Integrative approaches for mining transcriptional regulatory programs in Arabidopsis.
Challenges in modern biology demand shifting focus from components-genes and proteins-to their interacting whole. Integrating information from multiple genomic datasets is seen as a means to this end, capable of providing robust and accurate ways to unravel these functional associations. Integrative strategies, both novel and adapted from other well-studied organisms, are being employed in the model plant Arabidopsis thaliana to interpret genome-wide expression, metabolic profiling and protein interaction studies. Exciting inroads are being made in mining and interpretation of developmental, physiological and environmental-response 'programs' using sequence and functional information. The fundamental transcriptional regulatory logic is emerging in Arabidopsis, presently revealed as isolated conditional, spatial or temporal regulatory 'modules'. This immediately calls for efforts towards assembling these building blocks together into a unifying model, thus creating standards for future work to compare with. As a young field, Arabidopsis systems biology is ripe with such an opportunity, now scarcely realizable in other model organisms.
Krishnan
Arjun
A
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.
Pereira
Andy
A
D017360:Arabidopsis / Q000235:genetics*; D018744:DNA, Plant / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods*; D018506:Gene Expression Regulation, Plant; D018745:Genome, Plant; D023281:Genomics / Q000379:methods*; D011401:Promoter Regions, Genetic; D012680:Sensitivity and Specificity; D014158:Transcription, Genetic
D018744:DNA, Plant