Genetic Parameter Estimation with Normal and Poisson Error Mixed Models for Teat Number of Swine

Genomic evaluation and genome-wide association studies for total number of teats in a combined American and Danish Yorkshire pig populations selected in China

Joint genomic evaluation by combining data recordings and genomic information from different pig herds and populations is of interest for pig breeding companies because the efficiency of genomic selection (GS) could be further improved. In this work, an efficient strategy of joint genomic evaluation combining data from multiple pig populations is investigated. Total Teat Number (TTN), a trait that is equally recorded on 13 060 American Yorkshire (AY) populations (~14.68 teats) and 10 060 Danish Yorkshire (DY) pigs (~14.29 teats), was used to explore the feasibility and accuracy of GS combining datasets from different populations. We first estimated the genetic correlation (rg) of TTN between AY and DY pig populations (rg=0.79, se=0.23). Then we employed the genome-wide association study (GWAS) to identify QTL regions that are significantly associated with TTN and investigate the genetic architecture of TTN in different populations. Our results suggested that the genomic regions controlling TTN are slight different in the two Yorkshire populations, where the candidate QTL regions were on SSC 7 and SSC 8 for AY population and on SSC 7 for DY population. Finally, we explored an optimal way of genomic prediction for TTN via three different Genomic Best Linear Unbiased Prediction (GBLUP) models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multi-trait model, predictive abilities for both Yorkshire populations improve. As a conclusion, joint genomic evaluation for target traits in multiple pig populations is feasible in practice and more accurate, provided a proper model is used.