Genetic Diversity Analysis of the Only White-Red Deer Population in China

Ruobing Han, Shanshan Gui, Xunwu Zhao and Heping Li*

College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China.

ABSTRACT

The white-red deer population in China is composed of 28 individuals introduced from New Zealand. However, the genetic relationships between these individuals is unknown. The aim of the present study was to determine the genetic diversity and genetic relationship in the white-red deer population. We used ten microsatellite loci to genotype all 28 white-red deer individuals in China, and constructed a Neighbor-joining (NJ) tree based on genetic distances. In addition, genetic structure analysis was carried out. The results showed that a total of 67 alleles were detected, and the average number of alleles at each locus was 6.7. There was high genetic diversity but severe inbreeding in the white-red deer population, and there is no father-mother-offspring relationship or father-offspring relationship in white-red deer population. Our study provides the essential data support and reference for the conservation and sustainable development of the domestic white-red deer population in China.

Article Information

Received 29 December 2021

Revised 25 February 2022

Accepted 15 March 2022

Available online 09 June 2022

(early access)

Published 29 May 2023

Authors’ Contribution

HPL designed the experiment. SSG performed the experiment. RBH write the manuscript. HPL and XWZ revised the manuscript.

Key words

White-red deer, Genetic diversity, Microsatellite DNA, Genetic relationship, China

DOI: https://dx.doi.org/10.17582/journal.pjz/20211229081242

* Corresponding author: [email protected]

0030-9923/2023/0004-1593 $ 9.00/0

Copyright 2023 by the authors. Licensee Zoological Society of Pakistan.

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/).

Introduction

White-red deer, also known as Danish White-red deer in Europe, is a “subspecies” of red deer genetic variants (Bartos, 1992) that is only bred in very low numbers worldwide. Prior to 28 white-red deer introduced from New Zealand by Liaoning Deer Breeding Base of State Administration in April 2015, white-red deer did not occur in China. Additionally, it is well known that the white-red deer is a rare wild animal. It is not only a precious natural resource but also an essential economic resource, showing that the protection and research of white-red deer population are particularly crucial and necessary.

Microsatellite DNA marker is widely used in research of animal genetic diversity due to its unique characteristics (wide distribution, rich polymorphism, codominant inheritance, and rapid detection). At present, the application of microsatellites in cervid animals mainly includes sika deer, red deer, and black tail deer (Brinkman et al., 2010; Hu et al., 2018; Lv et al., 2014; Talbot et al., 1996). However, the research on white-red deer is still limited to describing its location and apparent characteristics, which have not been reported at the molecular level, such as the research on the genetic relationships and genetic diversity among 28 individuals in the white-red deer population.

The current study aims to explore the genetic relationship and genetic diversity of the only white-red deer population in China by microsatellite DNA marker based on feces DNA. It is of great practical significance for the conservation of wild animals to collect white-red deer fecal by non-invasive sampling method. Their genetic relationship was consequently identified. The genetic diversity analysis of the domestic white-red deer population provides novel insight into genetic information and reference for the genetic management of the white-red deer population in China.

MATERIALS AND METHODS

Sample collection

All individuals (28) in the white-red deer population were collected from Liaoning deer breeding base of the state forestry administration in China, including 16 males and 12 females. This is the only stable white-red deer population in China until now, introduced from three regions in New Zealand. To avoid repeated sampling of the same individual, we collected freshly shed excrements and recorded the collected samples immediately. Twenty-eight fecal samples were stored at -80°C until DNA extraction.

DNA extraction

DNA was extracted in accordance with the manufacturer instructions of the TIANamp Stool DNA Kit DP328. Concentration and purity of extracted DNA were evaluated on a Nano Drop 2000 spectrophotometer and by gel electrophoresis. The extracted DNA was stored at -20°C until use.

Screening of microsatellite loci and amplification

Based on the previous study (Steffen et al., 1993; Dewoody et al., 1995; Jones et al., 2000; Buchanan et al., 1994; Zhang et al., 2010), we first selected the twenty pair microsatellite primers with good polymorphism, and the information of specific primers is shown in Table I. For ensure the accuracy and reliability of the screening results, 10 μL and 25 μL PCR amplification systems were applied, respectively. The 10 μL reaction mixture included 1 μl buffer, 0.8 μl dNTP, 0.05 μl rTaq DNA polymerase, 0.25 μl of each primer, 50 ng DNA template, and adding sterilized deionized water up to a total volume of 10 μl. The 25 μL reaction mixture included 2 μl buffer, 2 μl dNTP, 0.2 μl rTaq DNA polymerase, 1 μl of each primer, 100 ng DNA template, and finally adding sterilized deionized water up to a total volume of 25 μl. Amplification program was pre-denaturation at 94°C for 5min, 35 cycles of denaturation at 94°C for 30 s, annealing at 48°C-60°C for 30 s, and extension at 72°C for 1 min. Finally, the amplification program was extension at 72 °C for 10 min. PCR amplified products were stored at 4°C.

Identification of genetic relationship

Because potential parent-offspring relationships among the 28 introduced white-red deer individuals was unknown, all individuals were used as offspring and candidate parents separately to analyze simulation of parentage 1000 times and the strict confidence was 95% as well as relaxed confidence was 80%. The higher the LOD value of candidate parents, the more likely they are to be real parents. Consequently, parentage analysis wizard was performed on 28 white-red deer individuals by Cervus 3.0 (Slate et al., 2000; Kalinowski, 2007).

Analysis of clustering

The genetic structure of white-red deer population was analyzed using STRUCTURE (Pritchard et al., 2000). Ten iterations were performed for each K value from 2 to 10. The Length of Burnin Period was 10000, followed by 10000 repeats of the MCMC algorithm. In addition, Structure Harverster was used to identify the most probably K in the white-red deer population.

 

Table I. Twenty microsatellite primer sequences.

Locus	Forward Primer	Reverse Primer	TM/°C
N	TCCAGAGAAGCAACCAATAG	GTGTGCCTTAAACAACCTGT	56
BM203	GGGTGTGACATTTTGTTCCC	CTGCTCGCCACTAGTCCTTC	54
BM848	TGGTTGGAAGGAAAACTTGG	CCTCTGCTCCTCAAGACAC	55
BM6506	GCACGTGGTAAAGAGATGGC	AGCAACTTGAGCATGGCAC	63
BM6438	TTGAGCACAGACACAGACTGG	ACTGAATGCCTCCTTTGTGC	58
BM4208	TCAGTACACTGGCCACCATG	CACTGCATGCTTTTCCAAAC	56
BM5004	TCTGGAGTGAATGTTTCTGAGG	TTGTGATGAGCACCTGAAGG	49
T123	GTTTCCTTGGCACATCTCT	CTGTCGTTGTTGTTCTGTTG	53
T156	TCTTCCTGACCTGTGTCTTG	GATGAATACCCAGTCTTGTCTG	55
T501	CTCCTCATTATTACCCTGTGAA	ACATGCTTTGACCAAGACC	53
T507	AGGCAGATGCTTCACCATC	TGTGGAGCACCTCACACAT	55
T530	GTCCTCACAGCAGCTCTATG	GCATTCTTTAGAACTCCAACTG	56
C217	GCAGGAAGGAGGAGACAGTA	GCTGGTTCGTTATCATTTAGC	56
C180	GGTGGGCATTCAGTAGA	AGGCAGAGAAGGCATTG	52
C143	AAGGAGTCTTTCAGTTTTGAGA	GGTTCTGTCTTTGCTTGTTG	53
C229	CCCTGTGGTCTAGCAAA	ATAGGCACATGCTCATAAG	52
T172	AGCATCTCCCCTTTCAACA	CTTCCCAACCCAAGTATCG	54
T193	AGTCCAAGCCTGCTAAATAA	CTGCTGTTGTCATCATTACC	53
T108	CATGTGGAGATAGGTAGACAGA	CCATTCTGAGTAGCTGATTCA	54
BM888	AGGCCATATAGGAGGCAAGCTT	CTCGGTCAGCTCAAAAGCAG	57

 

Statistical analysis

We used Excel, GeneMarkerV1.91 (Hulce et al., 2011), and MicroChecker to statistics of alleles size for each microsatellite locus. The analysis of Allele Frequency was performed using Cervus 3.0, including the calculation of many important parameters, such as the number of alleles (Na), polymorphism information content (PIC), observed heterozygosity (Ho), and expected heterozygosity (He). Meantime, the analysis of paternity inference was performed. The effective number of alleles (Ne), Allele frequency, genotype frequency, Shannon information index, Fis, Ewen-Watterson test, and Hardy-Weinberg equilibrium were calculated by POPGEN32 (Yeh et al., 1997). Finally, Population 1.2.32 was used to construct the NJ tree.

Results

Genotyping

In the current study, 12 pair microsatellite primers (BM203, BM6506, C217, T123, C180, BM5004, C143, T172, T156, T501, T507, and T193) that can amplify specific products were screened from 20 pair microsatellite primers. The results of genotyping showed that the amplification of two microsatellite loci (T501 and BM6506) was unstable and the polymorphism was low. Therefore, 10 pair microsatellite primers were screened due to their high polymorphism.

Allele frequency and genetic diversity

A total of 67 alleles were detected with allele frequency analysis, Na at each locus was 4-10, and the average number of alleles at each locus was 6.7 (Table II). The average Ne of 10 microsatellite loci in the introduced white-red deer population ranged from 3.0312 to 5.9268. The PIC of all microsatellite loci was more than 0.5, which was highly polymorphic. He of microsatellite locus in this population varied from 0.863 to 0.847, and the Ho varied from 0.071 to 0.37. The Shannon information index varied from 1.2103 to 1.9046, and the average Shannon information index was 1.6331. In addition, the average of Fis was 0.7818 (Table III).

Chi-square test was used to determine whether the genotype frequency of each microsatellite loci was consistent with Hardy-Weinberg equilibrium. Additionally, the Ewen-Watterson test was carried out. The p-value of 10 microsatellite loci was less than 0.01. It showed that the microsatellite loci of the introduced white-red deer population deviated significantly from Hardy-Weinberg equilibrium (0.01<P<0.05) (Supplementary Table SI).

The Ewen-Watterson test for neutrality equilibrium indicated that the three microsatellite loci were non-neutral sites (BM5004, T507, C180), the observed F values were below the lower limit of 95% confidence interval. The results suggested that these three loci may be affected by migration, genetic drift or selection. In addition, the remaining 7 microsatellites were neutral sites, indicating that these microsatellites loci could not be affected by the genetic structure of the white-red deer population (Supplementary Table SII).

 

Table II. The major genetic diversity parameters of the 10 loci.

Loci	Na	Ne	I	He	Ho	PIC
BM203	8	4.0165	1.6438	0.762	0.370	0.713
BM5004	7	5.6201	1.8253	0.837	0.179	0.798
T123	8	5.0744	1.7820	0.818	0.286	0.776
T156	8	4.5982	1.7515	0.797	0.071	0.755
T172	10	5.0744	1.9046	0.818	0.071	0.780
T193	5	3.5395	1.4140	0.731	0.143	0.675
T507	7	5.9268	1.8610	0.847	0.148	0.810
C143	4	3.3433	1.2922	0.714	0.143	0.650
C180	6	4.8986	1.6468	0.811	0.115	0.765
C217	4	3.0312	1.2103	0.683	0.111	0.608
Mean	6.7	4.5123	1.6331	0.7816	0.164	0.7331

 

No, number of alles; Ne, effective number of alleles; I, Shannon information index; Ho, observed heterozygosity; He, expected heterozygosity; PIC, polymorphism information content.

 

Table III. The result of Fis.

Locus	Sample size	Fis
BM203	54	0.4575
BM5004	56	0.7828
T123	56	0.6442
T156	56	0.9087
T172	56	0.9110
T193	56	0.8009
T507	54	0.8218
C143	56	0.7962
C180	52	0.8550
C217	54	0.8342
Mean	55	0.7818

 

Genetic distance and phylogenetic analysis

It can be concluded that the pairwise genetic distance among 28 white-red deer individuals ranged from 0.5289 to 2.9444, among which the distance between D33 and D26 was the farthest (2.9444), and the distance between D29 and D24 was the closest (0.5289) (Supplementary Table SIII).

The N-J tree revealed three clusters, namely A, B, and C. The number of white-red deer in A was the most (12), followed by C (10), and the number of while-red deer in B was the least (6) (Fig. 1).

 

Genetic relationship of white-red deer population

There were 12 females and 16 males in the white-red deer population. The LOD and critical Delta were calculated separately after 1000 simulations. The results showed that all LOD value were less than 0. According to the identification results of LOD and Delta, indicating that there was no father mother offspring relationship or father offspring relationship among 28 white red deer individuals.

 

Clustering in white-red deer population

We used Bayesian clustering to carry out the clustering analysis for the white-red deer population. The results of STRUCTURE showed that the most probably K was k=4, suggesting that there were four distinct groups (Fig. 2). D1, D2, D3, and D4 may have similar mixed ancestors. D7, D8, D9, and D10 may have the similar genetic structure. In addition, D24, D25, and D26 may also have similar mixture ancestors.

Discussion

The introduced white-red deer population from New Zealand to China has undoubtedly increased the species diversity of cervid animals in China. Unfortunately, the genetic relationship among 28 individuals and the genetic diversity of the white-red deer population remains unsolved. The study of genetic diversity and genetic relationships between different individuals provides a basic reference for the conservation and sustainable development of the white-red deer population.

In the present study, 10 pairs of microsatellite primers with good polymorphism were determined. There were many parameters that can be used to measure the genetic diversity of this population, including Na, Ne, Ho, He, and PIC. In addition, allele frequency can be used to estimate genetic variation. The allele difference of most significant was T172, which differs from 124 to 168 by 44bp. The gene frequency of 216 bp in the BM2003 locus is 0.3889, and that of 214 bp is only 0.0185. Meanwhile, the closer the Ne was to the Na, the more evenly alleles were distributed in this population. The average of Na (6.7) in the white-red deer population was higher than that of Ne (4.5123), proving that the alleles were unevenly distributed. This phenomenon may be caused by artificial selection or drift or new mutation.

The previous study showed that the loss of alleles could be roughly estimated by the difference between Na and Ne (Tian et al., 2010). He of 10 microsatellite loci in the white-red deer population was higher than that of Ho, and the average He (0.7816) was also much higher than that of Ho (0.164), indicating that the inbreeding of the population was serious. On the other hand, the average Fis of this white-red deer population was 0.7818. This vital parameter Fis also proved the inbreeding of this population was serious. It is well known that inbreeding was not conducive to development of white-red deer population. In summary, the results of our study showed that the inbreeding of domestic white-red deer populations was severe.

The PIC can reflect the degree of genetic variation of this population at multiple microsatellite loci. A microsatellite loci with PIC>0.5 was highly polymorphic, 0.25<PIC<0.5 was moderately polymorphic, while the microsatellite loci with PIC<0.25 was low polymorphic (Botstein et al., 1980). The PIC of most microsatellite loci in the current study was highly polymorphic (80%). Among them, the PIC of C217 and T507 were the highest and lowest, respectively. Furthermore, previous studies considered PIC>0.7 as the optimal genetic markers (Purvis and Franklin, 2015). Seven out of ten microsatellite loci in our study were optimal genetic markers, showing that the microsatellite loci screened was reasonable for studying the genetic diversity of white-red deer population. Moreover, the white-red deer population has the potential for conservation and sustainable development because of its high genetic diversity.

It is concluded that the introduced white-red deer population was deviated significantly from the Hardy-Weinberg equilibrium, which is consistent with the conclusion of previous studies. The phenomenon that rare endangered populations do not conform to the mendelian inheritance was common (Ardren, 1999). It may be artificial breeding selection has broken the Hardy-Weinberg equilibrium.

Twenty-eight white-red deer can be clustering three branches (A, B and C). This can be proved by the fact that the individuals in the white-red deer population were selected from deer farms in three regions when they were introduced from New Zealand. Besides, there was no father-mother-offspring relationships or father-offspring relationships among 28 white-red deer individuals. This is undoubted positive significance to the sustainable development of the white-red deer population in China. The results of STRUCTURE showed that the white-red deer population in China could be divided into four separate groups. We should pay attention to avoiding mating between individuals with the close relationship in the future breeding process.

In conclusion, genetic diversity plays an essential role during the species survival and evolution. The genetic diversity of the white-red deer population in China was high through microsatellite DNA marker analysis, which has a positive significance for the further sustainable development of the white-red deer population in China. Furthermore, the inbreeding in the white-red deer population was serious, and this reminds us that avoiding inbreeding could be contributed to the conservation and breeding of rare species. On the other hand, scientific feeding and management should be formulated to create conditions for the white-red deer populations to adapt the new environment. Moreover, human awareness of conserving the endangered species should be raised and excessive human interference should be avoided.

Acknowledgements

We are grateful to the financial support from the Introduction of rare white-red deer provenance and its key techniques for expanding population reproduction (2014-4-07).

Funding

The study was supported by the Introduction of rare white-red deer provenance and its key techniques for expanding population reproduction (2014-4-07).

Supplementary material

There is supplementary material associated with this article. Access the material online at: https://dx.doi.org/10.17582/journal.pjz/20211229081242

Statement of conflict of interest

The authors have declared no conflict of interest.

References

Ardren, W.R., 1999. Inheritance of 12 microsatellite loci in Oncorhynchus mykiss. J. Hered., 90: 529-536. https://doi.org/10.1093/jhered/90.5.529

Bartos, L., 1992. White red deer: The genetics of the “white” red deer coloration. Deer, 10: 20-25.

Botstein, D., White, R.L., Skolnick, M., and Davis, R.W., 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am. J. Hum. Genet., 32: 314-331.

Brinkman, T.J., Schwartz, M.K., Person, D.K., Pilgrim, K., and Hundertmark, K.J., 2010. Effects of time and rainfall on PCR success using DNA extracted from deer fecal pellets. Conserv. Genet., 11: 1547-1552. https://doi.org/10.1007/s10592-009-9928-7

Buchanan, F.C., Galloway, S.M., and Crawford, A.M., 1994. Ovine microsatellites at the OarFCB5, OarFCB19, OarFCB20, OarFCB48, OarFCB129 and OarFCB226 loci. Anim. Genet., 25: 60-60. https://doi.org/10.1111/j.1365-2052.1994.tb00418.x

Dewoody, J.A., Honeycutt, R.L., and Skow, L.C., 1995. Microsatellite markers in white-tailed deer. J. Hered., 86: 317-319. https://doi.org/10.1093/oxfordjournals.jhered.a111593

Hu, H.J., Xing, B., Yang, M., Mpemba, H., Lv, Z.H., and Zhang, M.H., 2018. Population and genetic diversity of Tibetan red deer based on fecal DNA. J. For. Res., 29: 1-6. https://doi.org/10.1007/s11676-017-0419-2

Hulce, D., Li, X., Snyderleiby, T., Johathan, and Liu. C.S., 2011. Gene marker genotyping software: Tools to increase the statistical power of DNA fragment analysis. J. biomol. Tech., 22: S35.

Jones, K.C., Levine, K.F., and Banks, J.D., 2000. DNA-based genetic markers in black-tailed nad mule deer for forensic applications. Calif. Fish Game., 86: 115-126.

Kalinowski, S.T., 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol., 16:1099-1106. https://doi.org/10.1111/j.1365-294X.2007.03089.x

Lv, S.J., Yan, Y., and Wang, X.B., 2014. Genetic diversity analysis by microsatellite markers in four captive populations of the sika deer (Cervus nippon). Biochem. Syst. Ecol., 57: 95-101. https://doi.org/10.1016/j.bse.2014.07.015

Pritchard, J.K., Stephens, M., and Donnelly, P., 2000. Inference of population structure using multilocus genotype data. Genetics, 155: 945-959. https://doi.org/10.1093/genetics/155.2.945

Purvis, W.I., and Franklin, I.R., 2005. Major genes and QTL influencing wool production and quality: A review. Genet. Sel. Evol., 37(S1): S97-S107. https://doi.org/10.1186/1297-9686-37-S1-S97

Slate, J.T., Marshall, J., and Pemberton, 2000. A retrospective assessment of the accuracy of the paternity inference program CERVUS. Mol. Ecol., 9: 801-808. https://doi.org/10.1046/j.1365-294x.2000.00930.x

Steffen, P., Eggen, A., Stranzinger, G., Fries, R., Dietz, A.B., and Womack, J.E., 1993. Isolation and mapping of polymorphic microsatellite in cattle. Anim. Genet., 24: 121-124. https://doi.org/10.1111/j.1365-2052.1993.tb00252.x

Talbot, J., Haigh, J., and Plante, Y., 1996. A parentage evaluation test in North American elk (Wapiti) using microsatellites of ovine and bovine origin. Anim. Genet., 27: 117-119. https://doi.org/10.1111/j.1365-2052.1996.tb00480.x

Tian, X.M., Zhang, M.H., Zhang, H., Yang, C.W., and Jin, Z.M., 2010. Microsatellite analysis of red deer population genetic diversity in East Forest of Wanda Mountain in Heilongjiang Province. Chin. J. Ecol., 29: 43–548.

Yeh, F.C., and Boyle, J., 1997. Popgene, the user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta.

Zhang, H., Zhang, M.H., and Luo, L.Y., 2010. Screening of microsatellite loci of red deer in the eastern forest of Wanda Mountain in Heilongjiang Province. Chin. J. Wildl., 31: 59–62.