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Wang R, Wang X, Qi Y, Li Y, Na Q, Yuan H, Rong Y, Ao X, Guo F, Zhang L, Liu Y, Shang F, Zhang Y, Wang Y. Genetic diversity analysis of Inner Mongolia cashmere goats (Erlangshan subtype) based on whole genome re-sequencing. BMC Genomics 2024; 25:698. [PMID: 39014331 PMCID: PMC11253418 DOI: 10.1186/s12864-024-10485-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 05/30/2024] [Indexed: 07/18/2024] Open
Abstract
BACKGROUND Inner Mongolia cashmere goat (IMCG), renowned for its superior cashmere quality, is a Chinese indigenous goat breed that has been developed through natural and artificial selection over a long period. However, recently, the genetic resources of IMCGs have been significantly threatened by the introduction of cosmopolitan goat breeds and the absence of adequate breed protection systems. RESULTS In order to assess the conservation effectiveness of IMCGs and efficiently preserve and utilize the purebred germplasm resources, this study analyzed the genetic diversity, kinship, family structure, and inbreeding of IMCGs utilizing resequencing data from 225 randomly selected individuals analyzed using the Plink (v.1.90), GCTA (v.1.94.1), and R (v.4.2.1) software. A total of 12,700,178 high-quality SNPs were selected through quality control from 34,248,064 SNP sites obtained from 225 individuals. The average minor allele frequency (MAF), polymorphic information content (PIC), and Shannon information index (SHI) were 0.253, 0.284, and 0.530, respectively. The average observed heterozygosity (Ho) and the average expected heterozygosity (He) were 0.355 and 0.351, respectively. The analysis of the identity by state distance matrix and genomic relationship matrix has shown that most individuals' genetic distance and genetic relationship are far away, and the inbreeding coefficient is low. The family structure analysis identified 10 families among the 23 rams. A total of 14,109 runs of homozygosity (ROH) were identified in the 225 individuals, with an average ROH length of 1014.547 kb. The average inbreeding coefficient, calculated from ROH, was 0.026 for the overall population and 0.027 specifically among the 23 rams, indicating a low level of inbreeding within the conserved population. CONCLUSIONS The IMCGs exhibited moderate polymorphism and a low level of kinship with inbreeding occurring among a limited number of individuals. Simultaneously, it is necessary to prevent the loss of bloodline to guarantee the perpetuation of the IMCGs' germplasm resources.
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Affiliation(s)
- Ruijun Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Xinle Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yunpeng Qi
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yanbo Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Qin Na
- Inner Mongolia Autonomous Region Agricultural and Animal Husbandry Technology Extension Center, Hohhot, 010010, China
| | - Huiping Yuan
- Bayannur Forestry and Grassland Career Development Center, Bayannur, 015006, China
| | - Youjun Rong
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Xiaofang Ao
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Furong Guo
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Lifei Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yan Liu
- College of Vocational and Technical, Inner Mongolia Agricultural University, Baotou, 014109, China
| | - Fangzheng Shang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yanjun Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China.
- Key Laboratory of Mutton Sheep Genetics and Breeding, Ministry of Agriculture, Hohhot, 010018, China.
- Key Laboratory of Goat and Sheep Genetics, Breeding and Reproduction, Inner Mongolia Autonomous Region, Hohhot, 010018, China.
- Northern Agriculture and Livestock Husbandry Technology Innovation Center, Hohhot, 010018, China.
| | - Yu Wang
- College of Veterinary Medicine, Inner Mongolia Agricultural University, Hohhot, 010018, China.
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Ma KY, Song JJ, Li DP, Wu Y, Wang CH, Liu ZL, Li TT, Ma YJ. Genomic structure analysis and construction of DNA fingerprint for four sheep populations. Animal 2024; 18:101116. [PMID: 38484632 DOI: 10.1016/j.animal.2024.101116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/16/2024] [Accepted: 02/16/2024] [Indexed: 04/20/2024] Open
Abstract
The Yongdeng Qishan sheep (QS) is a sheep population found locally in China. To gain in-depth knowledge of its population characteristics, three control groups were chosen, comprising the Lanzhou fat-tailed sheep (LFT), TAN sheep (TAN), and Minxian black fur sheep (MBF), inhabiting the nearby environments. This study genotyped a total of 120 individuals from four sheep populations: QS, LFT, TAN, and MBF. Using Specific-Locus Amplified Fragment Sequencing, we conducted genetic diversity, population structure, and selective sweep analysis, and constructed the fingerprint of each population. In total, there were 782 535 single nucleotide polymorphism (SNP) variations identified, with most being situated within regions that are intergenic or intronic. The genetic diversity analysis revealed that the QS population exhibited lower genetic diversity compared to the other three populations. Consistent results were obtained from the principal component, phylogenetic tree, and population structure analysis, indicating significant genetic differences between QS and the other three populations. However, a certain degree of differentiation was observed within the QS population. The linkage disequilibrium (LD) patterns among the four populations showed clear distinctions, with the QS group demonstrating the most rapid LD decline. Kinship analysis supported the findings of population structure, dividing the 90 QS individuals into two subgroups consisting of 23 and 67 individuals. Selective sweep analysis identified a range of genes associated with reproduction, immunity, and adaptation to high-altitude hypoxia. These genes hold potential as candidate genes for marker-assisted selection breeding. Additionally, a total of 86 523 runs of homozygosity (ROHs) were detected, showing non-uniform distribution across chromosomes, with chromosome 1 having the highest coverage percentage and chromosome 26 the lowest. In the high-frequency ROH islands, 79 candidate genes were associated with biological processes such as reproduction and fat digestion and absorption. Furthermore, a DNA fingerprint was constructed for the four populations using 349 highly polymorphic SNPs. In summary, our research delves into the genetic diversity and population structure of QS population. The construction of DNA fingerprint profiles for each population can provide valuable references for the identification of sheep breeds both domestically and internationally.
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Affiliation(s)
- Ke-Yan Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Juan-Juan Song
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Deng-Pan Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Yi Wu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Chun-Hui Wang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Zi-Long Liu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Tao-Tao Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - You-Ji Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China.
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Liu J, Sun Y, Chen Q, Wang M, Li Q, Zhou W, Cheng Y. Genetic Diversity Analysis of the Red Swamp Crayfish Procambarus clarkii in Three Cultured Populations Based on Microsatellite Markers. Animals (Basel) 2023; 13:1881. [PMID: 37889778 PMCID: PMC10251937 DOI: 10.3390/ani13111881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 05/26/2023] [Accepted: 06/01/2023] [Indexed: 10/29/2023] Open
Abstract
With the increasing scale of crayfish breeding, the self-propagation and "catch large and keep small" breeding patterns have led to serious degradation of the fry, so the selection and breeding of high-quality fry is very important. Selecting a population with a high genetic diversity as the base population for breeding can greatly improve the breeding efficiency. Fifteen microsatellite loci were used to understand the genetic structure and diversity of three Procambarus clarkii populations in Chongming, Shanghai; Gaoyou, Jiangsu; and Xuancheng, Anhui. The results indicated that the three populations were diverse and the number of alleles, observed heterozygosity, expected heterozygosity, Shannon information index, and polymorphic information content ranged from 4.8 to 6.2, 0.5567 to 0.6257, 0.6166 to 0.7086, 1.1292 to 1.3987, and 0.5446 to 0.6452, respectively. The Xuancheng population had the highest genetic diversity. The genetic differentiation coefficient and gene flow of the three populations were between 0.0553 and 0.1068 and 2.0908 and 4.2708, respectively, and there was extensive genetic exchange between the Chongming and Xuancheng populations. Analyses of molecular variance indicated that the genetic variation was mainly within the population (91.51%) and inter-population genetic variation accounted for 8.49%. The unweighted pair group method with an arithmetic mean clustering map was utilised based on the genetic distance between groups, and the results showed that the Gaoyou group was grouped alone, while the Chongming and Xuancheng groups were clustered together. The structural results indicated that the Chongming and Xuancheng groups had the same origin, although the Xuancheng group possessed a more complex genetic structure. This study indicated that all three populations had a high genetic diversity, with the Xuancheng population exhibiting the highest diversity. The results of the study provide a reference for the selection of base populations in breeding programs and confirm that the Xuancheng population in Anhui has a better genetic background. The selection of the Xuancheng population as one of the base populations for genetic breeding will be more efficient to accumulate superior traits.
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Affiliation(s)
- Jiaqing Liu
- Centre for Research on Environmental Ecology and Fish Nutrition of the Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China
- Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
- National Demonstration Centre for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China
| | - Yunfei Sun
- Centre for Research on Environmental Ecology and Fish Nutrition of the Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China
- Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
- National Demonstration Centre for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China
| | - Qianqian Chen
- Centre for Research on Environmental Ecology and Fish Nutrition of the Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China
- Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
- National Demonstration Centre for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China
| | - Miaomiao Wang
- Key Laboratory of Integrated Rice-Fish Farming, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Ministry of Agriculture and Rural Affairs, Wuxi 214081, China
- Jiangsu Provincial Aquatic Technology Extension Center, Nanjing 210036, China
| | - Qin Li
- Key Laboratory of Integrated Rice-Fish Farming, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Ministry of Agriculture and Rural Affairs, Wuxi 214081, China
- Jiangsu Provincial Aquatic Technology Extension Center, Nanjing 210036, China
| | - Wenzong Zhou
- Institute of Eco-Environmental Preservation, Shanghai Agricultural Academy of Sciences, Shanghai 201403, China
| | - Yongxu Cheng
- Centre for Research on Environmental Ecology and Fish Nutrition of the Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China
- Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
- National Demonstration Centre for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China
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Genetic Diversity Evaluation and Population Structure Analysis of Red Swamp Crayfish (Procambarus clarkii) from Lakes and Rice Fields by SSR Markers. FISHES 2022. [DOI: 10.3390/fishes7040142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The red swamp crayfish (Procambarus clarkii) is an important aquatic animal and has developed as a popular aquaculture species in China. In this study, a total of 72,839 SSR motifs were identified from transcriptional data, and 20 microsatellite markers of them were finally developed to assess the genetic diversities of seven wild populations from natural lakes and nine cultured populations from rice fields. Genetic diversity was slightly higher in the cultured populations than in the wild populations. The degree of genetic differentiation between cultured populations is slight, while a moderate to a large degree of genetic differentiation between wild populations and most of the variations occurred within individuals (79%). The analysis of cluster, principal coordinate analysis and STRUCTURE were similar, and they showed that isolation-by-distance pattern was not significant. The microsatellite markers developed in this study can not only be used for genetic monitoring of population but also provide important information for the management of breeding and cultured population in red swamp crayfish.
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