Genome-wide detection of copy number variations using high-density SNP genotyping platforms in HolsteinsReport as inadecuate

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BMC Genomics

, 14:131

Non-human and non-rodent vertebrate genomics


BackgroundCopy number variations CNVs are widespread in the human or animal genome and are a significant source of genetic variation, which has been demonstrated to play an important role in phenotypic diversity. Advances in technology have allowed for identification of a large number of CNVs in cattle. Comprehensive explore novel CNVs in the bovine genome would provide valuable information for functional analyses of genome structural variation and facilitating follow-up association studies between complex traits and genetic variants.

ResultsIn this study, we performed a genome-wide CNV detection based on high-density SNP genotyping data of 96 Chinese Holstein cattle. A total of 367 CNV regions CNVRs across the genome were identified, which cover 42.74Mb of the cattle genome and correspond to 1.61% of the genome sequence. The length of the CNVRs on autosomes range from 10.76 to 2,806.42 Kb with an average of 96.23 Kb. 218 out of these CNVRs contain 610 annotated genes, which possess a wide spectrum of molecular functions. To confirm these findings, quantitative PCR qPCR was performed for 17 CNVRs and 1376.5% of them were successfully validated.

ConclusionsOur study demonstrates the high density SNP array can significantly improve the accuracy and sensitivity of CNV calling. Integration of different platforms can enhance the detection of genomic structure variants. Our results provide a significant replenishment for the high resolution map of copy number variation in the bovine genome and valuable information for investigation of genomic structural variation underlying traits of interest in cattle.

KeywordsCopy number variations Cattle BovineHD beadChip Genome variation Quantitative real time PCR Electronic supplementary materialThe online version of this article doi:10.1186-1471-2164-14-131 contains supplementary material, which is available to authorized users.

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Author: Li Jiang - Jicai Jiang - Jie Yang - Xuan Liu - Jiying Wang - Haifei Wang - Xiangdong Ding - Jianfeng Liu - Qin Zhang


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