title: In silico discovery of human natural antisense transcripts.
abstract: BACKGROUND
  Several high-throughput searches for potential 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org
authors.forename: Yuan-Yuan
authors.initials: YY
authors.lastname: Li
authors.forename: Lei
authors.initials: L
authors.lastname: Qin
authors.forename: Zong-Ming
authors.initials: ZM
authors.lastname: Guo
authors.forename: Lei
authors.initials: L
authors.lastname: Liu
authors.forename: Hao
authors.initials: H
authors.lastname: Xu
authors.forename: Pei
authors.initials: P
authors.lastname: Hao
authors.forename: Jiong
authors.initials: J
authors.lastname: Su
authors.forename: Yixiang
authors.initials: Y
authors.lastname: Shi
authors.forename: Wei-Zhong
authors.initials: WZ
authors.lastname: He
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D030562:Databases, Protein; D006801:Humans; D008969:Molecular Sequence Data; D020543:Proteome / Q000235:genetics*; D016372:RNA, Antisense / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*; D014157:Transcription Factors / Q000235:genetics*
chemical_list: D020543:Proteome; D016372:RNA, Antisense; D014157:Transcription Factors