Influence of pre-mirna compositional properties on RISC complex recruitment and target selection

The mirna targets detection is a key goal of computational biology. This class of non-coding RNA have acquired appreciable importance in understanding molecular mechanism of diseases. In this paper we have investigated the relations between compositional fetures of microrna precursors and the target recognition of corresponding mature micrornas. In particular we want to determine the role of methylation on precursors. An increasing set of experimental evidences corroborate the hypothesis that microRNA methylation can be associated with pathological condition. Altered microRNA methylation seems to be associated with different cancers. In order to predict the set of microrna prone to methylation we have analysed the human precursors available in the MicroRNA registry release 16.0. Our analysis principally has been centered on compositional asymmetries correlated with the CG content. Unequal distribution of dinucleotide has been investigate at genomic level (CpG island) of region potentially coding mirna. The role of inhomogeneous distribution of CG in pre-mirna is not yet deeply analysed. It possible that the different frequency of these nucleotides can play a role both in mirna maturation process and/or DNA methylation. Our analysis has identified two extremal group of human pre-mirna: one that have high content of CG dinucleotides and the second lack of CG. The role compositional characteristics of mirnas. In particular premirna lacking CG dinucleotides seems to be involved in regulation of critical processes such gene transcription. Among these precursor we investigated the potential targets of hsa-let7a-1. on oxidative stress.