Metafounders May Reduce Bias in Composite Cattle Genomic Predictions - Kluska, Sabrina; Masuda, Yutaka; Ferraz, José Bento Sterman; Tsuruta, Shogo; Eler, Joanir Pereira; Baldi, Fernando; Lourenco, Daniela (Frontiers in Genetics, 2021)
Metafounders are pseudo-individuals that act as proxies for the animals in the base populations. When metafounders are used, individuals from different breeds can be related through the pedigree, improving the compatibility between genomic and pedigree relationships. The aim of this study was to investigate the use of metafounders and unknown parent groups in the genomic evaluation of a composite beef cattle population. Phenotypes were available for scrotal circumference at 14 months of age (SC14), postweaning gain (PWG), weaning weight (WW), and birth weight (BW). The pedigree included 680,551 animals, of which 1899 were genotyped for or imputed to around 30,000 SNPs. Evaluations were performed based on pedigree (BLUP), pedigree with unknown parent groups (BLUP_UPG), pedigree with metafounders (BLUP_MF), single-step genomic BLUP (ssGBLUP), ssGBLUP with unknown parent groups for genomic and pedigree relationship matrices (ssGBLUP_UPG) or only for the pedigree relationship matrices (ssGBLUP_UPGA), and ssGBLUP with metafounders (ssGBLUP_MF). Each evaluation considered either four or 10 groups that were assigned based on breed of founders and intermediate crosses. To evaluate the model performance, we used a validation method based on linear regression statistics to obtain accuracy, stability, dispersion, and bias of (G)EBV. Overall, relationships within and among metafounders were stronger in the scenario with 10 metafounders. Accuracy was greater for models with genomic information compared to BLUP. Also the stability of (G)EBVs was greater when genomic information was taken into account. Overall, pedigree-based methods had no inflation/deflation (slight differences from 1.0), except for WW that had regression coefficients from 0.77 to 0.80. The level of inflation/deflation in genomic models was small and trait-dependent. Compared to the regular ssGBLUP, ssGBLUP_MF and ssGBLUP_UPGA helped the regression coefficients to approach one. In general, the genomic models with metafounders seemed to be slightly more stable than models with UPG. This is because the results were more similar with different number of groups. Additionally, models with metafounders showed better genetic trends than ssGBLUP_UPG or ssGBLUP_UPGA. Metafounders can help to reduce bias in genomic evaluations of composite beef cattle populations without reducing the stability of GEBVs and providing adequate genetic trends.