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http://dx.doi.org/10.5713/ajas.18.0204

Detection of genome-wide structural variations in the Shanghai Holstein cattle population using next-generation sequencing  

Liu, Dengying (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Chen, Zhenliang (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Zhang, Zhe (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Sun, Hao (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Ma, Peipei (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Zhu, Kai (Shanghai Dairy Cattle Breeding Centre Co., Ltd)
Liu, Guanglei (Shanghai Dairy Cattle Breeding Centre Co., Ltd)
Wang, Qishan (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Pan, Yuchun (Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University)
Publication Information
Asian-Australasian Journal of Animal Sciences / v.32, no.3, 2019 , pp. 320-333 More about this Journal
Abstract
Objective: The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction. Methods: In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA). Results: The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle. Conclusion: Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.
Keywords
Genotyping by Genome Reducing and Sequencing (GGRS); Mastitis; Reproduction; Shanghai Holstein; Structural Variation;
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