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Article

Genetic Diversity and Population Structure Analysis of Chinese Mitten Crab (Eriocheir sinensis) in the Yangtze and Liaohe Rivers

by
Lin Zhou
1,
Jiancao Gao
2,
Yanping Yang
2,
Zhijuan Nie
2,
Kai Liu
2 and
Gangchun Xu
1,2,*
1
College of Fisheries and Life Science, Shanghai Ocean University, Shanghai 201306, China
2
Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China
*
Author to whom correspondence should be addressed.
Fishes 2023, 8(5), 253; https://doi.org/10.3390/fishes8050253
Submission received: 13 February 2023 / Revised: 22 April 2023 / Accepted: 8 May 2023 / Published: 10 May 2023
(This article belongs to the Special Issue Recent Advances in Crab Aquaculture)
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Abstract

:
Recently, the economic traits of Chinese mitten crab (Eriocheir sinensis) varieties have had a negative tendency. Meanwhile, the status of wild germplasm resources of E. sinensis is unknown, hindering the utilization of wild germplasm resources and the green development of the E. sinensis industry. Thus, the conservation of the wild E. sinensis germplasm resource is of great significance. To this end, we collected wild E. sinensis from two different river basins, the Yangtze River basin, and the Liaohe River basin, and analyzed the genetic diversity as well as the genetic differentiation in E. sinensis populations. Based on eight microsatellite markers, we found moderate genetic diversity in E. sinensis populations regardless of river basin. Based on the mitochondrial D-loop region, we found that all populations are at mutation drift equilibrium, while the Nm between any two populations is greater than 1. We hypothesized the existence of island model gene flow patterns among E. sinensis. Interestingly, genetic differentiation among E. sinensis populations was low, except that between Liaohe and Anqing or Shanghai populations. Additionally, geometric morphological analysis could distinguish E. sinensis from different basins, with an accuracy of 94.2–100%. Given the similar genetic diversity in the two basins, the genetic convergence of E. sinensis from different basins deserves further attention.
Keywords:
crabs; D-loop sequences; microsatellite; genetic; geometric morphometrics
Key Contribution: The present state of wild Eriocheir sinensis resources in the Yangtze River and Liaohe River basins was revealed.

Graphical Abstract

1. Introduction

Chinese mitten crab (Eriocheir sinensis) is an important economic aquatic animal in China. Due to the suitable environment of the middle and lower reaches of the Yangtze River basin, it has become the optimal area for E. sinensis growth and development [1]. The Yangtze River is the third largest river in the world, and its species diversity is ecologically vital. Previous studies have shown that Chinese mitten crabs in different basins of the Yangtze River have different genetic diversities. For example, the genetic diversity of E. sinensis (adult and juvenile) in the Zhenjiang region is lower than that in other regions [2]. In the 1980s, the expansion of the aquaculture scale led to a reduction in wild E. sinensis. Because of the shortage of wild germplasm resources, Chinese mitten crabs from other basins were introduced to the Yangtze River basin, including the Liaohe River basin [3]. In recent years, the economic shape of the cultured E. sinensis population has been degraded [4]. Meanwhile, the status quo of wild germplasm resources is unclear, which hinders scientific development and utilization, and is not conducive to the green development of the crab industry. In addition, in order to improve the scale and quality of crab aquaculture, a large number of new varieties have been obtained through different selection methods [5], such as “Changjiang 1”, “Changjiang 2”, “Noya No. 1” and “Sea & River 21” [6]. Although new species temporarily relieve breeding needs, the wild Yangtze crab is still a high-quality parent variety for selection and breeding [4]. Therefore, it is particularly important to investigate their population structure and availability of germplasm. In order to investigate the current state of wild E. sinensis germplasm resources and clarify the genetic differentiation relationship between different river systems of crab populations, in this study, four populations from the Yangtze River and one population from the Liaohe River were collected, and their population genetics were analyzed using the mitochondrial D-loop region and eight microsatellite markers.
Morphological characteristics are not only the important basis of taxonomy; also significant is the external expression of the genetic characteristics of species [7]. Morphology is the simplest and fastest method to identify species. Compared to traditional morphometry, geometric morphometrics is more suitable for obtaining the shape data of organisms, allowing the visual comparison of subtle differences between study subjects [8,9]. Through geometric morphometrics, it has been revealed that genital characteristics could be an indicator to distinguish giant Amazonian ants (Dinoponera) [10]. In Apidae, the size and shape of the forewing were of value in distinguishing the species [11]. A published study examined evidence that the species and sex of four planktivorous petrels can be distinguished by geometric morphometrics [12]. In addition, geometric morphometrics has been widely used in aquatic animals [13]. Emperor fishes (Lethrinidae) can be identified by geometric morphology in the late larval and early juvenile stages [14]. A previous study reported that different freshwater prawns were distinguished through chelae and carapace by geometric morphometrics [15]. In particular, it is applied to identify the geographical origin of aquatic animals, such as prawns [16], crabs [17], etc.
Morphological characteristics are determined jointly by genetic information and environment. Thus, under similar environmental conditions, morphological differences mainly contribute to genetic variations [18]. Although geometric morphometrics can accurately indicate morphological variation, it has some limitations in distinguishing populations in close geographic contact [19]. Molecular markers are specific DNA fragments that reflect some difference in the genome between individuals or populations of organisms, which is more accurate than morphology. Thereinto, microsatellite loci have the advantages of co-dominant inheritance, high polymorphism, and a large amount of information [20,21]. The D-loop region is a noncoding gene on the mitochondrial genome, located between the tRNA-Phe of mitochondrial DNA (mtDNA) [22], and it is the fastest-evolving and most abundant region in the mitochondria [23]. Microsatellites, derived from nuclear genes, are characterized by high polymorphism, sufficient quantity, rapid mutation, wide distribution, and a simple analysis methods [24,25]. Moreover, the frequency of microsatellites in the population is stable in theory, which is not subject to selection pressure [26]. Both are ideal molecular markers. The use of microsatellite analysis has been reported to confirm the finding of a single population of Paralichthys dentatus along the Atlantic coast [27]. Wang et al. distinguished Gymnocypris chilianensis, Gymnocypris przewalskii, and Gymnocypris eckloni using mitochondrial D-loop region markers and found that the latter two may be subspecies of each other [28]. A previous study successfully detected genetic differentiation in different populations of marine fishes [29]. In crustaceans, microsatellites are also widely used, often for genetic analysis [30,31]. Švara et al. conducted a microevolutionary dynamic analysis of the Gammarus pulex population with microsatellite markers [32]. Other authors reported that the rockpool shrimp (Palaemon elegans) demonstrated a weak but significant genetic differentiation between the Canary Islands and the Atlantic mainland through microsatellite analysis [33].
The current study was conducted to investigate the genetic diversity and population structure of E. sinensis by combining nuclear microsatellite markers, mitochondrial D-loop region sequences, and morphological methods. The aim was to estimate the diversity of the germplasm and understand the status of the germplasm resources of wild E. sinensis populations in the Yangtze and Liaohe river basins. The results of this study will help us understand the status of the germplasm resources and the degree of germplasm mixing of E. sinensis in the two basins. It will provide valuable information on the conservation and utilization of E. sinensis resources.

2. Materials and Methods

2.1. Ethics Statement

The experimental protocol was performed following the guidelines approved by the Institutional Animal Care and Use Committee of the Ministry of Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences (SYXK(HX)20210104006).

2.2. Sample Collection

In total, 132 wild adults of E. sinensis were collected from 5 locations along the Yangtze River and Liaohe River for genetic analysis. (Figure 1). Sampling sites were located in Anqing city (AQ), Changshu city (CS), Taizhou city (TZ), Shanghai (SH), and Panjin city (LH). Sampling information of the crabs is shown in Table S1. Crab samples were photographed with a Canon EOS 70D for morphological analysis, and then muscle was collected and stored in 96% alcohol for DNA extraction.

2.3. DNA Extraction, Microsatellite, and D-Loop Fragment Amplification

DNA was extracted from muscle tissue using Universal Genomic DNA Kit (CWBIO, Nanjing, China) according to the manufacturer’s instructions. The integrity and concentration of DNA were detected by 1% agarose gel electrophoresis and Nanodrop 2000 spectrophotometer. The D-loop region sequences’ amplification primers were: F: 5′-ACGTAACTGAAATGCTGTTC-3′ and R: 5′-ACCCGTTTCCCCTCTAGAGGA-3′ [34]. The PCR system of the D-loop used a 25 μL-total reaction system including 12.5 μL 2 × Taq Plus Master Mix (Vazyme, Nanjing, China), 2.5 μL DNA template, 1.25 μL each primer (10 μmol/L), and 7.5 μL sterile water. The reaction was amplified at 95 °C for 3 min, followed by 36 cycles of 95 °C for 15 s, 54 °C for 15 s, 72 °C for 30 s, and 72 °C for 5 min.
A total of eight microsatellite loci of E. sinensis were used to analyze the genetic variations among the five sampling populations [35]. The forward primers for each microsatellite locus were labeled with a fluorescence marker (Table S2). The PCR microsatellite system used a 10 μL-total reaction system including 5 μL 2 × Taq Plus Master Mix (Vazyme, Nanjing, China), 1 μL DNA template, 0.4 μL each primer (10 μmol/L), and 3.2 μL sterile water. The reaction was amplified at 94 °C for 3 min, followed by 38 cycles of 94 °C for 15 s, 55 °C for 1 min, 72 °C for 1 min, and 72 °C for 5 min. Before fragment length analysis, equal amounts of PCR products were mixed into two sets (Table S2). Fragment sizes were scored manually after electrophoresis on an ABI3730 sequencer (Yixin Biotechnology, Wuxi, China), using Liz500 as the internal size standard.

2.4. Carapace Morphology

In this study, 30 landmarks were used for analyzing the shape variation in carapaces (Figure S1). The tpsRelw32 was used to obtain the mean shape and the variance in each landmark. Grid deformation and variation visualization of the carapaces were calculated by MorphoJ 1.07a [36]. Discriminant analysis was conducted using SPSS 26.0 [37]. In the study, the main objective was to investigate whether the E. sinensis of the Yangtze and Liaohe river basins could be effectively distinguished by geometric morphology. In addition, a total of 54 E. sinensis carapaces from the Liaohe River basin and 172 from the Yangtze River basin were collected for analysis.

2.5. Molecular Genetic Analysis

Multiple alignments of mitochondrial D-loop region sequences was conducted using Clustalx [38]. The nucleotide diversity (Pi) and haplotype diversity (Hd), were analyzed by DnaSP 5.10 [39]. The fixation index (FST), gene flow (Nm), analysis of molecular variance (AMOVA), Tajima’s D, and Fu’s Fs test values were determined in Arlequin 3.5 [40]. The haplotype network was implemented by the median-joining method through POPART 1.7 [20]. A neighbor-joining phylogenetic tree and maximum likelihood tree were constructed based on the Kimura 2-parameter model by MAGE 11. Bootstrap values were based on 1000 rapid bootstrap replicates.
The Micro-checker was used to detect null alleles at each locus [41]. Analysis of molecular variance (AMOVA), expected heterozygosity (He), observed heterozygosity (Ho), and fixation index (FST) were then calculated for each microsatellite marker using Arlequin 3.5 [40], as well as the Hardy–Weinberg test. Allelic richness (AR) was calculated using FSTAT v 2.9.3 [42]. The Bayesian clustering analyses run in STRUCTURE v 2.3.4 were evaluated using the Evanno test to determine the most optimal number of K [43,44]. The neighbor-joining (N-J) tree was then constructed based on Nei’s DA genetic distances by Phylip 3.695 [45]. In addition, principal coordinate analysis (PCoA) was performed on various populations based on pairwise Nei’s genetic distances between populations using GenAlEx 6.51 [46,47].

3. Result

3.1. Geometric Morphometrics

Based on 30 landmarks selected in the study, all E. sinensis from the Yangtze and Liaohe rivers were analyzed by geometric morphometrics so as to determine the mean shape (Figure S2A) and the overlapped shape (Figure S2B). Next, we found that the landmarks with the highest contributions were 19 and 20, which accounted for 62.262% of the variance (Table S3). Then, relative warps in the principal component (PC) analysis result showed that the variance contribution of the first two principal components was the largest (Table S4), which could explain the morphological variation in the carapaces (Figure S3A). The results showed that the combination of PC1 and PC2 can well distinguish between the populations of the Yangtze and Liaohe rivers (Figure S3B). Using PC1, the Yangtze and Liaohe populations could not be well distinguished, while using PC2, they could (Figure S3B). The PC2 value of the Liaohe population was lower than that of the Yangtze population (Figure S3B). Furthermore, after visualizing the difference in carapaces (variations were enlarged three times), it was found that the morphological characteristics were mainly different in the distance to the posterior lateral edge (Figure 2). Based on the analysis of PC2 (Figure S3D) and the grid diagram (Figure 2), the changing trend mainly exists in the landmarks 21 and 22. The posterior lateral edge of the Yangtze population is narrower, while the posterior lateral edge of the Liaohe population is wider.
Furthermore, the result of the discriminant analysis showed that the accuracy of discrimination was 94.2% and 100.0% in the Yangtze population and the Liaohe population, respectively (Table 1). The discriminant analysis showed that 56 indices were included in the discriminant function of 56 relative warp principal component scores of the carapace morphology of the two basins (the discriminatory formula is found in Supplementary Materials). Based on the discriminant function, the E. sinensis in the two basins could be distinguished (Figure 3).

3.2. Population Genetic Diversity

In the present study, based on microsatellite loci data, the mean Ho values ranged from 0.571 to 0.712, with the highest values observed in the SH population and the lowest in the LH population (Table 2). The mean He values ranged from 0.653 to 0.678, with the highest values observed in the SH population (Table 2). Unlike Ho, the lowest mean He values were for the AQ population rather than the LH population. The mean AR values of each microsatellite locus ranged from 5.875 to 6.530, with the highest and the lowest mean AR values observed in the Yangtze population (Table 2). Regarding the result of the Hardy–Weinberg equilibrium, we found that some microsatellite loci in the five E. sinensis populations examined had an exact test probability of less than 0.05, revealing a significant deviation from the Hardy–Weinberg equilibrium (Table 3). The AQ and TZ populations had the most microsatellite loci deviating significantly from the Hardy–Weinberg equilibrium, with three loci.
According to the result of the D-loop analysis, in the different populations, Hd and Pi values ranged from 0.933 to 1.000 and from 0.006 to 0.020 (Table 3), respectively. The TZ population showed the lowest Hd value of all the populations. The LH population showed the highest Pi value, and the lowest Pi value was observed in the AQ population. In total, 22 haplotypes were identified, including 20 unique haplotypes, and 2 shared haplotypes: haplotype 1 in CS, AQ, and SH; and haplotype 15 in AQ, TZ, and SH (Table 4).

3.3. Population Structure

To assess the variation in the population, we analyzed microsatellite loci and D-loops in AMOVA (Table 5). The FST value of the microsatellite loci and D-loops were 0.025 and 0.011, respectively, indicating that there was no significant genetic differentiation between the five populations. At the same time, the results showed that the variation mainly occurred in individuals, and the interspecific difference was not significant.
Furthermore, this study found that E. sinensis have different degrees of genetic differentiation among different populations (Table 6). For the microsatellite loci, the FST value ranged from near-random mating (pairwise FST = 0.003 between TZ and AQ populations) to moderate differentiation (pairwise FST = 0.057 between TZ and CS populations). Based on the microsatellite loci, the Nm ranged from 4.182 to 70.863 (Table 7). The lowest Nm was detected between the CS and TZ populations, and the highest between the AQ and TZ populations.
The STRUCTURE analysis determined K = 2 to be the most likely number of genetically distinct clusters (Figure 4A,C). This result was also reflected by the principal coordinate analysis (Figure 4B). Interestingly, the LH and CS populations were independent of the other populations. Meanwhile, the N-J tree of microsatellite loci data based on the Nei’s DA genetic distance revealed that the LH population was independent, and the AQ, CS, TZ, and SH populations were clustered as one clade (Figure 5A).
Based on the D-loop sequences, the pairwise FST ranged from 0.021 (CS and AQ populations) to 0.202 (SH and LH populations) (Table 6). In the D-loop sequence, the Nm ranged from 1.969 to 23.692 (Table 7). The lowest Nm was observed between the SH and LH populations, and the highest between the CS and AQ populations. The result of the D-loop analysis showed that in the N-J tree, half of the LH individuals clustered into one clade, while the remaining individuals were found in the Yangtze River group (Figure 5B). The haplotype network exhibited the two main branches’ haplotypes, indicating that haplotypes from different regions were linked; the two shared haplotypes and dominant haplotypes were clearly defined (Figure S4A). Furthermore, the ML tree showed that haplotype 2 and haplotype 5 obtained support values of more than 80% (Figure S4B). These three haplotypes are shared haplotypes of the LH population and are consistent with the network results.
In the study, Tajima’s D test and Fu’s Fs test were executed on the D-loop sequences of E. sinensis. Both the D test value and Fs test value were negative, and they had no significant difference with 0 (Table 8), suggesting that all populations are at mutation-drift equilibrium. The mismatch distribution curve displayed a multi-peaked curve distribution, indicating a stable population size (Figure S5).

4. Discussion

4.1. Geometric Morphological Analysis

Geometric morphometry has proven to be an extraordinary tool for the study of morphology [10]. Morphological characters are external manifestations of intrinsic heredity and have a certain lag compared to genetic variation. Geometric morphology has the advantage of being able to exclude some confounding factors and identify morphological differences that are more difficult to detect with traditional morphology [48]. The existence of morphological differences between male and female crabs has been confirmed in a previous study [49]. Another previous study showed that differences in morphology, physiology, and even genetic levels can occur between population species due to geographical barriers [50]. In the present study, the morphology of crabs in different regional groups was found to differ slightly. The Liao River is located in northeastern China and has a cold climate, so the river crabs mature earlier and are smaller than those in the Yangtze River [51]. Our results confirm this statement. Compared with crabs from all areas of the Yangtze River, the frontal and lateral spina of female crabs in the Liao River are more closely distributed, while the M-pattern pattern of male crabs is contracted more inward. Crabs from the Liaohe River reach sexual maturity earlier than crabs from the Yangtze River. In the market, the price of mature early crabs is higher than that of crabs that mature normally. In order to improve the economic benefits of crab farming, farmers from the middle and lower reaches of the Yangtze River introduced crabs from the Liaohe River, resulting in a risk of germplasm mixture. Our results also indicated potential morphological differences among crabs in the different basins. We believe that this method has some potential for germplasm conservation by identifying crab sources and preventing germplasm mixture.

4.2. Genetic Diversity

Genetic diversity represents the evolutionary flexibility of populations, and higher genetic diversity means that the population has better evolutionary potential and ability to adapt to environmental changes. Mitochondrial DNA and microsatellite loci have been widely used in the genetic analysis of crustaceans [52], such as mud crabs (Scylla paramamosain) [53] and swimming crabs (Portunus trituberculatus) [54].
At present, the genetic diversity of crab populations is unclear. Besides the occurrence of genetic mutations, crabs often copulate with multiple mates, potentially resulting in offspring more abundant in genetic diversity than their parents. In aquaculture, crabs from other basins were introduced into local farms via breeding and escaping, and the artificial breeding of crabs caused the gene exchange of populations from different basins. At present, the genetic diversity of crabs in the Yangtze River and Liaohe River has decreased, so it is urgent to maintain their genetic diversity.
Compared to the previous study, the average expected heterozygosity (0.653 to 0.678) and observed heterozygosity (0.571 to 0.712) of the studied population were lower than that of the Liaohe (He: 0.88; Ho: 0.79), Nanliujiang (He: 0.84; Ho: 0.77), and Mudanjiang (He: 0.85; Ho: 0.73) populations, which could be due to the different number of molecular makers, sampling number, and basins selected [55]. In addition, genetic drift is a change in allele frequency in a population, due to a random selection of certain genes. This may also account for the decline in genetic diversity. Moreover, the nucleotide diversity and haplotype diversity were important indicators of genetic diversity. The high Hd (0.933 to 1) and Pi (0.006 to 0.020) found in the study indicate that the populations have a high level of diversity. As a result, although the Hd and Pi were both higher than critical values (Hd: 0.5, Pi: 0.05) [56], Hd was higher than Pi in this study, which may be due to the genetic bottleneck caused by the introduction of large crab populations from other basins [57].

4.3. Genetic Structure

Genetic structure is affected by many factors, such as a change in environment, climate change, and ecological structural changes [22]. Using nuclear and mitochondrial genetic markers may provide a more comprehensive explanation of genetic conditions [54,58,59,60]. The pairwise FST of the Liaohe River and Yangtze River crabs in this study was higher than in other studies [55,61], and we found a high Nm (all population > 1), indicating that there is gene flow between the Yangtze River and Liaohe River populations. The gene flow model is mainly classified into the island model (continent island model and island model), the stepping stone model, and the isolation by distance model [62,63]. The island model is suitable for populations with discontinuous habitats. The geographical distance between the Yangtze River and the Liao River is far (more than 985 km), which is consistent with the island pattern. These two basins have a strong geographical barrier, and the existence of gene exchange may be caused by aquaculture activity practices or the displacement of crabs as wild germplasm. Crabs from the Liaohe River basin were introduced to the Yangtze River basin for farming, and it is speculated that the farmed Liaohe population escaped and therefore had a gene exchange with the wild population in the Yangtze River basin [1].
An earlier study using microsatellite loci analysis showed that the Yangtze River and Liaohe River crabs share the same ancestry, and different gene pools exist due to biological evolution and natural geographic isolation [3]. In the present study, as seen from the results of the AMOVA analysis, the genetic differentiation between populations was not obvious (microsatellite: 2.48%; D-loop: 1.07%), and the genetic variation was mainly within populations (microsatellite: 97.52%; D-loop: 98.93%). This indicates that the genetic exchange between the Yangtze River and Liaohe River populations is frequent and genetic exchange is constant. Interestingly, within the Yangtze population, the microsatellite loci results showed that the CS population was clearly different from the other Yangtze populations, and the pairwise FST of the CS and TZ populations (0.056), and that of the CS and SH populations (0.055) was higher than 0.05, meaning they have moderate genetic differentiation [61]. A previous study found that the crabs from the same basin failed to cluster together, suggesting that the genetic differentiation of populations may not be related to geographic distance [1,64]. The sample size had a significant impact on the data analysis [65], and we speculate that the small number of crabs from the CS population was one of the reasons. In addition, it is possible that some crabs were collected earlier than those at other sites, and the crab collection site was close to the shore, meaning there might have been an escape from the farmed population [66,67]. However, in the D-loop sequence results, the pairwise FST within the Yangtze populations were all less than 0.05, and the genetic differentiation was not obvious. It is possible that the mutation rates of the two molecular makers are different, resulting in inconsistent genetic signals [22,61].
Tajima’s D test, Fu’s Fs test, and mismatched distribution were important indices in the analysis of the historical evolution of the population [20]. The negative results of both Tajima’s D and Fu’s Fs tests, as well as the multi-peaked results of the mismatched distribution curve, indicate that there was no population expansion in the recent past [68,69].

5. Conclusions

In conclusion, this study accurately distinguished wild E. sinensis from different basins by geometric morphometry. The genetic diversity of wild E. sinensis in the Yangtze River and the Liaohe River is relatively high, and there is moderate to strong gene flow between the populations in the two basins. These results suggest a risk of genetic homogeneity in E. sinensis populations from different basins. Thus, it is very important to take timely measures to strengthen the protection of the germplasm resources of E. sinensis. This study elucidates the genetic resources of wild Chinese mitten crabs (E. sinensis) and lays a foundation for the conservation and development of their germplasm resources.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/fishes8050253/s1, Table S1: Morphometric information of Chinese mitten crab (E. sinensis) populations; Table S2: Primers information of Chinese mitten crab (E. sinensis) populations in the present study; Table S3: Relative contribution of each landmark of four populations in Chinese mitten crab (E. sinensis); Table S4: Eigenvalues and contributions of the first ten principal components of relative warps scores; The discriminatory formula; Figure S1. Landmark points for morphological measurements on the carapace of Chinese mitten crab (E. sinensis); Figure S2. (A) Mean shape of landmarks on carapace of wild Chinese mitten crab (E. sinensis) from different populations. (B) superimposed landmarks of Chinese mitten crab (E. sinensis) of four population; Figure S3. (A)The variance of Principal components; (B) Scatter plots of PC1 and PC2 of wild Chinese mitten crab (E. sinensis) from different basins; (C) The change of 30 landmarks of PC1; (D) The change of 30 landmarks of PC2; Figure S4. (A) The median-joining network based on haplotype frequencies of Chinese mitten crab (E. sinensis). (B) Maximum likelihood tree based on haplotypes from D-loop region sequences; Figure S5. Mismatch distribution for the five inferred populations of Chinese mitten crab (E. sinensis).

Author Contributions

L.Z. collected the crab samples, performed the experiment, analyzed the data, and wrote the manuscript. J.G. analyzed the data and assisted in writing and proofreading the article. Y.Y. collected the crab samples. Z.N. provided language help. K.L. provided the study materials, laboratory animals, and instruments. G.X. and J.G. conceptualized the experiment. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Central Public-interest Scientific Institution Basal Research Fund, Freshwater Fisheries Research Center, CAFS (NO. 2021JBFM06), and the earmarked fund for CARS48.

Institutional Review Board Statement

Institutional Animal Care and Use Committee of the Ministry of Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences. (SYXK(HX)20210104006).

Data Availability Statement

The datasets generated and/or analyzed for the current study are available from the corresponding author on reasonable request.

Acknowledgments

The authors would like to express their sincere thanks to the personnel of these teams for their kind assistance.

Conflicts of Interest

The authors declare no conflict of interest.

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Fishes 08 00253 g001 550
Figure 1. Five sampling sites in this study: Anqing city (AQ), Taizhou city (TZ), Changshu city (CS), Shanghai city (SH), and Panjin city (LH).
Figure 1. Five sampling sites in this study: Anqing city (AQ), Taizhou city (TZ), Changshu city (CS), Shanghai city (SH), and Panjin city (LH).
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Fishes 08 00253 g002 550
Figure 2. Grid deformation and variation visualization of the carapace of wild Chinese mitten crab (E. sinensis) (variations are enlarged three times). (A) Liaohe River population; (B) Yangtze River population. The circles represent landmarks.
Figure 2. Grid deformation and variation visualization of the carapace of wild Chinese mitten crab (E. sinensis) (variations are enlarged three times). (A) Liaohe River population; (B) Yangtze River population. The circles represent landmarks.
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Figure 3. The discriminate analysis by carapace geometrical morphometry for the Chinese mitten crab (E. sinensis) populations. (A) Liaohe River population; (B) Yangtze River population.
Figure 3. The discriminate analysis by carapace geometrical morphometry for the Chinese mitten crab (E. sinensis) populations. (A) Liaohe River population; (B) Yangtze River population.
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Figure 4. (A) Inference of best K based on microsatellite loci in STRUCTURE v 2.3.4. (B) Principal coordinate analysis (PCoA) of pairwise distances between the five populations based on microsatellite loci. (C) Genetic structure among Chinese mitten crab (E. sinensis) populations. Individual assignment to two genetically distinct clusters using STRUCTURE v 2.3.4. Likelihood of assignment for each individual is shown as a vertical bar.
Figure 4. (A) Inference of best K based on microsatellite loci in STRUCTURE v 2.3.4. (B) Principal coordinate analysis (PCoA) of pairwise distances between the five populations based on microsatellite loci. (C) Genetic structure among Chinese mitten crab (E. sinensis) populations. Individual assignment to two genetically distinct clusters using STRUCTURE v 2.3.4. Likelihood of assignment for each individual is shown as a vertical bar.
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Figure 5. (A) Neighbor-joining (NJ) tree based on Nei’s DA genetic distances among five populations. (B) Neighbor-joining (NJ) tree of all of the D-loops for Chinese mitten crabs (E. sinensis); letters represent populations and numbers represent individuals. The outgroups are Eriocheir hepuensis (FJ455506.1) and Eriocheir japonica (FJ455505.1).
Figure 5. (A) Neighbor-joining (NJ) tree based on Nei’s DA genetic distances among five populations. (B) Neighbor-joining (NJ) tree of all of the D-loops for Chinese mitten crabs (E. sinensis); letters represent populations and numbers represent individuals. The outgroups are Eriocheir hepuensis (FJ455506.1) and Eriocheir japonica (FJ455505.1).
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Table
Table 1. Classification results of Chinese mitten crab (E. sinensis) from different basins.
Table 1. Classification results of Chinese mitten crab (E. sinensis) from different basins.
PopulationLiaohe RiverYangtze River
Liaohe River54 (100.0%)0
Yangtze River10 (5.8%)162 (94.2%)
Table
Table 2. Observed heterozygosity (Ho), expected heterogeneity (He), allelic richness (AR), and Hardy–Weinberg equilibrium (HWE) for 8 microsatellite loci of Chinese mitten crabs (E. sinensis) from the different basins.
Table 2. Observed heterozygosity (Ho), expected heterogeneity (He), allelic richness (AR), and Hardy–Weinberg equilibrium (HWE) for 8 microsatellite loci of Chinese mitten crabs (E. sinensis) from the different basins.
LocusCX140CX287CX256CX416CX003CX254CX400CX427Mean
LHHo0.4330.6660.9660.3440.40.60.5330.6330.571
He0.3970.7650.9570.4340.4670.8160.680.8370.669
AR3.6096.30515.3354.224.0326.8984.5976.8456.48
HWE10.2460.2270.1850.1980.0010.1010.023
CSHo0.250.6660.9090.750.6660.5830.5830.4160.602
He0.3580.670.9820.6660.5860.7310.5860.8470.678
AR2.9174.83194.8345.8346.8336.53
HWE0.40310.1380.62710.340.6210.001
AQHo0.5330.70.9660.33310.6330.5660.5660.662
He0.4370.7880.9370.3750.5240.7690.5330.8660.653
AR3.3156.37613.2963.692.3676.5364.1097.7275.927
HWE0.7350.1560.0140.29500.0760.6880
TZHo0.40.6330.9330.43310.80.5330.5660.662
He0.3450.7770.9390.3630.5080.8610.5960.8560.655
AR2.8756.77114.1373.09427.73.6987.6355.988
HWE10.0330.8270.77500.4850.2340.001
SHHo0.6330.76610.43310.6330.5670.6670.712
He0.4930.7710.9270.370.540.8470.650.7990.674
AR3.6396.78612.4783.1962.7337.184.7036.2925.875
HWE0.5370.5890.239100.0570.2230.169
Table
Table 3. Summary statistics for D-loop polymorphisms of five Chinese mitten crab (E. sinensis) populations.
Table 3. Summary statistics for D-loop polymorphisms of five Chinese mitten crab (E. sinensis) populations.
PopulationNumber of Haplotypes (n)Haplotype Diversity (Hd)Nucleotide Diversity (Pi)Variable Sites
LH61.000 ± 0.0960.02009 ± 0.0036024
AQ61.000 ± 0.0960.00624 ± 0.009489
CS41.000 ± 0.1770.00948 ± 0.002259
TZ50.933 ± 0.1220.01276 ± 0.0037418
SH51.000 ± 0.1260.00778 ± 0.002539
Table
Table 4. Haplotype frequency distribution in five Chinese mitten crab (E. sinensis) populations from the Liaohe River and Yangtze River.
Table 4. Haplotype frequency distribution in five Chinese mitten crab (E. sinensis) populations from the Liaohe River and Yangtze River.
HaplotypeCSLHAQTZSHTotal
Hap_1101013
Hap_2100001
Hap_3100001
Hap_4100001
Hap_5010001
Hap_6010001
Hap_7010001
Hap_8010001
Hap_9010001
Hap_10010001
Hap_11001001
Hap_12001001
Hap_13001001
Hap_14001001
Hap_15001214
Hap_16000101
Hap_17000101
Hap_18000101
Hap_19000101
Hap_20000011
Hap_21000011
Hap_22000011
Note: Bold represents shared haplotype.
Table
Table 5. Analysis of molecular variance in Chinese mitten crabs (E. sinensis) based on microsatellite loci and D-loop sequences.
Table 5. Analysis of molecular variance in Chinese mitten crabs (E. sinensis) based on microsatellite loci and D-loop sequences.
Source of Variationd.f.Sum of ComponentsVariance ComponentsPercentage of VariationFixation Indexp-Value
(A) MicrosatellitesAmong populations424.5860.06752.48
Within populations259686.3422.65097.52
Total263710.9282.718 0.0250.000
(B) D-loopAmong groups10.5950.0214.15
Among populations within groups31.238−0.015−3.08
Within populations2210.8330.49298.93
Total2612.6670.498 0.0110.892
Table
Table 6. Pairwise FST (below diagonal) and P (above diagonal) values were calculated from variations in 8 microsatellite loci and D-loop sequences among five populations of Chinese mitten crabs (E. sinensis).
Table 6. Pairwise FST (below diagonal) and P (above diagonal) values were calculated from variations in 8 microsatellite loci and D-loop sequences among five populations of Chinese mitten crabs (E. sinensis).
PopulationLHAQCSTZSH
(A) MicrosatellitesLH 0.0000.0540.0000.000
AQ0.032 0.0000.1350.009
CS0.0180.048 0.0000.000
TZ0.0360.0030.057 0.793
SH0.0360.0120.056−0.002
(B) D-loopLH 0.0360.0630.1350.027
AQ0.200 0.13870.9280.829
CS0.1720.021 0.1980.315
TZ0.081−0.0300.038 0.162
SH0.202−0.0460.0330.044
Note: Pairwise FST of microsatellite loci were corrected with the ENA method.
Table
Table 7. Nm based on microsatellite loci (below diagonal) and D-loop sequences (above diagonal) between Chinese mitten crab (E. sinensis) populations.
Table 7. Nm based on microsatellite loci (below diagonal) and D-loop sequences (above diagonal) between Chinese mitten crab (E. sinensis) populations.
PopulationLHAQCSTZSH
LH 2.0002.3955.6781.969
AQ7.751 23.692infinf
CS13.0885.022 12.80014.500
TZ6.52470.8634.182 10.989
SH6.55923.9184.301inf
Table
Table 8. Neutrality tests for D-loop sequences of Chinese mitten crabs (E. sinensis).
Table 8. Neutrality tests for D-loop sequences of Chinese mitten crabs (E. sinensis).
PopulationTajima’s D Testp-ValueFu’s Fs Testp-Value
LH−0.1960.435−1.0640.154
AQ−1.0110.201−3.7090.005
CS−0.0690.603−0.7150.163
TZ−1.2600.095−0.0550.415
SH−0.5260.412−1.7160.056
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Zhou, L.; Gao, J.; Yang, Y.; Nie, Z.; Liu, K.; Xu, G. Genetic Diversity and Population Structure Analysis of Chinese Mitten Crab (Eriocheir sinensis) in the Yangtze and Liaohe Rivers. Fishes 2023, 8, 253. https://doi.org/10.3390/fishes8050253

AMA Style

Zhou L, Gao J, Yang Y, Nie Z, Liu K, Xu G. Genetic Diversity and Population Structure Analysis of Chinese Mitten Crab (Eriocheir sinensis) in the Yangtze and Liaohe Rivers. Fishes. 2023; 8(5):253. https://doi.org/10.3390/fishes8050253

Chicago/Turabian Style

Zhou, Lin, Jiancao Gao, Yanping Yang, Zhijuan Nie, Kai Liu, and Gangchun Xu. 2023. "Genetic Diversity and Population Structure Analysis of Chinese Mitten Crab (Eriocheir sinensis) in the Yangtze and Liaohe Rivers" Fishes 8, no. 5: 253. https://doi.org/10.3390/fishes8050253

APA Style

Zhou, L., Gao, J., Yang, Y., Nie, Z., Liu, K., & Xu, G. (2023). Genetic Diversity and Population Structure Analysis of Chinese Mitten Crab (Eriocheir sinensis) in the Yangtze and Liaohe Rivers. Fishes, 8(5), 253. https://doi.org/10.3390/fishes8050253

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