Genome Selection and Genome-Wide Association Analyses for Litter Size Traits in Large White Pigs

Abstract

(1) Background: Litter size traits are critical for pig breeding efficiency but pose challenges due to low heritability and sex-limited influences. This study aimed to elucidate the genetic architecture and identify candidate genes for these traits in Large White pigs using genomic selection (GS) and genome-wide association analyses (GWAS). (2) Methods: This study utilized phenotypic data from nine litter size traits in Large White sows. Genotyping-by-sequencing (GBS) was performed to obtain genotype data, retaining 153,782 high-quality SNPs after quality control. Genetic evaluation was conducted using single-step genomic best linear unbiased prediction (ssGBLUP), with genetic parameters (heritability and genetic correlations) estimated via an animal model (repeatability model). To assess prediction accuracy, 10-fold cross-validation was employed to compare traditional BLUP with ssGBLUP. Furthermore, a single-step genome-wide association study (ssGWAS) integrated genomic information and pedigree-based relationship matrices to screen for significant SNPs associated with litter size traits across the genome. Functional analysis of key candidate genes was subsequently conducted based on ssGWAS results. (3) Results: Heritabilities for litter traits ranged from 0.01 to 0.06. ssGBLUP improved genomic prediction accuracy by 6.38-13.33% over BLUP. Six genomic windows explaining 1.07-1.77% of genetic variance were identified via ssGWAS, highlighting GPR12 on SSC11 as a key candidate gene linked to oocyte development. (4) Conclusions: This study demonstrates the efficacy of ssGBLUP for low-heritability traits and identifies GPR12 as a pivotal gene for litter size. Prioritizing NHB and LBWT in breeding programs could enhance genetic gains while mitigating adverse effects on piglet health. These findings advance genomic strategies for improving reproductive efficiency in swine.

Keywords: GS; Large White; genetic parameters; litter size traits; ssGWAS.

Figure 1

Manhattan plots for the percentage of genetic variance by 0.3 Mb window for litter size traits. gVar (%) represents the proportion of genetic variance explained by the 0.3 Mb window. The horizontal coordinate represents the chromosomes of pigs: total number born (TNB), number of piglets born alive (NBA), number of healthy births (NHB), rate of NHB (rNHB), number of weak births (NWB), number of deform fetus (NDF), number of stillborn (NSB), mummified pigs (MUMM), litter weight at birth (LBWT), and gVar (%) = the proportion of the genetic variance explained by the 0.3 Mb-adjacent SNP window.

Figure 2

Candidate region plots illustrating the two major candidate regions on SSC11 and SSC3. The results are displayed for the total number born (TNB) at approximately 4.0–4.8 Mb on SSC11 (left) and for mummified pigs (MUMM) at 126.8–127.8 Mb on SSC3 (right). Various levels of linkage disequilibrium between the primary SNP and surrounding SNPs are represented by distinct colors. gVar (%) denotes the proportion of the genetic variance explained by the 0.3 Mb-adjacent SNP window.