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

Abstract

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.

Genome‐wide association analysis revealed new QTL and candidate genes affecting the teat number in Dutch Large White pigs

“…In this study, the mean values of LTN, RTN and TTN were 7.81, 7.98 and 15.79, respectively, which were slightly higher the values in previous reports (Bovo et al, 2021;Fang et al, 2022;Tan et al, 2016;Tang et al, 2016). The coefficients of variation were 8.07% for LTN, 8.02% for RTN and 6.59% for TTN, indicating that there are some variations in the phenotypes of the TNUM in the study population, and this population is conducive to mining candidate genes associated with TNUM.…”

“…A lack of teats is also detrimental to the weight gain and growth of piglets (Chalkias et al, 2013). Therefore, in the process of pig breeding, the sow teat number (TNUM) trait has attracted the attention of breeding researchers (Fang et al, 2022). It is important to identify genetic loci and genes that influence the teat number trait of sows, which contributes to the genetic improvement of sow reproductive performance.The teat number of different breeds varies greatly in pigs.…”

Genome‐wide re‐sequencing data reveals the genetic diversity and population structure of Wenchang chicken in China

“…Single nucleotide polymorphisms lie at the heart of the investigation of modern genetics. In the field of animal research, genome‐wide association analysis (Fang et al, 2022; Yang et al, 2022) and selection signature analysis (Nanaei et al, 2022; Yuan et al, 2022) are now being widely applied to reveal the genetic mechanisms of complex traits at the genome level. The prerequisite of these analyses are genome‐wide genetic markers.…”

Identifying selection signatures for litter size in Guangxi Bama Xiang pigs

“…Litter size is a low heritability trait of about 0.1 (Martínez‐Giner et al, 2011; Merks et al, 2012), thus the improvement of litter size through traditional breeding is difficult. The marker‐assisted selection (Dekkers, 2007) and genome selection (Fang et al, 2022) were used in animal breeding with the development of biotechnology, which enhanced the genetic progress effectively. However, the lack of reliable molecular labels limits the effectiveness of molecular breeding.…”

“…selection (Dekkers, 2007) and genome selection (Fang et al, 2022) were used in animal breeding with the development of biotechnology, which enhanced the genetic progress effectively. However, the lack of reliable molecular labels limits the effectiveness of molecular breeding.…”