Genome Wide Association Study (GWAS) applied to in vitro embryo production in Nellore cattle

Abstract

Considering the importance of in vitro embryo production and its increasing use in beef cattle production, the objective of this study was to identify regions associated with reproductive traits, such as the number of oocytes aspirates (OA), the number of viable oocytes (OV) and the number of viable embryos (EV). The database presents about 2,700 follicular aspirations of oocytes from approximately 500 genotyped Nelore cows, the GWAS methodology (Genome Wide Association Study) is based on the search for relevant markers related to the phenotype of interest, in addition to pointing out candidate regions in the genome that may have influence on the characteristic under study. Genomic analysis will be performed by the parametric ssGBLUP (single step Genomic Best Linear Unbiased Prediction), which uses information from the SNP markers and the change in the kinship matrix, generating an array that considers the pedigree and genomic information. Considering the importance of in vitro embryo production and its increasing use in the production of beef cattle, the objective of this study was to identify genomic regions associated with the characteristics of embryo production and where there may be candidate genes to express phenotypes that can be considered in processes donor selection, such as the number of oocytes aspirated, the number of viable oocytes and the number of embryos produced. The database has about 2,700 follicular aspirations of oocytes from approximately 500 genotyped Nelore cows, with notes on the identification of the donor, farm, parents and mother, date of birth, name of donor semen and characteristics: number of oocytes number of viable oocytes, no cumulus, expanded, atretic, degenerate and total, IVM, cleaved, viable embryos, fresh and thawed transfers, and pregnancy rate. The GWAS (Genome Wide Association Study) methodology is based on the search for relevant markers related to the phenotype of interest, besides pointing out candidate regions in the genome that may have influence on the characteristic under study. The genomic analysis will be performed by the parametric method ssBLUP (Single Set Best Linear Unbiased Prediction), which uses information from the SNP markers and the change of the kin matrix, generating a matrix that considers the pedigree and the genomic information.