Deciphering the regulation of porcine genes influencing growth, fatness and yield-related traits through genetical genomics

• Published in: Mammalian genome Vol. 28; no. 3-4; pp. 130 - 142
• Main Authors: Martínez-Montes, Angel M., Muiños-Bühl, Anixa, Fernández, Almudena, Folch, Josep M., Ibáñez-Escriche, Noelia, Fernández, Ana I.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2017; Springer Nature B.V
• Subjects: Animal Genetics and Genomics; Animals; backcrossing; Biomedical and Life Sciences; Cell Biology; chromosomes; Chromosomes - genetics; gene expression; Gene Expression Regulation - genetics; genes; Genome-Wide Association Study; Genomics; Genotype; Human Genetics; landraces; Life Sciences; longissimus muscle; Meat; meat quality; messenger RNA; microarray technology; non-coding RNA; Phenotype; Polymorphism, Single Nucleotide; quantitative trait loci; Quantitative Trait Loci - genetics; RNA, Long Noncoding - genetics; single nucleotide polymorphism; swine; Swine - genetics; Swine - growth & development; Swine - metabolism; Thioredoxin-Disulfide Reductase - genetics; transcription (genetics); Residual Feed Intake; Candidate SNPs; Minimum Allele Frequency; Meat Quality Trait; Potential Causal Variant
• ISSN: 0938-8990; 1432-1777; 1432-1777
• DOI: 10.1007/s00335-016-9674-3

Genetical genomics approaches aim at identifying quantitative trait loci for molecular traits, also known as intermediate phenotypes, such as gene expression, that could link variation in genetic information to physiological traits. In the current study, an expression GWAS has been carried out on an experimental Iberian × Landrace backcross in order to identify the genomic regions regulating the gene expression of those genes whose expression is correlated with growth, fat deposition, and premium cut yield measures in pig. The analyses were conducted exploiting Porcine 60K SNP BeadChip genotypes and Porcine Expression Microarray data hybridized on mRNA from Longissimus dorsi muscle. In order to focus the analysis on productive traits and reduce the number of analyses, only those probesets whose expression showed significant correlation with at least one of the seven phenotypes of interest were selected for the eGWAS. A total of 63 eQTL regions were identified with effects on 36 different transcripts. Those eQTLs overlapping with phenotypic QTLs on SSC4, SSC9, SSC13, and SSC17 chromosomes previously detected in the same animal material were further analyzed. Moreover, candidate genes and SNPs were analyzed. Among the most promising results, a long non-coding RNA, ALDBSSCG0000001928 , was identified, whose expression is correlated with premium cut yield. Association analysis and in silico sequence domain annotation support TXNRD 3 polymorphisms as candidate to regulate ALDBSSCG0000001928 expression, which can be involved in the transcriptional regulation of surrounding genes, affecting productive and meat quality traits.