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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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Sarviaho K, Uimari P, Martikainen K. Signatures of positive selection after the introduction of genomic selection in the Finnish Ayrshire population. J Dairy Sci 2024; 107:4822-4832. [PMID: 38490540 DOI: 10.3168/jds.2024-24105] [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: 08/21/2023] [Accepted: 02/15/2024] [Indexed: 03/17/2024]
Abstract
The Finnish Ayrshire (FAY) belongs to the Nordic Red breeds and is characterized by high milk yield, high milk components, good fertility, and functional conformation. The FAY breeding program is based on genomic selection. Despite the benefits of selection on breeding values, autozygosity in the genome may increase due to selection, and increased autozygosity may cause inbreeding depression in selected traits. However, there is lack of studies concerning selection signatures in the FAY after genomic selection introduction. The aim of this study was to identify signatures of selection in FAY after the introduction of genomic selection. Genomic data included 45,834 SNPs. The genotyped animals were divided into 2 groups: animals born before genomic selection introduction (6,108 cows) and animals born after genomic selection introduction (47,361 cows). We identified the selection signatures using 3 complementary methods: 2 based on identification of selection signatures from runs of homozygosity (ROH) islands and one based on the decay of site-specific extended haplotype between populations at SNP sites (Rsb). In total, we identified 34 ROH islands on chromosomes 1, 3, 6, 8, 12-15, 17, 19, 22, and 26 in FAY animals born before genomic selection (between 1980 and 2011) and 30 ROH islands on chromosomes 1-3, 13-17, 22, and 25-26 in FAY animals born after genomic selection introduction (between 2015 and 2020). We additionally detected 22 ΔROH islands on chromosomes 2-3, 11, 13, 14, 16, 18, 20, and 25-26. Finally, a total of 31 Rsb regions on chromosomes 2, 3, 14, 18, 20, and 25 were identified. Based on the results, genomic selection has favored certain alleles and haplotypes on genomic regions related to traits relevant in the FAY breeding program: milk production, fertility, growth, beef production traits, and feed efficiency. Several genes related to these traits (e.g., PLA2G4A, MECR, CHUK, COX15, RICTOR, SHISA9, and SEMA4G) overlapped or partially overlapped the observed selection signature regions. The association of genotypes within these regions and their effects on traits relevant in the FAY breeding program should be studied and genetic regions undergoing selection monitored in the FAY population.
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Affiliation(s)
- Katri Sarviaho
- Department of Agricultural Sciences, University of Helsinki, Helsinki 00014, Finland.
| | - Pekka Uimari
- Department of Agricultural Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Katja Martikainen
- Department of Agricultural Sciences, University of Helsinki, Helsinki 00014, Finland
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Kambal S, Tijjani A, Ibrahim SAE, Ahmed MKA, Mwacharo JM, Hanotte O. Candidate signatures of positive selection for environmental adaptation in indigenous African cattle: A review. Anim Genet 2023; 54:689-708. [PMID: 37697736 DOI: 10.1111/age.13353] [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: 07/28/2023] [Revised: 07/28/2023] [Accepted: 08/19/2023] [Indexed: 09/13/2023]
Abstract
Environmental adaptation traits of indigenous African cattle are increasingly being investigated to respond to the need for sustainable livestock production in the context of unpredictable climatic changes. Several studies have highlighted genomic regions under positive selection probably associated with adaptation to environmental challenges (e.g. heat stress, trypanosomiasis, tick and tick-borne diseases). However, little attention has focused on pinpointing the candidate causative variant(s) controlling the traits. This review compiled information from 22 studies on signatures of positive selection in indigenous African cattle breeds to identify regions under positive selection. We highlight some key candidate genome regions and genes of relevance to the challenges of living in extreme environments (high temperature, high altitude, high infectious disease prevalence). They include candidate genes involved in biological pathways relating to innate and adaptive immunity (e.g. BoLAs, SPAG11, IL1RL2 and GFI1B), heat stress (e.g. HSPs, SOD1 and PRLH) and hypoxia responses (e.g. BDNF and INPP4A). Notably, the highest numbers of candidate regions are found on BTA3, BTA5 and BTA7. They overlap with genes playing roles in several biological functions and pathways. These include but are not limited to growth and feed intake, cell stability, protein stability and sweat gland development. This review may further guide targeted genome studies aiming to assess the importance of candidate causative mutations, within regulatory and protein-coding genome regions, to further understand the biological mechanisms underlying African cattle's unique adaption.
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Affiliation(s)
- Sumaya Kambal
- Livestock Genetics, International Livestock Research Institute, Addis Ababa, Ethiopia
- Department of Genetics and Animal Breeding, Faculty of Animal Production, University of Khartoum, Khartoum, Sudan
- Department of Bioinformatics and Biostatistics, National University, Khartoum, Sudan
| | - Abdulfatai Tijjani
- Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Addis Ababa, Ethiopia
- The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Sabah A E Ibrahim
- Department of Bioinformatics and Biostatistics, National University, Khartoum, Sudan
| | - Mohamed-Khair A Ahmed
- Department of Genetics and Animal Breeding, Faculty of Animal Production, University of Khartoum, Khartoum, Sudan
| | - Joram M Mwacharo
- Scotland's Rural College and Centre for Tropical Livestock Genetics and Health, Edinburgh, UK
- Small Ruminant Genomics, International Centre for Agricultural Research in the Dry Areas, Addis Ababa, Ethiopia
| | - Olivier Hanotte
- Livestock Genetics, International Livestock Research Institute, Addis Ababa, Ethiopia
- Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Addis Ababa, Ethiopia
- School of Life Sciences, University of Nottingham, Nottingham, UK
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Hu M, Jiang H, Lai W, Shi L, Yi W, Sun H, Chen C, Yuan B, Yan S, Zhang J. Assessing Genomic Diversity and Signatures of Selection in Chinese Red Steppe Cattle Using High-Density SNP Array. Animals (Basel) 2023; 13:ani13101717. [PMID: 37238146 DOI: 10.3390/ani13101717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/13/2023] [Accepted: 05/19/2023] [Indexed: 05/28/2023] Open
Abstract
Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.
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Affiliation(s)
- Mingyue Hu
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Hao Jiang
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Weining Lai
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Lulu Shi
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Wenfeng Yi
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Hao Sun
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Chengzhen Chen
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Bao Yuan
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Shouqing Yan
- College of Animal Science, Jilin University, Changchun 130062, China
| | - Jiabao Zhang
- College of Animal Science, Jilin University, Changchun 130062, China
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Ma J, Gao X, Li J, Gao H, Wang Z, Zhang L, Xu L, Gao H, Li H, Wang Y, Zhu B, Cai W, Wang C, Chen Y. Assessing the Genetic Background and Selection Signatures of Huaxi Cattle Using High-Density SNP Array. Animals (Basel) 2021; 11:ani11123469. [PMID: 34944246 PMCID: PMC8698132 DOI: 10.3390/ani11123469] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 11/24/2021] [Accepted: 12/02/2021] [Indexed: 11/16/2022] Open
Abstract
Huaxi cattle, a specialized beef cattle breed in China, has the characteristics of fast growth, high slaughter rate, and net meat rate, good reproductive performance, strong stress resistance, and wide adaptability. In this study, we evaluated the genetic diversity, population structure, and genetic relationships of Huaxi cattle and its ancestor populations at the genome-wide level, as well as detecting the selection signatures of Huaxi cattle. Principal component analysis (PCA) and phylogenetic analysis revealed that Huaxi cattle were obviously separated from other cattle populations. The admixture analysis showed that Huaxi cattle has distinct genetic structures among all populations at K = 4. It can be concluded that Huaxi cattle has formed its own unique genetic features. Using integrated haplotype score (iHS) and composite likelihood ratio (CLR) methods, we identified 143 and 199 potentially selected genes in Huaxi cattle, respectively, among which nine selected genes (KCNK1, PDLIM5, CPXM2, CAPN14, MIR2285D, MYOF, PKDCC, FOXN3, and EHD3) related to ion binding, muscle growth and differentiation, and immunity were detected by both methods. Our study sheds light on the unique genetic feature and phylogenetic relationship of Huaxi cattle, provides a basis for the genetic mechanism analysis of important economic traits, and guides further intensive breeding improvement of Huaxi cattle.
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Affiliation(s)
- Jun Ma
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Xue Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Zezhao Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Han Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Hongwei Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Yahui Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Bo Zhu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Wentao Cai
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
| | - Congyong Wang
- Beijing Lianyu Beef Cattle Breeding Technology Limited Company, Beijing 100193, China;
| | - Yan Chen
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (J.M.); (X.G.); (J.L.); (H.G.); (Z.W.); (L.Z.); (L.X.); (H.G.); (H.L.); (Y.W.); (B.Z.); (W.C.)
- Correspondence:
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