An expectation-maximization algorithm for the analysis of allelic expression imbalance

A significant proportion of the variation between individuals in gene expression levels is genetic, and it is likely that these differences correlate with phenotypic differences or with risk of disease. Cis-acting polymorphisms are important in determining interindividual differences in gene expression that lead to allelic expression imbalance, which is the unequal expression of homologous alleles in individuals heterozygous for such a polymorphism. This expression imbalance can be detected using a transcribed polymorphism, and, once it is established, the next step is to identify the polymorphisms that are responsible for or predictive of allelic expression levels. We present an expectation-maximization algorithm for such analyses, providing a formal statistical framework to test whether a candidate polymorphism is associated with allelic expression differences.     

Analysis of the porcine APOA2 gene expression in liver,polymorphism identification and association with fatty acid composition traits

APOA2 is a protein implicated in triglyceride, fatty acid and glucose metabolism. In pigs, the APOA2 gene is located on pig chromosome 4 (SSC4) in a QTL region affecting fatty acid composition, fatness and growth traits. In this study, we evaluated APOA2 as a candidate gene for meat quality traits in an Iberian × Landrace backcross population. The APOA2:c.131T>A polymorphism, located in exon 3 of APOA2 and determining a missense mutation, was associated with the percentage of hexadecenoic acid [C16:1(n–9)], linoleic acid [C18:2(n–6)], α‐linolenic acid [C18:3(n–3)], dihomo‐gamma‐linolenic acid [C20:3(n–6)] and polyunsaturated fatty acids (PUFAs) in backfat. Furthermore, this SNP was associated with the global mRNA expression levels of APOA2 in liver and was used as a marker to determine allelic expression imbalance by pyrosequencing. We determined an overexpression of the T allele in heterozygous samples with a mean ratio of 2.8 (T/A), observing a high variability in the allelic expression among individuals. This result suggests that complex regulatory mechanisms, beyond a single polymorphism (e.g. epigenetic effects or multiple cis‐acting polymorphisms), may be regulating APOA2 gene expression.