This article is part of the supplement: The 2008 International Conference on Bioinformatics & Computational Biology (BIOCOMP'08) .

Research

Genome-wide prediction of cis-acting RNA elements regulating tissue-specific pre-mRNA alternative splicing

Xin Wang^1,2,3 , Kejun Wang¹ , Milan Radovich⁴ , Yue Wang⁵ , Guohua Wang^2,3,7 , Weixing Feng^1,2,3 , Jeremy R Sanford⁸ and Yunlong Liu^2,3,6

¹College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, PR China

²Division of Biostatistics Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA

³Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA

⁴Division of Hematology/Oncology Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA

⁵Department of Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA

⁶Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, IN 46202, USA

⁷School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, PR China

⁸Department of Molecular, Cellular and Developmental Biology, University of California Santa Cruz, Santa Cruz, California 95064, USA

author email corresponding author email

BMC Genomics 2009, 10(Suppl 1):S4doi:10.1186/1471-2164-10-S1-S4

Published:	7 July 2009

Abstract

Background

Human genes undergo various patterns of pre-mRNA splicing across different tissues. Such variation is primarily regulated by trans-acting factors that bind on exonic and intronic cis-acting RNA elements (CAEs). Here we report a computational method to mechanistically identify cis-acting RNA elements that contribute to the tissue-specific alternative splicing pattern. This method is an extension of our previous model, SplicingModeler, which predicts the significant CAEs that contribute to the splicing differences between two tissues. In this study, we introduce tissue-specific functional levels estimation step, which allows evaluating regulatory functions of predicted CAEs that are involved in more than two tissues.

Results

Using a publicly available Affymetrix Genechip^® Human Exon Array dataset, our method identifies 652 cis-acting RNA elements (CAEs) across 11 human tissues. About one third of predicted CAEs can be mapped to the known RBP (RNA binding protein) binding sites or match with other predicted exonic splicing regulator databases. Interestingly, the vast majority of predicted CAEs are in intronic regulatory regions. A noticeable exception is that many exonic elements are found to regulate the alternative splicing between cerebellum and testes. Most identified elements are found to contribute to the alternative splicing between two tissues, while some are important in multiple tissues. This suggests that genome-wide alternative splicing patterns are regulated by a combination of tissue-specific cis-acting elements and "general elements" whose functional activities are important but differ across multiple tissues.

Conclusion

In this study, we present a model-based computational approach to identify potential cis-acting RNA elements by considering the exon splicing variation as the combinatorial effects of multiple cis-acting regulators. This methodology provides a novel evaluation on the functional levels of cis-acting RNA elements by estimating their tissue-specific functions on various tissues.