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Expression profiling analysis for genes related to meat quality and carcass traits during postnatal development of backfat in two pig breeds

DOI: 10.1007/s11427-008-0090-0

Keywords: pig,adipose,microarray,differential gene expression,clustering analysis,gene regulatory network (GRN)

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Abstract:

The competitive equilibrium of fatty acid biosynthesis and oxidation in vivo determines porcine subcutaneous fat thickness (SFT) and intramuscular fat (IMF) content. Obese and lean-type pig breeds show obvious differences in adipose deposition; however, the molecular mechanism underlying this phenotypic variation remains unclear. We used pathway-focused oligo microarray studies to examine the expression changes of 140 genes associated with meat quality and carcass traits in backfat at five growth stages (1–5 months) of Landrace (a leaner, Western breed) and Taihu pigs (a fatty, indigenous, Chinese breed). Variance analysis (ANOVA) revealed that differences in the expression of 25 genes in Landrace pigs were significant (FDR adjusted permutation, P<0.05) among 5 growth stages. Gene class test (GCT) indicated that a gene-group was very significant between 2 pig breeds across 5 growth stages (P ErmineJ<0.01), which consisted of 23 genes encoding enzymes and regulatory proteins associated with lipid and steroid metabolism. These findings suggest that the distinct differences in fat deposition ability between Landrace and Taihu pigs may closely correlate with the expression changes of these genes. Clustering analysis revealed a very high level of significance (FDR adjusted, P<0.01) for 2 gene expression patterns in Landrace pigs and a high level of significance (FDR adjusted, P<0.05) for 2 gene expression patterns in Taihu pigs. Also, expression patterns of genes were more diversified in Taihu pigs than those in Landrace pigs, which suggests that the regulatory mechanism of micro-effect polygenes in adipocytes may be more complex in Taihu pigs than in Landrace pigs. Based on a dynamic Bayesian network (DBN) model, gene regulatory networks (GRNs) were reconstructed from time-series data for each pig breed. These two GRNs initially revealed the distinct differences in physiological and biochemical aspects of adipose metabolism between the two pig breeds; from these results, some potential key genes could be identified. Quantitative, real-time RT-PCR (QRT-PCR) was used to verify the microarray data for five modulated genes, and a good correlation between the two measures of expression was observed for both 2 pig breeds at different growth stages (R=0.874±0.071). These results highlight some possible candidate genes for porcine fat characteristics and provide some data on which to base further study of the molecular basis of adipose metabolism.

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