RESUMO
In arid and semi-arid zones, animal health and production are closely correlated with body conformation traits. These selected traits, in turn, allow livestock to adapt unfavorable soil and environmental conditions. The primary objective of this study was to perform a genome-wide association analysis for a set of sampled and imputed SNPs with 16 conformation traits in a population of Holstein cows from a desert area of Northwestern Mexico. Imputation from 6K to 50K SNPs was performed as a low-cost optimization strategy. Results show eight SNPs associated with two conformation traits. The Udder Depth trait resulted in seven associated SNPs from chromosome 10, that related to Marbling Score, Milk Yield, Fat Yield, Protein Yield, and Protein Percentage Quantitative Trait Loci (QTLs). The Body Depth trait resulted in one associated SNP from chromosome 2, although no QTL relation was found. The discovery of genes associated with conformation traits may be indicative of the adaptive selection pressures the Holstein breed has undergone in response to the extreme weather conditions found in the northwestern areas of Mexico. Results of this study indicate that traits such as stature and body depth may be used as indicators of cows' potential genetic merits for milk, fat, and protein production.
Assuntos
Composição Corporal/genética , Tamanho Corporal/genética , Bovinos/genética , Polimorfismo de Nucleotídeo Único , Característica Quantitativa Herdável , Animais , Cruzamento/métodos , Estudo de Associação Genômica Ampla , GenótipoRESUMO
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.