Exploring genomic selection opportunities in Italian local cattle breed

Here we assessed the impact of genomic selection (GS) on 4 Italian local cattle breeds: Rendena (REN), Reggiana, Alpine Grey, and Valdostana. Our objectives were i) to compare current models (PBLUP) with GS for milk yield, and ii) to evaluate potential gains due to GS. To integrate SNP data with production records, we included phenotypic data >2010. Imputation achieved an average accuracy of 95%, and genomic EBVs (gEVB) were estimated with ssGBLUP. PBLUP and ssGBLUP were compared using a LR approach, with young animals serving as validation cohort. Across all breeds, ssGBLUP consistently outperformed (i.e., in REN 0.31 vs. 0.45 of accuracy for PBLUP and ssGBLUP, resp.). Notably, ssGBLUP showed higher accuracy in gEBVs, particularly in young bulls. Comparing current progeny testing to scenarios involving selection of young bulls on gEBVs, we observed greater genetic gains with GS, along with a reduction in inbreeding due to a larger pool of reproducers. This study highlights the favourable application of GS in local cattle breeds. Acknowledgements: Funded within the “Agritech” – Next-Generation EU PNRR – Missione 4 Comp. 2, Invest. 1.4 – D.D. 1032 17/06/2022, CN00000022. Also funded within PSRN – Dual Breeding 2 (CUP J61J18000030005, J51J18000000005, J71J18000020005, J81J18000030005), and by PRIN 2022 – Research Project n. 2022F43HWL.