Genetic diversity and population structure in five Inner Mongolia cashmere goat populations using whole-genome genotyping

다국어 초록 (Multilingual Abstract)

Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future.Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations.Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations.Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.

다국어 초록 (Multilingual Abstract)

Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future.
Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations.
Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations.
Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.

참고문헌 (Reference)

• 1 Yang X, "Thoughts on current situation and development of cashmere industry in China" 45 : 84-87, 2017
• 2 Danecek P, "The variant call format and VCFtools" 27 : 2156-2158, 2011
• 3 Zheng Z, "The origin of domestication genes in goats" 6 : eaaz5216-, 2020
• 4 Zhao YH, "The genetic diversity analysis on 4 Inner Mongolian Cashmere goats" 8 : 1681-1683, 2012
• 5 Montana G, "Statistical software for gene mapping by admixture linkage disequilibrium" 8 : 393-395, 2007
• 6 Catchen J, "Stacks : an analysis tool set for population genomics" 22 : 3124-3140, 2013
• 7 Su R, "Screening the key genes of hair follicle growth cycle in Inner Mongolian Cashmere goat based on RNA sequencing" 63 : 155-164, 2020
• 8 Deniskova TE, "SNP-based genotyping provides insight into the west asian origin of russian local goats" 12 : 708740-, 2021
• 9 Crawford A, "Relationships between single nucleotide polymorphisms of antioxidant enzymes and disease" 501 : 89-103, 2012
• 10 Deniskova TE, "Population structure and genetic diversity of 25 Russian sheep breeds based on whole-genome genotyping" 50 : 29-, 2018
• 11 Purcell S, "PLINK : a tool set for whole-genome association and population-based linkage analyses" 81 : 559-575, 2007
• 12 Al-Atiyat RM, "Microsatellite based genetic diversity and population structure of three Saudi goat breeds" 130 : 90-94, 2015
• 13 Li X, "Identification of selection signals by large-scale whole-genome resequencing of cashmere goats" 7 : 15142-, 2017
• 14 Zhang M, "Genomic diversity dynamics in conserved chicken populations are revealed by genomewide SNPs" 19 : 598-, 2018
• 15 Rabiul Islam ; Xuexue Liu ; Gebremedhin Gebreselassie ; Adam Abied ; Qing Ma ; Yuehui Ma, "Genomewide association analysis reveals the genetic locus for high reproduction trait in Chinese Arbas Cashmere goat" 42 : 893-899, 2020
• 16 Guo F, "Genetic diversity, population structure, and environmental adaptation signatures of chinese coastal hard-shell mussel Mytilus coruscus revealed by whole-genome sequencing" 24 : 13641-, 2023
• 17 Wang X, "Genetic diversity, population structure and phylogenetic relationships of three indigenous pig breeds from Jiangxi Province, China, in a worldwide panel of pigs" 49 : 275-283, 2018
• 18 Machete JB, "Genetic diversity and population structure of three strains of Indigenous Tswana chickens and commercial broiler using single nucleotide polymormophic(SNP)markers" 11 : 515-531, 2021
• 19 Meseret S, "Genetic diversity and population structure of six ethiopian cattle breeds from different geographical regions using high density single nucleotide polymorphisms" 234 : 103979-, 2020
• 20 Mtileni BJ, "Genetic diversity and conservation of South African indigenous chicken populations" 128 : 209-218, 2011
• 21 Yang J, "GCTA : a tool for genome-wide complex trait analysis" 88 : 76-82, 2011
• 22 Weir BS, "Estimating f-statistics for the analysis of population structure" 38 : 1358-1370, 1984
• 23 Zhang Y, "Estimates of genetic parameters and genetic changes for fleece traits in Inner Mongolia cashmere goats" 117 : 41-46, 2014
• 24 Grover A, "Development and use of molecular markers : past and present" 36 : 290-302, 2016
• 25 Chan BKC, "Data analysis using R programming" 1082 : 47-122, 2018
• 26 Botstein D, "Construction of a genetic linkage map in man using restriction fragment length polymorphisms" 32 : 314-331, 1980
• 27 Toro MA, "Characterization and conservation of genetic diversity in subdivided populations" 360 : 1367-1378, 2005
• 28 Jung Y, "BWA-MEME : BWA-MEM emulated with a machine learning approach" 38 : 2404-2413, 2022
• 29 Danecek P, "BCFtools/csq : haplotype-aware variant consequences" 33 : 2037-2039, 2017
• 30 Wang K, "ANNOVAR : functional annotation of genetic variants from high-throughput sequencing data" 38 : e164-, 2010