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

J Anim Sci. 2022 Jul 1;100(7):skac174. doi: 10.1093/jas/skac174.

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 to identify quantitative trait locus (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 slightly different in the two Yorkshire populations, where the candidate QTL regions were on SSC 7 and SSC 8 for the AY population and on SSC 7 for the DY population. Finally, we explored an optimal way of genomic prediction for TTN via three different genomic best linear unbiased prediction models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multitrait 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.

Keywords: association; genomic prediction; multiple populations; teats number.

Plain language summary

This study aimed at investigating joint genomic evaluation by combining data from multiple pig populations. Genomic evaluation is commonly applied in the pig industry to select the best animals to be the parents for the next generation. A bottleneck of genomic evaluation is that the selection accuracy is not high enough. To increase the selection accuracy, in theory, larger datasets are needed. In this article, multiple pig populations were considered together and we explored the feasibility and accuracy of genomic evaluation combining datasets from different populations. To realize the objective, total teat number (TTN), a trait that is equally recorded across different populations, was chosen. We first estimated the genetic correlation of TTN between American and Danish Yorkshire pig populations. Then to interpret why such genetic correlation was obtained, we employed the genome-wide association study to identify quantitative trait locus regions that are significantly associated with TTN and investigated the genetic architecture of TTN in different populations. Finally, we explored an optimal way of genomic prediction for TTN via three different genomic models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multitrait model, predictive abilities for both Yorkshire populations improve.

MeSH terms

  • Animals
  • Denmark
  • Genome-Wide Association Study* / veterinary
  • Genomics / methods
  • Genotype
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Quantitative Trait Loci
  • Swine / genetics