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

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...

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Veröffentlicht in:Plant, cell and environment Jg. 32; H. 12; S. 1633 - 1651
Hauptverfasser: USADEL, BJÖRN, OBAYASHI, TAKESHI, MUTWIL, MAREK, GIORGI, FEDERICO M, BASSEL, GEORGE W, TANIMOTO, MIMI, CHOW, AMANDA, STEINHAUSER, DIRK, PERSSON, STAFFAN, PROVART, NICHOLAS J
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford, UK Oxford, UK : Blackwell Publishing Ltd 01.12.2009
Blackwell Publishing Ltd
Blackwell
Schlagworte:
Arabidopsis
bioinformatics
Biological and medical sciences
Computational Biology
correlation
data collection
Databases, Genetic
Fundamental and applied biological sciences. Psychology
gene expression
Gene Expression Profiling
Gene Expression Profiling - methods
Gene Expression Profiling - statistics & numerical data
genes
Genes, Plant
genetics
methods
Oligonucleotide Array Sequence Analysis
Oligonucleotide Array Sequence Analysis - methods
Oligonucleotide Array Sequence Analysis - statistics & numerical data
plant biology
Plants
Plants - genetics
prediction
reverse genetics
statistics & numerical data
databases
Correlation
reverse genetics
Arabidopsis
Plant ecology
Plant biology
Arabidopsis thaliana
Generation
Cruciferae
Dicotyledones
Angiospermae
Database
Genetics
Spermatophyta
Experimental plant
Bioinformatics
ISSN:0140-7791, 1365-3040, 1365-3040
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:http://dx.doi.org/10.1111/j.1365-3040.2009.02040.x
Co‐first authors.
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ISSN:0140-7791
1365-3040
1365-3040
DOI:10.1111/j.1365-3040.2009.02040.x