|Joung, Je-Gun -|
|Corbett, Anthony -|
|Fellman, Shanna -|
|Tieman, Denise -|
|Klee, Harry -|
|Fei, Zhangjun -|
Submitted to: Plant Physiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 9, 2009
Publication Date: November 9, 2009
Citation: Joung, J., Corbett, A., Fellman, S., Tieman, D., Klee, H., Giovannoni, J.J., Fei, Z. 2009. Plant MetGenMAP: an integrative analysis system for plant systems biology. Plant Physiology. 151:1758-1768. Interpretive Summary: The information and resources generated from diverse ‘omics’ technologies provide opportunities for producing novel biological knowledge. It is essential to integrate various kinds of biological information and large-scale ‘omics’ datasets through systematic analysis in order to describe and understand complex biological phenomena. For this purpose, we have developed a web-based system, Plant MetGenMAP, which can comprehensively integrate and analyze large-scale gene expression and metabolite profile datasets along with diverse biological information. Using this system, significantly altered biochemical pathways and biological processes under given conditions can be retrieved rapidly and efficiently, and transcriptional events and/or metabolic changes in a pathway can be easily visualized. In addition, the system provides a unique function that can identify candidate promoter motifs associated with regulation of specific biochemical pathways. We demonstrate the functions and application of the system using datasets from Arabidopsis and tomato, respectively. The results obtained by Plant MetGenMAP can aid in a better understanding of the mechanisms that underlie interesting biological phenomena and provide novel insights into the biochemical changes associated with them at the gene and metabolite levels. Plant MetGenMAP is freely available at http://bioinfo.bti.cornell.edu/tool/MetGenMAP.
Technical Abstract: We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. Plant MetGenMAP is an easy-to-use, powerful analysis system that supports many functions of systems biology analyses in the context of biochemical pathways and gene ontology (GO) terms. It provides an analytical platform in which highly altered pathways can be explored rapidly and efficiently through intuitive visualization and robust statistical tests. Since it allows for the analysis of transcriptional and metabolic changes simultaneously for each pathway, the association between gene expression and biochemical changes in specific pathways under specific conditions can be easily inferred. Functional analysis of differentially regulated pathways can help to properly define functional roles of genes within pathways. In addition, the system embeds a function that can identify major regulators putatively related to the change of transcripts and metabolites in specific pathways. We present comprehensive results identified with Plant MetGenMAP including differentially regulated metabolic pathways, functions of genes associated with pathway changes, putative regulators associated with these genes, and probabilistic associations between genes, metabolites, and phenotypes.