mtDNA CR Evidence Indicates High Genetic Diversity of Captive Forest Musk Deer in Shaanxi Province, China
1
School of Ecology and Nature Conservation, Beijing Forestry University, Qinghua East Road 35, Beijing 100083, China
2
China Wildlife Conservation Association, Beijing 100714, China
*
Author to whom correspondence should be addressed.
Animals 2023, 13(13), 2191; https://doi.org/10.3390/ani13132191
Submission received: 10 April 2023
/
Revised: 1 June 2023
/
Accepted: 1 June 2023
/
Published: 4 July 2023
(This article belongs to the Section Animal Genetics and Genomics)
Abstract
:Simple Summary
Forest musk deer (Moschus berezovskii) is a species that is currently classified as endangered and found in China and Vietnam. In order to prevent their extinction, China initiated captive breeding programs in the 1950s. Maintaining the high genetic diversity of the population is a crucial factor for ensuring the sustainable and rapid growth of these captive populations. Mitochondrial DNA (mtDNA) possesses a unique lineage of matrilineal evolution, and the control region (CR) is considered to be one of the most popular molecular markers for conducting a genetic diversity analysis and determining maternal lines. In this study, we assessed the current genetic diversity status of 338 individuals from seven captive forest musk deer populations located in the Shaanxi province using mtDNA CR, and the results showed that the genetic diversity was high. We also made full use of previous mtDNA CR data clearly defining 65 haplotypes with their frequency and concluded with about 90 maternal lines. The analysis revealed no significant genetic differentiation among the populations, and the populations might not have experienced rapid population expansion. The current study represents the most comprehensive research of genetic diversity of captive forest musk deer to date, and will be helpful to preserve and enhance the genetic diversity of the captive forest musk deer populations.
Abstract
Forest musk deer (Moschus berezovskii) are endangered ruminants whose adult males secrete musk. China has been breeding forest musk deer artificially since the 1950s in an effort to restore wild populations, with Shaanxi and Sichuan provinces as the two main sites for captive breeding. Genetic diversity is a significant indicator that determines the long-term viability and status of a population, particularly for species at risk of extinction. In this study, we analyzed the current genetic makeup of seven captive forest musk deer populations in the Shaanxi province, using the mitochondrial DNA (mtDNA) control region (CR) as the molecular marker. We sequenced 604 bp of mtDNA CR, with an average content of A+T higher than G+C. We observed 111 variable sites and 39 different haplotypes from 338 sequences. The nucleotide diversity (Pi) and haplotype diversity (Hd) were 0.02887 and 0.908, respectively. Genetic differentiation between these populations was not significant, and the populations might not have experienced rapid growth. By combining our sequences with previous ones, we identified 65 unique haplotypes with 26 rare haplotypes and estimated a total of 90 haplotypes in Shaanxi province captive populations. The Shaanxi province and Sichuan province obtained 88 haplotypes, the haplotypes from the two populations were mixed together, and the two populations showed moderate genetic differentiation. Our findings suggested that captive forest musk deer populations in the Shaanxi province had high genetic diversity, with a rich founder population of about 90 maternal lines. Additionally, managers could develop genetic management plans for forest musk deer based on the haplotype database. Overall, our study will provide insights and guidelines for the conservation of genetic diversity in captive forest musk deer populations in the Shaanxi province.
1. Introduction
The process of genetic diversity ensues through the mutation and aggregation of genetic material during the evolution of a species [1]. As the genetic diversity of a species increases, its capacity for evolutionary potential is amplified, thereby augmenting its ability to cope with changes in the environment [2,3]. To successfully preserve an endangered species, it is essential to not only shield its population but also to conserve its genetic diversity for the prospects of its long-term survival [4,5].
Musk deer (Moschus spp.), indigenous to East Asia with solitary nature and high stress, are renowned for the secretion of musk by adult males. At one point, China housed the largest population of musk deer, accounting for 70% of the total population with an estimated 2.5 million wild musk deer in the 1950s [6]. Miserably, the musk deer population has dwindled significantly as their existence has been threatened due to human encroachment on their habitat and other contributing factors. Currently, they are found only in a few areas, hovering close to extinction [7].
The forest musk deer (Moschus berezovskii), one of seven musk deer species and the most widespread in China, continues to face a perilous situation, with its population listed as Endangered on the IUCN Red List [8]. To prevent the extinction of these wild populations, the Chinese government, in 1958, authoritied to commence captive breeding of musk deer in Shaanxi, Sichuan, and Anhui provinces. Over the last 60 years, China has made some strides in the artificial breeding of forest musk deer, with the total number of captive forest musk deer exceeding 30,000 [9]. However, a major concern persists as the lineage of most captive forest musk deer is ambiguous, lacking strict documentation. Inbreeding in such populations often results in a decrease in genetic diversity and a higher risk of disease. Therefore, it is paramount to assess the genetic status of captive populations and try to trace the pedigree to conserve the forest musk deer resources.
The advent of molecular marker technology has provided an effective tool for conserving the genetic diversity of species [10,11]. Mitochondrial DNA (mtDNA), the genetic material outside the nucleus, is characterized by maternal transmission and a faster rate of evolution than nuclear DNA (nDNA) [12,13,14]. In particular, its control region (CR), which has a main function related to mtDNA replication, termination, and transcription, as a non-coding region, does not participate in protein coding, so it is subjected to the least selection pressure and the fastest evolution speed [15]. mtDNA CR is generally used for the research of intra-species differentiation and is a useful molecular marker for the study of genetic diversity [16]. Alvarez et al. [17] found that the genetic background established by mtDNA CR was comparable to that in the studbooks. mtDNA CR has also been demonstrated in numerous articles to be an effective tool for maternal line reconstruction [18] or was used for the correction of dam lines [19].
Previous studies on the genetic diversity of forest musk deer based on mtDNA CR markers only focused on the comparison of the genetic diversity of various groups. Here, we introduced Chao 1, which is used to estimate richness in ecological studies, to estimate the number of all haplotypes. This research level included assessing the current genetic diversity as well as tracing the maternal lines of the captive forest musk deer in the Shaanxi province.
2. Materials and Methods
2.1. Sample Collection
We obtained feces, tissue, and blood samples from a total of 338 forest musk deer in seven captive populations: randomly sampled from Feng County (35 different farms; R, n = 35), Fumin (medium farm: more than 100 individuals; FM, n = 46), Pianzaihuang (large farm: more than 200 individuals; PZH, n = 44), Haixing (large farm; HX, n = 118), Liangdang (small farm: with fewer than 100 individuals; LD, n = 39), Hongda (medium farm; HD, n = 30), and Guanling (medium farm; GL, n = 26). Except for LD, which is situated in the Gansu province but where the forest musk deer population has been introduced from the Shaanxi province, all other populations are located in the Shaanxi province. In the process of sampling, we adhered to the principle of random sampling and did not know the genetic relationship of each population. We stored the samples in a laboratory refrigerator at a temperature of −20 °C until DNA extraction.
2.2. DNA Extraction and Amplification
The method reported by Tang et al. [20] was used to process fecal samples into cell suspensions. Subsequently, genomic DNA was extracted utilizing the DNeasy Blood/Tissue/Cell Kit (TIANGEN) and stored at −80 °C for future use.
The mtDNA CR was amplified by a polymerase chain reaction (PCR) using the primers F: 5′-CAACTAACCTCCCTAAGACTTCAAG-3′ and R: 5′-CCAAATGTATGACAGCACAGTTATG-3′. The PCR amplification volume was 25 μL, including 12.5 μL 2 × Taq PCR Master Mix (Dye), 30–50 ng DNA template, 1 μL forward primer, and 1 μL reverse primer. The conditions were performed as follows: initial denaturation at 94 °C for 5 min, followed by 34 cycles of PCR (denaturation at 94 °C for 30 s, annealing at 57 °C for 30 s, and extension at 72 °C for 1 min), and a final extension of 72 °C for 8 min. PCR products were examined by electrophoresis on a 1.0% agarose gel. All reagents and labware used are listed in Tables S1 and S2, respectively. PCR products with bands detected by electrophoresis on a 1.0% agarose gel were sent to The Beijing Genomics Institute for purification and Sanger sequencing bidirectionally.
2.3. Data Analysis
Individual mtDNA CR sequences were edited by the SeqMan Pro program in DNASTAR Lasergene version 7.1 (DNASTAR Inc., Madison WI, USA) [21] and then rechecked manually. Molecular Evolutionary Genetics Analysis version 5 (MEGA 5, Mega Limited, Auckland, New Zealand) [22] was used to align all sequences, determine the nucleotide composition, calculate the genetic distance using the Kimura 2-parameter model, and then construct a neighbor-joining (NJ) phylogenetic tree with 1000 bootstrap replicates. The variable sites, number of haplotypes, nucleotide diversity (Pi), haplotype diversity (Hd), average number of nucleotide differences (K), and mismatch distribution were determined for each population by DNA Sequence Polymorphism version 6 (DnaSP 6, Julio Rozas’ Research Group · Universitat de Barcelona, Barcelona, Spain) [23]. Statistical Estimation of Species Richness and Shared Species from Samples version 9.1.0 (EstimateS 9.1.0, Professor Robert K. Colwell, Colorado, America) [24] was applied to estimate the total haplotype richness based on the classic Chao 1 Richness Estimator (Chao-1); its 95% confidence intervals (95% CIs) were computed using 1000 permutations. A median-joining network was constructed using Population Analysis with Reticulate Trees version 1.7 (POPART 1.7, Dr. Jessica W. leigh, Dunedin, New Zealand) [25]. Genetic differentiation (Fst), analysis of molecular variance (AMOVA), Tajima’s D (reflects long-term population events), and Fu’s Fs (relatively sensitive to recent population events) statistics were carried out with Arlequin 3.5 (Swiss Institute of Bioinformatics, Lausanne, Switzerland) [26]. The level of significance was set at p < 0.05; the extremely significant level was set at p < 0.01; p > 0.05 indicates no significant difference.
2.4. Data Acquisition of mtDNA CR
In order to build the existing haplotype frequency of captive forest musk deer in the Shaanxi province and infer all haplotypes, mtDNA CR sequences from captive forest musk deer in the Shaanxi province were downloaded from NCBI, accession: JX499255-69 [27], MH047347 [28], OM100019-54 [29], KR074194-197, KR074199, KR074202, KR074205, and KR074207 [30]; in addition, seven mtDNA CR haplotype sequences were obtained in Guo’s [31] master’s thesis, and the number of occurrences for each haplotype was determined based on relevant articles. In order to find out whether the Shaanxi population and the Sichuan population are differentiated, so as to provide the basis for the subsequent provenance exchange, 112 mtDNA CR sequences from captive forest musk deer in the Sichuan province were also obtained from NCBI, accession: EU795773-881 [32], KR074200 [30], JQ409122, and MW879208.
3. Results
3.1. Genetic Diversity
Upon editing and multiple sequence alignment, the effective sequence length of mtDNA CR for 338 forest musk deer was 604 bp. The nucleotide composition was typically A+T-biased, with an average content of A+T (63.3%) higher than that of G+C (36.7%). The total number of sites, excluding those with gaps or missing data, was 597, with 7 sites containing alignment gaps or missing data. Invariable sites were 486, variable sites were 111, and the total number of mutations was 114. Singleton variable sites with two variants were 5, while parsimony informative sites with two variants were 103. There were no singleton variable sites with three variants, but there were 3 parsimony informative sites with three variants. Variable sites with four variants were absent. The Pi was 0.02887, and the K was 17.236. In total, 39 haplotypes were defined for the 338 individuals, and the Hd was 0.908. The HD population had the highest Pi, while the LD population had the lowest Pi. PZH had the highest Hd, whereas HX had the lowest Hd. There was no significant difference between Pi and HD in various populations. The information regarding haplotype variation sites is illustrated in Figure 1, while the genetic information for the seven populations is presented in Table 1.
3.2. Haplotype Analyses
We obtained a total of 65 known haplotypes, and the total haplotype richness at the sampling site, estimated using the sample-based Chao-1 estimator, is 90 (95% CI: 75–130). The range of genetic distance, according to the Kimura 2-parameter model, between each haplotype was 0.002 to 0.131, and the average genetic distance was 0.041. Table 2 shows the frequency and distribution of haplotypes. Hap8 was the most frequent haplotype, shared by 92 individuals out of 553, accounting for approximately 16.64%. Hap3 was the second most frequent haplotype, accounting for 12.48% of all individuals. In total, 26 haplotypes appeared only once and were deemed rare haplotypes. Haplotype distribution was extremely uneven in each population, with FM having individuals sharing Hap3 and Hap12, each accounting for over 30% of the population; in HX, Hap23 had a frequency of more than 20%, while Hap8 had a frequency of more than 40%; in LD, Hap3 and Hap4 accounted for more than 30%, respectively, of the total; Hap8 accounted for more than 30% each of the HD population and the GL population. The proportion of each haplotype in R and PZH was relatively balanced, without too many single haplotypes. Hap5 was exclusive to R, Hap11 and Hap13 (appeared twice) were exclusive to FM, Hap17, Hap27, and Hap28 were exclusive to PZH, and Hap34 and Hap36 were exclusive to LD.
A total of 88 haplotypes of forest musk deer were obtained by combining the existing haplotypes from Shaanxi and Sichuan provinces, and 7 haplotypes were shared between the two populations. Based on genetic distance, we constructed an NJ tree with 1000 bootstrap replicates (Figure 2). All haplotypes were classified into three distinct clades, each of which varied greatly in size and included rare haplotypes. Except for the shared haplotype, the haplotypes from the Shaanxi population and Sichuan population were not separated. Additionally, Clade Ⅰ had the largest number of haplotypes and was considered the dominant haplogroup, followed by Clade Ⅱ and then Clade Ⅲ. The median-joining network clustering results were consistent with those of the NJ tree (Figure S1).
3.3. Genetic Structure
Data from this study and the Sichuan population were used in the genetic structure study, and Table 3 shows the mean genetic distances between and within each population. The genetic distance was highest between HD and PZH, as well as HD and HX, and lowest between GL and LD. The maximum genetic distance was observed within HD, while the minimum was within LD. It was apparent that the genetic distance between HD and the other populations was large. The genetic distance between the Shaanxi and Sichuan populations was greater than that within the Shaanxi population and less than that within the Sichuan population.
Table 4 shows the Fst between each of the populations and p-values. The analysis results display that HX and FM, as well as HX and LD, were highly differentiated, with the Fst value of more than 0.15. Most of the populations showed moderate differentiation from each other, while a few populations exhibited low differentiation. Specifically, the Shaanxi and Sichuan populations demonstrated moderate differentiation from each other.
The AMOVA involved the separation of variation between populations (Va) and within populations (Vb), followed by a significance test (Table 5). The results show that 9.47% of the total variation was attributed to variation among populations, while 90.53% was attributed to variation within populations. The fixation index was 0.09468, indicating a highly significant difference. These results suggest that the majority of genetic variation in the population was from within the population itself.
3.4. Demographic History
Regarding the results of the neutrality tests, Tajima’s D and Fu’s Fs did not achieve statistical significance (Table S3), indicating that the captive forest musk deer population in the Shaanxi province did not depart from the neutral selection. The mismatch distribution curve shows a multi-peak distribution (Figure 3), which does not adhere to the model of population expansion. These suggest that none of the populations might have undergone rapid population expansion.
4. Discussion
Captive breeding followed by reintroduction is an indispensable technique to safeguard endangered species [33,34]. This methodology has been successfully implemented in preserving the Przewalski horse (Equus ferus) [35], Persian fallow deer (Dama mesopotamica) [36], and Pere David’s deer (Elaphurus davidianus) [37]. Its purpose is not only to rapidly increase the population but also to avoid inbreeding depression and ensure genetic variability over the long term [34]. Understanding the genetic status of captive forest musk deer populations will help us better protect their genetic diversity [38,39].
This was the largest sampling range research on the genetic diversity of captive forest musk deer populations in the Shaanxi province, aiming to objectively evaluate genetic diversity and the total number of haplotypes. Pi is defined as the average number of nucleotide differences at each site between randomly selected DNA sequences in a given population. Hd refers to the frequency at which two different haplotypes are randomly selected from a sample. Pi and Hd are commonly used to measure genetic diversity, with higher values indicating a greater polymorphism in the population and a more abundant genetic diversity [40]. The Pi and Hd of 338 forest musk deer in seven populations were 0.02887 and 0.908, respectively. Compared to previous studies, the Pi and Hd values were lower than those found in captive [29] and wild [41] forest musk deer populations in the Shaanxi province, as well as in Sichuan province captive forest musk deer populations [32], but higher than those of wild forest musk deer in the Sichuan province [42]. According to the study of Was and Bowen [43], a higher Pi than 0.005 and a higher Hd than 0.5 indicated a higher genetic diversity in the population. The results of this study were all higher than the standard value, which means that forest musk deer still exhibited high genetic diversity. We inferred with Chao 1 that there were 90 mtDNA CR haplotypes of captive forest musk deer in the Shaanxi province, including 90 maternal lines [44]. The reasons for the high genetic diversity of forest musk deer may be the abundant maternal lines with rich genetic resources and short breeding time. It is crucial to pay attention to the conservation of their genetic resources. For the seven populations, the ordering of Pi and Hd was not consistent. This likely relates to the increase in population number, leading to the accumulation of haplotype diversity through mutation, but insufficient time for the diversity of nucleotide sequences to accumulate [43].
We conducted the analysis of the frequency of known haplotypes; of the 65 haplotypes, 26 haplotypes were rare haplotypes. In populations with high genetic diversity, rare haplotypes are at risk of being lost when the carrier dies. Therefore, increasing the frequency of rare haplotypes in the population is crucial. One noteworthy issue is that multiple individuals share the same haplotype, except for R and PZH populations, on account of an unbalanced representation of the haplotypes affecting the genetic diversity [28]. The forest musk deer in Feng County were all classified as the R population, while the forest musk deer of population PZH were collected from multiple farms with a wide range of sources, so none of these problems occurred.
The genetic structure analysis indicated that high genetic variation exists within populations, but low genetic differentiation exists between populations [45]. With little genetic differentiation between captive populations, they can be adjusted based on the haplotype distribution of each musk deer farm. Moreover, the issue of disease transmission between different populations should be considered. According to our study and the article published by Liu et al. [46], there was no significant genetic differentiation in Shaanxi and Sichuan populations. The haplotypes of the two populations are mixed together, and they have seven shared haplotypes. However, whether to switch the provenance remains a topic for future investigation.
Tajima [47] believed that if both Tajima’s D and Fu’s Fs values are negative and the difference is statistically significant (p < 0.05), the sequence contains more change in nucleotide sites than the neutral evolutionary model, which might indicate that the population has experienced a history of expansion. With a nucleotide mismatch analysis, the mismatch distribution curve had a single peak, which accords with the theoretical distribution expected by the population expansion model [26]. In this study, Tajima’s D and Fu’s Fs did not reach statistical significance, and the mismatch distribution curve presented multiple peaks; this meant that there was no significant population expansion of forest musk deer in the Shaanxi province. This may have something to do with the habits and reproduction of forest musk deer. Forest musk deer have strong territorial behavior and are highly stressed [48]. Even after 60 years of captivity, they still maintain their original habits. Additionally, they breed once a year and give birth to one to three young per birth, mostly two. All these prevent forest musk deer from expanding in large numbers, even in captivity and conservation.
5. Conclusions
To sum up, our research aimed to evaluate the genetic diversity of seven captive forest musk deer populations in the Shaanxi province and trace maternal lines. Our findings showed that the genetic diversity was abundant and the differentiation among each population was not very high. Furthermore, the populations did not undergo a fast population expansion. We also identified about 90 maternal lines and created a haplotype database. We firmly believe that our study will aid the breeding and conservation of captive forest musk deer in the Shaanxi province.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ani13132191/s1, Figure S1: The median-joining network of mtDNA control region haplotypes of captive forest musk deer in Shaanxi population and Sichuan population; Table S1: The information of reagents used; Table S2: The information of labware used; Table S3: Tajima’s D and Fu’s Fs tests of captive forest musk deer populations in Shaanxi Province.
Author Contributions
Conceptualization, Z.W.; methodology, Z.W.; software, Z.W. and L.Y.; validation, D.H. and D.Z.; formal analysis, Z.W. and L.Y.; investigation, Z.W. and G.L.; resources, Z.W., G.L. and Y.G.; data curation, Z.W.; writing—original draft preparation, Z.W.; writing—review and editing, D.Z.; visualization, Z.W.; supervision, D.Z.; project administration, M.L. and D.Z.; funding acquisition, D.H. and D.Z. All authors have read and agreed to the published version of the manuscript.
Funding
This study was funded by the National Key R&D Program of China (2022YFC2601601), the Key R&D Project of the National Forestry and Grassland Administration (GLM [2021] 45), the Project Entrusted by Zhangzhou Pientzehuang Pharmaceutical Co., Ltd. (YC-20018), and the Beijing Forestry University Outstanding Young Talent Cultivation Project (2019JQ0318).
Institutional Review Board Statement
We confirm that the Ethics and Animal Welfare Committee of Beijing Forestry University approved our sampling procedure, with Approval No: EAWC-BJFU-2022026 and that we strictly adhered to the principles of animal ethics during the sampling process.
Informed Consent Statement
Not applicable.
Data Availability Statement
The mtDNA CR haplotype sequence data are available from the NCBI, accession: OQ718515—OQ718553.
Acknowledgments
We are very grateful to Fumin farm, Pianzaihuang farm, Haixing farm, Liangdang farm, Hongda farm, Guanling farm, and many other farms in Feng County, including Huayuan farm, Fengchun farm, Longyuxiang farm, Tingsongge farm, Kanpingyuan farm, Dajikang farm, and Shanhe farm, as well as their franchisee for their strong support of sample collection. Many thanks to Xiaobing Guo for providing the master’s thesis data.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Romiguier, J.; Gayral, P.; Ballenghien, M.; Bernard, A.; Cahais, V.; Chenuil, A.; Chiari, Y.; Dernat, R.; Duret, L.; Faivre, N.; et al. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature 2014, 515, 261–263. [Google Scholar] [CrossRef] [PubMed]
- Pauls, S.U.; Nowak, C.; Balint, M.; Pfenninger, M. The impact of global climate change on genetic diversity within populations and species. Mol. Ecol. 2013, 22, 925–946. [Google Scholar] [CrossRef] [PubMed]
- Leigh, D.M.; Hendry, A.P.; Vazquez-Dominguez, E.; Friesen, V.L. Estimated six per cent loss of genetic variation in wild populations since the industrial revolution. Evol. Appl. 2019, 12, 1505–1512. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Reed, D.H.; Frankham, R. Correlation between fitness and genetic diversity. Conserv. Biol. 2003, 17, 230–237. [Google Scholar] [CrossRef]
- Ellegren, H.; Galtier, N. Determinants of genetic diversity. Nat. Rev. Genet. 2016, 17, 422–433. [Google Scholar] [CrossRef] [Green Version]
- Wu, J.; Wang, W. The Musk Deer of China; The China Forestry Publishing House: Beijing, China, 2006. [Google Scholar]
- Sheng, H.; Liu, Z. The Musk Deer in China; The Shanghai Scientific & Technical Publishers: Shanghai, China, 2007. [Google Scholar]
- Wang, Y.; Harris, R. Moschus berezovskii (Errata Version Published in 2016). The IUCN Red List of Threatened Species 2015: E.T13894A103431781. 2015. Available online: https://dx.doi.org/10.2305/IUCN.UK.2015-4.RLTS.T13894A61976926.en (accessed on 26 March 2023).
- Zheng, C.L.; Zhao, R.H.; Meng, Z.B.; Hu, D.F.; Chen, S.K.; Liu, B.Q.; Wang, J.M. Current situation and future perspectives of musk deer farming in China. Mod. Chin. Med. 2022, 24, 1684–1692. [Google Scholar]
- Frankham, R. Challenges and opportunities of genetic approaches to biological conservation. Biol. Conserv. 2010, 143, 1919–1927. [Google Scholar] [CrossRef]
- Nadeem, M.A.; Nawaz, M.A.; Shahid, M.Q.; Dogan, Y.; Comertpay, G.; Yildiz, M.; Hatipoglu, R.; Ahmad, F.; Alsaleh, A.; Labhane, N.; et al. DNA molecular markers in plant breeding: Current status and recent advancements in genomic selection and genome editing. Biotechnol. Biotechnol. Equip. 2018, 32, 261–285. [Google Scholar] [CrossRef] [Green Version]
- Bruford, M.W.; Bradley, D.G.; Luikart, G. DNA markers reveal the complexity of livestock domestication. Nat. Rev. Genet. 2003, 4, 900–910. [Google Scholar] [CrossRef]
- Galtier, N.; Nabholz, B.; Glemin, S.; Hurst, G.D.D. Mitochondrial DNA as a marker of molecular diversity: A reappraisal. Mol. Ecol. 2009, 18, 4541–4550. [Google Scholar] [CrossRef]
- Allio, R.; Donega, S.; Galtier, N.; Nabholz, B. Large variation in the ratio of mitochondrial to nuclear mutation rate across animals: Implications for genetic diversity and the use of mitochondrial DNA as a molecular marker. Mol. Biol. Evol. 2017, 34, 2762–2772. [Google Scholar] [CrossRef] [Green Version]
- Saccone, C.; Attimonelli, M.; Sbisa, E. Structural elements highly preserved during the evolution of the D-loop-containing region in vertebrate mitochondrial DNA. J. Mol. Evol. 1987, 26, 205–211. [Google Scholar] [CrossRef] [PubMed]
- Sbisa, E.; Tanzariello, F.; Reyes, A.; Pesole, G.; Saccone, C. Mammalian mitochondrial D-loop region structural analysis: Identification of new conserved sequences and their functional and evolutionary implications. Gene 1997, 205, 125–140. [Google Scholar] [CrossRef] [PubMed]
- Alvarez, I.; Fernandez, I.; Lorenzo, L.; Payeras, L.; Cuervo, M.; Goyache, F. Founder and present maternal diversity in two endangered Spanish horse breeds assessed via pedigree and mitochondrial DNA information. J. Anim. Breed. Genet. 2012, 129, 271–279. [Google Scholar] [CrossRef]
- Giontella, A.; Cardinali, I.; Lancioni, H.; Giovannini, S.; Pieramati, C.; Silvestrelli, M.; Sarti, F.M. Mitochondrial DNA survey reveals the lack of accuracy in Maremmano horse Studbook records. Animals 2020, 10, 839. [Google Scholar] [CrossRef] [PubMed]
- Bower, M.A.; Whitten, M.; Nisbet, R.E.R.; Spencer, M.; Dominy, K.M.; Murphy, A.M.; Cassidy, R.; Barrett, E.; Hill, E.W.; Binns, M. Thoroughbred racehorse mitochondrial DNA demonstrates closer than expected links between maternal genetic history and pedigree records. J. Anim. Breed. Genet. 2013, 130, 227–235. [Google Scholar] [CrossRef] [PubMed]
- Tang, J.; Li, J.J.; Wang, B.; Suo, L.J.; Li, F.R.; Liu, W.H.; Wang, Y.; Yan, R.X. Analysis two methods for extracting DNA from musk deer feces. Acta Agric. Boreali-Occident. Sin. 2018, 27, 326–330. [Google Scholar]
- Burland, T.G. DNASTAR’s Lasergene sequence analysis software. Methods Mol. Biol. 2000, 132, 71–91. [Google Scholar]
- Tamura, K.; Peterson, D.; Peterson, N.; Stecher, G.; Nei, M.; Kumar, S. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 2011, 28, 2731–2739. [Google Scholar] [CrossRef] [Green Version]
- Rozas, J.; Ferrer-Mata, A.; Sanchez-DelBarrio, J.C.; Guirao-Rico, S.; Librado, P.; Ramos-Onsins, S.E.; Sanchez-Gracia, A. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 2017, 34, 3299–3302. [Google Scholar] [CrossRef]
- Colwell, R.K. Estimates: Statistical Estimation of Species Richness and Shared Species from Samples. Version 9.1.0. 2019. Available online: https://www.robertkcolwell.org/pages/1407-estimates (accessed on 15 May 2023).
- Leigh, J.W.; Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 2015, 6, 1110–1116. [Google Scholar] [CrossRef]
- Excoffier, L.; Lischer, H.E.L. Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 2010, 10, 564–567. [Google Scholar] [CrossRef]
- Liu, G.; Xu, C.Q.; He, L.; Zhao, S.S.; Hu, D.F. Fecal DNA analysis of mitochondrial D-Loop region sequence polymorphism in captive forest musk deer. Proc. Natl. Biogenet. Divers. Summit Forum 2012, 26–27. [Google Scholar]
- Yang, C.; Tang, J.; Bian, K.; Suo, L.J.; Yuan, H.; Wang, Y.; Huang, Y. Next generation sequencing yields the complete mitogenome of captive forest musk deer, Moschus berezovskii (Ruminantia: Moschidae). Mitochondrial DNA Part B-Resour. 2018, 3, 472–473. [Google Scholar] [CrossRef] [Green Version]
- Guo, X.B.; Huang, Z.X.; Zhang, T.X.; Ding, J.H.; Gao, Y.Y.; Fu, Y.J.; Hu, D.F.; Liu, G. Analysis of mtDNA genetic diversity and genetic structure of captive forest musk deer population. J. Beijing For. Univ. 2020, 44, 98–105. [Google Scholar]
- Cai, R.B. Genetic Diversity of MHC Genes and Mitochondrial Sequences in Captive Forest Musk Deer (Moschus berezovskii). Master’s Thesis, Beijing Forestry University, Beijing, China, 2016. [Google Scholar]
- Guo, X.B. Study on Genetic Diversity of Mitochondrial DNA Control Region in Captive Forest Musk Deer Populations in Shaanxi Province. Master’s Thesis, Beijing Forestry University, Beijing, China, 2021. [Google Scholar]
- Peng, H.; Liu, S.; Zou, F.; Zeng, B.; Yue, B. Genetic diversity of captive forest musk deer (Moschus berezovskii) inferred from the mitochondrial DNA control region. Anim. Genet. 2009, 40, 65–72. [Google Scholar] [CrossRef]
- Shan, L.; Hu, Y.B.; Zhu, L.F.; Yan, L.; Wang, C.D.; Li, D.S.; Jin, X.L.; Zhang, C.L.; Wei, F.W. Large-scale genetic survey provides insights into the captive management and reintroduction of giant pandas. Mol. Biol. Evol. 2014, 31, 2663–2671. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Frankham, R. Genetic adaptation to captivity in species conservation programs. Mol. Ecol. 2008, 17, 325–333. [Google Scholar] [CrossRef]
- Liu, G.; Shafer, A.B.A.; Zimmermann, W.; Hu, D.F.; Wang, W.T.; Chu, H.J.; Cao, J.; Zhao, C.X. Evaluating the reintroduction project of Przewalski’s horse in China using genetic and pedigree data. Biol. Conserv. 2014, 171, 288–298. [Google Scholar] [CrossRef]
- Bar-David, S.; Saltz, D.; Dayan, T. Predicting the spatial dynamics of a reintroduced population: The Persian fallow deer. Ecol. Appl. 2005, 15, 1833–1846. [Google Scholar] [CrossRef]
- Zhang, Y.Y.; Bai, J.D.; Zhu, A.N.; Chen, R.S.; Xue, D.Y.; Zhong, Z.Y.; Cheng, Z.B. Reversing extinction in China’s Pere David’s deer. Science 2021, 371, 685. [Google Scholar] [CrossRef]
- Groeneveld, L.F.; Lenstra, J.A.; Eding, H.; Toro, M.A.; Scherf, B.; Pilling, D.; Negrini, R.; Finlay, E.K.; Jianlin, H.; Groeneveld, E.; et al. Genetic diversity in farm animals—A review. Anim. Genet. 2010, 41, 6–31. [Google Scholar] [CrossRef] [Green Version]
- DeWoody, J.A.; Harder, A.M.; Mathur, S.; Willoughby, J.R. The long-standing significance of genetic diversity in conservation. Mol. Ecol. 2021, 30, 4147–4154. [Google Scholar] [CrossRef]
- Hu, Y.B.; Fan, H.Z.; Chen, Y.H.; Chang, J.; Zhan, X.J.; Wu, H.; Zhang, B.W.; Wang, M.; Zhang, W.Y.; Yang, L.; et al. Spatial patterns and conservation of genetic and phylogenetic diversity of wildlife in China. Sci. Adv. 2021, 7, 9. [Google Scholar] [CrossRef] [PubMed]
- Feng, H.; Feng, C.L.; Huang, Y.; Tang, J. Structure of mitochondrial DNA control region and genetic diversity of Moschus berezovskii populations in Shaanxi Province. Genet. Mol. Res. 2016, 15, 11. [Google Scholar] [CrossRef] [PubMed]
- Hu, D.M.; Hou, Z.Z.; Zheng, C.M.; Chen, X.; Wu, J.; Chen, L.; Chen, Q.; Yue, B.S.; Zhang, X.Y. A Genetic diversity study based on microsatellite and mitochondria of forest musk deer in the Baishuihe National Nature Reserve, Sichuan. Sichuan J. Zool. 2021, 40, 641–648. [Google Scholar]
- Was, G.; Bowen, B.W. Shallow population histories in deep evolutionary lineages of marine fishes: Insights from sardines and anchovies and lessons for conservation. J. Hered. 1998, 89, 415–426. [Google Scholar]
- Cacic, M.; Cubric-Curik, V.; Ristov, S.; Curik, I. Computational approach to utilisation of mitochondrial DNA in the verification of complex pedigree errors. Livest. Sci. 2014, 169, 42–47. [Google Scholar] [CrossRef]
- Zhao, L.; Zhang, J.; Liu, Z.J.; Funk, S.M.; Wei, F.W.; Xu, M.Q.; Li, M. Complex population genetic and demographic history of the Salangid, Neosalanx taihuensis, based on cytochrome b sequences. BMC Evol. Biol. 2008, 8, 18. [Google Scholar] [CrossRef] [Green Version]
- Liu, G.; Zhang, B.F.; Chang, J.; Hu, X.L.; Li, C.; Xu, T.T.; Liu, S.Q.; Hu, D.F. Population genomics reveals moderate genetic differentiation between populations of endangered forest musk deer located in Shaanxi and Sichuan. BMC Genom. 2022, 23, 11. [Google Scholar] [CrossRef] [PubMed]
- Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 1989, 123, 585–595. [Google Scholar] [CrossRef] [PubMed]
- Wang, W.X.; He, L.; Liu, S.Q.; Wronski, T.; Hu, D.F. Behavioral and physiological responses of forest musk deer (Moschus berezovskii) to experimental fawn manipulation. Acta Ethol. 2016, 19, 133–141. [Google Scholar] [CrossRef]
Figure 1.
The variation sites of 39 mtDNA CR haplotypes of captive forest musk deer in Shaanxi province.
Figure 1.
The variation sites of 39 mtDNA CR haplotypes of captive forest musk deer in Shaanxi province.
Figure 2.
The neighbor-joining phylogenetic tree of mtDNA control region haplotypes of captive forest musk deer in Shaanxi population and Sichuan population. Note: Blue: Shaanxi; yellow: Sichuan; purple: shared.
Figure 2.
The neighbor-joining phylogenetic tree of mtDNA control region haplotypes of captive forest musk deer in Shaanxi population and Sichuan population. Note: Blue: Shaanxi; yellow: Sichuan; purple: shared.
Figure 3.
Observed (solid lines) and expected (dotted lines) mismatch distribution for captive forest musk deer populations in Shaanxi province.
Figure 3.
Observed (solid lines) and expected (dotted lines) mismatch distribution for captive forest musk deer populations in Shaanxi province.
Table 1.
Genetic diversity parameters of seven captive forest musk deer populations in Shaanxi province.
Table 1.
Genetic diversity parameters of seven captive forest musk deer populations in Shaanxi province.
| Population | Sample Size (n) | Number of Variable Sites | Number of Haplotypes (H) | Nucleotide Diversity (Pi) | Haplotype Diversity (Hd) | Average Number of Nucleotide Differences (k) |
|---|---|---|---|---|---|---|
| R | 35 | 54 | 10 | 0.02583 | 0.892 | 15.499 |
| FM | 46 | 47 | 9 | 0.01925 | 0.794 | 11.553 |
| PZH | 44 | 70 | 24 | 0.02686 | 0.959 | 18.462 |
| HX | 118 | 61 | 14 | 0.02794 | 0.764 | 16.763 |
| LD | 39 | 56 | 14 | 0.01816 | 0.854 | 10.880 |
| HD | 30 | 84 | 7 | 0.04385 | 0.811 | 26.223 |
| GL | 26 | 51 | 12 | 0.01901 | 0.886 | 11.403 |
| Total | 338 | 111 | 39 | 0.02887 | 0.908 | 17.236 |
Table 2.
Distribution of mtDNA CR haplotype of captive forest musk deer populations in Shaanxi province.
Table 2.
Distribution of mtDNA CR haplotype of captive forest musk deer populations in Shaanxi province.
| Population | R | FM | PZH | HX | LD | HD | GL | Published | Total | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | |||||||||||
| Haplotype | |||||||||||
| Hap1 | 5 | 5 | 3 | 1 | 11 | 25 | |||||
| Hap2 | 6 | 4 | 6 | 2 | 6 | 5 | 1 | 8 | 38 | ||
| Hap3 | 5 | 15 | 2 | 5 | 9 | 2 | 2 | 29 | 69 | ||
| Hap4 | 6 | 1 | 1 | 11 | 3 | 13 | 35 | ||||
| Hap5 | 1 | 1 | |||||||||
| Hap6 | 2 | 5 | 12 | 19 | |||||||
| Hap7 | 1 | 2 | 3 | ||||||||
| Hap8 | 3 | 2 | 49 | 2 | 11 | 8 | 17 | 92 | |||
| Hap9 | 1 | 3 | 2 | 1 | 2 | 2 | 1 | 12 | |||
| Hap10 | 5 | 3 | 3 | 3 | 7 | 21 | |||||
| Hap11 | 1 | 1 | |||||||||
| Hap12 | 14 | 3 | 1 | 1 | 3 | 1 | 2 | 25 | |||
| Hap13 | 2 | 2 | |||||||||
| Hap14 | 2 | 1 | 2 | 5 | |||||||
| Hap15 | 4 | 13 | 17 | ||||||||
| Hap16 | 1 | 1 | 1 | 9 | 12 | ||||||
| Hap17 | 1 | 1 | |||||||||
| Hap18 | 1 | 1 | 2 | ||||||||
| Hap19 | 2 | 2 | 5 | 9 | |||||||
| Hap20 | 1 | 1 | 1 | 3 | |||||||
| Hap21 | 3 | 2 | 5 | ||||||||
| Hap22 | 1 | 1 | 2 | ||||||||
| Hap23 | 1 | 28 | 5 | 34 | |||||||
| Hap24 | 1 | 1 | 1 | 3 | 6 | ||||||
| Hap25 | 1 | 1 | 2 | ||||||||
| Hap26 | 2 | 2 | 4 | ||||||||
| Hap27 | 1 | 1 | |||||||||
| Hap28 | 1 | 1 | |||||||||
| Hap29 | 1 | 4 | 3 | 14 | 22 | ||||||
| Hap30 | 1 | 1 | 2 | ||||||||
| Hap31 | 4 | 4 | 8 | ||||||||
| Hap32 | 8 | 1 | 9 | ||||||||
| Hap33 | 4 | 1 | 2 | 7 | |||||||
| Hap34 | 1 | 1 | |||||||||
| Hap35 | 1 | 1 | 2 | ||||||||
| Hap36 | 1 | 1 | |||||||||
| Hap37 | 5 | 2 | 7 | ||||||||
| Hap38 | 1 | 1 | 2 | ||||||||
| Hap39 | 1 | 1 | 2 | ||||||||
| Hap40 | 5 | 5 | |||||||||
| Hap41 | 1 | 1 | |||||||||
| Hap42 | 1 | 1 | |||||||||
| Hap43 | 1 | 1 | |||||||||
| Hap44 | 1 | 1 | |||||||||
| Hap45 | 1 | 1 | |||||||||
| Hap46 | 2 | 2 | |||||||||
| Hap47 | 1 | 1 | |||||||||
| Hap48 | 2 | 2 | |||||||||
| Hap49 | 8 | 8 | |||||||||
| Hap50 | 1 | 1 | |||||||||
| Hap51 | 1 | 1 | |||||||||
| Hap52 | 1 | 1 | |||||||||
| Hap53 | 1 | 1 | |||||||||
| Hap54 | 1 | 1 | |||||||||
| Hap55 | 1 | 1 | |||||||||
| Hap56 | 2 | 2 | |||||||||
| Hap57 | 1 | 1 | |||||||||
| Hap58 | 1 | 1 | |||||||||
| Hap59 | 2 | 2 | |||||||||
| Hap60 | 1 | 1 | |||||||||
| Hap61 | 1 | 1 | |||||||||
| Hap62 | 1 | 1 | |||||||||
| Hap63 | 1 | 1 | |||||||||
| Hap64 | 1 | 1 | |||||||||
| Hap65 | 3 | 3 | |||||||||
Table 3.
The mean genetic distances between (under the diagonal) and within (on the diagonal) seven captive forest musk deer populations in Shaanxi province, as well as Shaanxi and Sichuan populations.
Table 3.
The mean genetic distances between (under the diagonal) and within (on the diagonal) seven captive forest musk deer populations in Shaanxi province, as well as Shaanxi and Sichuan populations.
| Population | R | FM | PZH | HX | LD | HD | GL | Shaanxi | Sichuan |
|---|---|---|---|---|---|---|---|---|---|
| R | 0.027 | ||||||||
| FM | 0.025 | 0.020 | |||||||
| PZH | 0.030 | 0.028 | 0.032 | ||||||
| HX | 0.031 | 0.030 | 0.032 | 0.029 | |||||
| LD | 0.023 | 0.021 | 0.029 | 0.029 | 0.019 | ||||
| HD | 0.040 | 0.039 | 0.042 | 0.042 | 0.038 | 0.047 | |||
| GL | 0.024 | 0.022 | 0.028 | 0.027 | 0.020 | 0.036 | 0.020 | ||
| Shaanxi | 0.032 | ||||||||
| Sichuan | 0.045 | 0.050 |
Table 4.
The genetic differentiation between each of the populations (under the diagonal) and p-values (above the diagonal).
Table 4.
The genetic differentiation between each of the populations (under the diagonal) and p-values (above the diagonal).
| Population | R | FM | PZH | HX | LD | HD | GL | Shaanxi | Sichuan |
|---|---|---|---|---|---|---|---|---|---|
| R | 0.00000 | 0.12613 ±0.0309 | 0.00000 | 0.08108 ±0.0286 | 0.01802 ±0.0182 | 0.12613 ±0.0364 | |||
| FM | 0.08076 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | |||
| PZH | 0.02023 | 0.08415 | 0.00000 | 0.00000 | 0.00000 | 0.00901 ±0.0091 | |||
| HX | 0.07689 | 0.16246 | 0.05156 | 0.00000 | 0.00000 | 0.00000 | |||
| LD | 0.02444 | 0.08726 | 0.10643 | 0.15678 | 0.00000 | 0.02703 ±0.0194 | |||
| HD | 0.06420 | 0.14706 | 0.05357 | 0.09365 | 0.13224 | 0.02703 ±0.0194 | |||
| GL | 0.02497 | 0.10263 | 0.06311 | 0.08097 | 0.03319 | 0.06902 | |||
| Shaanxi | 0.00000 | ||||||||
| Sichuan | 0.10404 |
Note: Bold font means p-values < 0.05.
Table 5.
AMOVA of captive forest musk deer populations in Shaanxi province.
| Source of Variation | Degrees of Freedom | Sum of Squares | Variance Components | Percentage of Variation |
|---|---|---|---|---|
| Among populations | 6 | 273.781 | 0.83116 Va | 9.47 |
| Within populations | 331 | 2630.452 | 7.94699 Vb | 90.53 |
| Total | 337 | 2904.234 | 8.77814 | |
| Fixation Index | 0.09468 (++) |
Note: (++) means p-value < 0.01.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Wang, Z.; Lu, G.; Gao, Y.; Yan, L.; Li, M.; Hu, D.; Zhang, D. mtDNA CR Evidence Indicates High Genetic Diversity of Captive Forest Musk Deer in Shaanxi Province, China. Animals 2023, 13, 2191. https://doi.org/10.3390/ani13132191
AMA Style
Wang Z, Lu G, Gao Y, Yan L, Li M, Hu D, Zhang D. mtDNA CR Evidence Indicates High Genetic Diversity of Captive Forest Musk Deer in Shaanxi Province, China. Animals. 2023; 13(13):2191. https://doi.org/10.3390/ani13132191
Chicago/Turabian StyleWang, Zhe, Guanjie Lu, Yunyun Gao, Liping Yan, Mingzhe Li, Defu Hu, and Dong Zhang. 2023. "mtDNA CR Evidence Indicates High Genetic Diversity of Captive Forest Musk Deer in Shaanxi Province, China" Animals 13, no. 13: 2191. https://doi.org/10.3390/ani13132191
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
