GWAS using 2b-RAD sequencing identified three mastitis important SNPs via two-stage association analysis in Chinese Holstein cows

Background Bovine mastitis is a key disease restricting developing global dairy industry. Genomic wide association studies (GWAS) provided a convenient way to understand the biological basis of mastitis and better prevent or treat the disease. 2b-RADseq is a reduced-representation sequencing that offered a powerful method for genome-wide genetic marker development and genotyping. This study, GWAS using two-stage association analysis identified mastitis important genes’ single nucleotide polymorphisms (SNP) in Chinese Holstein cows. Results In the selected Chinese Holstein cows’ population, we identified 10,058 SNPs and predicted their allele frequencies. In stage I, 42 significant SNPs screened out in Chinese Holstein cows via Bayesian (P<0.001), while logistic regression model identified 51 SNPs (PT, PIC=0.2999; rs88640083, A>G, PIC=0.1676; rs20438858, G>A, PIC=0.3366) located in non-coding region (introns and intergenic) screened out associated with inflammation or immune response. GO enrichment analysis showed that they annotated to three genes (PTK2B, SYK and TNFRSF21), respectively. Stage II? case-control study used to verify three important SNPs associated with dairy cows mastitis traits in independent population. Data suggested that the correlation between these three SNPs (rs75762330, P<0.025; rs88640083, P<0.005; rs20438858, P<0.001) and mastitis traits in dairy cows were consistent with stage I. Conclusion Two-stage association analysis approved that three significant SNPs associated with mastitis traits in Chinese Holstein cows. Gene function analysis indicated that three genes (PTK2B, SYK and TNFRSF21) involved in inflammation and immune response of dairy cows. Suggesting that they as new candidate genes have an impact on mastitis susceptibility (PTK2B and SYK, OR>1) or resistance (TNFRSF21, OR<1) in Chinese Holstein cows.