Association and expression quantitative trait loci (eQTL) analysis of porcine AMBP, GC and PPP1R3B genes with meat quality traits

Abstract

The aim of this research was to screen polymorphism and to perform association study of porcine AMBP (alpha-1-microglobulin/bikunin precursor), GC (group-specific component protein) and PPP1R3B (protein phosphatase 1, regulatory (inhibitor) subunit 3B) genes with meat quality traits as well as to unravel the transcriptional regulation of these genes by expression QTL (eQTL) study. For this purpose, Duroc×Pietrain F2 resource population (DuPi; n=313) and a commercial breed Pietrain (Pi; n=110) were used for association and only DuPi for expression and eQTL study. A SNP was identified in the genes AMBP (g.22229C>T), GC (g.398C>T) and PPP1R3B (c.479A>G), respectively. In DuPi SNP of AMBP was associated (P<0.05) with meat colour, pH(1L), pH(24L), pH(24H) and conductivity(24L); SNP of GC showed tendency to association (P<0.10) with pH24H, conductivity(1L) and thawing loss, and SNP of PPP1R3B was associated (P<0.05) with meat colour, pH(1L), pH(24L), pH(24H) and shear force. In Pi SNPs of AMBP and GC was associated with pH(24H) and PPP1R3B SNP was associated with pH(24L). The mRNA levels in Longissimus dorsi muscle tissue of these three genes were evaluated by using qRT-PCR to identify association between gene expression and meat quality traits as well as to analyse eQTL. The mRNA expression of PPP1R3B associated with pH(24L) (P<0.05). Expression of these three genes was higher in animals with low pH of muscle. Linkage analysis using QTL Express revealed ten trans-regulated eQTL on seven porcine autosomes. Suggestive eQTL [P<0.05, CW (chromosome-wide)] were found for PPP1R3B on SSC3 and 13. These results revealed that genetic variation and gene expression of these genes are associated with the meat quality traits. These three genes could influence meat quality and could be potential positional, physiological and functional candidate gene for meat quality traits in pigs. However, the analysis of eQTL also suggested that we need to consider additional genes encoding for transcription factors (TF), via fine-mapping underlying the eQTL peaks, in order to understand interaction among these genes.