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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.)

Assessing the accuracy of prediction for milk fatty acids by using a small reference population of tropical Holstein cows

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Author(s):
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Petrini, Juliana [1, 2] ; de Souza Iung, Laiza Helena [1] ; Petersen Rodriguez, Mary Ana [1] ; Salvian, Mayara [1] ; Rovadoscki, Gregori Alberto [1] ; Robles Colonia, Saditt Rocio [2] ; Cassoli, Laerte Dagher [1] ; Coutinho, Luiz Lehmann [1] ; Machado, Paulo Fernando [1] ; Wiggans, George [3, 4] ; Mourao, Gerson Barreto [1]
Total Authors: 11
Affiliation:
[1] Univ Sao Paulo, Dept Anim Sci, Piracicaba - Brazil
[2] Univ Fed Alfenas, Inst Exact Sci, Dept Stat, Alfenas - Brazil
[3] ARS, Anim Genom & Improvement Lab, USDA, Beltsville, MD - USA
[4] Council Dairy Cattle Breeding, Bowie, MD - USA
Total Affiliations: 4
Document type: Journal article
Source: JOURNAL OF ANIMAL BREEDING AND GENETICS; AUG 2019.
Web of Science Citations: 0
Abstract

Fatty acids (FA) have been related to effects on human health, sensory quality and shelf life of dairy products, cow's health and methane emission. However, despite their importance, they are not regularly measured in all dairy herds yet, which can affect the accuracy of estimated breeding values (EBV) for these traits. In this case, an alternative is to use genomic selection. Thus, the aim was to assess the use of genomic information in the genetic evaluation for milk traits in a tropical Holstein population. Monthly records (n = 36,457) of milk FA percentage, daily milk yield and quality traits from 4,203 cows as well as the genotypes of 755 of these cows for 57,368 single nucleotide polymorphisms (SNP) were used. Polygenic and genomic-polygenic models were applied for EBV prediction, and both models were compared through the EBV accuracy calculated from the prediction error and Spearman's correlation among EBV rankings. Prediction accuracy was assessed by using cross-validation. In this case, the accuracy was the correlation between the genomic breeding values (GEBV) obtained as the sum of SNP effects and the EBV obtained in the polygenic model in each validation group. For all traits, the use of the genomic-polygenic model did not alter the animals' ranking, with correlations higher than 0.87. Nevertheless, through this model, the accuracy increased from 1.5% to 6.8% compared to the polygenic model. The correlations between GEBV and EBV varied from 0.52 to 0.68. Therefore, the use of a small group of genotyped cows in the genetic evaluation can increase the accuracy of EBV for milk FA and other traditional milk traits. (AU)

FAPESP's process: 12/15948-7 - Inclusion of genomic information in the development of economic index for dairy cattle selection
Grantee:Juliana Petrini
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 10/12929-6 - Quantitative-molecular genetic analysis for production traits, fatty acid profile and milk quality
Grantee:Gerson Barreto Mourão
Support type: Regular Research Grants
FAPESP's process: 12/24788-3 - Epistatic interactions between SNPs associated with composition and fatty acid profile in bovine milk
Grantee:Laiza Helena de Souza Iung
Support type: Scholarships in Brazil - Master