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Choudhury MP, Wang Z, Zhu M, Teng S, Yan J, Cao S, Yi G, Liu Y, Liao Y, Tang Z. Genome-Wide Detection of Copy Number Variations Associated with Miniature Features in Horses. Genes (Basel) 2023; 14:1934. [PMID: 37895283 PMCID: PMC10606273 DOI: 10.3390/genes14101934] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/10/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Copy number variations (CNVs) are crucial structural genomic variants affecting complex traits in humans and livestock animals. The current study was designed to conduct a comprehensive comparative copy number variation analysis among three breeds, Debao (DB), Baise (BS), and Warmblood (WB), with a specific focus on identifying genomic regions associated with miniature features in horses. Using whole-genome next-generation resequencing data, we identified 18,974 CNVs across 31 autosomes. Among the breeds, we found 4279 breed-specific CNV regions (CNVRs). Baise, Debao, and Warmblood displayed 2978, 986, and 895 distinct CNVRs, respectively, with 202 CNVRs shared across all three breeds. After removing duplicates, we obtained 1545 CNVRs from 26 horse genomes. Functional annotation reveals enrichment in biological functions, including antigen processing, cell metabolism, olfactory conduction, and nervous system development. Debao horses have 970 genes overlapping with CNVRs, possibly causing their small size and mountainous adaptations. We also found that the genes GHR, SOX9, and SOX11 may be responsible for the miniature features of the Debao horse by analyzing their overlapping CNVRs. Overall, this study offers valuable insights into the widespread presence of CNVs in the horse genome. The findings contribute to mapping horse CNVs and advance research on unique miniature traits observed in the Debao horse.
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Affiliation(s)
- Md. Panir Choudhury
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 518124, China; (M.P.C.); (G.Y.); (Y.L.)
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Bangladesh Livestock Research Institute, Ministry of Fisheries and Livestock, Savar, Dhaka 1341, Bangladesh
| | - Zihao Wang
- Animal Husbandry Research Institute, Guangxi Vocational University of Agriculture, Nanning 530002,China; (Z.W.); (M.Z.); (S.T.); (J.Y.); (S.C.)
| | - Min Zhu
- Animal Husbandry Research Institute, Guangxi Vocational University of Agriculture, Nanning 530002,China; (Z.W.); (M.Z.); (S.T.); (J.Y.); (S.C.)
| | - Shaohua Teng
- Animal Husbandry Research Institute, Guangxi Vocational University of Agriculture, Nanning 530002,China; (Z.W.); (M.Z.); (S.T.); (J.Y.); (S.C.)
| | - Jing Yan
- Animal Husbandry Research Institute, Guangxi Vocational University of Agriculture, Nanning 530002,China; (Z.W.); (M.Z.); (S.T.); (J.Y.); (S.C.)
| | - Shuwei Cao
- Animal Husbandry Research Institute, Guangxi Vocational University of Agriculture, Nanning 530002,China; (Z.W.); (M.Z.); (S.T.); (J.Y.); (S.C.)
| | - Guoqiang Yi
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 518124, China; (M.P.C.); (G.Y.); (Y.L.)
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yuwen Liu
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 518124, China; (M.P.C.); (G.Y.); (Y.L.)
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yuying Liao
- Guangxi Veterinary Research Institute, Nanning 530001, China
| | - Zhonglin Tang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 518124, China; (M.P.C.); (G.Y.); (Y.L.)
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-omics of MARA, Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
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Zhang Z, Peng M, Wen Y, Chai Y, Liang J, Yang P, Liu X, Li J, Huang Y, Li L, Huang W, Qi Z, Yang G, Chen F, Shi Q, Li Z, Ru B, Lei C, Wang E, Huang Y. Copy number variation of
EIF4A2
loci related to phenotypic traits in Chinese cattle. Vet Med Sci 2022; 8:2147-2156. [PMID: 36052549 PMCID: PMC9514498 DOI: 10.1002/vms3.875] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science Henan Academy of Agricultural Sciences Zhengzhou Henan People's Republic of China
| | - Mengyang Peng
- College of Animal Science and Technology Northwest A&F University Yangling Shaanxi People's Republic of China
| | - Yifan Wen
- College of Animal Science and Technology Northwest A&F University Yangling Shaanxi People's Republic of China
| | - Yanan Chai
- Institute of Animal Husbandry and Veterinary Science Henan Academy of Agricultural Sciences Zhengzhou Henan People's Republic of China
| | - Juntong Liang
- College of Animal Science and Technology Northwest A&F University Yangling Shaanxi People's Republic of China
| | - Peng Yang
- College of Animal Science and Technology Northwest A&F University Yangling Shaanxi People's Republic of China
| | - Xian Liu
- Henan Provincial Animal Husbandry General Station Zhengzhou Henan People's Republic of China
| | - Jungang Li
- Jiaxian Animal Husbandry Bureau Jiaxian Henan People's Republic of China
| | - Yajun Huang
- Jiaxian Animal Husbandry Bureau Jiaxian Henan People's Republic of China
| | - Lijuan Li
- Jiaxian Animal Husbandry Bureau Jiaxian Henan People's Republic of China
| | - Weihong Huang
- Jiaxian Animal Husbandry Bureau Jiaxian Henan People's Republic of China
| | - Zengfang Qi
- Jiaxian Animal Husbandry Bureau Jiaxian Henan People's Republic of China
| | - Guojie Yang
- Jiaxian Animal Husbandry Bureau Jiaxian Henan People's Republic of China
| | - Fuying Chen
- Institute of Animal Husbandry and Veterinary Science Henan Academy of Agricultural Sciences Zhengzhou Henan People's Republic of China
| | - Qiaoting Shi
- Institute of Animal Husbandry and Veterinary Science Henan Academy of Agricultural Sciences Zhengzhou Henan People's Republic of China
| | - Zhiming Li
- Henan Provincial Animal Husbandry General Station Zhengzhou Henan People's Republic of China
| | - Baorui Ru
- Henan Provincial Animal Husbandry General Station Zhengzhou Henan People's Republic of China
| | - Chuzhao Lei
- Institute of Animal Husbandry and Veterinary Science Henan Academy of Agricultural Sciences Zhengzhou Henan People's Republic of China
| | - Eryao Wang
- Institute of Animal Husbandry and Veterinary Science Henan Academy of Agricultural Sciences Zhengzhou Henan People's Republic of China
| | - Yongzhen Huang
- College of Animal Science and Technology Northwest A&F University Yangling Shaanxi People's Republic of China
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3
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Zhou Y, Yang L, Han X, Han J, Hu Y, Li F, Xia H, Peng L, Boschiero C, Rosen BD, Bickhart DM, Zhang S, Guo A, Van Tassell CP, Smith TPL, Yang L, Liu GE. Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history. Genome Res 2022; 32:1585-1601. [PMID: 35977842 PMCID: PMC9435747 DOI: 10.1101/gr.276550.122] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 07/21/2022] [Indexed: 02/03/2023]
Abstract
A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Lv Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaotao Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Jiazheng Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Fan Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Lingwei Peng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Derek M Bickhart
- Dairy Forage Research Center, ARS USDA, Madison, Wisconsin 53706, USA
| | - Shujun Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Aizhen Guo
- The State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Timothy P L Smith
- U.S. Meat Animal Research Center, ARS USDA, Clay Center, Nebraska 68933, USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
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4
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Wang M, Liu Y, Bi X, Ma H, Zeng G, Guo J, Guo M, Ling Y, Zhao C. Genome-Wide Detection of Copy Number Variants in Chinese Indigenous Horse Breeds and Verification of CNV-Overlapped Genes Related to Heat Adaptation of the Jinjiang Horse. Genes (Basel) 2022; 13:genes13040603. [PMID: 35456409 PMCID: PMC9033042 DOI: 10.3390/genes13040603] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/23/2022] [Accepted: 03/25/2022] [Indexed: 02/05/2023] Open
Abstract
In the present study, genome-wide CNVs were detected in a total of 301 samples from 10 Chinese indigenous horse breeds using the Illumina Equine SNP70 Bead Array, and the candidate genes related to adaptability to high temperature and humidity in Jinjiang horses were identified and validated. We determined a total of 577 CNVs ranging in size from 1.06 Kb to 2023.07 Kb on the 31 pairs of autosomes. By aggregating the overlapping CNVs for each breed, a total of 495 CNVRs were detected in the 10 Chinese horse breeds. As many as 211 breed-specific CNVRs were determined, of which 64 were found in the Jinjiang horse population. By removing repetitive CNV regions between breeds, a total of 239 CNVRs were identified in the Chinese indigenous horse breeds including 102 losses, 133 gains and 4 of both events (losses and gains in the same region), in which 131 CNVRs were novel and only detected in the present study compared with previous studies. The total detected CNVR length was 41.74 Mb, accounting for 1.83% of the total length of equine autosomal chromosomes. The coverage of CNVRs on each chromosome varied from 0.47% to 15.68%, with the highest coverage on ECA 12, but the highest number of CNVRs was detected on ECA1 and ECA24. A total of 229 genes overlapping with CNVRs were detected in the Jinjiang horse population, which is an indigenous horse breed unique to the southeastern coast of China exhibiting adaptability to high temperature and humidity. The functional annotation of these genes showed significant relation to cellular heat acclimation and immunity. The expression levels of the candidate genes were validated by heat shock treatment of various durations on fibroblasts of horses. The results show that the expression levels of HSPA1A were significantly increased among the different heat shock durations. The expression level of NFKBIA and SOCS4 declined from the beginning of heat shock to 2 h after heat shock and then showed a gradual increase until it reached the highest value at 6 h and 10 h of heat shock, respectively. Breed-specific CNVRs of Chinese indigenous horse breeds were revealed in the present study, and the results facilitate mapping CNVs on the whole genome and also provide valuable insights into the molecular mechanisms of adaptation to high temperature and humidity in the Jinjiang horse.
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Affiliation(s)
- Min Wang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (M.W.); (Y.L.); (X.B.); (Y.L.)
- Equine Center, China Agricultural University, Beijing 100193, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Beijing 100193, China
- National Engineering Laboratory for Animal Breeding, Beijing 100193, China
- Beijing Key Laboratory for Genetic Improvement of Livestock and Poultry, Beijing 100193, China
| | - Yu Liu
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (M.W.); (Y.L.); (X.B.); (Y.L.)
- Equine Center, China Agricultural University, Beijing 100193, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Beijing 100193, China
- National Engineering Laboratory for Animal Breeding, Beijing 100193, China
- Beijing Key Laboratory for Genetic Improvement of Livestock and Poultry, Beijing 100193, China
| | - Xiaokun Bi
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (M.W.); (Y.L.); (X.B.); (Y.L.)
- Equine Center, China Agricultural University, Beijing 100193, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Beijing 100193, China
- National Engineering Laboratory for Animal Breeding, Beijing 100193, China
- Beijing Key Laboratory for Genetic Improvement of Livestock and Poultry, Beijing 100193, China
| | - Hongying Ma
- Shaanxi Key Laboratory for Animal Conservation, Shaanxi Institute of Zoology, Xi’an 710032, China;
| | - Guorong Zeng
- Jinjiang Animal Husbandry and Veterinary Station, Quanzhou 362200, China; (G.Z.); (J.G.); (M.G.)
| | - Jintu Guo
- Jinjiang Animal Husbandry and Veterinary Station, Quanzhou 362200, China; (G.Z.); (J.G.); (M.G.)
| | - Minghao Guo
- Jinjiang Animal Husbandry and Veterinary Station, Quanzhou 362200, China; (G.Z.); (J.G.); (M.G.)
| | - Yao Ling
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (M.W.); (Y.L.); (X.B.); (Y.L.)
| | - Chunjiang Zhao
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (M.W.); (Y.L.); (X.B.); (Y.L.)
- Equine Center, China Agricultural University, Beijing 100193, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, Beijing 100193, China
- National Engineering Laboratory for Animal Breeding, Beijing 100193, China
- Beijing Key Laboratory for Genetic Improvement of Livestock and Poultry, Beijing 100193, China
- Correspondence:
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5
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Berton MP, de Antunes Lemos MV, Seleguim Chud TC, Bonvino Stafuzza N, Kluska S, Amorim ST, Silva Ferlin Lopes L, Cravo Pereira AS, Bickhart D, Liu G, Galvão de Albuquerque L, Baldi F. Genome-wide association study between copy number variation regions and carcass- and meat-quality traits in Nellore cattle. ANIMAL PRODUCTION SCIENCE 2021. [DOI: 10.1071/an20275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Context
Indicine breeds are the main source of beef products in tropical and subtropical regions. However, genetic improvement for carcass- and meat-quality traits in zebu cattle have been limited and genomics studies concerning structural variations that influence these traits are essential.
Aim
The aim of this study was to perform a genome-wide association study between copy number variation regions (CNVRs) and carcass- and meat quality-traits in Nellore cattle.
Methods
In total, 3794 animals, males and females included, were genotyped using a 777962 single-nucleotide polymorphism platform of BovineHD BeadChip (777k; Illumina Inc.). Of these, 1751 Nellore bulls were slaughtered at 24 months of age for further carcass beef analysis. The following traits were studied: beef tenderness, marbling, rib-eye area, backfat thickness and meat colour (lightness, redness and yellowness). The CNV detection was conducted through PennCNV software. The association analyses were performed using CNVRuler software.
Key results
Several identified genomic regions were linked to quantitative trait loci associated with fat deposition (FABP7) and lipid metabolism (PPARA; PLA2 family; BCHE), extracellular matrix (INS; COL10A1), contraction (SLC34A3; TRDN) and muscle development (CAPZP). The gene-enrichment analyses highlighted biological mechanisms directly related to the metabolism and synthesis of lipids and fatty acids.
Conclusions
The large number of potential candidate genes identified within the CNVRs, as well as the functions and pathways identified, should help better elucidate the genetic mechanisms involved in the expression of beef and carcass traits in Nellore cattle. Several CNVRs harboured genes that might have a functional impact to improve the beef and carcass traits.
Implications
The results obtained contribute to upgrade the sensorial and organoleptic attributes of Nellore cattle and make feasible the genetic improvement of carcass- and meat-quality traits.
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Yang L, Niu Q, Zhang T, Zhao G, Zhu B, Chen Y, Zhang L, Gao X, Gao H, Liu GE, Li J, Xu L. Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle. Genomics 2020; 113:812-820. [PMID: 33080318 DOI: 10.1016/j.ygeno.2020.10.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/21/2020] [Accepted: 10/05/2020] [Indexed: 11/25/2022]
Abstract
Copy number variation (CNV) represents a major source of genetic variation, which may have potentially large effects, including alternating gene regulation and dosage, as well as contributing to gene expression and risk for normal phenotypic variability. We carried out a comprehensive analysis of CNV based on whole genome sequencing in Chinese Simmental beef cattle. Totally, we found 9313 deletion and 234 duplication events, covering 147.5 Mb autosomal regions. Within them, 257 deletion events of high frequency overlapped with 193 known RefGenes. Among these genes, we observed several genes were related to economically important traits, like residual feed intake, immune responding, pregnancy rate and muscle differentiation. Using a locus-based analysis, we identified 11 deletions and 1 duplication, which were significantly associated with three traits including carcass weight, tenderloin and longissimus muscle area. Our sequencing-based study provided important insights into investigating the association of CNVs with important traits in beef cattle.
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Affiliation(s)
- Liu Yang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
| | - Qunhao Niu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Tianliu Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Guoyao Zhao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Bo Zhu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yan Chen
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lupei Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Xue Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Huijiang Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Service, Beltsville, MD 20705, USA.
| | - Junya Li
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lingyang Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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7
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Mielczarek M, Frąszczak M, Nicolazzi E, Williams JL, Szyda J. Landscape of copy number variations in Bos taurus: individual - and inter-breed variability. BMC Genomics 2018; 19:410. [PMID: 29843606 PMCID: PMC5975385 DOI: 10.1186/s12864-018-4815-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 05/22/2018] [Indexed: 11/24/2022] Open
Abstract
Background The number of studies of Copy Number Variation in cattle has increased in recent years. This has been prompted by the increased availability of data on polymorphisms and their relationship with phenotypes. In addition, livestock species are good models for some human phenotypes. In the present study, we described the landscape of CNV driven genetic variation in a large population of 146 individuals representing 13 cattle breeds, using whole genome DNA sequence. Results A highly significant variation among all individuals and within each breed was observed in the number of duplications (P < 10−15) and in the number of deletions (P < 10−15). We also observed significant differences between breeds for duplication (P = 0.01932) and deletion (P = 0.01006) counts. The same variation CNV length - inter-individual and inter-breed differences were significant for duplications (P < 10−15) and deletions (P < 10−15). Moreover, breed-specific variants were identified, with the largest proportion of breed-specific duplications (9.57%) found for Fleckvieh and breed-specific deletions found for Brown Swiss (5.00%). Such breed-specific CNVs were predominantly located in intragenic regions, however in Simmental, one deletion present in five individuals was found in the coding sequence of a novel gene ENSBTAG00000000688 on chromosome 18. In Brown Swiss, Norwegian Red and Simmental breed-specific deletions were located within KIT and MC1R genes, which are responsible for a coat colour. The functional annotation of coding regions underlying the breed-specific CNVs showed that in Norwegian Red, Guernsey, and Simmental significantly under- and overrepresented GO terms were related to chemical stimulus involved in sensory perception of smell and the KEGG pathways for olfactory transduction. In addition, specifically for the Norwegian Red breed, the dopaminergic synapse KEGG pathway was significantly enriched within deleted parts of the genome. Conclusions The CNV landscape in Bos taurus genome revealed by this study was highly complex, with inter-breed differences, but also a significant variation within breeds. The former, may explain some of the phenotypic differences among analysed breeds, and the latter contributes to within-breed variation available for selection. Electronic supplementary material The online version of this article (10.1186/s12864-018-4815-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- M Mielczarek
- Biostatistics group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland. .,National Research Institute of Animal Production, Krakowska 1, 32-083, Balice, Poland.
| | - M Frąszczak
- Biostatistics group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland
| | - E Nicolazzi
- Council on Dairy Cattle Breeding (CDCB), 4201 Northview Dr, Bowie, MD, 20716, USA
| | - J L Williams
- Davies Research Centre, University of Adelaide, School of Animal and Veterinary Sciences, Roseworthy, SA, 5371, Australia
| | - J Szyda
- Biostatistics group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland.,National Research Institute of Animal Production, Krakowska 1, 32-083, Balice, Poland
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8
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Pierce MD, Dzama K, Muchadeyi FC. Genetic Diversity of Seven Cattle Breeds Inferred Using Copy Number Variations. Front Genet 2018; 9:163. [PMID: 29868114 PMCID: PMC5962699 DOI: 10.3389/fgene.2018.00163] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 04/23/2018] [Indexed: 11/25/2022] Open
Abstract
Copy number variations (CNVs) comprise deletions, duplications, and insertions found within the genome larger than 50 bp in size. CNVs are thought to be primary role-players in breed formation and adaptation. South Africa boasts a diverse ecology with harsh environmental conditions and a broad spectrum of parasites and diseases that pose challenges to livestock production. This has led to the development of composite cattle breeds which combine the hardiness of Sanga breeds and the production potential of the Taurine breeds. The prevalence of CNVs within these respective breeds of cattle and the prevalence of CNV regions (CNVRs) in their diversity, adaptation and production is however not understood. This study therefore aimed to ascertain the prevalence, diversity, and correlations of CNVRs within cattle breeds used in South Africa. Illumina Bovine SNP50 data and PennCNV were utilized to identify CNVRs within the genome of 287 animals from seven cattle breeds representing Sanga, Taurine, Composite, and cross breeds. Three hundred and fifty six CNVRs of between 36 kb to 4.1 Mb in size were identified. The null hypothesis that one CNVR loci is independent of another was tested using the GENEPOP software. One hunded and two and seven of the CNVRs in the Taurine and Sanga/Composite cattle breeds demonstrated a significant (p ≤ 0.05) association. PANTHER overrepresentation analyses of correlated CNVRs demonstrated significant enrichment of a number of biological processes, molecular functions, cellular components, and protein classes. CNVR genetic variation between and within breed group was measured using phiPT which allows intra-individual variation to be suppressed and hence proved suitable for measuring binary CNVR presence/absence data. Estimate PhiPT within and between breed variance was 2.722 and 0.518 respectively. Pairwise population PhiPT values corresponded with breed type, with Taurine Holstein and Angus breeds demonstrating no between breed CNVR variation. Phylogenetic trees were drawn. CNVRs primarily clustered animals of the same breed type together. This study successfully identified, characterized, and analyzed 356 CNVRs within seven cattle breeds. CNVR correlations were evident, with many more correlations being present among the exotic Taurine breeds. CNVR genetic diversity of Sanga, Taurine and Composite breeds was ascertained with breed types exposed to similar selection pressures demonstrating analogous incidences of CNVRs.
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Affiliation(s)
- Magretha D Pierce
- Animal Production, Agricultural Research Council, Pretoria, South Africa
| | - Kennedy Dzama
- Department of Animal Sciences, University of Stellenbosch, Stellenbosch, South Africa
| | - Farai C Muchadeyi
- Biotechnology Platform, Agricultural Research Council, Pretoria, South Africa
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Antunes de Lemos MV, Berton MP, Ferreira de Camargo GM, Peripolli E, de Oliveira Silva RM, Ferreira Olivieri B, Cesar AS, Pereira ASC, de Albuquerque LG, de Oliveira HN, Tonhati H, Baldi F. Copy number variation regions in Nellore cattle: Evidences of environment adaptation. Livest Sci 2018. [DOI: 10.1016/j.livsci.2017.11.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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10
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Huang J, Li R, Zhang X, Huang Y, Dang R, Lan X, Chen H, Lei C. Copy number veriation regions detection in Qinchuan cattle. Livest Sci 2017. [DOI: 10.1016/j.livsci.2017.08.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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11
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Genome-Wide SNP Signal Intensity Scanning Revealed Genes Differentiating Cows with Ovarian Pathologies from Healthy Cows. SENSORS 2017; 17:s17081920. [PMID: 28825658 PMCID: PMC5580201 DOI: 10.3390/s17081920] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 07/04/2017] [Accepted: 07/06/2017] [Indexed: 01/09/2023]
Abstract
Hypoplasia and ovarian cysts are the most common ovarian pathologies in cattle. In this genome-wide study we analyzed the signal intensity of 648,315 Single Nucleotide Polymorphisms (SNPs) and identified 1338 genes differentiating cows with ovarian pathologies from healthy cows. The sample consisted of six cows presenting an ovarian pathology and six healthy cows. SNP signal intensities were measured with a genotyping process using the Axiom Genome-Wide BOS 1 SNPchip. Statistical tests for equality of variance and mean were applied to SNP intensities, and significance p-values were obtained. A Benjamini-Hochberg multiple testing correction reveled significant SNPs. Corresponding genes were identified using the Bovine Genome UMD 3.1 annotation. Principal Components Analysis (PCA) confirmed differentiation. An analysis of Copy Number Variations (CNVs), obtained from signal intensities, revealed no evidence of association between ovarian pathologies and CNVs. In addition, a haplotype frequency analysis showed no association with ovarian pathologies. Results show that SNP signal intensity, which captures not only information for base-pair genotypes elucidation, but the amount of fluorescence nucleotide synthetization produced in an enzymatic reaction, is a rich source of information that, by itself or in combination with base-pair genotypes, might be used to implement differentiation, prediction and diagnostic procedures, increasing the scope of applications for Genotyping Microarrays.
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12
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Association study and expression analysis of CYP4A11 gene copy number variation in Chinese cattle. Sci Rep 2017; 7:46599. [PMID: 28492277 PMCID: PMC5425913 DOI: 10.1038/srep46599] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 03/22/2017] [Indexed: 11/09/2022] Open
Abstract
The identification of copy number variations (CNVs) allow us to explore genomic polymorphisms. In recent years, significant progress in understanding CNVs has been made in studies of human and animals, however, association and expression studies of CNVs are still in the early stage. It was previously reported that the Cytochrome P-450 4A11 (CYP4A11) gene is located within a copy number variable region (CNVR) that encompasses quantitative trait loci (QTLs) for economic traits like meat quality and milk production. So, this study was performed to determine the presence of CYP4A11 CNV in six distinct cattle breeds, identify its relationship with growth, and explore the biological effects of gene expression. For three CYP4A11 CNV types, Normal was more frequent than Gain or Loss. Association analysis revealed a positive effect of CYP4A11 copy number on growth traits (P < 0.05). One-way analysis of variance (ANOVA) analysis revealed that more CYP4A11 copies increased the gene expression level. Moreover, overexpression of CYP4A11 in vitro revealed its effect on lipid deposit. The data provide evidence for the functional role of CYP4A11 CNV and provide the basis for future applications in cattle breeding.
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13
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In vivo and in vitro ageing results in accumulation of de novo copy number variations in bulls. Sci Rep 2017; 7:1631. [PMID: 28487564 PMCID: PMC5431667 DOI: 10.1038/s41598-017-01793-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 04/03/2017] [Indexed: 11/24/2022] Open
Abstract
We have identified de novo copy number variations (CNVs) generated in bulls as they age. Blood samples from eight bulls were collected and SNP arrayed in a prospective design over 30 months allowing us to differentiate de novo CNVs from constant CNVs that are present throughout the sampling period. Quite remarkably, the total number of CNVs doubled over the 30-month period, as we observed an almost equal number of de novo and constant CNVs (107 and 111, respectively, i.e. 49% and 51%). Twice as many de novo CNVs emerged during the second half of the sampling schedule as in the first part. It suggests a dynamic generation of de novo CNVs in the bovine genome that becomes more frequent as the age of the animal progresses. In a second experiment de novo CNVs were detected through in vitro ageing of bovine fibroblasts by sampling passage #5, #15 and #25. De novo CNVs also became more frequent, but the proportion of them was only ~25% of the total number of CNVs (21 out of 85). Temporal generation of de novo CNVs resulted in increasing genome coverage. Genes and quantitative trait loci overlapping de novo CNVs were further investigated for ageing related functions.
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14
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Ben Sassi N, González-Recio Ó, de Paz-del Río R, Rodríguez-Ramilo ST, Fernández AI. Associated effects of copy number variants on economically important traits in Spanish Holstein dairy cattle. J Dairy Sci 2016; 99:6371-6380. [DOI: 10.3168/jds.2015-10487] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Accepted: 04/15/2016] [Indexed: 11/19/2022]
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15
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Kader A, Liu X, Dong K, Song S, Pan J, Yang M, Chen X, He X, Jiang L, Ma Y. Identification of copy number variations in three Chinese horse breeds using 70K single nucleotide polymorphism BeadChip array. Anim Genet 2016; 47:560-9. [PMID: 27440410 DOI: 10.1111/age.12451] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2016] [Indexed: 02/06/2023]
Abstract
Copy number variation (CNV), an essential form of genetic variation, has been increasingly recognized as one promising genetic marker in the analysis of animal genomes. Here, we used the Equine 70K single nucleotide polymorphism genotyping array for the genome-wide detection of CNVs in 96 horses from three diverse Chinese breeds: Debao pony (DB), Mongolian horse (MG) and Yili horse (YL). A total of 287 CNVs were determined and merged into 122 CNV regions (CNVRs) ranging from 199 bp to 2344 kb in size and distributed in a heterogeneous manner on chromosomes. These CNVRs were integrated with seven existing reports to generate a composite genome-wide dataset of 1558 equine CNVRs, revealing 69 (56.6%) novel CNVRs. The majority (69.7%) of the 122 CNVRs overlapped with 438 genes, whereas 30.3% were located in intergenic regions. Most of these genes were associated with common CNVRs, which were shared by divergent horse breeds. As many as 60, 42 and 91 genes overlapping with the breed-specific ss were identified in DB, MG and YL respectively. Among these genes, FGF11, SPEM1, PPARG, CIDEB, HIVEP1 and GALR may have potential relevance to breed-specific traits. These findings provide valuable information for understanding the equine genome and facilitating association studies of economically important traits with equine CNVRs in the future.
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Affiliation(s)
- Adiljan Kader
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China.,Xinjiang Academy of Animal Science, Urumqi, Xinjiang, 83000, China
| | - Xuexue Liu
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China
| | - Kunzhe Dong
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China.,United States Department of Agriculture, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA
| | - Shen Song
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China.,Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100094, China
| | - Jianfei Pan
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China
| | - Min Yang
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China
| | - Xiaofei Chen
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China
| | - Xiaohong He
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China
| | - Lin Jiang
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China.
| | - Yuehui Ma
- The Key Laboratory for Farm Animal Genetic Resources and Utilization of Ministry of Agriculture of China, Institute of Animal Sciences (IAS), Chinese Academy of Agricultural Sciences (CAAS), No 2 Yuanmingyuan West Rd., Haidian, Beijing, 100193, China.
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da Silva VH, Regitano LCDA, Geistlinger L, Pértille F, Giachetto PF, Brassaloti RA, Morosini NS, Zimmer R, Coutinho LL. Genome-Wide Detection of CNVs and Their Association with Meat Tenderness in Nelore Cattle. PLoS One 2016; 11:e0157711. [PMID: 27348523 PMCID: PMC4922624 DOI: 10.1371/journal.pone.0157711] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 06/03/2016] [Indexed: 12/20/2022] Open
Abstract
Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina® High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing ≈6.5% of the genome. Comparing our results with previous studies revealed an overlap in ≈1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.
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Affiliation(s)
- Vinicius Henrique da Silva
- Animal Biotechnology Laboratory, Animal Science Department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
- * E-mail: (LLC); (VHS)
| | | | - Ludwig Geistlinger
- Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München (LMU), Amalienstrasse 17, 80333, München, Germany
| | - Fábio Pértille
- Animal Biotechnology Laboratory, Animal Science Department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Ricardo Augusto Brassaloti
- Animal Biotechnology Laboratory, Animal Science Department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Natália Silva Morosini
- Animal Biotechnology Laboratory, Animal Science Department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Ralf Zimmer
- Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München (LMU), Amalienstrasse 17, 80333, München, Germany
| | - Luiz Lehmann Coutinho
- Animal Biotechnology Laboratory, Animal Science Department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
- * E-mail: (LLC); (VHS)
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17
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da Silva JM, Giachetto PF, da Silva LO, Cintra LC, Paiva SR, Yamagishi MEB, Caetano AR. Genome-wide copy number variation (CNV) detection in Nelore cattle reveals highly frequent variants in genome regions harboring QTLs affecting production traits. BMC Genomics 2016; 17:454. [PMID: 27297173 PMCID: PMC4907077 DOI: 10.1186/s12864-016-2752-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2016] [Accepted: 05/19/2016] [Indexed: 11/10/2022] Open
Abstract
Background Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance. Results Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively. Conclusions Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2752-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Joaquim Manoel da Silva
- Faculdade de Ciências Agrárias, Biológicas e Sociais Aplicadas, Universidade do Estado de Mato Grosso (UNEMAT), Av. Prof Dr. Renato Figueiro Varella, CEP 78.690-000, Nova Xavantina, Mato Grosso, Brazil.,Programa de Pós-Graduação em Genética e Biologia Molecular-Instituto de Biologia, Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Poliana Fernanda Giachetto
- Embrapa Informática Agropecuária - Laboratório Multiusuário de Bioinformática (LMB), Campinas, São Paulo, Brazil
| | | | - Leandro Carrijo Cintra
- Embrapa Informática Agropecuária - Laboratório Multiusuário de Bioinformática (LMB), Campinas, São Paulo, Brazil
| | - Samuel Rezende Paiva
- Embrapa - Secretaria de Relações Internacionais, Brasília, Distrito Federal, Brazil.,Embrapa Recursos Genéticos e Biotecnologia, Brasília, Distrito Federal, Brazil.,CNPq Fellow, ᅟ, ᅟ
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18
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Jenkins GM, Goddard ME, Black MA, Brauning R, Auvray B, Dodds KG, Kijas JW, Cockett N, McEwan JC. Copy number variants in the sheep genome detected using multiple approaches. BMC Genomics 2016; 17:441. [PMID: 27277319 PMCID: PMC4898393 DOI: 10.1186/s12864-016-2754-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2015] [Accepted: 05/19/2016] [Indexed: 02/07/2023] Open
Abstract
Background Copy number variants (CNVs) are a type of polymorphism found to underlie phenotypic variation, both in humans and livestock. Most surveys of CNV in livestock have been conducted in the cattle genome, and often utilise only a single approach for the detection of copy number differences. Here we performed a study of CNV in sheep, using multiple methods to identify and characterise copy number changes. Comprehensive information from small pedigrees (trios) was collected using multiple platforms (array CGH, SNP chip and whole genome sequence data), with these data then analysed via multiple approaches to identify and verify CNVs. Results In total, 3,488 autosomal CNV regions (CNVRs) were identified in this study, which substantially builds on an initial survey of the sheep genome that identified 135 CNVRs. The average length of the identified CNVRs was 19 kb (range of 1 kb to 3.6 Mb), with shorter CNVRs being more frequent than longer CNVRs. The total length of all CNVRs was 67.6Mbps, which equates to 2.7 % of the sheep autosomes. For individuals this value ranged from 0.24 to 0.55 %, and the majority of CNVRs were identified in single animals. Rather than being uniformly distributed throughout the genome, CNVRs tended to be clustered. Application of three independent approaches for CNVR detection facilitated a comparison of validation rates. CNVs identified on the Roche-NimbleGen 2.1M CGH array generally had low validation rates with lower density arrays, while whole genome sequence data had the highest validation rate (>60 %). Conclusions This study represents the first comprehensive survey of the distribution, prevalence and characteristics of CNVR in sheep. Multiple approaches were used to detect CNV regions and it appears that the best method for verifying CNVR on a large scale involves using a combination of detection methodologies. The characteristics of the 3,488 autosomal CNV regions identified in this study are comparable to other CNV regions reported in the literature and provide a valuable and sizeable addition to the small subset of published sheep CNVs. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2754-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gemma M Jenkins
- AbacusBio Limited, 442 Moray Place, PO Box 5585, Dunedin, 9058, New Zealand.
| | - Michael E Goddard
- Victorian Department of Economic Development, Jobs, Transport and Resources, Bundoora, VIC, 3083, Australia
| | - Michael A Black
- Department of Biochemistry, University of Otago, 710 Cumberland St, Dunedin, 9054, New Zealand
| | - Rudiger Brauning
- AgResearch, Invermay Agricultural Centre, PB 50034, Mosgiel, 9053, New Zealand
| | - Benoit Auvray
- Department of Biochemistry, University of Otago, 710 Cumberland St, Dunedin, 9054, New Zealand
| | - Ken G Dodds
- AgResearch, Invermay Agricultural Centre, PB 50034, Mosgiel, 9053, New Zealand
| | - James W Kijas
- CSIRO Animal, Food and Health Sciences, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia
| | - Noelle Cockett
- Utah State University, 1435 Old Main Hill, Logan, UT, 84322-1435-1435, USA
| | - John C McEwan
- AgResearch, Invermay Agricultural Centre, PB 50034, Mosgiel, 9053, New Zealand
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Zhou Y, Utsunomiya YT, Xu L, Hay EHA, Bickhart DM, Alexandre PA, Rosen BD, Schroeder SG, Carvalheiro R, de Rezende Neves HH, Sonstegard TS, Van Tassell CP, Ferraz JBS, Fukumasu H, Garcia JF, Liu GE. Genome-wide CNV analysis reveals variants associated with growth traits in Bos indicus. BMC Genomics 2016; 17:419. [PMID: 27245577 PMCID: PMC4888316 DOI: 10.1186/s12864-016-2461-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 02/11/2016] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed). RESULTS We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894 bp to 4,855,088 bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate correction (P < 0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits. CONCLUSION This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12.
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Affiliation(s)
- Yang Zhou
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Agricultural Molecular Biology, Yangling, Shaanxi, 712100, China
| | - Yuri T Utsunomiya
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Lingyang Xu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - El Hamidi Abdel Hay
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Pamela Almeida Alexandre
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Roberto Carvalheiro
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Haroldo Henrique de Rezende Neves
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,Present address: Recombinetics, Inc., St Paul, MN, 55104, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - José Bento Sterman Ferraz
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Heidge Fukumasu
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Jose Fernando Garcia
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil. .,Departamento de Apoio, Produção e Saúde Animal, Faculdade de Medicina Veterinária de Araçatuba, UNESP - Univ Estadual Paulista, Araçatuba, São Paulo, 16050-680, Brazil. .,International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.
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Bickhart DM, Xu L, Hutchison JL, Cole JB, Null DJ, Schroeder SG, Song J, Garcia JF, Sonstegard TS, Van Tassell CP, Schnabel RD, Taylor JF, Lewin HA, Liu GE. Diversity and population-genetic properties of copy number variations and multicopy genes in cattle. DNA Res 2016; 23:253-62. [PMID: 27085184 PMCID: PMC4909312 DOI: 10.1093/dnares/dsw013] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Accepted: 02/29/2016] [Indexed: 11/14/2022] Open
Abstract
The diversity and population genetics of copy number variation (CNV) in domesticated animals are not well understood. In this study, we analysed 75 genomes of major taurine and indicine cattle breeds (including Angus, Brahman, Gir, Holstein, Jersey, Limousin, Nelore, and Romagnola), sequenced to 11-fold coverage to identify 1,853 non-redundant CNV regions. Supported by high validation rates in array comparative genomic hybridization (CGH) and qPCR experiments, these CNV regions accounted for 3.1% (87.5 Mb) of the cattle reference genome, representing a significant increase over previous estimates of the area of the genome that is copy number variable (∼2%). Further population genetics and evolutionary genomics analyses based on these CNVs revealed the population structures of the cattle taurine and indicine breeds and uncovered potential diversely selected CNVs near important functional genes, including AOX1, ASZ1, GAT, GLYAT, and KRTAP9-1. Additionally, 121 CNV gene regions were found to be either breed specific or differentially variable across breeds, such as RICTOR in dairy breeds and PNPLA3 in beef breeds. In contrast, clusters of the PRP and PAG genes were found to be duplicated in all sequenced animals, suggesting that subfunctionalization, neofunctionalization, or overdominance play roles in diversifying those fertility-related genes. These CNV results provide a new glimpse into the diverse selection histories of cattle breeds and a basis for correlating structural variation with complex traits in the future.
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Affiliation(s)
- Derek M Bickhart
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Lingyang Xu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Jana L Hutchison
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - John B Cole
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Daniel J Null
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Steven G Schroeder
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | | | - Tad S Sonstegard
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | | | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA Informatics Institute, University of Missouri, Columbia, MO, USA
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Harris A Lewin
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - George E Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
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21
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Xu L, Hou Y, Bickhart DM, Zhou Y, Hay EHA, Song J, Sonstegard TS, Van Tassell CP, Liu GE. Population-genetic properties of differentiated copy number variations in cattle. Sci Rep 2016; 6:23161. [PMID: 27005566 PMCID: PMC4804293 DOI: 10.1038/srep23161] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 02/25/2016] [Indexed: 01/24/2023] Open
Abstract
While single nucleotide polymorphism (SNP) is typically the variant of choice for population genetics, copy number variation (CNV) which comprises insertion, deletion and duplication of genomic sequence, is an informative type of genetic variation. CNVs have been shown to be both common in mammals and important for understanding the relationship between genotype and phenotype. However, CNV differentiation, selection and its population genetic properties are not well understood across diverse populations. We performed a population genetics survey based on CNVs derived from the BovineHD SNP array data of eight distinct cattle breeds. We generated high resolution results that show geographical patterns of variations and genome-wide admixture proportions within and among breeds. Similar to the previous SNP-based studies, our CNV-based results displayed a strong correlation of population structure and geographical location. By conducting three pairwise comparisons among European taurine, African taurine, and indicine groups, we further identified 78 unique CNV regions that were highly differentiated, some of which might be due to selection. These CNV regions overlapped with genes involved in traits related to parasite resistance, immunity response, body size, fertility, and milk production. Our results characterize CNV diversity among cattle populations and provide a list of lineage-differentiated CNVs.
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Affiliation(s)
- Lingyang Xu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA.,Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Yali Hou
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Yang Zhou
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Agricultural Molecular Biology, Yangling, Shaanxi, 712100, China
| | - El Hamidi Abdel Hay
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
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22
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Bongiorni S, Gruber CEM, Bueno S, Chillemi G, Ferrè F, Failla S, Moioli B, Valentini A. Transcriptomic investigation of meat tenderness in two Italian cattle breeds. Anim Genet 2016; 47:273-87. [DOI: 10.1111/age.12418] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2015] [Indexed: 12/23/2022]
Affiliation(s)
- S. Bongiorni
- Department for Innovation in Biological, Agro-food and Forest systems, DIBAF; University of Tuscia; via S. Camillo de Lelliss.n.c. Viterbo 01100 Italy
| | - C. E. M. Gruber
- Molecular Digital Diagnostics (MDD); s.r.l., via San Camillo de Lellis Viterbo 01100 Italy
| | - S. Bueno
- Cineca Supercomputing Center; via dei Tizii 6 Rome 00185 Italy
| | - G. Chillemi
- Cineca Supercomputing Center; via dei Tizii 6 Rome 00185 Italy
| | - F. Ferrè
- Cineca Supercomputing Center; via dei Tizii 6 Rome 00185 Italy
- Centre for Molecular Bioinformatics; Biology Department; University of Rome Tor Vergata; Rome Italy
| | - S. Failla
- Consiglio per la Ricerca e la sperimentazione in Agricoltura; Monterotondo Italy
| | - B. Moioli
- Consiglio per la Ricerca e la sperimentazione in Agricoltura; Monterotondo Italy
| | - A. Valentini
- Department for Innovation in Biological, Agro-food and Forest systems, DIBAF; University of Tuscia; via S. Camillo de Lelliss.n.c. Viterbo 01100 Italy
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23
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Sasaki S, Watanabe T, Nishimura S, Sugimoto Y. Genome-wide identification of copy number variation using high-density single-nucleotide polymorphism array in Japanese Black cattle. BMC Genet 2016; 17:26. [PMID: 26809925 PMCID: PMC4727303 DOI: 10.1186/s12863-016-0335-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2015] [Accepted: 01/14/2016] [Indexed: 12/12/2022] Open
Abstract
Background Copy number variation (CNV) is an important source of genetic variability associated with phenotypic variation and disease susceptibility. Comprehensive genome-wide CNV maps provide valuable information for genetic and functional studies. To identify CNV in Japanese Black cattle, we performed a genome-wide autosomal screen using genomic data from 1,481 animals analyzed with the Illumina Bovine High-Density (HD) BeadChip Array (735,293 single-nucleotide polymorphisms (SNPs) with an average marker interval of 3.4 kb on the autosomes). Results We identified a total of 861 CNV regions (CNVRs) across all autosomes, which covered 43.65 Mb of the UMD3.1 genome assembly and corresponded to 1.74 % of the 29 bovine autosomes. Overall, 35 % of the CNVRs were present at a frequency of > 1 % in 1,481 animals. The estimated lengths of CNVRs ranged from 1.1 kb to 1.4 Mb, with an average of 50.7 kb. The average number of CNVR events per animal was 35. Comparisons with previously reported cattle CNV showed that 72 % of the CNVR calls detected in this study were within or overlapped with known CNVRs. Experimentally, three CNVRs were validated using quantitative PCR, and one CNVR was validated using PCR with flanking primers for the deleted region. Out of the 861 CNVRs, 390 contained 717 Ensembl-annotated genes significantly enriched for stimulus response, cellular defense response, and immune response in the Gene Ontology (GO) database. To associate genes contained in CNVRs with phenotypes, we converted 560 bovine Ensembl gene IDs to their 438 orthologous associated mouse gene IDs, and 195 of these mouse orthologous genes were categorized into 1,627 phenotypes in the Mouse Genome Informatics (MGI) database. Conclusions We identified 861 CNVRs in 1,481 Japanese Black cattle using the Illumina BovineHD BeadChip Array. The genes contained in CNVRs were characterized using GO analysis and the mouse orthologous genes were characterized using the MGI database. The comprehensive genome-wide CNVRs map will facilitate identification of genetic variation and disease-susceptibility alleles in Japanese Black cattle. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0335-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shinji Sasaki
- National Livestock Breeding Center, Odakura, Nishigo, Fukushima, 961-8511, Japan.
| | - Toshio Watanabe
- National Livestock Breeding Center, Odakura, Nishigo, Fukushima, 961-8511, Japan.
| | - Shota Nishimura
- Shirakawa Institute of Animal Genetics, Japan Livestock Technology Association, Odakura, Nishigo, Fukushima, 961-8061, Japan.
| | - Yoshikazu Sugimoto
- Shirakawa Institute of Animal Genetics, Japan Livestock Technology Association, Odakura, Nishigo, Fukushima, 961-8061, Japan.
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24
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Wang MD, Dzama K, Rees DJG, Muchadeyi FC. Tropically adapted cattle of Africa: perspectives on potential role of copy number variations. Anim Genet 2015; 47:154-64. [DOI: 10.1111/age.12391] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/01/2015] [Indexed: 12/12/2022]
Affiliation(s)
- M. D. Wang
- Department of Animal Sciences; University of Stellenbosch; Private Bag X1 Matieland 7602 South Africa
- Biotechnology Platform; Agricultural Research Council; Private Bag X5 Onderstepoort 0110 South Africa
| | - K. Dzama
- Department of Animal Sciences; University of Stellenbosch; Private Bag X1 Matieland 7602 South Africa
| | - D. J. G. Rees
- Biotechnology Platform; Agricultural Research Council; Private Bag X5 Onderstepoort 0110 South Africa
| | - F. C. Muchadeyi
- Biotechnology Platform; Agricultural Research Council; Private Bag X5 Onderstepoort 0110 South Africa
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25
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Boussaha M, Esquerré D, Barbieri J, Djari A, Pinton A, Letaief R, Salin G, Escudié F, Roulet A, Fritz S, Samson F, Grohs C, Bernard M, Klopp C, Boichard D, Rocha D. Genome-Wide Study of Structural Variants in Bovine Holstein, Montbéliarde and Normande Dairy Breeds. PLoS One 2015; 10:e0135931. [PMID: 26317361 PMCID: PMC4552564 DOI: 10.1371/journal.pone.0135931] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 07/28/2015] [Indexed: 11/26/2022] Open
Abstract
High-throughput sequencing technologies have offered in recent years new opportunities to study genome variations. These studies have mostly focused on single nucleotide polymorphisms, small insertions or deletions and on copy number variants. Other structural variants, such as large insertions or deletions, tandem duplications, translocations, and inversions are less well-studied, despite that some have an important impact on phenotypes. In the present study, we performed a large-scale survey of structural variants in cattle. We report the identification of 6,426 putative structural variants in cattle extracted from whole-genome sequence data of 62 bulls representing the three major French dairy breeds. These genomic variants affect DNA segments greater than 50 base pairs and correspond to deletions, inversions and tandem duplications. Out of these, we identified a total of 547 deletions and 410 tandem duplications which could potentially code for CNVs. Experimental validation was carried out on 331 structural variants using a novel high-throughput genotyping method. Out of these, 255 structural variants (77%) generated good quality genotypes and 191 (75%) of them were validated. Gene content analyses in structural variant regions revealed 941 large deletions removing completely one or several genes, including 10 single-copy genes. In addition, some of the structural variants are located within quantitative trait loci for dairy traits. This study is a pan-genome assessment of genomic variations in cattle and may provide a new glimpse into the bovine genome architecture. Our results may also help to study the effects of structural variants on gene expression and consequently their effect on certain phenotypes of interest.
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Affiliation(s)
- Mekki Boussaha
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- * E-mail:
| | - Diane Esquerré
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Johanna Barbieri
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Anis Djari
- INRA, SIGENAE, UR 875, INRA Auzeville, BP 52627, Castanet-Tolosan, France
| | - Alain Pinton
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Rabia Letaief
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
| | - Gérald Salin
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Frédéric Escudié
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Alain Roulet
- INRA, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENSAT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet-Tolosan, France
- Université de Toulouse INPT ENVT, UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Toulouse, France
| | - Sébastien Fritz
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- Union Nationale des Coopératives Agricoles d’Elevage et d’Insémination Animale, Paris, France
| | - Franck Samson
- INRA, UR1077, Mathématique Informatique et Génome, Domaine de Vilvert, Jouy-en-Josas, France
| | - Cécile Grohs
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
| | - Maria Bernard
- INRA, SIGENAE, UR 875, INRA Auzeville, BP 52627, Castanet-Tolosan, France
| | - Christophe Klopp
- INRA, SIGENAE, UR 875, INRA Auzeville, BP 52627, Castanet-Tolosan, France
| | - Didier Boichard
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
| | - Dominique Rocha
- INRA, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
- AgroParisTech, UMR1313, Génétique Animale et Biologie Intégrative, Domaine de Vilvert, Jouy-en-Josas, France
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Ma Y, Zhang Q, Lu Z, Zhao X, Zhang Y. Analysis of copy number variations by SNP50 BeadChip array in Chinese sheep. Genomics 2015; 106:295-300. [PMID: 26244906 DOI: 10.1016/j.ygeno.2015.08.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 07/28/2015] [Accepted: 08/01/2015] [Indexed: 12/18/2022]
Abstract
The sheep (Ovis aries) plays a major socio-economic role in the world. Copy number variations (CNVs) are increasingly recognized as a key and potent source of genetic variation and phenotypic diversity, but little is known about the extent to which CNVs contribute to genetic variation in Chinese sheep breeds. Analyses of CNVs in the genomes of eight sheep breeds were performed using the sheep SNP50 BeadChip genotyping array. A total of 111 CNV regions (CNVRs) were obtained from 160 Chinese sheep breeds. These CNVRs covered 13.75Mb of the sheep genome sequence. A total of 22 Go terms and 17 candidate genes were obtained from the functional analysis. Ten CNVRs were selected for validation, of which 7 CNVRs were further experimentally confirmed by quantitative PCR. Four candidate genes were selected to confirm the results of the functional analysis. These results provide a resource for furthering understanding of ruminant biology, and for further improving the genetic quality of sheep breeds.
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Affiliation(s)
- Youji Ma
- College of Animal Science and Technology, Gansu Agriculture University, Lanzhou 730070, China.
| | - Quanwei Zhang
- College of Veterinary Medicine, Gansu Agriculture University, Lanzhou 730070, China
| | - Zengkui Lu
- College of Animal Science and Technology, Gansu Agriculture University, Lanzhou 730070, China
| | - Xingxu Zhao
- College of Veterinary Medicine, Gansu Agriculture University, Lanzhou 730070, China
| | - Yong Zhang
- College of Veterinary Medicine, Gansu Agriculture University, Lanzhou 730070, China
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27
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Identification of copy number variations in Qinchuan cattle using BovineHD Genotyping Beadchip array. Mol Genet Genomics 2014; 290:319-27. [DOI: 10.1007/s00438-014-0923-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2014] [Accepted: 09/15/2014] [Indexed: 12/14/2022]
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28
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Xu L, Cole JB, Bickhart DM, Hou Y, Song J, VanRaden PM, Sonstegard TS, Van Tassell CP, Liu GE. Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins. BMC Genomics 2014; 15:683. [PMID: 25128478 PMCID: PMC4152564 DOI: 10.1186/1471-2164-15-683] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Accepted: 07/31/2014] [Indexed: 12/21/2022] Open
Abstract
Background Milk production is an economically important sector of global agriculture. Much attention has been paid to the identification of quantitative trait loci (QTL) associated with milk, fat, and protein yield and the genetic and molecular mechanisms underlying them. Copy number variation (CNV) is an emerging class of variants which may be associated with complex traits. Results In this study, we performed a genome-wide association between CNVs and milk production traits in 26,362 Holstein bulls and cows. A total of 99 candidate CNVs were identified using Illumina BovineSNP50 array data, and association tests for each production trait were performed using a linear regression analysis with PCA correlation. A total of 34 CNVs on 22 chromosomes were significantly associated with at least one milk production trait after false discovery rate (FDR) correction. Some of those CNVs were located within or near known QTL for milk production traits. We further investigated the relationship between associated CNVs with neighboring SNPs. For all 82 combinations of traits and CNVs (less than 400 kb in length), we found 17 cases where CNVs directly overlapped with tag SNPs and 40 cases where CNVs were adjacent to tag SNPs. In 5 cases, CNVs located were in strong linkage disequilibrium with tag SNPs, either within or adjacent to the same haplotype block. There were an additional 20 cases where CNVs did not have a significant association with SNPs, suggesting that the effects of those CNVs were probably not captured by tag SNPs. Conclusion We conclude that combining CNV with SNP analyses reveals more genetic variations underlying milk production traits than those revealed by SNPs alone. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-683) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | | | | | | | | | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA.
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29
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Salomon-Torres R, Matukumalli LK, Van Tassell CP, Villa-Angulo C, Gonzalez-Vizcarra VM, Villa-Angulo R. High density LD-based structural variations analysis in cattle genome. PLoS One 2014; 9:e103046. [PMID: 25050984 PMCID: PMC4106904 DOI: 10.1371/journal.pone.0103046] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 06/27/2014] [Indexed: 12/13/2022] Open
Abstract
Genomic structural variations represent an important source of genetic variation in mammal genomes, thus, they are commonly related to phenotypic expressions. In this work, ∼770,000 single nucleotide polymorphism genotypes from 506 animals from 19 cattle breeds were analyzed. A simple LD-based structural variation was defined, and a genome-wide analysis was performed. After applying some quality control filters, for each breed and each chromosome we calculated the linkage disequilibrium (r2) of short range (≤100 Kb). We sorted SNP pairs by distance and obtained a set of LD means (called the expected means) using bins of 5 Kb. We identified 15,246 segments of at least 1 Kb, among the 19 breeds, consisting of sets of at least 3 adjacent SNPs so that, for each SNP, r2 within its neighbors in a 100 Kb range, to the right side of that SNP, were all bigger than, or all smaller than, the corresponding expected mean, and their P-value were significant after a Benjamini-Hochberg multiple testing correction. In addition, to account just for homogeneously distributed regions we considered only SNPs having at least 15 SNP neighbors within 100 Kb. We defined such segments as structural variations. By grouping all variations across all animals in the sample we defined 9,146 regions, involving a total of 53,137 SNPs; representing the 6.40% (160.98 Mb) from the bovine genome. The identified structural variations covered 3,109 genes. Clustering analysis showed the relatedness of breeds given the geographic region in which they are evolving. In summary, we present an analysis of structural variations based on the deviation of the expected short range LD between SNPs in the bovine genome. With an intuitive and simple definition based only on SNPs data it was possible to discern closeness of breeds due to grouping by geographic region in which they are evolving.
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Affiliation(s)
- Ricardo Salomon-Torres
- Laboratory of Bioinformatics and Biofotonics, Engineering Institute, Autonomous University of Baja California, Baja California, Mexico
- * E-mail:
| | - Lakshmi K. Matukumalli
- Animal Breeding, Genetics and Genomics at USDA, National Institute of Food and Agriculture (NIFA), Washington, District of Columbia, United States of America
| | - Curtis P. Van Tassell
- USDA-ARS, Bovine Functional Genomics Laboratories, Beltsville, Maryland, United States of America
| | - Carlos Villa-Angulo
- Laboratory of Bioinformatics and Biofotonics, Engineering Institute, Autonomous University of Baja California, Baja California, Mexico
| | | | - Rafael Villa-Angulo
- Laboratory of Bioinformatics and Biofotonics, Engineering Institute, Autonomous University of Baja California, Baja California, Mexico
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Xu L, Hou Y, Bickhart DM, Song J, Van Tassell CP, Sonstegard TS, Liu GE. A genome-wide survey reveals a deletion polymorphism associated with resistance to gastrointestinal nematodes in Angus cattle. Funct Integr Genomics 2014; 14:333-9. [PMID: 24718732 DOI: 10.1007/s10142-014-0371-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2013] [Revised: 03/26/2014] [Accepted: 03/27/2014] [Indexed: 01/17/2023]
Abstract
Gastrointestinal (GI) nematode infections are a worldwide threat to human health and animal production. In this study, we performed a genome-wide association study between copy number variations (CNVs) and resistance to GI nematodes in an Angus cattle population. Using a linear regression analysis, we identified one deletion CNV which reaches genome-wide significance after Bonferroni correction. With multiple mapped human olfactory receptor genes but no annotated bovine genes in the region, this significantly associated CNV displays high population frequencies (58.26 %) with a length of 104.8 kb on chr7. We further investigated the linkage disequilibrium (LD) relationships between this CNV and its nearby single nucleotide polymorphisms (SNPs) and genes. The underlining haplotype blocks contain immune-related genes such as ZNF496 and NLRP3. As this CNV co-segregates with linked SNPs and associated genes, we suspect that it could contribute to the detected variations in gene expression and thus differences in host parasite resistance.
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Affiliation(s)
- Lingyang Xu
- GEL: Bovine Functional Genomics Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
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Bickhart DM, Liu GE. The challenges and importance of structural variation detection in livestock. Front Genet 2014; 5:37. [PMID: 24600474 PMCID: PMC3927395 DOI: 10.3389/fgene.2014.00037] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2013] [Accepted: 01/31/2014] [Indexed: 01/25/2023] Open
Abstract
Recent studies in humans and other model organisms have demonstrated that structural variants (SVs) comprise a substantial proportion of variation among individuals of each species. Many of these variants have been linked to debilitating diseases in humans, thereby cementing the importance of refining methods for their detection. Despite progress in the field, reliable detection of SVs still remains a problem even for human subjects. Many of the underlying problems that make SVs difficult to detect in humans are amplified in livestock species, whose lower quality genome assemblies and incomplete gene annotation can often give rise to false positive SV discoveries. Regardless of the challenges, SV detection is just as important for livestock researchers as it is for human researchers, given that several productive traits and diseases have been linked to copy number variations (CNVs) in cattle, sheep, and pig. Already, there is evidence that many beneficial SVs have been artificially selected in livestock such as a duplication of the agouti signaling protein gene that causes white coat color in sheep. In this review, we will list current SV and CNV discoveries in livestock and discuss the problems that hinder routine discovery and tracking of these polymorphisms. We will also discuss the impacts of selective breeding on CNV and SV frequencies and mention how SV genotyping could be used in the future to improve genetic selection.
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Affiliation(s)
- Derek M Bickhart
- Animal Improvement Programs Laboratory, United States Department of Agriculture-Agricultural Research Service Beltsville, MD, USA
| | - George E Liu
- Bovine Functional Genomics Laboratory, United States Department of Agriculture-Agricultural Research Service Beltsville, MD, USA
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Copy Number Variation in Chickens: A Review and Future Prospects. MICROARRAYS 2014; 3:24-38. [PMID: 27605028 PMCID: PMC5003453 DOI: 10.3390/microarrays3010024] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/15/2013] [Revised: 01/22/2014] [Accepted: 01/23/2014] [Indexed: 12/19/2022]
Abstract
DNA sequence variations include nucleotide substitution, deletion, insertion, translocation and inversion. Deletion or insertion of a large DNA segment in the genome, referred to as copy number variation (CNV), has caught the attention of many researchers recently. It is believed that CNVs contribute significantly to genome variability, and thus contribute to phenotypic variability. In chickens, genome-wide surveys with array comparative genome hybridization (aCGH), SNP chip detection or whole genome sequencing have revealed a large number of CNVs. A large portion of chicken CNVs involves protein coding or regulatory sequences. A few CNVs have been demonstrated to be the determinant factors for single gene traits, such as late-feathering, pea-comb and dermal hyperpigmentation. The phenotypic effects of the majority of chicken CNVs are to be delineated.
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McDaneld TG, Kuehn LA, Thomas MG, Pollak EJ, Keele JW. Deletion on chromosome 5 associated with decreased reproductive efficiency in female cattle. J Anim Sci 2014; 92:1378-84. [PMID: 24492568 DOI: 10.2527/jas.2013-6821] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Reproductive efficiency is arguably the most economically important trait in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed per cow exposed to breeding. Identification of variation in the genome with predictive merit for reproductive success would facilitate accurate prediction of daughter pregnancy rate in sires enabling effective selection of bulls producing daughters with improved fertility. Copy number variation (CNV) is one form of structural variation that results in abnormal copies of DNA in the genome. Our lab previously reported a region between 25 and 70 Mb on chromosome 5 associated with reproductive efficiency. To further evaluate this region for genomic variations such as CNV, we initially applied a genomewide association approach based on the >700,000 SNP marker assay and PennCNV analysis to 68 Bos indicus cross females from a large commercial ranch in central Florida. A genomic segment located on chromosome 5, spanning the region of approximately 58.37 to 58.44 Mb (Bovine UMD3.1 assembly) was identified as containing a deletion associated with decreased reproductive efficiency. To verify this deletion, a quantitative real-time PCR test was developed to evaluate additional females in the central Florida and U.S. Meat Animal Research Center (USMARC) populations. The frequency of the homozygous deletion was 7% (23/319) in the central Florida population (Bos indicus cross) for females with 2 consecutive failed breeding seasons and 0% in the USMARC population (predominantly Bos taurus) of low reproductive females. To date, we have not identified the deletion in Bos taurus cattle, suggesting that the deletion is specific to Bos indicus cattle. From these data, we have identified a deletion on chromosome 5 associated with reproductive efficiency in Bos indicus-influenced cattle.
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Affiliation(s)
- T G McDaneld
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE 68933
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Wang W, Wang S, Hou C, Xing Y, Cao J, Wu K, Liu C, Zhang D, Zhang L, Zhang Y, Zhou H. Genome-wide detection of copy number variations among diverse horse breeds by array CGH. PLoS One 2014; 9:e86860. [PMID: 24497987 PMCID: PMC3907382 DOI: 10.1371/journal.pone.0086860] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 12/13/2013] [Indexed: 01/08/2023] Open
Abstract
Recent studies have found that copy number variations (CNVs) are widespread in human and animal genomes. CNVs are a significant source of genetic variation, and have been shown to be associated with phenotypic diversity. However, the effect of CNVs on genetic variation in horses is not well understood. In the present study, CNVs in 6 different breeds of mare horses, Mongolia horse, Abaga horse, Hequ horse and Kazakh horse (all plateau breeds) and Debao pony and Thoroughbred, were determined using aCGH. In total, seven hundred CNVs were identified ranging in size from 6.1 Kb to 0.57 Mb across all autosomes, with an average size of 43.08 Kb and a median size of 15.11 Kb. By merging overlapping CNVs, we found a total of three hundred and fifty-three CNV regions (CNVRs). The length of the CNVRs ranged from 6.1 Kb to 1.45 Mb with average and median sizes of 38.49 Kb and 13.1 Kb. Collectively, 13.59 Mb of copy number variation was identified among the horses investigated and accounted for approximately 0.61% of the horse genome sequence. Five hundred and eighteen annotated genes were affected by CNVs, which corresponded to about 2.26% of all horse genes. Through the gene ontology (GO), genetic pathway analysis and comparison of CNV genes among different breeds, we found evidence that CNVs involving 7 genes may be related to the adaptation to severe environment of these plateau horses. This study is the first report of copy number variations in Chinese horses, which indicates that CNVs are ubiquitous in the horse genome and influence many biological processes of the horse. These results will be helpful not only in mapping the horse whole-genome CNVs, but also to further research for the adaption to the high altitude severe environment for plateau horses.
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Affiliation(s)
- Wei Wang
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Shenyuan Wang
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Chenglin Hou
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Yanping Xing
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Junwei Cao
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Kaifeng Wu
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Chunxia Liu
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Dong Zhang
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Li Zhang
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
| | - Yanru Zhang
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
- * E-mail: (YZ); (HZ)
| | - Huanmin Zhou
- College of Life Sciences Inner Mongolia Agricultural University, Hohhot, China
- Key Laboratory of Biological Manufacturing, Hohhot, China
- * E-mail: (YZ); (HZ)
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