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Abstract
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 data sets 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 data sets 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 the regulation of specific biochemical pathways. We demonstrate the functions and application of the system using data sets from Arabidopsis (Arabidopsis thaliana) and tomato (Solanum lycopersicum), 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.
Highlights
The information and resources generated from diverse “omics” technologies provide opportunities for producing novel biological knowledge
We have developed a Web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes and predict functional roles of pathway genes and potential pathway-related regulatory motifs from transcript and metabolite profile data sets
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
Summary
The information and resources generated from diverse “omics” technologies provide opportunities for producing novel biological knowledge. We have developed a Web-based system, Plant MetGenMAP, which can comprehensively integrate and analyze large-scale gene expression and metabolite profile data sets 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 visualized. In addition to the integration of heterogeneous data sources, analysis of them under the context of pathways is regarded as an essential step for functional studies of a complex biological system In this type of analysis, transcriptomic data are normally mapped onto specific metabolic pathways to investigate the coordinated behavior of a set of genes. The database EGENES was developed to place genomic information, including ESTs of many plant species, into metabolic pathways and was integrated into the KEGG suite of databases (Masoudi-Nejad et al, 2007)
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