GWAS for Production Traits in the Mexican Holstein Population Using High Density Arrays

Milk production is an important part of modern agriculture and genomics have been heavily implemented to improve its efficiency worldwide. A GWAS was performed for production traits in Mexican Holstein cattle (Milk Yield, Fat %, Fat yield, Protein % and protein Yield)

The GWAS was accomplished with a correlation/trend test implemented in SVS software using only SNPs with an imputation accuracy value of at least 80%. A total of 911 Mexican Holstein cattle with 541,915 SNPs each were used. Haplotype blocks were also computed by SVS software and their frequencies were obtained with the expectation maximization algorithm. Gene ontology and pathways analyses were performed using the DAVID Bioinformatics Resources 6.8 (http://david.abcc.ncifcrf.gov/) with the false discovery rate correction.

A total of 551, 114, 111, 94 and 86 SNPs on 6, 11, 13, 6 and 10 autosomes showed genome-wide significance association with fat percentage fat yield, milk, protein percentage and protein yield, respectively, with 55, 21, 19, 21 and 4 annotated genes for the same characteristics. When these results were compared with a previous work with 45,195 SNPs in the same population, 147 more SNPs per trait were found significant on average.

We acknowledge the Council of Dairy Cattle Breeding and Holstein de Mexico A.C. for sharing genomic data. This work received funding from CONACYT, México (project “IDENTIFICACIÓN DE VARIACIONES ESTRUCTURALES Y REGIONES GENÓMICAS ASOCIADAS A RESISTENCIA A MASTITIS EN BOVINOS PRODUCTORES DE LECHE”, 176039).