Systems approaches to identifying gene regulatory networks in plants.
Complex gene regulatory networks are composed of genes, noncoding RNAs, proteins, metabolites, and signaling components. The availability of genome-wide mutagenesis libraries; large-scale transcriptome, proteome, and metabalome data sets; and new high-throughput methods that uncover protein interactions underscores the need for mathematical modeling techniques that better enable scientists to synthesize these large amounts of information and to understand the properties of these biological systems. Systems biology approaches can allow researchers to move beyond a reductionist approach and to both integrate and comprehend the interactions of multiple components within these systems. Descriptive and mathematical models for gene regulatory networks can reveal emergent properties of these plant systems. This review highlights methods that researchers are using to obtain large-scale data sets, and examples of gene regulatory networks modeled with these data. Emergent properties revealed by the use of these network models and perspectives on the future of systems biology are discussed.
Long
Terri A
TA
1Department of Biology, Duke University, Durham, North Carolina 27708, USA.
Brady
Siobhan M
SM
Benfey
Philip N
PN
D001683:Biological Clocks / Q000502:physiology; D002940:Circadian Rhythm / Q000502:physiology; D030541:Databases, Genetic; D018506:Gene Expression Regulation, Plant; D053263:Gene Regulatory Networks; D017343:Genes, Plant; D007210:Indoleacetic Acids / Q000378:metabolism; D008957:Models, Genetic; D063245:Plant Development; D010944:Plants / Q000033:anatomy & histology / Q000378:metabolism; D049490:Systems Biology; D014158:Transcription, Genetic
D007210:Indoleacetic Acids