Dinucleotide step parameterization of pre-miRNAs using multi-objective evolutionary algorithms

  • Authors:

  • Jin-Wu Nam;In-Hee Lee;Kyu-Baek Hwang;Seong-Bae Park;Byoung-Tak Zhang

  • Affiliations:

  • Graduate Program in Bioinformatics and Center for Bioinformation Technology;Biointelligence Laboratory, School of Computer Science and Engineering, Seoul National University, Seoul, Korea;School of Computing, Soongsil University, Seoul, Korea;Department of Computer Engineering, Kyungpook National University, Daegu, Korea;Graduate Program in Bioinformatics, Center for Bioinformation Technology and Biointelligence Laboratory, School of Computer Science and Engineering, Seoul National University, Seoul, Korea

  • Venue:
  • EvoBIO'07 Proceedings of the 5th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
  • Year:
  • 2007

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Abstract

MicroRNAs (miRNAs) form a large functional family of small noncoding RNAs and play an important role as posttranscriptional regulators, by repressing the translation of mRNAs. Recently, the processing mechanism of miRNAs has been reported to involve Drosha/DGCR8 complex and Dicer, however, the exact mechanism and molecular principle are still unknown. We thus have tried to understand the related phenomena in terms of the tertiary structure of pre-miRNA. Unfortunately, the tertiary structure of RNA double helix has not been studied sufficiently compared to that of DNA double helix. The tertiary structure of pre-miRNA double helix is determined by 15 types of dinucleotide step (d-step) parameters for three classes of angles, i.e., twist, roll, and tilt. In this study, we estimate the 45 d-step parameters (15 types by 3 classes) using an evolutionary algorithm, under several assumptions inferred from the literature. Considering the trade-off among the four objective functions in our study, we deployed a multi-objective evolutionary algorithm, NSGA-II, to the search for a nondominant set of parameters. The performance of our method was evaluated on a separate test dataset. Our study provides a novel approach to understanding the processing mechanism of pre-miRNAs with respect to their tertiary structure and would be helpful for developing a comprehensible prediction method for pre-miRNA and mature miRNA structures.