Research article

In silico discovery of human natural antisense transcripts

Yuan-Yuan Li^1* , Lei Qin^1* , Zong-Ming Guo^1* , Lei Liu² , Hao Xu¹ , Pei Hao¹ , Jiong Su¹ , Yixiang Shi¹ , Wei-Zhong He¹ and Yi-Xue Li¹

¹  Shanghai Center for Bioinformation Technology, Shanghai 200235, China

²  The W. M. Keck Center for Comparative and Functional Genomics, University of Illinois at Urbana-Champaign, 1201 W. Gregory Dr., Urbana, Illinois 61801, USA

author email corresponding author email* Contributed equally

BMC Bioinformatics 2006, 7:18doi:10.1186/1471-2105-7-18

Published:	13 January 2006

Abstract

Background

Several high-throughput searches for ppotential natural antisense transcripts (NATs) have been performed recently, but most of the reports were focused on cis type. A thorough in silico analysis of human transcripts will help expand our knowledge of NATs.

Results

We have identified 568 NATs from human RefSeq RNA sequences. Among them, 403 NATs are reported for the first time, and at least 157 novel NATs are trans type. According to the pairing region of a sense and antisense RNA pair, hNATs are divided into 6 classes, of which about 87% involve 5' or 3' UTR sequences, supporting the regulatory role of UTRs. Among a total of 535 NAT pairs related with splice variants, 77.4% (414/535) have their pairing regions affected or completely eliminated by alternative splicing, suggesting significant relationship of alternative splicing and antisense-directed regulation. The extensive occurrence of splice variants in hNATs and other multiple pairing patterns results in a one-to-many relationship, allowing the formation of complex regulation networks. Based on microarray data from Stanford Microarray Database, two hNAT pairs were found to display significant inverse expression patterns before and after insulin injection.

Conclusion

NATs might carry out more extensive and complex functions than previously thought. Combined with endogenous micro RNAs, hNATs could be regarded as a special group of transcripts contributing to the complex regulation networks.