Technical note: Genomic evaluation for crossbred performance in a single-step approach with metafounders

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Genomic Prediction

Background:

• Single-step genomic best linear unbiased prediction (ssGBLUP) is effective for purebred and crossbred performance in pigs.
• Current ssGBLUP requires genotype phasing and allele breed origin inference in crossbreds, adding inconvenience.
• The metafounder concept offers a novel approach to handle relationships within and across base populations.

Purpose of the Study:

• To re-evaluate purebred and crossbred pig performance using ssGBLUP with the metafounder concept.
• To estimate genetic variances and correlations between purebred and crossbred performances.
• To compare model-based reliabilities and predictive abilities of different ssGBLUP scenarios.

Main Methods:

• Utilized ssGBLUP with two metafounders on data from Danish Landrace, Yorkshire, and 2-way crossbred pigs.
• Re-estimated genetic variances and genetic correlations between purebred and crossbred performances.
• Compared predictive abilities and reliabilities against a previous study using identical data but requiring known breed origins.

Main Results:

• Found similarities in base individual relationships within Landrace and Yorkshire populations.
• Confirmed relatedness between the ancestor populations of Landrace and Yorkshire.
• ssGBLUP with metafounders demonstrated comparable model-based reliabilities and predictive abilities to the phasing method at reduced complexity.

Conclusions:

• ssGBLUP incorporating the metafounder concept provides an efficient and effective alternative for genomic predictions in crossbred populations.
• This method simplifies the process by eliminating the need for genotype phasing and allele origin inference.
• The metafounder approach ensures automatic compatibility between genomic and pedigree-based relationships, streamlining analyses.