A combined GWAS approach reveals key loci for socially-affected traits in Yorkshire pigs

Socially affected traits in livestock, where an individual's phenotype is influenced by the genotypes of its social partners, present a challenge for genetic analysis. Understanding the genetic architecture of these traits is crucial for effective breeding programs aimed at improving productivity and welfare. In pigs, numerous traits such as feed intake, growth rate, and even behavior are known to be affected by social interactions. Traditional genetic analyses often focus on direct genetic effects (DGE), the effect of an individual's own genotype on its phenotype, neglecting the substantial influence of social genetic effects (SGE), the effect of other individuals' genotypes on a given individual's phenotype. This study addresses this gap by employing a combined single-locus and haplotype-based GWAS to unravel the genetic basis of both DGE and SGE for eight socially affected traits in Yorkshire pigs. Yorkshire pigs are a commercially important breed, and understanding the interplay between DGE and SGE in this breed can contribute significantly to optimizing breeding strategies. This study's innovative approach is to use imputed whole-genome sequence (WGS) data, providing much higher marker density than previously used SNP chips, to identify genetic variants associated with both DGE and SGE, offering a more comprehensive understanding of the complex genetic architecture of socially affected traits in pigs. The significance of this research lies in its potential to improve breeding programs by incorporating both DGE and SGE into selection indexes, leading to more efficient and sustainable pig production.

Previous research has highlighted the importance of both direct and social genetic effects in shaping various economically important traits in pigs. Studies have shown the considerable contribution of social effects to the heritable variation in finishing traits, emphasizing the necessity of incorporating SGE in genetic evaluations. Several studies using different approaches, including single-step GWAS, have identified quantitative trait loci (QTL) associated with both DGE and SGE, although the results vary across studies and traits. There is a need for further research that leverages high-density marker data, such as WGS, to improve the power and resolution of QTL detection for socially-affected traits. There is limited literature on the combined application of single-locus and haplotype-based GWAS on imputed WGS data for the genetic dissection of socially-affected traits in pigs. The current study seeks to bridge this gap by using a comprehensive approach that combines these methods.

This study utilized phenotypic data from 1204 Yorkshire pigs obtained from a commercial pig performance testing station. Eight socially affected traits were analyzed: average daily gain (ADG), days to 100 kg (D100), backfat thickness at 100 kg (B100), average daily feed intake (ADFI), residual feed intake (RFI), feed conversion ratio (FCR), time in feeder per day (TPD), and feeding speed (FS). Direct and social genetic effects (DGE and SGE) for each trait were estimated using a social genetic effect model implemented in DMU software. Deregressed breeding values (EBVs) for DGE and SGE were then used in the association analyses. Genotyping was performed using the Illumina Porcine SNP50K BeadChip. WGS data from a reference population of 60 pigs (20 Landrace and 40 Yorkshire pigs) were used for imputation to WGS level in the target population using Beagle 5.1 software. The imputation accuracy was assessed using Beagle R². After quality control, 3,072,572 SNPs were retained. Haplotype blocks were constructed using PLINK software, and haplotype-based GWAS was performed along with single-locus GWAS (both chip-based and imputed-based) using GEMMA software. Significant SNPs and haplotype loci were identified using Bonferroni correction. Candidate genes within 1 Mb regions of significant SNPs were identified, and gene ontology (GO) analysis was conducted using DAVID Bioinformatics Resources to explore the biological functions of these genes. Finally, the results were compared with the PigQTL database to assess replication with previously identified QTLs.

The study identified 19 SNPs and 25 haplotype loci associated with DGE across the eight traits, and 19 SNPs and 11 haplotype loci associated with SGE. Two significant SNPs (SSC6:18,635,874 and SSC6:18,635,895) were shared by a significant haplotype locus (HapL1412, with haplotype allele 'GGG') for both DGE and SGE in ADFI. The MT3 gene, known to be involved in growth, nervous, and immune processes, was identified as a candidate gene within this region. Significant associations were predominantly found for ADFI and ADG, with fewer associations observed for other traits. The study demonstrated that haplotype-based GWAS identified more associations than single-locus GWAS for both DGE and SGE. A comparison of DGE and SGE revealed distinct genetic architectures for many traits. Several candidate genes were identified, including CDH11, IQCM, and genes in the zinc-finger protein family. The identified SNPs and haplotype loci frequently overlapped with previously reported QTL in the PigQTL database, particularly for DGE. GO analysis indicated enrichment of pathways associated with nucleic acid binding, calcium binding, and metal ion binding.

This study's findings provide strong evidence for the distinct genetic architectures underlying DGE and SGE for socially-affected traits in Yorkshire pigs. The identification of shared SNPs and haplotype loci across multiple traits highlights the complexity and pleiotropic nature of the genetic control of these traits. The discovery of the MT3 gene as a candidate gene associated with both DGE and SGE for feed intake is a significant contribution. MT3's involvement in growth, nervous, and immune processes suggests potential indirect effects on feed intake through these pathways. The identification of several other candidate genes, particularly in pathways related to cell adhesion, growth, and transcription, further underscores the complex interplay between genetic and social factors in determining phenotypic outcomes. These findings are relevant for pig breeding programs, suggesting that incorporating both DGE and SGE into selection indexes would improve the accuracy of genetic evaluations and lead to more efficient genetic improvement. This integrated approach can facilitate selection for pigs with both high productivity and improved welfare.

This study successfully employed a combined single-locus and haplotype-based GWAS using imputed WGS data to identify genetic variants influencing both DGE and SGE for socially affected traits in Yorkshire pigs. The results highlight the distinct genetic architectures of DGE and SGE, suggesting that consideration of both is crucial for effective genetic improvement. The identification of candidate genes such as MT3 and the overlap with previously reported QTL provides valuable insights into the biological mechanisms underlying these traits. Future studies could focus on validating these findings with larger datasets and exploring the functional roles of identified candidate genes in greater detail. Additionally, exploring the potential interaction effects between DGE and SGE warrants further investigation.

The study's sample size, while larger than many previous studies in this area, could be increased to further improve the power of the association analysis and enhance the precision of the estimates. The use of imputation introduces potential errors, although the high imputation accuracy achieved in this study mitigates this issue. The study focused on a single breed of pigs; therefore, the generalizability of the findings to other breeds needs to be further investigated. The social genetic model utilized assumes a specific structure of social interaction, and other models could be explored in future studies.