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Comparison of single-step methods for genomic prediction of age at first calving in dairy buffaloes

Published online by Cambridge University Press:  14 November 2024

Jessica Cristina Gonçalves dos Santos ,
Francisco Ribeiro de Araújo Neto Open the ORCID record for Francisco Ribeiro de Araújo Neto [Opens in a new window] ,
Gabriela Stefani Fernandez ,
Daniel Jordan de Abreu Santos ,
Felipe Pereira Cunha ,
Rusbel Raul Aspilcueta-Borquis  and
Humberto Tonhati
Jessica Cristina Gonçalves dos Santos
Affiliation:
Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal – UNESP, Jaboticabal, São Paulo, Brazil
Francisco Ribeiro de Araújo Neto*
Affiliation:
Instituto Federal de Ciência e Tecnologia Goiano – IFGoiano, Rio Verde, Goiás
Gabriela Stefani Fernandez
Affiliation:
Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal – UNESP, Jaboticabal, São Paulo, Brazil
Daniel Jordan de Abreu Santos
Affiliation:
Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal – UNESP, Jaboticabal, São Paulo, Brazil
Felipe Pereira Cunha
Affiliation:
Instituto Federal de Ciência e Tecnologia Goiano – IFGoiano, Rio Verde, Goiás
Rusbel Raul Aspilcueta-Borquis
Affiliation:
Universidade Tecnológica Federal do Paraná – UFTPR, Dois Vizinhos, Paraná
Humberto Tonhati
Affiliation:
Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal – UNESP, Jaboticabal, São Paulo, Brazil
*
Corresponding author: F. R. Araujo Neto; Email: [email protected]
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Abstract

The age at first calving (AFC) is an important trait to be considered in breeding programmes of dairy buffaloes, where new approaches and technologies, such as genomic selection, are constantly applied. Thus, the objective of this study was to compare the predictive ability of different genomic single-step methods using AFC information from Murrah buffaloes. From a pedigree file containing 3320 buffaloes, 2247 cows had AFC records and 553 animals were genotyped. The following models were performed: pedigree-based BLUP (PBLUP), single-step GBLUP (ssGBLUP), weighted single-step GBLUP (WssGBLUP), and single-step Bayesian regression methods (ssBR-BayesA, BayesBπ, BayesCπ, Bayes-Lasso, and BayesRR). To compare the methodologies, the accuracy and dispersion of (G)EBVs were assessed using the LR method. Accuracy estimates for the genotyped animals ranged from 0.30 (PBLUP) to 0.39 (WssGBLUP). Predictions with the traditional model (PBLUP) were very dispersed from what was expected, while BayesCπ (0.99) and WssGBLUP (1.00) obtained the lowest dispersion. The results indicate that the use of genomic information can improve the genetic gain for AFC by increasing the accuracy and reducing inflation/deflation of predictions compared to the traditional pedigree-based model. In addition, among all genomic single-step models studied, WssGBLUP and single-step BayesA were the most advantageous methods to be used in the genomic evaluation of AFC of buffaloes from this population.

Keywords

Bayesian inferenceBubalus bubalisgenomic selectionreproductive traits
Type
Animal Research Paper
Information
The Journal of Agricultural Science , Volume 162 , Issue 4 , August 2024 , pp. 377 - 383
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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