Arabidopsis 2010: Visual Informatics Tools to Interactively Link Arabidopsis Metabolic and Regulatory Network Maps with Genome-Wide Expression Data

Iowa State University, Ames IA

Investigators

Abstract

Emerging molecular technologies are enabling the collection of massive data sets that contain information about the full complement of mRNAs, proteins and metabolites in an organism. These data sets detail the fluctuations in levels of mRNAs, proteins, and metabolites in different organs, tissues and cell types, over time, and as the organism is subjected to environmental stresses. The development of Arabidopsis as a model plant system, and the ensuing emphasis on functional genomics in the Arabidopsis 2010 program, is leading to the generation of a multitude of such data sets. These data sets can compare wild-type and genetically modified Arabidopsis to understand how a change in a single gene can affect the function of the entire genome. The overall goal is to understand the interactions occurring between all the genes in a simple plant system, as the basis for developing a logical framework to improve the composition and yield of agronomically important plant species. Computational technologies are essential to integrate and interpret these large data sets. The goal is to develop and implement powerful software tools for analysis of genome-wide expression data. The software tools will consist of three modules that will integrate the visualization of the mRNA, protein, and metabolite data sets with our current understanding of the Arabidopsis metabolic and regulatory network. These are: 1) A metabolic and regulatory network mapping capability with an interactive graph display. 2) A data integration capability, wherein global profiling data can be clustered, visualized, superimposed on the metabolic and regulatory map. 3) A modeling capability in which the metabolic or regulatory flow in the network is modeled using fuzzy cognitive maps. These tools will be used by the biological community to generate and test hypotheses about the regulation of metabolic pathways that contribute to the final composition and yield of the plant. The 24-month deliverable will provide a proof-of-concept for the software, using test data sets from Arabidopsis. The proposed multidisciplinary research will provide invaluable opportunities for the integration of genomics and bioinformatics education into undergraduate and graduate curricula. Three-five undergraduate students and two graduate students will be involved over the course of two years. In addition, interations with local high school teachers are planned to enable motivated high school students to participate in this research. There is also a plan to integrate students from underrepresented groups into the research project. The ability to reach young, computer savvy students even in high school will be further enhanced by the high power computer graphics used in the project. Development of this software will lead directly to its use as a teaching tool in secondary education. This coordinated approach to displaying multiple views of metabolic networks, cellular functions, and datasets will put abstract data in the context in which it arises, and facilitate studies of uncertainty and variation in metabolic networks. Although the software will be directed specifically towards the biology of Arabidopsis, it can be modified for use in any species. These tools, and the database will be freely available to the scientific community for academic purposes http://www.botany.iastate.edu/~mash/metnetex/metabolicnetex.html. They will provide a novel framework to formulate testable hypotheses regarding the function of specific genes and expand our holistic understanding of metabolism.