. The GMYC model on ITS sequence gave optimal solutions of 3 evolving entities, which was in agreement with the above two detections. In the case of the mtCOI gene, different species delimitation methods yielded different results. Four groups were found with the prior maximal distance of 0.06 using the ABGD method, while species number estimates ranged from 6 to 21 using the PTP model, and the most conservative estimate of 3 evolving entities was shown in the GMYC analysis. According to a report by Papakostas et al. (2016), species delimitations in the B. calyciflorus complex based on nuclear DNA markers proved to be a more reliable predictor of morphological variation than delimitations using the mitochondrial COI gene. Also, in cases where there was discordance in the amount of splitting, we chose to keep the conservative number of entities for the further phylogenetic and population structure analyses. Therefore, the most consistent number of lineages was the estimate of 3 species obtained from ITS (Fig. 1), and the three potential species were also the main well-supported lineages seen on the phylogenetic trees with the mtCOI dataset (Fig. 2).
The topological structure of phylogenetic trees, as reconstructed by the NJ, MP, ML, and Bayesian methods, was accordant in the clades close to the root node (Fig. 1). With the ML phylogenetic tree, the eight seasonal populations of the B. calyciflorus species complex from Guangzhou and Wuhu were grouped into three clades with strong support. Clade I-ITS, containing a unique geographical and seasonal population, was made up of 21 haplotypes of B. calyciflorus from Wuhu in winter (WD); the clade II-ITS consisted of 40 haplotypes from Guangzhou in spring, summer, and autumn, and from Wuhu in spring and summer. The remaining 57 haplotypes from Guangzhou (spring, summer, and winter) and Wuhu (spring, summer, and autumn) were all incorporated into clade III-ITS. The percentages of sequence divergence within and among the three clades of the ML phylogenetic tree based on the ITS sequences are available in the Supplementary material (Tab. S1).
The phylogenetic trees based on the COI partial sequences were reconstructed with the ML, MP, NJ, and Bayesian methods. The topologies of all of the phylogenetic trees were similar with well-supported main nodes differing only in minor rearrangements of the terminal branches (Fig. 2; the latter three trees are not shown). Based on the ML phylogenetic tree, 113 haplotypes of the COI partial sequences were split into three clades with strong support. The I-COI clade was made up of 22 haplotypes of B. calyciflorus from only Wuhu in winter (WD); the II-COI clade consisted of 34 haplotypes from Guangzhou in spring, summer, and autumn, and from Wuhu in spring and summer; and the III-COI clade was composed of the remaining 57 haplotypes from Guangzhou (spring, summer, and winter) and Wuhu (spring, summer, and autumn). The percentages of sequence divergence within and among the three clades of the ML phylogenetic tree based on the COI partial sequences are shown in Supplementary Table S2. Except for the GC4, WX21, WC3, WC9, and WC12 haplotypes, the phylogenetic relationships of all haplotypes based on the COI partial sequences were matched with those from the ITS sequences.
Three independently evolving entities were confirmed in this species complex by the ABGD, PTP, and GMYC models, coherent with the criterion of the molecular experiments and mating tests developed by Xiang et al. (2011a) and Gilbert and Walsh (2005), which designated the lineages as separate cryptic species accompanied by sequence divergences >9.6% (COI) and >3.8% (ITS). Accordingly, we here refer to the three evolving entities as distinct cryptic species that were labeled I-ITS, II-ITS, and III-ITS or I-COI, II-COI, and III-COI, because no named species were described from China. The distributions of all cryptic species in each season are shown in Figures 3 (ITS) and 4 (COI).
The ML phylogenetic tree based on ITS sequences. Values isolated by slashes represent Bayesian, ML, MP, and NJ bootstrap support.
The ML phylogenetic tree based on COI sequences. Values isolated by slashes represent Bayesian, ML, MP, and NJ bootstrap support.
Distribution of cryptic species in Guangzhou and Wuhu over four seasons based on the ITS sequences.
Distribution of cryptic species in Guangzhou and Wuhu over four seasons based on the COI gene partial sequences.
Considering the composition of just one population in cryptic species I-ITS or I-COI, we did not analyze the population-level genetic differentiation of this cryptic species.
Five populations in the cryptic species II-ITS, including spring (5) and summer (2) in Wuhu, as well as spring (6), summer (12), and autumn (18) in Guangzhou (the figure in parentheses represents number of haplotypes; the same below) were included in the analysis of molecular variance. According to the sampling site, the GC, GX, and GQ populations were included in one group, and the WC and WX populations were placed into the other group. The results of the hierarchical AMOVA showed that the percentage of variation among groups (FCT) was 5.73%, that among populations within the groups (FSC) was 3.95%, and that within populations (FST) was 90.33%, suggesting a much greater genetic differentiation among different sampling sites than that among seasonal populations within a geographical site. The Fst values among and within five populations of cryptic species II-ITS are showed in Supplementary Table S3.
The analyses of molecular variance in cryptic species II-COI included five populations: WC (2), WX (1), GC (8), GX (9), and GQ (14). Based on the sampling sites, the percentages of variation among groups (FCT), among populations within the groups (FSC), and within populations (FST) were 43.96%, 20.18%, and 35.86%, respectively, suggesting a higher genetic differentiation between sampling sites than between seasons at the same sampling site, which is in accordance with the results of the ITS sequences. The Fst values among and within five populations of cryptic species II-COI are shown in Supplementary Table S4.
The cryptic species III-ITS consisted of six populations: WC (8), WX (16), WQ (19), GC (8), GX (1), and GD (10). The hierarchical AMOVA results indicated that the fixation indices of FCT, FSC, and FST were −5.00%, 36.59%, and 68.41%, respectively, based on the sampling site grouping. Using the COI data set, six populations in the cryptic species III-COI were analyzed with AMOVA, including WC (7), WX (18), WQ (19), GC (6), GX (1), and GD (9). The FCT, FSC, and FST were −6.03%, 23.99%, and 82.04% respectively, indicating that the genetic differentiation between geographical populations was smaller than that among seasonal populations in the cryptic species III-ITS or III-COI for the two molecular markers. The Fst values among and within six populations of cryptic species III-ITS and III-COI are shown in Supplementary Tables S5 and S6, respectively.
The partial correlation analyses controlling for the potentially confounding factors (season and latitude) were conducted between water environment parameters, including water temperature, pH value, and NH4-N concentration, and genetic diversity indices, such as Fst value, haplotype diversity, and nucleotide diversity in two cryptic species (II-ITS and III-ITS) using SPSS (Tab. 2). The results show that the nucleotide diversity of cryptic species II-ITS was significantly negative in correlation with NH4-N concentration (r = −0.998, P < 0.05). Based on the COI sequences, the correlation analyses in the two cryptic species (II-COI and III-COI) suggested that the haplotype diversity of cryptic species III-COI was negatively related to the pH value (r = −0.976, P < 0.05) (Tab. 3).
The water environment parameters and genetic diversity indices in all populations of two B. calyciflorus cryptic species based on the ITS sequences.
The water environment parameters and genetic diversity indices in all populations of two B. calyciflorus cryptic species based on the COI sequences.
Understanding the patterns and processes influencing biological diversity is a critical task given the current rapid environmental change (Mills et al., 2017). The biodiversity of zooplankters would be underestimated and misunderstood without taking cryptic speciation into consideration. With such increasing evidence as mating behavior, allozyme patterns, microsatellite markers, and DNA sequencing, the conception of a species complex has been proposed for both rotifers (Ruttner-Kolisko, 1989; Gómez and Snell, 1996; Segers, 2007) and cladocerans (Frey, 1982, 1987). In zooplankton, mate recognition systems based on contact chemoreception have evolved, in order to distinguish conspecifics from other species and to discriminate males from females (Snell and Morris, 1993; Snell et al., 1995), suggesting that morphological features are not the species boundaries in rotifers, and that speciation can proceed independently of morphological differentiation. In addition, the characteristics of cyclical parthenogenesis, island-like habitats, and seasonal preferences in rotifers all promote their rapid genetic differentiation and cryptic speciation (Serra et al., 1997). In one of the most recent publications, using B. calyciflorus as a representative case, the potential of integrative taxonomy for guiding species delimitation by combining molecular, morphological, and ecological approaches was demonstrated in the presence of discordance between mitochondrial and nuclear markers. From this study, species delimitations based on the nuclear DNA markers were proven to be a more reliable predictor of morphological variation and competitive ability than delimitations using the mitochondrial COI gene (Papakostas et al., 2016). In another case, the existence of 15 B. plicatilis cryptic species was confirmed by applying three different approaches in DNA taxonomy (ABGD, PTP, and GMYC) (Mills et al., 2017).
In this study, various methods with different criteria were used to delineate species and, as a result, we were met with some degree of incongruence in the estimates of species numbers. DNA taxonomy based on the nuITS and mtCOI sequences provided estimates of evolving entities ranging from 3 to 21. According to the conclusions drawn by Papakostas et al. (2016), which proved that nuclear DNA markers were more reliable tools than the mitochondrial COI gene, a conservative number (3) of entities was chosen for future phylogenetic and population structure analyses. Certainly, the three potential species are also the main well-supported lineages on the phylogenetic trees in the mtCOI dataset. In addition, extreme nucleotide diversity was revealed in the B. calyciflorus species complex by two different molecular markers. In opposition, the nucleotide diversity was not high in any of the cryptic species. With the ITS fragment, the nucleotide diversity of the species complex was 0.0399 ± 0.0194, but was 0.0983 ± 0.0471 for the COI gene sequences, thus the mixture of multiple cryptic species might be responsible for the high diversity. Even so, there was still relatively little nucleotide diversity occurring in the winter populations of Guangzhou and Wuhu, and the autumn populations had the second lowest, which may be due to the composition of single-species. On the whole, the nucleotide diversity of Wuhu was larger than that of Guangzhou, which is closely related to the distribution of more cryptic species in Wuhu.
For zooplankton, most of the fluctuations in the physical, chemical, and biotic environments may have been relatively minor, so that, to some extent, individuals in the population could adapt by modifying their underwater position and regulating their physiological actions. When exposed to more unfavorable environments, populations could be selected by nature, motivating the changes in population genetic structure, including the numbers of genotypes and their relative frequencies throughout both space and time. As far as the temporal pattern is concerned, seasonal variation in population genetic structure is the most common type of temporal differentiation (King and Serra, 1998). Different genotypes of E. dilatata, A. girodi, B. plicatilis, and B. calyciflorus have been reported to dwell in sympatric shallow lakes exhibiting distinct ecological preferences (King, 1972, 1980; Snell, 1980; King and Zhao, 1987). Daphnia is also a globally distributed complex of cryptic species, and compared to the species complex, each of component species is distributed in and tolerates a narrower ecological niche (Cerný and Hebert, 1999). These cases suggest that ecological preference plays an important role in the seasonal variation of genetic structure and the maintenance of higher rotifer species diversity.
In this study, the compositions of cryptic species was substantially identical based on ITS fragments and COI partial sequences, and each cryptic species was specialized in particular ecological niches, with strong temperature preferences. In Guangzhou, the temperature in summer and autumn is highest among the four seasons, and the dominant species was cryptic species II (-COI/-ITS), which prefers a higher temperature, while cryptic species III (-COI/-ITS) occurred rarely in summer, and disappeared completely in autumn. The water temperature was relatively lower in winter, and the composition consisted entirely of cryptic species III (-COI/-ITS), so this species might prefer a moderate temperature. With the onset of spring, the diapausing eggs of cryptic species II (-COI/-ITS) began to germinate and gradually occupy the majority of the ecological niches in the water. Simultaneously, the component ratio of cryptic species III (-COI/-ITS) decreased, until only one clone remained in the summer. In Wuhu, located at the northern subtropical zone, the water temperature was lower than that in Guangzhou over time, so it was hard for cryptic species II (-COI/-ITS), which prefers higher temperatures, to hold a dominant position, and its genotype frequencies were low. As a result, cryptic species III (-COI/-ITS) dominated the water column in spring, summer, and autumn. In winter, however, the monopolizer was cryptic species I (-COI/-ITS), which favors lower temperatures and was not found at all in Guangzhou, where the temperatures were higher. The clonal groups or genotypes involved in each seasonal succession were in fact the sibling or cryptic species in B. calyciflorus.
Due to the high degree of specialization in ecological features of each cryptic species, although environments tend to promote the elimination of cryptic species with low fitness through selection or competition in any given period of time, environments change before the death of all individuals, and, in turn, the new situation benefits this cryptic species. Finally, the result could be that none of these cryptic species will be eliminated, which is consistent with the “incomplete genetic discontinuity” model (King, 1972, 1977). In contrast, if the environment changes slowly, natural selection could exert distinguishing effects on different cryptic species for a long time, thus resulting in the complete elimination of certain genotypes that might regenerate until the occurrence of new suitable environments. The second case matches the “complete genetic discontinuity” model (King, 1972, 1977). Therefore, the seasonal succession patterns in zooplankton depend upon the stability of the environment and the degree of environment change. The two genetic models are not contradictory, but are merely two scenarios under the influence of different intensities of environment change. The life history regime of seasonal succession in zooplankton depends upon the environmental conditions in which they live, rather than their species type. In this study, similar patterns of seasonal succession in B. calyciflorus were revealed in two distant habitats, as assessed with nuclear and mitochondrial markers.
Rotifers are characterized by island-like habitats, so their geographical distribution is necessarily patchy with a lack of hybridization or clear geographical isolation barriers between populations (Boileau et al., 1992; De Meester et al., 2002; Gómez et al., 2007). On the other hand, rotifer populations in capricious environments are often seasonal or ephemeral, and sympatric species can occur in seasonal succession (Gómez et al., 1995). In this study, the patterns of genetic differentiation in the two cryptic species were diverse from each other based on either the ITS fragment or the COI gene. In cryptic species II (-COI/-ITS), the genetic differentiation between geographical populations was obviously greater than that among seasonal populations. In opposition, seasonal changes seemed to have a stronger impact on the population genetic differentiation in cryptic species III (-COI/-ITS), suggesting that genetic differentiation was largely dependent upon the evolutionary force shaping seasonal differentiation, rather than spatial subdivision. Accordingly, the spatio-temporal patterns of population genetic differentiation in zooplankton varied with species or cryptic species.
The authors thank the Shenzhen Nobel Science and Technology Service Co. Ltd for the language editing service. We appreciate Dr. Tylor Johnson and Prof. Ruanbao Zhou at South Dakota State University for their comments, which greatly improved the manuscript. We are grateful to the anonymous reviewers for their valuable comments and constructive suggestions. This research was funded by the Natural Science Foundation of China (31200324, 31470015), the Natural Science Foundation of Anhui Province (1708085MC79), and the Foundation of Provincial Key Laboratories of Conservation and Utilization for Important Biological Resources in Anhui.
- Arnaud JF, Laval G. 2004. Stability of genetic structure and effective population size inferred from temporal changes of microsatellite DNA polymorphisms in the land snail Helix aspersa (Gastropoda: Helicidae). Biol J Linn Soc 82: 89–102. [CrossRef] [Google Scholar]
- Boileau MG, Hebert PDN, Schwartz SS. 1992. Non-equilibrium gene frequency divergence: persistent founder effects in natural populations. J Evol Biol 5: 25–39. [CrossRef] [Google Scholar]
- Bonecker CC, Aoyagui ASM. 2005. Relationships between rotifers, phytoplankton and bacterioplankton in the Corumbá reservoir, Goiás State, Brazil. Hydrobiology 546: 415–421. [CrossRef] [Google Scholar]
- Bousset L, Henry PY, Sourrouille P, Jarne P. 2004. Population biology of the invasive freshwater snail Physa acuta approached through genetic markers, ecological characterization and demography. Mol Ecol 13: 2023–2036. [CrossRef] [PubMed] [Google Scholar]
- Cerný M, Hebert PDN. 1999. Intercontinental allozyme differentiation among four holartic Daphnia species. Limnol Oceanogr 44: 1381–1387. [CrossRef] [Google Scholar]
- Chan YL, Hadly EA. 2011. Genetic variation over 10000 years in Ctenomys: comparative phylochronology provides a temporal perspective on rarity, environmental change and demography. Mol Ecol 20: 4592–4605. [CrossRef] [PubMed] [Google Scholar]
- Charbonnel N, Quesnoit M, Razatavonjizay R, Brémond P, Jarne P. 2002. A spatial and temporal approach to micorevolutionary forces affecting population biology in the freshwater snail Biomphalaria pfeifferi. Am Nat 160: 741–755. [CrossRef] [PubMed] [Google Scholar]
- Cheng XF, Xi YL, Li HB. 2008. Seasonal changes in the genetic structure of a Brachionus calyciflorus population in Lake Liantang based on its sequences. Acta Zool Sin 54, 245–255. [Google Scholar]
- Colbourne JK, Hebert PDN, Taylor DJ. Evolutionary origins of phenotypic diversity in Daphnia. In: Givnish TJ, Systma KJ, eds. Molecular evolution and adaptive radiation. Cambridge: Cambridge University Press, 1997, pp. 163–188. [Google Scholar]
- De Meester L, Gómez A, Okamura B, Schwenk K. 2002. The monopolization hypothesis and the dispersal-gene flow paradox in aquatic organisms. Acta Oecol 23: 121–135. [CrossRef] [EDP Sciences] [Google Scholar]
- De Ridder M, Segers H. Rotifera Monogononta in six zoogeographical regions after publications between 1960–1992. In: Van Goethem J, ed. Studiedocumenten van het Koninklijk Belgisch Instituut voor Natuurwetenschappen, 1997, p. 481. [Google Scholar]
- Dumont HJ. 1983. Biogeography of rotifers. Hydrobiology 104: 19–30. [CrossRef] [Google Scholar]
- Excoffier L, Schneider S. 2005. Arlequin ver. 3.0: an integrated software package for population genetics data analyses. Evol Bioinform 1: 47–50. [CrossRef] [Google Scholar]
- Fontaneto D, Herniou EA, Boschetti C, Caprioli M, Melone G, Ricci C, Barraclough TG. 2007. Independently evolving species in asexual bdelloid rotifers. PLoS Biol 5: 1–8. [CrossRef] [Google Scholar]
- Fontaneto D, Kaya M, Herniou EA, Barraclough TG. 2009. Extreme levels of hidden diversity in microscopic animals (Rotifera) revealed by DNA taxonomy. Mol Phylogenet Evol 53: 182–189. [Google Scholar]
- Fontaneto D, Iakovenko N, Eyres I, Kaya M, Wyman M, Barraclough TG. 2011. Cryptic diversity in the genus Adineta Hudson & Gosse, 1886 (Rotifera: Bdelloidea: Adinetidae): a DNA taxonomy approach. Hydrobiology 662: 27–33. [CrossRef] [Google Scholar]
- Fontaneto D, Flot J-F, Tang CQ. 2015. Guidelines for DNA taxonomy with a focus on the meiofauna. Mar Biodivers 45: 433–451. [CrossRef] [Google Scholar]
- Frey DG. 1982. Questions concerning cosmopolitanism in Cladocera. Arch. Hydrobiol 93: 484–502. [Google Scholar]
- Frey DG. 1987. The taxonomy and biogeography of the Cladocera. Hydrobiology 145: 5–17. [Google Scholar]
- Gilbert JJ, Walsh EJ. 2005. Brachionus calyciflorus is a species complex: mating behavior and genetic differentiation among four geographically isolated strains. Hydrobiology 546: 257–265. [CrossRef] [Google Scholar]
- Gómez A, Snell TW. 1996. Sibling species and cryptic speciation in the Brachionus plicatilis species complex (Rotifera). J Evol Biol 9: 953–964. [CrossRef] [Google Scholar]
- Gómez A, Temprano M, Serra M. 1995. Ecological genetics of a cyclical parthenogen in temporary habitats. J Evol Biol 8: 601–622. [CrossRef] [Google Scholar]
- Gómez A, Serra M, Carvalho GR, Lunt DH. 2002. Speciation in ancient cryptic species complexes: evidence from the molecular phylogeny of Brachionus plicatilis (rotifera). Evolution 56: 1431–1444. [CrossRef] [PubMed] [Google Scholar]
- Gómez A, Montero-Pau J, Lunt DH, Serra M, Campillo S. 2007. Persistent genetic signatures of colonization in Brachionus manjavacas rotifers in the Iberian Peninsula. Mol Ecol 16: 3228–3240. [CrossRef] [PubMed] [Google Scholar]
- Hartl DL, Clark AG. 1989. Principals of population genetics. 2nd ed. Sunderland: Sinauer Associates, Inc. Publishers. [Google Scholar]
- Heath DD, Busch C, Kelly J, Atagi DY. 2002. Temporal change in genetic structure and effective population size in steelhead trout (Oncorhynchus mykiss). Mol Ecol 11: 197–214. [CrossRef] [PubMed] [Google Scholar]
- Hebert PDN. Variable environments and evolutionary diversification in inland waters. In: Carvalho GR, ed. Advances in molecular ecology. Amsterdam: IOS Press, 1998, pp. 267–290. [Google Scholar]
- Katoh K, Asimenos G, Toh H. 2009. Multiple alignment of DNA sequences with MAFFT. Methods Mol Biol 537: 39–64. [CrossRef] [PubMed] [Google Scholar]
- King CE. 1972. Adaptation of rotifers to seasonal variation. Ecology 53: 408–418. [CrossRef] [Google Scholar]
- King CE. 1977. Genetics of reproduction, variation and adaptation in rotifers. Archiv für Hydrobiol Beiheft Ergeb der Limnol 8: 187–201. [Google Scholar]
- King CE. 1980. The genetic structure of zooplankton populations. In: Kerfoot WC, ed. Evolution and ecology of zooplankton communities. Hanover: The University Press of New England, pp. 315–328. [Google Scholar]
- King CE, Serra M. 1998. Seasonal variation as a determinant of population structure in rotifers reproducing by cyclical parthenogenesis. Hydrobiology 387/388: 361–372. [CrossRef] [Google Scholar]
- King CE, Snell TW. 1980. Density-dependent sexual reproduction in natural populations of the rotifer Asplanchna girodi. Hydrobiology 73: 149–152. [CrossRef] [Google Scholar]
- King CE, Zhao Y. 1987. Coexistence of rotifer (Brachionus plicatilis) clones in Soda Lake (Nevada). Hydrobiology 147: 57–64. [CrossRef] [Google Scholar]
- Knowlton N. 1993. Sibling species in the sea. Annu Rev Ecol Syst 24: 189–216. [CrossRef] [Google Scholar]
- Lee HJ, Boulding ZG. 2009. Spatial and temporal population genetic structure of four northeastern Pacific littorinid gastropods: the effect of mode of larval development on variation at one mitochondrial and two nuclear DNA markers. Mol Ecol 18: 2165–2184. [CrossRef] [PubMed] [Google Scholar]
- Lessios HA, Weinberg JR, Starczak VR. 1994. Temporal variation in populations of the marine isopod Excirolana: how stable are gene frequencies and morphology. Evolution 48: 549–563. [CrossRef] [PubMed] [Google Scholar]
- Li SH, Zhu H, Xia YZ et al. 1959. The mass culture of unicellular green algae. Acta Hydrobiol Sin 4: 462–472. [Google Scholar]
- Li HB, Xi YL, Cheng XF, Xiang XL et al. 2008. Sympatric speciation in rotifers: evidence from molecular phylogenetic relationships and reproductive isolation among Brachionus calyciflorus clones. Acta Zool Sin 54: 256–264. [Google Scholar]
- Librado P, Rozas J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452. [CrossRef] [PubMed] [Google Scholar]
- Mills S, Alcantara-Rodriguez JA, Ciros-Pérez J, Gómez A et al. 2017. Fifteen species in one: deciphering the Brachionus plicatilis species complex (Rotifera, Monogononta) through DNA taxonomy. Hydrobiology 796: 39–58. [CrossRef] [Google Scholar]
- Monaghan MT, Wild R, Elliot M. 2009. Accelerated species inventory on Madagascar using coalescent-based models of species delineation. Syst Biol 58: 298–311. [CrossRef] [PubMed] [Google Scholar]
- Ortells R, Gómez A, Serra M. 2003. Coexistence of cryptic rotifer species: ecological and genetic characterisation of Brachionus plicatilis. Freshw Biol 48: 2194–2202. [CrossRef] [Google Scholar]
- Papakostas S, Michaloudi E, Proios K et al. 2016. Integrative taxonomy recognizes evolutionary units despite widespread mitonuclear discordance: evidence from a rotifer cryptic species complex. Syst Biol 65: 508–524. [CrossRef] [PubMed] [Google Scholar]
- Pejler B. 1977. On the global distribution of the family Brachionidae (Rotatoria). Arch Hydrobiol 53: 255–306. [Google Scholar]
- Peltier WH, Weber CI. 1985. Methods for measuring the acute toxicity of effluents to freshwater and marine organisms. EPA/600/4-85/013. United States Environmental Protect Agency, Ohio, Cincinnati. [Google Scholar]
- Pons J, Barraclough TG, Gómez-Zurita J, Cardoso A. 2006. Sequence based species delimitation for the DNA taxonomy of undescribed insects. Syst Biol 55: 595–609. [Google Scholar]
- Posada D, Crandall KA. 1998. Modeltest: testing the model of DNA substitution. Bioinformatics 14: 817–818. [CrossRef] [PubMed] [Google Scholar]
- Puillandre N, Lambert A, Brouillet S, Achaz G. 2012. ABGD, automatic barcode gap discovery for primary species delimitation. Mol Ecol 21: 1864–1877. [Google Scholar]
- Ronquist F, Huelsenbeck JP. 2003. Mrbayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 1572–1574. [CrossRef] [PubMed] [Google Scholar]
- Ruttner-Kolisko A. 1989. Problems in taxonomy of rotifers, exemplified by the Filinia longiseta – terminalis complex. Hydrobiology 186/187: 291–298. [CrossRef] [Google Scholar]
- Sanderson MJ. 2002. Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Mol Biol Evol 19: 101–109. [CrossRef] [PubMed] [Google Scholar]
- Segers H. 2007. A global checklist of the rotifers (Phylum Rotifera). Zootaxa 1564: 1–104. [Google Scholar]
- Segers H. 2008. Global diversity of rotifers (Rotifera) in freshwater. Hydrobiology 595: 49–59. [CrossRef] [Google Scholar]
- Segers H, De Smet WH. 2008. Diversity and endemism in Rotifera: a review, and Keratella Bory de St Vincent. Biodivers Conserv 17: 303–316. [CrossRef] [Google Scholar]
- Serra M, Galiana A, Gómez A. 1997. Speciation in monogonont rotifers. Hydrobiology 358: 63–70. [CrossRef] [Google Scholar]
- Snell TW. 1979. Intraspecific competition and population structure in rotifers. Ecology 60: 494–502. [CrossRef] [Google Scholar]
- Snell TW. 1980. Blue-green algae and selection in rotifer populations. Oecologia 46: 343–346. [CrossRef] [PubMed] [Google Scholar]
- Snell TW, Morris PD. 1993. Sexual communication in copepods and rotifers. Hydrobiology 255: 109–116. [CrossRef] [Google Scholar]
- Snell TW, Rico-Martinez R, Kelly LN, Battle TE. 1995. Identification of a sex pheromone from a rotifer. Mar Biol 123: 347–353. [CrossRef] [Google Scholar]
- Swofford DL. 2002. Phylogenetic analysis using parsimony (*and other methods). Sunderland: Sinauer Associates, Inc. Publishers. [Google Scholar]
- Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. 1997. The clustal_x windows interface: flexible strategies for multiple sequence alignment aided by quality analyses tools. Nucleic Acids Res 24: 4876–4882. [Google Scholar]
- Vanderploeg HA, Pothoven SA, Fahnenstiel GL et al. 2012. Seasonal zooplankton dynamics in Lake Michigan: disentangling impacts of resource limitation, ecosystem engineering, and predation during a critical ecosystem transition. J Great Lakes Res 38: 336–352. [CrossRef] [Google Scholar]
- Xiang XL, Xi YL, Wen XL et al. 2011a. Genetic differentiation and phylogeographical structure of the Brachionus calyciflorus complex in eastern China. Mol Ecol 20: 3027–3044. [CrossRef] [PubMed] [Google Scholar]
- Xiang XL, Xi YL, Wen XL et al. 2011b. Patterns and processes in the genetic differentiation of the Brachionus calyciflorus complex, a passively dispersing freshwater zooplankton. Mol Phylogenet Evol 59: 386–398. [CrossRef] [PubMed] [Google Scholar]
- Zhang J, Kapli P, Pavlidis P, Stamatakis A. 2013. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29: 2869–2876. [CrossRef] [PubMed] [Google Scholar]
- Zhao Y, King CE. 1989. Ecological genetics of the rotifer Branchionus plicatilis in Soda Lake, Nevada, USA. Hydrobiology 185: 175–181. [CrossRef] [Google Scholar]
Cite this article as: Xiang X-L, Xi Y-L, Wen X-L, Ge Y-L. 2017. Molecular phylogeny and population genetic differentiation patterns in Brachionus calyciflorus Pallas (Rotifera) complex from two lakes in China. Ann. Limnol. - Int. J. Lim. 53: 401–410
Supplementary tables. Access here
The ML phylogenetic tree based on ITS sequences. Values isolated by slashes represent Bayesian, ML, MP, and NJ bootstrap support.
|In the text|
The ML phylogenetic tree based on COI sequences. Values isolated by slashes represent Bayesian, ML, MP, and NJ bootstrap support.
|In the text|
Distribution of cryptic species in Guangzhou and Wuhu over four seasons based on the ITS sequences.
|In the text|
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.