Institute of Genetic Medicine

Staff Profile

Dr Mauro Santibanez Koref

Senior Lecturer


Research Interests

Using allelic expression differences to ascertain cis-acting functional polymorphisms

In general a polymorphism can have a phenotypic consequence either by modifying the nature of a gene product or its expression levels. Although polymorphisms influencing expression levels are not frequently involved in simple highly penetrant traits it has been suggested that variation in regulatory regions may be of particular interest for common diseases with a complex genetic background. Of particular interest is genetic variation affecting expression in cis. This includes sequence variation affecting promoter function or message stability. In individuals heterozygous for such a polymorphism the amounts of mRNA originating from each allele are not equal. This allelic expression imbalance can be measured in individuals heterozygous for a transcribed polymorphism. The relative transcript level of one allele with respect to the other, or allelic expression ratio, is often easier to measure than absolute levels, since each allele acts as a parallel internal control for the other. The use of allelic expression ratios for detecting cis acting genetic variation is also attractive because many sources of expression variability such as environmental influences are likely to act in trans and affect both alleles.

However measurement allelic expression differences can be of interest beyond the identification of common genetic variants associated with disease predisposition and the characterisation of the mechanisms mediating such associations. Processes regulating mRNA stability such as non sense mediated decay can also lead to dramatic differences in allelic expression. Thus assessment of allelic expression can be used to identify mutation carriers in genes such as BRCA1 and 2 or MLH1 where changes leading to premature termination of the coded protein are known to dramatically increase disease susceptibility and more generally to identify loci were rare variants influencing expression are involved in disease predisposition. We have developed a formal statistical to test associations between polymorphisms with allelic expression differences. This allows to map polymorphisms affecting expression in vivo. These methods can be used to assess the effects associated with single nucleotide polymorphisms and of more variable sequences such as microsatellites, a class of polymorphisms whose effects on gene expression can be difficult assess in vivo. This work is mainly directed to the identification of sets of polymorphisms that are predictive of expression levels. The polymorphisms can then be used to estimate the effect of differences in expression levels upon more complex traits. In such a case expression levels are seen as an intermediate trait. This can be used to understand pathogenesis and to refine risk estimates.