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Genomic evaluation for two-way crossbred performance in cattle.

Quanshun Mei^1,2, Huiming Liu³, Shuhong Zhao¹

¹Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan, 430070, China.

Genetics, Selection, Evolution : GSE

|March 18, 2023

Summary

Metafounder ssGBLUP (MF-ssGBLUP) and breed-specific ssGBLUP (BS-ssGBLUP) improve predictive ability for crossbred cattle performance over standard ssGBLUP. MF-ssGBLUP offers more robust superiority, especially for average daily gain and feed conversion ratio.

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Area of Science:

Animal breeding and genetics
Quantitative genetics
Genomic selection

Background:

Dairy cattle production increasingly uses crossbreeding, necessitating advanced genetic evaluation methods.
Existing single-step genomic best linear unbiased prediction (ssGBLUP) methods like MF-ssGBLUP and BS-ssGBLUP need evaluation for two-way crossbreds.
Understanding genetic parameter estimation differences between ssGBLUP methods is crucial.

Purpose of the Study:

Compare genetic parameter estimates for average daily gain (ADG) and feed conversion ratio (FCR) using ssGBLUP, MF-ssGBLUP, and BS-ssGBLUP.
Evaluate the impact of these ssGBLUP methods on the predictive ability for crossbred performance.
Assess the robustness and superiority of MF-ssGBLUP and BS-ssGBLUP over standard ssGBLUP.

Main Methods:

Bivariate ssGBLUP, MF-ssGBLUP, and BS-ssGBLUP models were applied for genetic evaluation of ADG and FCR.
Predictive ability was measured using bias, dispersion, population accuracy, and ratio of population accuracies via linear regression.
Genetic parameters, including heritability and variance components, were estimated and compared across methods.

Main Results:

Heritabilities for ADG and FCR were low across all methods.
BS-ssGBLUP showed large deviations in genetic parameter estimates for ADG compared to ssGBLUP and MF-ssGBLUP.
MF-ssGBLUP consistently yielded higher population accuracies than ssGBLUP for both traits; BS-ssGBLUP was highest for FCR and lowest for ADG.

Conclusions:

MF-ssGBLUP and BS-ssGBLUP demonstrate superior predictive ability over standard ssGBLUP in two-way crossbred cattle.
MF-ssGBLUP shows more consistent superiority compared to BS-ssGBLUP, particularly when variance components are aligned.
These findings support the use of advanced ssGBLUP methods for improved genetic evaluations in crossbred dairy cattle populations.