Effect of different genotypes quality control criteria on Genome-Wide Association Studies

• Grant number: 14/14431-6
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: October 01, 2014
• End date: March 31, 2015
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Lucia Galvão de Albuquerque
• Grantee: Tiago Bresolin
• Supervisor: Guilherme J. M. Rosa
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Institution abroad: University of Wisconsin-Madison (UW-Madison), United States
• Associated to the scholarship: 13/26264-4 - Effect of using different criteria for quality control of genotypes in studies of association and genome-wide selection, BP.MS

Abstract

From sequencing the bovine genome, a large number of genomic tools has became available due to the rapid advancement in DNA marker technologies. Therewith, it was proposed a variation in marker-assisted selection, called genomic selection, which uses information of single nucleotide polymorphism markers (SNPs) widely distributed over the genome. Thus, high density chips were developed, where the genotypes are read from signal intensity of the "spots". Many factors may affect the genotypes reading and genotyping errors can occur in some SNPs and samples, which may affect SNP effect estimates in Genome-Wide Association Studies (GWAS). Some of these genotyping errors can be removed by performing quality control. There are still divergences in the proper criteria and corresponding threshold values for the quality control of the genotypes in GWAS. The aim of this project is to evaluate the effect of different criteria for the quality control of genotypes on GWAS in Nellore cattle, in order to define the appropriate quality control. Phenotypic, genotypic and pedigree information provided by different Nellore breeding programs will be used. The animals were genotyped with the HDBovineSNP BeadChip (Illumina Infinium®), containing approximately 777 thousand SNPs. Different quality control criteria for SNPs and samples will be applied. The GWAS analyses will be performed using nonlinear model under Bayesian approach (BAYES CÀ). At the end we intent to define the proper quality control criteria of the genotypes for GWAS studies in Nellore population. (AU)