Literature DB >> 18160330

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

Kazuki Saito1, Masami Y Hirai, Keiko Yonekura-Sakakibara.   

Abstract

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

Entities:  

Mesh:

Year:  2007        PMID: 18160330     DOI: 10.1016/j.tplants.2007.10.006

Source DB:  PubMed          Journal:  Trends Plant Sci        ISSN: 1360-1385            Impact factor:   18.313


  118 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

Review 2.  Transcriptional and metabolic programs following exposure of plants to UV-B irradiation.

Authors:  Takayuki Tohge; Miyako Kusano; Atsushi Fukushima; Kazuki Saito; Alisdair R Fernie
Journal:  Plant Signal Behav       Date:  2011-12

Review 3.  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

4.  Toward genome-wide metabolotyping and elucidation of metabolic system: metabolic profiling of large-scale bioresources.

Authors:  Masami Yokota Hirai; Yuji Sawada; Shigehiko Kanaya; Takashi Kuromori; Masatomo Kobayashi; Romy Klausnitzer; Kosuke Hanada; Kenji Akiyama; Tetsuya Sakurai; Kazuki Saito; Kazuo Shinozaki
Journal:  J Plant Res       Date:  2010-04-06       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.  Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights.

Authors:  Nicole E Soltis; Daniel J Kliebenstein
Journal:  Plant Physiol       Date:  2015-08-13       Impact factor: 8.340

8.  Comparative co-expression network analysis extracts the SlHSP70 gene affecting to shoot elongation of tomato.

Authors:  Nam Tuan Vu; Ken Kamiya; Atsushi Fukushima; Shuhei Hao; Wang Ning; Tohru Ariizumi; Hiroshi Ezura; Miyako Kusano
Journal:  Plant Biotechnol (Tokyo)       Date:  2019-09-25       Impact factor: 1.133

Review 9.  Integrative systems biology: an attempt to describe a simple weed.

Authors:  Louisa M Liberman; Rosangela Sozzani; Philip N Benfey
Journal:  Curr Opin Plant Biol       Date:  2012-01-23       Impact factor: 7.834

10.  Central Metabolic Responses to Ozone and Herbivory Affect Photosynthesis and Stomatal Closure.

Authors:  Stefano Papazian; Eliezer Khaling; Christelle Bonnet; Steve Lassueur; Philippe Reymond; Thomas Moritz; James D Blande; Benedicte R Albrectsen
Journal:  Plant Physiol       Date:  2016-10-06       Impact factor: 8.340

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.