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dc.contributor.authorCarrera, Javier-
dc.contributor.authorRodrigo, Guillermo-
dc.contributor.authorJaramillo, Alfonso-
dc.contributor.authorElena, Santiago F.-
dc.identifier.citationGenome Biology 10:R96 (2009)en_US
dc.description46 pages, 4 tables, 6 figures, 3 additinoal files.en_US
dc.description.abstract[Background] Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modelling to dissect the transcriptional control of A. thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes.en_US
dc.description.abstract[Results] We show that A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feedforward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures.en_US
dc.description.abstract[Conclusions] These data suggest that A. thaliana has evolved a high connectivity in terms of transcriptional regulations among cellular functions involved in response and adaptation to changing environments; while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this Eukaryote.en_US
dc.description.sponsorshipThis work was supported by grants BFU2006-14819-C02-01/BMC and TIN2006-12860 from the Spanish Ministerio de Ciencia e Innovación to S.F.E and A.J., respectively; FP6-NESTs 043340 (BioModularH2) and 043338 (Emergence), FP7-KBBE-212894 (Tarpol), the Structural Funds of the European Regional Development Fund (ERDF), the 91-A3405-ATIGE Genopole/UEVE and the MIT-France grants to A.J. J.C, G.R. and A.J. acknowledge the HPC-Europa program (RII3-CT-2003-506079). G.R. was supported by a graduate fellowship from the Generalitat Valenciana and an EMBO Short-term fellowship (ref. ASTF-343.00-2007). S.F.E. also acknowledges support from the Santa Fe Institute.en_US
dc.format.extent4231406 bytes-
dc.publisherBioMed Centralen_US
dc.relation.isversionofPublisher’s version-
dc.subjectArabidopsis thalianaen_US
dc.titleReverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditionsen_US
dc.description.peerreviewedPeer revieweden_US
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