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. 2025 Jun 13;15(12):1754.
doi: 10.3390/ani15121754.

Genome-Wide Association Study for Individual Primal Cut Quality Traits in Canadian Commercial Crossbred Pigs

Affiliations

Genome-Wide Association Study for Individual Primal Cut Quality Traits in Canadian Commercial Crossbred Pigs

Zohre Mozduri et al. Animals (Basel). .

Abstract

This study identified genomic variants and potential candidate genes associated with 11 primal cut traits (back fat, belly fat, total fat, loin fat, ham fat, picnic fat, butt fat, loin intramuscular fat content, ham side fat, shoulder dorsal fat, and belly side fat thicknesses) in Canadian commercial crossbred pigs. Genome-wide association studies using whole genome sequencing data were conducted using genotyping data from 1118 commercial crossbred pigs. This analysis revealed multiple QTLs across chromosomes SSC1, 2, 3, 6, 7, 9, 14, 15, and 17, associated with fat traits. Notably, an SNP at position 160,230,075 bp on SSC1 was significantly associated with multiple fat traits, including belly fat, butt fat, ham fat, loin fat, picnic fat, and side fat. Common genes in windows associated with multiple traits, such as MC4R, RNF152, and CDH20 were shared across these traits, suggesting pleiotropic effects. Some of the QTLs were near previously identified QTLs or candidate genes that have been reported to be linked to meat quality traits associated with backfat and intramuscular fat. Other candidate genes identified in the study include TNFRSF11A, LEPR, and genes from the SERPINB family, highlighting their roles in fat deposition and composition. Additional candidate genes were also implicated in regulation of fat metabolism, adipogenesis, and adiposity. These findings offer valuable insights into the genetic architecture of fat traits in pigs, which could inform breeding strategies aimed at improving the pork quality.

Keywords: SNPs; fat metabolism; pork quality; primal fat; whole genome sequencing.

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Conflict of interest statement

Kerry Houlahan and Robert Kemp were employees of Genesus Genetic Technology Inc. at the time of the study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Manhattan and QQ plot of GWAS for individual primal cut traits: (A) backfat (λ = 0.97), (B) picnic fat% (λ = 0.98), (C) butt fat% (λ = 0.96), (D) loin fat% (λ = 0.97), (E) ham fat% (λ = 0.96), (F) belly fat (λ = 0.96), and (G) Total fat (λ = 0.97) in commercial pigs. The horizontal red line indicates the genome-wide significance threshold (significant threshold p < 2.62 × 10−7 correct for multiple testing), we applied corrected for multiple testing using the simple method described by Gao et al. (2008) [24].
Figure 1
Figure 1
Manhattan and QQ plot of GWAS for individual primal cut traits: (A) backfat (λ = 0.97), (B) picnic fat% (λ = 0.98), (C) butt fat% (λ = 0.96), (D) loin fat% (λ = 0.97), (E) ham fat% (λ = 0.96), (F) belly fat (λ = 0.96), and (G) Total fat (λ = 0.97) in commercial pigs. The horizontal red line indicates the genome-wide significance threshold (significant threshold p < 2.62 × 10−7 correct for multiple testing), we applied corrected for multiple testing using the simple method described by Gao et al. (2008) [24].
Figure 2
Figure 2
Manhattan and QQ plot of GWAS for individual primal cut traits: (A) IMF (λ = 0.98), (B) ham side fat thickness (λ = 0.98), (C) shoulder dorsal fat (λ = 0.94) and (D) belly side fat (λ = 0.96) in commercial pigs. The horizontal red line indicates the genome-wide significance threshold (significant threshold p < 2.62 × 10−7 correct for multiple testing), we applied corrected for multiple testing using the simple method described by Gao et al. (2008) [24]. Part 2.
Figure 2
Figure 2
Manhattan and QQ plot of GWAS for individual primal cut traits: (A) IMF (λ = 0.98), (B) ham side fat thickness (λ = 0.98), (C) shoulder dorsal fat (λ = 0.94) and (D) belly side fat (λ = 0.96) in commercial pigs. The horizontal red line indicates the genome-wide significance threshold (significant threshold p < 2.62 × 10−7 correct for multiple testing), we applied corrected for multiple testing using the simple method described by Gao et al. (2008) [24]. Part 2.
Figure 3
Figure 3
Upset plot showing the number of common SNPs shared among the 11 traits in our GWAS analysis. Notably, SNP 1:160230075A:C was significantly associated with six fat traits: belly fat, butt fat, ham fat, loin fat, picnic fat, and side fat, and is detailed in Table 4. Two key SNPs were found to be associated with butt fat, loin fat, and total fat; for example, 1:160526956C:T. In addition, six SNPs—such as 1:160174493T:A, 1:160277320G:A, and 1:160044355T:G—were commonly associated with butt fat, ham fat, and picnic fat. Furthermore, a total of 13 SNPs, including 1:160452236C:T, 1:160521384A:T, and 1:160494546G:A (as examples), were jointly associated with butt fat, ham fat, and loin fat. A complete list of key SNPs with pleiotropic effects is provided in Table 4.
Figure 4
Figure 4
Heatmap illustrating gene–trait associations based on shared SNPs identified in Canadian commercial crossbred pigs. Only genes associated with more than two primal cut traits (i.e., 2, 3, 4, or 6 traits) through shared SNPs are included. Each cell indicates whether a gene (rows) is associated with a given trait (columns), based on overlapping SNPs. Blue cells represent confirmed gene–trait associations, while white cells indicate the absence of association. This visualization highlights pleiotropic genes involved in multiple traits, providing insight into their functional relevance. Gene–trait relationships are derived from the significant SNPs detailed in Table 4, which summarizes mutation types, minor allele frequencies (MAF), genotype distributions, and associated genes for each pleiotropic SNP.
Figure 5
Figure 5
Upset plot displaying the overlapping genes shared among the 11 traits in our GWAS analysis.

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