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Related Experiment Video

Updated: Apr 23, 2026

Author Spotlight: Improving Beef Cattle Nutrition and Production with a Focus on Feed Efficiency and Meat Quality Traits Through Advanced Biochemical and Molecular Assays

Author Spotlight: Improving Beef Cattle Nutrition and Production with a Focus on Feed Efficiency and Meat Quality Traits Through Advanced Biochemical and Molecular Assays

Published on: July 12, 2024

Better Multi-Breed Genomic Predictions for Tropical Bull Fertility Using a Breed-Adjusted Genomic Relationship

Antonio Reverter¹, Pâmela A Alexandre¹, Marina R S Fortes²

¹CSIRO Agriculture & Food, St. Lucia, Queensland, Australia.

Journal of Animal Breeding and Genetics = Zeitschrift Fur Tierzuchtung Und Zuchtungsbiologie

|April 22, 2026

Summary

This summary is machine-generated.

Multi-breed genomic predictions improve bull fertility selection in tropical cattle. Adjusting the genomic relationship matrix for breed-specific allele frequencies significantly enhances prediction accuracy, supporting sustainable beef production.

Keywords:

Brahman Santa Gertrudis fertility genomic prediction multi‐breed percent normal sperm scrotal circumference sheath score tropical beef

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Area of Science:

Animal Genetics
Reproductive Biology
Agricultural Science

Background:

Climate change adaptation necessitates sustainable breeding in tropical agriculture.
Bull fertility traits are crucial for beef cattle operations in tropical environments.

Purpose of the Study:

To evaluate multi-breed genomic prediction models for bull fertility traits in tropical cattle.
To compare genomic relationship matrices adjusted and unadjusted for breed-specific allele frequencies.

Main Methods:

Genomic predictions were generated for Brahman, Santa Gertrudis, and UltraBlack bulls.
Five models were tested: three single-breed and two multi-breed (using GRM_u and GRM_a).
Cross-validation was used to assess bias, dispersion, and accuracy of genomic predictions.

Main Results:

Adjusting the genomic relationship matrix (GRM_a) improved prediction accuracy for scrotal circumference (3.7%), sheath score (2.6%), and percent normal sperm (26.2%).
Heritability estimates varied between GRM_u and GRM_a models, with GRM_a showing potentially lower estimates for percent normal sperm.
Genetic correlations were similar, except for sheath score and percent normal sperm, which became more negative with GRM_a.

Conclusions:

Multi-breed genomic predictions offer a viable alternative to single-breed systems for tropical bull fertility.
Adjusting the genomic relationship matrix for breed-specific allele frequencies is computationally justified by improved prediction accuracy.
These findings support early selection for bull fertility, enhancing genetic improvement in tropical beef production.