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Braga LG, Chud TCS, Watanabe RN, Savegnago RP, Sena TM, do Carmo AS, Machado MA, Panetto JCDC, da Silva MVGB, Munari DP. Identification of copy number variations in the genome of Dairy Gir cattle. PLoS One 2023; 18:e0284085. [PMID: 37036840 PMCID: PMC10085049 DOI: 10.1371/journal.pone.0284085] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 03/23/2023] [Indexed: 04/11/2023] Open
Abstract
Studying structural variants that can control complex traits is relevant for dairy cattle production, especially for animals that are tolerant to breeding conditions in the tropics, such as the Dairy Gir cattle. This study identified and characterized high confidence copy number variation regions (CNVR) in the Gir breed genome. A total of 38 animals were whole-genome sequenced, and 566 individuals were genotyped with a high-density SNP panel, among which 36 animals had both sequencing and SNP genotyping data available. Two sets of high confidence CNVR were established: one based on common CNV identified in the studied population (CNVR_POP), and another with CNV identified in sires with both sequence and SNP genotyping data available (CNVR_ANI). We found 10 CNVR_POP and 45 CNVR_ANI, which covered 1.05 Mb and 4.4 Mb of the bovine genome, respectively. Merging these CNV sets for functional analysis resulted in 48 unique high confidence CNVR. The overlapping genes were previously related to embryonic mortality, environmental adaptation, evolutionary process, immune response, longevity, mammary gland, resistance to gastrointestinal parasites, and stimuli recognition, among others. Our results contribute to a better understanding of the Gir breed genome. Moreover, the CNV identified in this study can potentially affect genes related to complex traits, such as production, health, and reproduction.
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Affiliation(s)
- Larissa G Braga
- Departamento de Engenharia e Ciências Exatas, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brazil
| | - Tatiane C S Chud
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada
| | - Rafael N Watanabe
- Departamento de Engenharia e Ciências Exatas, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brazil
| | - Rodrigo P Savegnago
- Department of Animal Science, Michigan State University, East Lansing, Michigan, United States of America
| | - Thomaz M Sena
- Departamento de Engenharia e Ciências Exatas, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brazil
| | - Adriana S do Carmo
- Departamento de Zootecnia, Universidade Federal de Goiás, Goiânia, Goiás, Brazil
| | | | | | | | - Danísio P Munari
- Departamento de Engenharia e Ciências Exatas, Universidade Estadual Paulista, Jaboticabal, São Paulo, Brazil
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Moradi MH, Mahmodi R, Farahani AHK, Karimi MO. Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds. Sci Rep 2022; 12:14286. [PMID: 35996004 PMCID: PMC9395407 DOI: 10.1038/s41598-022-18571-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 08/16/2022] [Indexed: 11/23/2022] Open
Abstract
Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.
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Affiliation(s)
- Mohammad Hossein Moradi
- Department of Animal Science, Faculty of Agriculture and Natural Resources, Arak University, Arak, 38156-8-8349, Iran.
| | - Roqiah Mahmodi
- Department of Animal Science, Faculty of Agriculture and Natural Resources, Arak University, Arak, 38156-8-8349, Iran
| | | | - Mohammad Osman Karimi
- Department of Animal Science, Faculty of Agriculture and Natural Resources, Herat University, Herat, Afghanistan
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Butty AM, Chud TCS, Miglior F, Schenkel FS, Kommadath A, Krivushin K, Grant JR, Häfliger IM, Drögemüller C, Cánovas A, Stothard P, Baes CF. High confidence copy number variants identified in Holstein dairy cattle from whole genome sequence and genotype array data. Sci Rep 2020; 10:8044. [PMID: 32415111 PMCID: PMC7229195 DOI: 10.1038/s41598-020-64680-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 04/15/2020] [Indexed: 12/15/2022] Open
Abstract
Multiple methods to detect copy number variants (CNV) relying on different types of data have been developed and CNV have been shown to have an impact on phenotypes of numerous traits of economic importance in cattle, such as reproduction and immunity. Further improvements in CNV detection are still needed in regard to the trade-off between high-true and low-false positive variant identification rates. Instead of improving single CNV detection methods, variants can be identified in silico with high confidence when multiple methods and datasets are combined. Here, CNV were identified from whole-genome sequences (WGS) and genotype array (GEN) data on 96 Holstein animals. After CNV detection, two sets of high confidence CNV regions (CNVR) were created that contained variants found in both WGS and GEN data following an animal-based (n = 52) and a population-based (n = 36) pipeline. Furthermore, the change in false positive CNV identification rates using different GEN marker densities was evaluated. The population-based approach characterized CNVR, which were more often shared among animals (average 40% more samples per CNVR) and were more often linked to putative functions (48 vs 56% of CNVR) than CNV identified with the animal-based approach. Moreover, false positive identification rates up to 22% were estimated on GEN information. Further research using larger datasets should use a population-wide approach to identify high confidence CNVR.
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Affiliation(s)
- Adrien M Butty
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada
| | - Tatiane C S Chud
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada
| | - Filippo Miglior
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada
| | - Arun Kommadath
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada.,Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, Canada
| | - Kirill Krivushin
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Jason R Grant
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Irene M Häfliger
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, BE, Switzerland
| | - Cord Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, BE, Switzerland
| | - Angela Cánovas
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Christine F Baes
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada. .,Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, BE, Switzerland.
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Jia C, Wang H, Li C, Wu X, Zan L, Ding X, Guo X, Bao P, Pei J, Chu M, Liang C, Yan P. Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip. BMC Genomics 2019; 20:376. [PMID: 31088363 PMCID: PMC6518677 DOI: 10.1186/s12864-019-5759-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 05/02/2019] [Indexed: 01/29/2023] Open
Abstract
Background Copy number variations (CNVs), which are genetic variations present throughout mammalian genomes, are a vital source of phenotypic variation that can lead to the development of unique traits. In this study we used the Illunima BovineHD BeadChip to conduct genome-wide detection of CNVs in 215 polled yaks. Results A total of 1066 CNV regions (CNVRs) were detected with a total length of 181.6 Mb, comprising ~ 7.2% of the bovine autosomal genome. The size of these CNVRs ranged from 5.53 kb to 1148.45 kb, with an average size of 170.31 kb. Eight out of nine randomly chosen CNVRs were successfully validated by qPCR. A functional enrichment analysis of the CNVR-associated genes indicated their relationship to a number of molecular adaptations that enable yaks to thrive at high altitudes. One third of the detected CNVRs were mapped to QTLs associated with six classes of economically important traits, indicating that these CNVRs may play an important role in variations of these traits. Conclusions Our genome-wide yak CNV map may thus provide valuable insights into both the molecular mechanisms of high altitude adaptation and the potential genomic basis of economically important traits in yak. Electronic supplementary material The online version of this article (10.1186/s12864-019-5759-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Congjun Jia
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.,College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Hongbo Wang
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Chen Li
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Xiaoyun Wu
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Xuezhi Ding
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Xian Guo
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Pengjia Bao
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Jie Pei
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Min Chu
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Chunnian Liang
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.
| | - Ping Yan
- Key Laboratory of Yak Breeding Engineering Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.
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