Research Article

Genome-wide identification of copy number variations in Holstein cattle from Baja California, Mexico, using high-density SNP genotyping arrays

Published: October 02, 2015
Genet. Mol. Res. 14 (4) : 11848-11859 DOI: https://doi.org/10.4238/2015.October.2.18
Cite this Article:
R. Salomón-Torres, V.M. González-Vizcarra, G.E. Medina-Basulto, M.F. Montaño-Gómez, P. Mahadevan, V.H. Yaurima-Basaldúa, C. Villa-Angulo, R. Villa-Angulo (2015). Genome-wide identification of copy number variations in Holstein cattle from Baja California, Mexico, using high-density SNP genotyping arrays. Genet. Mol. Res. 14(4): 11848-11859. https://doi.org/10.4238/2015.October.2.18
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Abstract

Copy number variations (CNVs) are an important source of genomic structural variation, and can be used as markers to investigate phenotypic and economic traits. CNVs also have functional effects on gene expression and can contribute to disease susceptibility in mammals. Currently, single nucleotide polymorphism genotyping arrays (SNP chips) are the technology of choice for identifying CNV variations. Microarray technologies have recently been used to study the bovine genome. The objective of the present study was to develop CNVs in Holstein cows from the Northwest of Mexico using the Affymetrix Axiom Genome-Wide BOS 1 Array, which assays 648,315 SNPs and provides a wide coverage for genome-wide studies. We applied the two most widely used algorithms for the discovery of CNVs (PennCNV and QuantiSNP) and found 56 CNV regions (CNVRs) representing 0.33% of the bovine genome (8.46 Mb). These CNVRs ranged from 1.5 to 970.8 kb with an average length of 151 kb. They involved 103 genes and showed a 28% overlap with CNVRs already reported. Of the 56 CNVRs found, 20 were novel. In this study we present the first genomic analysis of CNVs in Mexican cattle using high-density SNP data. Our results provide a new reference basis for future genomic variation and association studies between CNVs and phenotypes, especially in Mexican cattle.

Copy number variations (CNVs) are an important source of genomic structural variation, and can be used as markers to investigate phenotypic and economic traits. CNVs also have functional effects on gene expression and can contribute to disease susceptibility in mammals. Currently, single nucleotide polymorphism genotyping arrays (SNP chips) are the technology of choice for identifying CNV variations. Microarray technologies have recently been used to study the bovine genome. The objective of the present study was to develop CNVs in Holstein cows from the Northwest of Mexico using the Affymetrix Axiom Genome-Wide BOS 1 Array, which assays 648,315 SNPs and provides a wide coverage for genome-wide studies. We applied the two most widely used algorithms for the discovery of CNVs (PennCNV and QuantiSNP) and found 56 CNV regions (CNVRs) representing 0.33% of the bovine genome (8.46 Mb). These CNVRs ranged from 1.5 to 970.8 kb with an average length of 151 kb. They involved 103 genes and showed a 28% overlap with CNVRs already reported. Of the 56 CNVRs found, 20 were novel. In this study we present the first genomic analysis of CNVs in Mexican cattle using high-density SNP data. Our results provide a new reference basis for future genomic variation and association studies between CNVs and phenotypes, especially in Mexican cattle.