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Effect of using different criteria for quality control of genotypes in studies of association and genome-wide selection

Grant number: 13/26264-4
Support type:Scholarships in Brazil - Master
Effective date (Start): April 01, 2014
Effective date (End): July 31, 2015
Field of knowledge:Agronomical Sciences - Animal Husbandry
Principal Investigator:Lucia Galvão de Albuquerque
Grantee:Tiago Bresolin
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
Associated research grant:09/16118-5 - Genomic tools to genetic improvement of direct economic important traits in Nelore cattle, AP.TEM
Associated scholarship(s):14/14431-6 - Effect of different genotypes quality control criteria on Genome-Wide Association Studies, BE.EP.MS

Abstract

From the sequencing of the bovine genome, a large number of genomic tools has become available due to rapid advancement of DNA marker technology. With this, it was proposed a variation of marker-assisted selection, called genomic selection, that uses information from single nucleotide polymorphisms (SNPs) markers distributed throughout the genome. Thus, high density beat chips have been developed, in which the genotypes are read from the signal intensity of the "spots". However, many factors can affect the reading of genotypes and genotyping errors can occur in a few SNPs and samples, which may lead to over or underestimation of SNPs effects. Nonetheless, it is possible to remove these genotyping errors using some exclusion criteria in the quality control step. However, there are differences in values of thresholds exclusion adopted for each of these criteria and whether or not there are effects of these different values in genomic analyzes. The objective of this project is evaluate the effect of different criteria for quality control of genotypes aiming to define appropriate criteria for editing data in genome-wide association studies and genome-wide selection in Nellore cattle. For this, it will be used phenotypic, genotypic, and pedigree information which come from farms that are part of the following animal breeding programs: DeltaGen, Nellore Qualitas, and CRV Paint. The animals were genotyped with the Illumina Bovine HD panel, which contains approximately 777,000 SNPs. It will be applied different levels of SNPs or samples exclusion for the different criteria. Analyses of genomic selection will be carried out using a linear model, "Best Linear Unbiased Predictor Genomic" (GBLUP), and nonlinear under Bayesian approach (BAYES Cpi). For the genome-wide association analysis, the nonlinear model under Bayesian approach (BAYES Cpi) will be used. At the end is expected to define appropriate criteria for genotypes edition.

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BRESOLIN, TIAGO; ROSA, GUILHERME JORDAO DE MAGALHAES; VALENTE, BRUNO DOURADO; ESPIGOLAN, RAFAEL; MANSAN GORDO, DANIEL GUSTAVO; BRAZ, CAMILA URBANO; FERNANDES JUNIOR, GERARDO ALVES; BRAGA MAGALHAES, ANA FABRICIA; GARCIA, DIOGO ANASTACIO; FREZARIM, GABRIELA BONFA; CARNEIRO LEAO, GUILHERME FONSECA; CARVALHEIRO, ROBERTO; BALDI, FERNANDO; DE OLIVEIRA, HENRIQUE NUNES; DE ALBUQUERQUE, LUCIA GALVAO. Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle. ANIMAL PRODUCTION SCIENCE, v. 59, n. 1, p. 48-54, 2018. Web of Science Citations: 0.
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
BRESOLIN, Tiago. Efeito da utilização de diferentes critérios de controle de qualidade dos genótipos em estudos de associação e seleção genômica ampla. 2015. Master's Dissertation - Universidade Estadual Paulista "Júlio de Mesquita Filho" Faculdade de Ciências Agrárias e Veterinárias..

Please report errors in scientific publications list by writing to: cdi@fapesp.br.