Literature DB >> 19712066

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

Björn Usadel1, Takeshi Obayashi, Marek Mutwil, Federico M Giorgi, George W Bassel, Mimi Tanimoto, Amanda Chow, Dirk Steinhauser, Staffan Persson, Nicholas J Provart.   

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.

Mesh:

Year:  2009        PMID: 19712066     DOI: 10.1111/j.1365-3040.2009.02040.x

Source DB:  PubMed          Journal:  Plant Cell Environ        ISSN: 0140-7791            Impact factor:   7.228


  195 in total

1.  COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems.

Authors:  Yasunobu Okamura; Yuichi Aoki; Takeshi Obayashi; Shu Tadaka; Satoshi Ito; Takafumi Narise; Kengo Kinoshita
Journal:  Nucleic Acids Res       Date:  2014-11-11       Impact factor: 16.971

2.  On the discordance of metabolomics with proteomics and transcriptomics: coping with increasing complexity in logic, chemistry, and network interactions scientific correspondence.

Authors:  Alisdair R Fernie; Mark Stitt
Journal:  Plant Physiol       Date:  2012-01-17       Impact factor: 8.340

3.  ORTom: a multi-species approach based on conserved co-expression to identify putative functional relationships among genes in tomato.

Authors:  Laura Miozzi; Paolo Provero; Gian Paolo Accotto
Journal:  Plant Mol Biol       Date:  2010-04-22       Impact factor: 4.076

Review 4.  Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways.

Authors:  Takeshi Obayashi; Kengo Kinoshita
Journal:  J Plant Res       Date:  2010-04-10       Impact factor: 2.629

5.  Combining genetic diversity, informatics and metabolomics to facilitate annotation of plant gene function.

Authors:  Takayuki Tohge; Alisdair R Fernie
Journal:  Nat Protoc       Date:  2010-06-10       Impact factor: 13.491

6.  Exploring tomato gene functions based on coexpression modules using graph clustering and differential coexpression approaches.

Authors:  Atsushi Fukushima; Tomoko Nishizawa; Mariko Hayakumo; Shoko Hikosaka; Kazuki Saito; Eiji Goto; Miyako Kusano
Journal:  Plant Physiol       Date:  2012-02-03       Impact factor: 8.340

7.  Identification of the 2-hydroxyglutarate and isovaleryl-CoA dehydrogenases as alternative electron donors linking lysine catabolism to the electron transport chain of Arabidopsis mitochondria.

Authors:  Wagner L Araújo; Kimitsune Ishizaki; Adriano Nunes-Nesi; Tony R Larson; Takayuki Tohge; Ina Krahnert; Sandra Witt; Toshihiro Obata; Nicolas Schauer; Ian A Graham; Christopher J Leaver; Alisdair R Fernie
Journal:  Plant Cell       Date:  2010-05-25       Impact factor: 11.277

8.  Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis.

Authors:  Chuang Ma; Mingming Xin; Kenneth A Feldmann; Xiangfeng Wang
Journal:  Plant Cell       Date:  2014-02-11       Impact factor: 11.277

Review 9.  Engineering crassulacean acid metabolism to improve water-use efficiency.

Authors:  Anne M Borland; James Hartwell; David J Weston; Karen A Schlauch; Timothy J Tschaplinski; Gerald A Tuskan; Xiaohan Yang; John C Cushman
Journal:  Trends Plant Sci       Date:  2014-02-19       Impact factor: 18.313

10.  VirtualPlant: a software platform to support systems biology research.

Authors:  Manpreet S Katari; Steve D Nowicki; Felipe F Aceituno; Damion Nero; Jonathan Kelfer; Lee Parnell Thompson; Juan M Cabello; Rebecca S Davidson; Arthur P Goldberg; Dennis E Shasha; Gloria M Coruzzi; Rodrigo A Gutiérrez
Journal:  Plant Physiol       Date:  2009-12-09       Impact factor: 8.340

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.