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Optimizing genomic prediction for Australian Red dairy cattle.

I van den Berg¹, I M MacLeod¹, C M Reich¹

¹Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3083, Australia.

Journal of Dairy Science

|April 26, 2020

Summary

This summary is machine-generated.

Optimizing genomic prediction for Australian Red dairy cattle involves carefully selecting reference populations. Including too many individuals from a dominant breed like Holstein can decrease prediction reliability.

Keywords:

Australian Red dairy cattle genomic prediction multi-breed prediction reference population

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Area of Science:

Animal Genetics and Breeding
Dairy Cattle Genomics
Quantitative Genetics

Background:

Genomic prediction reliability is challenged in breeds with small reference populations, such as Australian Red dairy cattle.
Incorporating diverse breeds into reference populations can increase size but requires careful consideration of relatedness.
Optimizing reference population composition is crucial for accurate genomic predictions in underrepresented breeds.

Purpose of the Study:

To determine the optimal reference population structure for enhancing genomic prediction reliability in Australian Red dairy cattle.
To evaluate the impact of reference population size and breed composition on prediction accuracy.
To compare different genomic prediction methodologies (GBLUP, Bayes R) for multi-breed applications.

Main Methods:

Utilized a reference population including Holstein and Jersey cattle alongside Australian Red cows.
Employed single-trait and multi-trait genomic best linear unbiased predictor (GBLUP) and single-trait Bayes R methods.
Tested various reference population compositions, varying breed inclusion and relatedness to the Australian Red validation population.

Main Results:

Multi-trait GBLUP demonstrated higher prediction reliabilities than single-trait GBLUP by treating traits across breeds as correlated.
Adding a small number of closely related Holstein individuals improved reliability, but larger numbers decreased it.
Over-reliance on a single dominant breed (Holstein) within a multi-breed reference population reduced prediction reliability for Australian Reds.

Conclusions:

The composition, not just the size, of the reference population is critical for accurate genomic prediction in smaller breeds.
Multi-trait analyses are more effective than single-trait analyses when incorporating data from different but related dairy breeds.
Careful management of breed proportions in multi-breed reference populations is essential to avoid diluting prediction accuracy.