Association of porcine IGF binding protein-5 gene with meat quality

Effect of the <i>IGF-I</i> gene polymorphism on growth, body size, carcass and meat quality traits in Coloured Polish Merino sheep

Abstract. Insulin-like growth factor I, encoded by the IGF-I gene, plays a role in cell growth and differentiation, embryogenesis, metabolism regulation, skeletal growth, and protein synthesis. The aims of this study were to investigate the polymorphism in the 5′ flanking region of the IGF-I gene and evaluate associations between the single-nucleotide polymorphism (SNP) in this gene and growth, body size, carcass and meat quality traits in Coloured Polish Merino sheep. In total 78 live and post mortem traits were investigated. Polymorphism in the IGF-I gene was identified with the use of the polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) method in 305 Coloured Polish Merino sheep. In association studies, traits of interest were analysed with the use of the MIXED and GENMOD procedures of the SAS statistical package. Two alleles named A and B, and two IGF-I genotypes – AA and AB – were detected. The A allele and the AA genotype were predominant, with the frequencies of 91.6 and 83.3 %, respectively. The IGF-I genotype was found to have a highly significant effect on fore shank weight (P  =  0.006), kidney fat class (P  =  0.002) and EUROP fat class (P  =  0.005). Furthermore, the IGF-I genotype significantly affected external fatness of carcass class (P  =  0.038), drip loss (P  =  0.049), and subjective assessment of meat colour (P  =  0.043), and it tended to be associated with longissimus dorsi (LD) muscle width (P  =  0.063) and flavour (0.067). Concluding, the IGF-I gene could be considered as a candidate gene of selected carcass and meat quality traits in sheep.

Whole-genome association analysis of pork meat pH revealed three significant regions and several potential genes in Finnish Yorkshire pigs

Background

One of the most commonly used quality measurements of pork is pH measured 24 h after slaughter. The most probable mode of inheritance for this trait is oligogenic with several known major genes, such as PRKAG3. In this study, we used whole-genome SNP genotypes of over 700 AI boars; after a quality check, 42,385 SNPs remained for association analysis. All the boars were purebred Finnish Yorkshire. To account for relatedness of the animals, a pedigree-based relationship matrix was used in a mixed linear model to test the effect of SNPs on pH measured from loin. A bioinformatics analysis was performed to identify the most promising genes in the significant regions related to meat quality.

Results

Genome-wide association study (GWAS) revealed three significant chromosomal regions: one on chromosome 3 (39.9 Mb–40.1 Mb) and two on chromosome 15 (58.5 Mb–60.5 Mb and 132 Mb–135 Mb including PRKAG3). A conditional analysis with a significant SNP in the PRKAG3 region, MARC0083357, as a covariate in the model retained the significant SNPs on chromosome 3. Even though linkage disequilibrium was relatively high over a long distance between MARC0083357 and other significant SNPs on chromosome 15, some SNPs retained their significance in the conditional analysis, even in the vicinity of PRKAG3. The significant regions harbored several genes, including two genes involved in cyclic AMP (cAMP) signaling: ADCY9 and CREBBP. Based on functional and transcription factor-gene networks, the most promising candidate genes for meat pH are ADCY9, CREBBP, TRAP1, NRG1, PRKAG3, VIL1, TNS1, and IGFBP5, and the key transcription factors related to these genes are HNF4A, PPARG, and Nkx2-5.

Conclusions

Based on SNP association, pathway, and transcription factor analysis, we were able to identify several genes with potential to control muscle cell homeostasis and meat quality. The associated SNPs can be used in selection for better pork. We also showed that post-GWAS analysis reveals important information about the genes’ potential role on meat quality. The gained information can be used in later functional studies.