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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Genomic regions associated with principal components for growth, visual score and reproductive traits in Nellore cattle

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Author(s):
Vargas, Giovana [1] ; Schenkel, Flavio Schramm [2] ; Brito, Luiz Fernando [3] ; de Rezende Neves, Haroldo Henrique [4] ; Munari, Danisio Prado [5, 6] ; de Albuquerque, Lucia Galvao [1, 5] ; Carvalheiro, Roberto [1, 5]
Total Authors: 7
Affiliation:
[1] Sao Paulo State Univ UNESP, Sch Agr & Vet Sci, Dept Anim Sci, Via Acesso Prof Paulo Donato Castellane, BR-14884900 Jaboticabal, SP - Brazil
[2] Univ Guelph, Ctr Genet Improvement Livestock, Dept Anim Biosci, 50 Stone Rd East, Guelph, ON N1G 2W1 - Canada
[3] Purdue Univ, Dept Anim Sci, 610 Purdue Mall, W Lafayette, IN 47907 - USA
[4] Gensys Associated Consultants, BR-90680000 Porto Alegre, RS - Brazil
[5] Natl Council Sci & Technol Dev, BR-71605001 Brasilia, DF - Brazil
[6] Sao Paulo State Univ UNESP, Sch Agr & Vet Sci, Dept Exact Sci, Via Acesso Prof Paulo Donato Castellane, BR-14884900 Jaboticabal, SP - Brazil
Total Affiliations: 6
Document type: Journal article
Source: LIVESTOCK SCIENCE; v. 233, MAR 2020.
Web of Science Citations: 0
Abstract

The search for candidate genes underlying the expression of principal components (PCs) for different traits is a useful tool that allows exploring biological mechanisms associated with the traits of interest. The aim of this study was to identify genomic regions associated with PCs for growth, visual score and reproductive traits in Nellore cattle by performing a genome-wide association study (GWAS). Phenotypic and pedigree data from 355,524 animals and genotypes from 3,519 animals, were used in this investigation. The estimated breeding values (EBV) were obtained from a multi-trait analysis using a mixed linear animal model. The eigen-decomposition of the additive genetic (co)variance matrix among traits was used to calculate the EBVs for the main PCs. The SNP effects were estimated using the weighted single-step GBLUP and the BayesC method. The top-10 ranking windows that explained the highest proportion of variance were identified for further functional analyses. The most important genomic regions were identified on BTA7 and BTA24 for PC1, BTA8 for PC2, and BTA3 and BTA10 for PC3. The functional analyses contributed to unravel biological interpretation of PCs by identifying genes potentially associated with growth, carcass traits, conformation, and fatty acid composition traits. These findings are of relevance to the biological understanding of the PCs and their related biotypes in Nellore cattle, potentially allowing for genetic selection for more specific breeding goals. (AU)

FAPESP's process: 09/16118-5 - Genomic tools to genetic improvement of direct economic important traits in Nelore cattle
Grantee:Lucia Galvão de Albuquerque
Support type: Research Projects - Thematic Grants
FAPESP's process: 17/03331-9 - Genome-wide association study of principal components of growth traits and visual scores in Nellore cattle
Grantee:Giovana Vargas
Support type: Scholarships abroad - Research Internship - Doctorate
FAPESP's process: 15/25449-6 - Genomic association and prediction of principal components of growth traits and visual scores in Nelore cattle
Grantee:Giovana Vargas
Support type: Scholarships in Brazil - Doctorate