National single-step genomic method that integrates multi-national genomic information

Area of Science:

• Animal Breeding and Genetics
• Genomic Evaluation
• Quantitative Genetics

Background:

• National genetic evaluations often lack complete foreign data, impacting unbiased breeding value estimation.
• Traditional methods like Multiple Across-Country Evaluation (MACE) address this but have limitations in genomic selection.
• Multi-step genomic evaluations may assume data independence, which is not always accurate.

Purpose of the Study:

• To develop a national single-step genomic BLUP (ssGBLUP) method for integrating multi-national genomic estimated breeding values (EBV) and reliabilities.
• To avoid double counting of dependent data contributions from various national and international evaluations.
• To enhance the accuracy and transparency of genetic evaluations in breeding programs.

Main Methods:

• Developed a single-step genomic BLUP that jointly incorporates national phenotypic, pedigree, and genomic data.
• Integrated multi-national genomic information, including EBVs and reliabilities, from international consortia.
• Implemented a method to prevent redundant data usage from an animal's own records and relatives' records.

Main Results:

• Demonstrated the method's effectiveness using Brown Swiss sires in Slovenian national evaluations.
• Showcased an increase in the reliability of national genomic evaluations.
• Achieved consistent ranking of all animals (bulls, cows, young stock) and expanded the genomic training population size.

Conclusions:

• The developed ssGBLUP method successfully integrates multi-national genomic data, improving national evaluation reliability.
• This approach leads to more accurate and consistent animal rankings, facilitating more efficient breeding program management.
• The method enhances transparency and increases the size of the genomic training population, crucial for advancing genomic selection.