PSXI-2 - Genome-wide association study and possibilities for genomic selection of Simmental cattle breed in Russia

The implementation of genomic selection methods in dairy cattle is limited due to the size of the reference population, quantitative traits variability and genetic structure of population. The Simmental cattle and related breeds in Russia occupy the third place by registered cows - 87.6 thousand, and are bred from the western borders of central Russia to Yakutia in Siberia. The study aim was to search for QTL using as a pseudo phenotype sires’ EBV to validate the effectiveness of genomic assessments for Simmental cattle in Russia. Reference group based on 358 bulls from different Russian regional populations was formed. By the dataset of 61976 cows, using BLUP Animal Model approach, animals’ EBV were calculated. The GBLUP procedure was used to get genomic prediction (DGV). Genotype quality control selected of 37143 SNPs. GWAS analysis was perform by Plink 1.90. To prove DGV we used verification procedure to comparison with EBV in training population dataset that showed slightly moderate repeatability for 305-milk yield - 37.6%, milk fat - 39.8% and milk protein - 43.6%. Significant SNPs associated with bulls EBV according to milk production and fertility traits revealed for: 305-milk yield on BTA5 (ACO2,p=0.0005), BTA29 (NAP1L4, P = 0.00004; KCNQ1, P = 0.00004 ); fat percentage on BTA3 (ROR1, P = 0.0003), BTA14 (CRH, P = 0.0003; TRIM55, P = 0.0003; DNAJC5B, P = 0.0003; REX2, P = 0.0020; ZFHX4, P = 0.0020) BTA17 (TLR2, P = 0.0011); days open on BTA1 (TNIK, P = 0.0007; FNDC3B, P = 0.0007), BTA21 (IGF1R, P = 0.0002). Using Cattle QTL Database, the identified genes were associated with milk yield, fat and protein percentage, protein yield, somatic cell score, protein-to-fat ratio, stearic fatty acid content, calving ease, daughter pregnancy rate, stillbirth and inseminations per conception. GWAS results identified significant SNPs associated with milk production and fertility traits that will allow in the nearest future improve reliability for genomic prediction of young bulls and boost genetic trend in the Russian Simmental cattle population. The study was funded by RFBR within project No.17-29-08030