Omics meet networks - using systems approaches to infer regulatory networks in plants

Abstract

Many genomic-scale datasets in plants have been generated over the last few years. This substantial achievement has led to impressive progress, including some of the most detailed molecular maps in any multicellular organism. Networks and pathways have been reconstructed using transcriptome, genome-wide transcription factor binding, proteome and metabolome data, and subsequently used to infer functional interactions among genes, proteins, and metabolites. However, more sophisticated systems biology approaches are needed to integrate different omics datasets. Ultimately, the integration of diverse and massive datasets into coherent models will improve our understanding of the molecular networks that underlie biological processes.

Figure 1

Approaches to network inference and reconstruction. Profiling of metabolites, transcripts and proteins as well as chromatin immunoprecipitation coupled with hybridization to microarrays or sequencing can be used to infer functional interactions among genes, proteins and metabolites. Interpretation and integration of omic datasets facilitates hypothesis generation and prediction of novel gene functions in plant biology.