In silico identification of candidate MECP2 targets and quantitative analysis in rett syndrome

Abstract

Rett syndrome (RTT) is an X-linked neuro-developmental disorder seen exclusively girls in the childhood. It is one of the most common causes of mental retardation with an incidence rate of 1/10,000-1/15,000. Mutations in MECP2 gene was described as a common cause of RTT. MECP2 is a transcriptional repressor that regulates gene expression. It is not fully understood which MECP2 targets are affected in RTT and therefore contribute to disease pathogenesis. Researchers approached the problem in two directions: a) Global expression profile analysis and b) Candidate gene analysis. Global expression profile analysis revealed which a limited number of genes including those on the X-chromosome are de-regulated. Candidate gene analysis studies showed that loss of imprinting as exemplified by DLX5 could also contribute to disease pathogenesis. We hypothesize that Xchromosome inactivation (XCI) is an important physiological epigenetic mechanism that could be involved in Rett pathogenesis. We predicted a MECP2 binding motif by a distinctive bioinformatic approach. Using this algorithm we searched for the candidate MECP2 target genes on the X-chromosome and whole genome. The genes FHL1 and MPP1, whose interaction with MECP2 were heuristically displayed were predicted by our algorithm. We identified more than 100 genes which are on the Xchromosome. 10 genes from the list were selected according to their MECP2 binding homology score and X-inactivation status. In order to test this hypothesis we analyzed these genes with quantitative RT-PCR .We expect to identify the key genes that potentially contribute to RTT pathogenesis via disturbances in X-chromosome inactivation.