Co-expression tools for plant biology: Opportunities for hypothesis generation and caveats

Björn Usadel, Takeshi Obayashi, Marek Mutwil, Federico M. Giorgi, George W. Bassel, Mimi Tanimoto, Amanda Chow, Dirk Steinhauser, Staffan Persson, Nicholas J. Provart

Research output: Contribution to journalReview articlepeer-review

334 Citations (Scopus)

Abstract

Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology.

Original languageEnglish
Pages (from-to)1633-1651
Number of pages19
JournalPlant, Cell and Environment
Volume32
Issue number12
DOIs
Publication statusPublished - 2009 Dec
Externally publishedYes

Keywords

  • Arabidopsis
  • Bioinformatics
  • Correlation
  • Databases
  • Reverse genetics

ASJC Scopus subject areas

  • Physiology
  • Plant Science

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