Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle

Detalhes bibliográficos
Autor(a) principal: Bresolin, Tiago [UNESP]
Data de Publicação: 2017
Outros Autores: Rosa, Guilherme Jordão De Magalhães, Valente, Bruno Dourado, Espigolan, Rafael [UNESP], Gordo, Daniel Gustavo Mansan [UNESP], Braz, Camila Urbano [UNESP], Fernandes, Gerardo Alves [UNESP], Magalhães, Ana Fabrícia Braga [UNESP], Garcia, Diogo Anastacio [UNESP], Frezarim, Gabriela Bonfá [UNESP], Leão, Guilherme Fonseca Carneiro [UNESP], Carvalheiro, Roberto [UNESP], Baldi, Fernando [UNESP], Nunes De Oliveira, Henrique [UNESP], Galvão De Albuquerque, Lucia [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1071/AN16821
http://hdl.handle.net/11449/176526
Resumo: This study was designed to test the impact of quality control, density and allele frequency of single nucleotide polymorphisms (SNP) markers on the accuracy of genomic predictions, using three traits with different heritabilities and two methods of prediction in a Nellore cattle population genotyped with the Illumina Bovine HD Assay. A total of 1756∼ 3150 and 3119 records of age at first calving (AFC)∼ weaning weight (WW) and yearling weight (YW), respectively, were used. Three scenarios with different exclusion thresholds for minor allele frequency (MAF), deviation from Hardy-Weinberg equilibrium (HWE) and correlation between SNP pairs (r2) were constructed for all traits: (1) high rigor (S1): call rate <0.98, MAF <0.05, HWE with P <10-5, and r2 >0.999∼ (2) Moderate rigor (S2): call rate <0.85 and MAF <0.01∼ (3) Low rigor (S3): only non-Autosomal SNP and those mapped on the same position were excluded. Additionally, to assess the prediction accuracy from different markers density, six panels (10K, 50K, 100K, 300K, 500K and 700K) were customised using the high-density genotyping assay as reference. Finally, from the markers available in high-density genotyping assay, six groups (G) with different minor allele frequency bins were defined to estimate the accuracy of genomic prediction. The range of MAF bins was approximately equal for the traits studied: G1 (0.000-0.009), G2 (0.010-0.064), G3 (0.065-0.174), G4 (0.175-0.325), G5 (0.326-0.500) and G6 (0.000-0.500). The Genomic Best Linear Unbiased Predictor and BayesCπ methods were used to estimate the SNP marker effects. Five-fold cross-validation was used to measure the accuracy of genomic prediction for all scenarios. There were no effects of genotypes quality control criteria on the accuracies of genomic predictions. For all traits, the higher density panel did not provide greater prediction accuracies than the low density one (10K panel). The groups of SNP with low MAF (MAF ≤0.007 for AFC, MAF ≤0.009 for WW and MAF ≤0.008 for YW) provided lower prediction accuracies than the groups with higher allele frequencies.
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spelling Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattleaccuracy of predictionbeef cattlemarker densitymarker editingmarker effects.This study was designed to test the impact of quality control, density and allele frequency of single nucleotide polymorphisms (SNP) markers on the accuracy of genomic predictions, using three traits with different heritabilities and two methods of prediction in a Nellore cattle population genotyped with the Illumina Bovine HD Assay. A total of 1756∼ 3150 and 3119 records of age at first calving (AFC)∼ weaning weight (WW) and yearling weight (YW), respectively, were used. Three scenarios with different exclusion thresholds for minor allele frequency (MAF), deviation from Hardy-Weinberg equilibrium (HWE) and correlation between SNP pairs (r2) were constructed for all traits: (1) high rigor (S1): call rate <0.98, MAF <0.05, HWE with P <10-5, and r2 >0.999∼ (2) Moderate rigor (S2): call rate <0.85 and MAF <0.01∼ (3) Low rigor (S3): only non-Autosomal SNP and those mapped on the same position were excluded. Additionally, to assess the prediction accuracy from different markers density, six panels (10K, 50K, 100K, 300K, 500K and 700K) were customised using the high-density genotyping assay as reference. Finally, from the markers available in high-density genotyping assay, six groups (G) with different minor allele frequency bins were defined to estimate the accuracy of genomic prediction. The range of MAF bins was approximately equal for the traits studied: G1 (0.000-0.009), G2 (0.010-0.064), G3 (0.065-0.174), G4 (0.175-0.325), G5 (0.326-0.500) and G6 (0.000-0.500). The Genomic Best Linear Unbiased Predictor and BayesCπ methods were used to estimate the SNP marker effects. Five-fold cross-validation was used to measure the accuracy of genomic prediction for all scenarios. There were no effects of genotypes quality control criteria on the accuracies of genomic predictions. For all traits, the higher density panel did not provide greater prediction accuracies than the low density one (10K panel). The groups of SNP with low MAF (MAF ≤0.007 for AFC, MAF ≤0.009 for WW and MAF ≤0.008 for YW) provided lower prediction accuracies than the groups with higher allele frequencies.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Jaboticabal, Via de acesso Prof. Paulo Donato Castellane, s/nDepartment of Animal Sciences University of Wisconsin, 436 Animal Science BuildingNational Counsel of Technological and Scientific Development CNPq SHIS QI 1 Conjunto B-Blocos A B C e DDepartamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Jaboticabal, Via de acesso Prof. Paulo Donato Castellane, s/nUniversidade Estadual Paulista (Unesp)University of WisconsinC e DBresolin, Tiago [UNESP]Rosa, Guilherme Jordão De MagalhãesValente, Bruno DouradoEspigolan, Rafael [UNESP]Gordo, Daniel Gustavo Mansan [UNESP]Braz, Camila Urbano [UNESP]Fernandes, Gerardo Alves [UNESP]Magalhães, Ana Fabrícia Braga [UNESP]Garcia, Diogo Anastacio [UNESP]Frezarim, Gabriela Bonfá [UNESP]Leão, Guilherme Fonseca Carneiro [UNESP]Carvalheiro, Roberto [UNESP]Baldi, Fernando [UNESP]Nunes De Oliveira, Henrique [UNESP]Galvão De Albuquerque, Lucia [UNESP]2018-12-11T17:21:13Z2018-12-11T17:21:13Z2017-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1071/AN16821Animal Production Science.1836-57871836-0939http://hdl.handle.net/11449/17652610.1071/AN168212-s2.0-85049235553Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAnimal Production Science0,6370,637info:eu-repo/semantics/openAccess2021-10-23T16:57:51Zoai:repositorio.unesp.br:11449/176526Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T16:57:51Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
title Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
spellingShingle Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
Bresolin, Tiago [UNESP]
accuracy of prediction
beef cattle
marker density
marker editing
marker effects.
title_short Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
title_full Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
title_fullStr Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
title_full_unstemmed Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
title_sort Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle
author Bresolin, Tiago [UNESP]
author_facet Bresolin, Tiago [UNESP]
Rosa, Guilherme Jordão De Magalhães
Valente, Bruno Dourado
Espigolan, Rafael [UNESP]
Gordo, Daniel Gustavo Mansan [UNESP]
Braz, Camila Urbano [UNESP]
Fernandes, Gerardo Alves [UNESP]
Magalhães, Ana Fabrícia Braga [UNESP]
Garcia, Diogo Anastacio [UNESP]
Frezarim, Gabriela Bonfá [UNESP]
Leão, Guilherme Fonseca Carneiro [UNESP]
Carvalheiro, Roberto [UNESP]
Baldi, Fernando [UNESP]
Nunes De Oliveira, Henrique [UNESP]
Galvão De Albuquerque, Lucia [UNESP]
author_role author
author2 Rosa, Guilherme Jordão De Magalhães
Valente, Bruno Dourado
Espigolan, Rafael [UNESP]
Gordo, Daniel Gustavo Mansan [UNESP]
Braz, Camila Urbano [UNESP]
Fernandes, Gerardo Alves [UNESP]
Magalhães, Ana Fabrícia Braga [UNESP]
Garcia, Diogo Anastacio [UNESP]
Frezarim, Gabriela Bonfá [UNESP]
Leão, Guilherme Fonseca Carneiro [UNESP]
Carvalheiro, Roberto [UNESP]
Baldi, Fernando [UNESP]
Nunes De Oliveira, Henrique [UNESP]
Galvão De Albuquerque, Lucia [UNESP]
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
University of Wisconsin
C e D
dc.contributor.author.fl_str_mv Bresolin, Tiago [UNESP]
Rosa, Guilherme Jordão De Magalhães
Valente, Bruno Dourado
Espigolan, Rafael [UNESP]
Gordo, Daniel Gustavo Mansan [UNESP]
Braz, Camila Urbano [UNESP]
Fernandes, Gerardo Alves [UNESP]
Magalhães, Ana Fabrícia Braga [UNESP]
Garcia, Diogo Anastacio [UNESP]
Frezarim, Gabriela Bonfá [UNESP]
Leão, Guilherme Fonseca Carneiro [UNESP]
Carvalheiro, Roberto [UNESP]
Baldi, Fernando [UNESP]
Nunes De Oliveira, Henrique [UNESP]
Galvão De Albuquerque, Lucia [UNESP]
dc.subject.por.fl_str_mv accuracy of prediction
beef cattle
marker density
marker editing
marker effects.
topic accuracy of prediction
beef cattle
marker density
marker editing
marker effects.
description This study was designed to test the impact of quality control, density and allele frequency of single nucleotide polymorphisms (SNP) markers on the accuracy of genomic predictions, using three traits with different heritabilities and two methods of prediction in a Nellore cattle population genotyped with the Illumina Bovine HD Assay. A total of 1756∼ 3150 and 3119 records of age at first calving (AFC)∼ weaning weight (WW) and yearling weight (YW), respectively, were used. Three scenarios with different exclusion thresholds for minor allele frequency (MAF), deviation from Hardy-Weinberg equilibrium (HWE) and correlation between SNP pairs (r2) were constructed for all traits: (1) high rigor (S1): call rate <0.98, MAF <0.05, HWE with P <10-5, and r2 >0.999∼ (2) Moderate rigor (S2): call rate <0.85 and MAF <0.01∼ (3) Low rigor (S3): only non-Autosomal SNP and those mapped on the same position were excluded. Additionally, to assess the prediction accuracy from different markers density, six panels (10K, 50K, 100K, 300K, 500K and 700K) were customised using the high-density genotyping assay as reference. Finally, from the markers available in high-density genotyping assay, six groups (G) with different minor allele frequency bins were defined to estimate the accuracy of genomic prediction. The range of MAF bins was approximately equal for the traits studied: G1 (0.000-0.009), G2 (0.010-0.064), G3 (0.065-0.174), G4 (0.175-0.325), G5 (0.326-0.500) and G6 (0.000-0.500). The Genomic Best Linear Unbiased Predictor and BayesCπ methods were used to estimate the SNP marker effects. Five-fold cross-validation was used to measure the accuracy of genomic prediction for all scenarios. There were no effects of genotypes quality control criteria on the accuracies of genomic predictions. For all traits, the higher density panel did not provide greater prediction accuracies than the low density one (10K panel). The groups of SNP with low MAF (MAF ≤0.007 for AFC, MAF ≤0.009 for WW and MAF ≤0.008 for YW) provided lower prediction accuracies than the groups with higher allele frequencies.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-01
2018-12-11T17:21:13Z
2018-12-11T17:21:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1071/AN16821
Animal Production Science.
1836-5787
1836-0939
http://hdl.handle.net/11449/176526
10.1071/AN16821
2-s2.0-85049235553
url http://dx.doi.org/10.1071/AN16821
http://hdl.handle.net/11449/176526
identifier_str_mv Animal Production Science.
1836-5787
1836-0939
10.1071/AN16821
2-s2.0-85049235553
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Animal Production Science
0,637
0,637
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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