Journal Article

ARTADE2DB: Improved Statistical Inferences for Arabidopsis Gene Functions and Structure Predictions by Dynamic Structure-Based Dynamic Expression (DSDE) Analyses

Kei Iida, Shuji Kawaguchi, Norio Kobayashi, Yuko Yoshida, Manabu Ishii, Erimi Harada, Kousuke Hanada, Akihiro Matsui, Masanori Okamoto, Junko Ishida, Maho Tanaka, Taeko Morosawa, Motoaki Seki and Tetsuro Toyoda

in Plant and Cell Physiology

Published on behalf of Japanese Society of Plant Physiologists

Volume 52, issue 2, pages 254-264
Published in print February 2011 | ISSN: 0032-0781
Published online January 2011 | e-ISSN: 1471-9053 | DOI:

More Like This

Show all results sharing these subjects:

  • Biochemistry
  • Molecular and Cell Biology
  • Plant Sciences and Forestry


Show Summary Details


Recent advances in technologies for observing high-resolution genomic activities, such as whole-genome tiling arrays and high-throughput sequencers, provide detailed information for understanding genome functions. However, the functions of 50% of known Arabidopsis thaliana genes remain unknown or are annotated only on the basis of static analyses such as protein motifs or similarities. In this paper, we describe dynamic structure-based dynamic expression (DSDE) analysis, which sequentially predicts both structural and functional features of transcripts. We show that DSDE analysis inferred gene functions 12% more precisely than static structure-based dynamic expression (SSDE) analysis or conventional co-expression analysis based on previously determined gene structures of A. thaliana. This result suggests that more precise structural information than the fixed conventional annotated structures is crucial for co-expression analysis in systems biology of transcriptional regulation and dynamics. Our DSDE method, ARabidopsis Tiling-Array-based Detection of Exons version 2 and over-representation analysis (ARTADE2-ORA), precisely predicts each gene structure by combining two statistical analyses: a probe-wise co-expression analysis of multiple transcriptome measurements and a Markov model analysis of genome sequences. ARTADE2-ORA successfully identified the true functions of about 90% of functionally annotated genes, inferred the functions of 98% of functionally unknown genes and predicted 1,489 new gene structures and functions. We developed a database ARTADE2DB that integrates not only the information predicted by ARTADE2-ORA but also annotations and other functional information, such as phenotypes and literature citations, and is expected to contribute to the study of the functional genomics of A. thaliana. URL:

Keywords: Arabidopsis thaliana; Database; Function prediction; Genome tiling array; Unknown genes

Journal Article.  6608 words.  Illustrated.

Subjects: Biochemistry ; Molecular and Cell Biology ; Plant Sciences and Forestry

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.