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Identification of brassinosteroid-related genes by means of transcript co-response analyses

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons97275

Lisso,  J.
Brassinosteroids, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97425

Steinhauser,  D.
Small Molecules, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;
Systems Metabolomics, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97050

Altmann,  T.
Developmental Physiology and Genomics, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97239

Kopka,  J.
Applied Metabolome Analysis, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons97308

Muessig,  C.
Developmental Physiology and Genomics, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;
Brassinosteroids, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Lisso-2005-Identification of br.pdf
(beliebiger Volltext), 675KB

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Zitation

Lisso, J., Steinhauser, D., Altmann, T., Kopka, J., & Muessig, C. (2005). Identification of brassinosteroid-related genes by means of transcript co-response analyses. Nucleic Acids Research, 33(8), 2685-2696. doi:10.1093/nar/gki566.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-2B83-D
Zusammenfassung
The comprehensive systems-biology database (CSB.DB) was used to reveal brassinosteroid (BR)-related genes from expression profiles based on co-response analyses. Genes exhibiting simultaneous changes in transcript levels are candidates of common transcriptional regulation. Combining numerous different experiments in data matrices allows ruling out outliers and conditional changes of transcript levels. CSB.DB was queried for transcriptional co-responses with the BR-signalling components BRI1 and BAK1: 301 out of 9694 genes represented in the nasc0271 database showed co-responses with both genes. As expected, these genes comprised pathway-involved genes (e.g. 72 BR-induced genes), because the BRI1 and BAK1 proteins are required for BR-responses. But transcript co-response takes the analysis a step further compared with direct approaches because BR-related non BR-responsive genes were identified. Insights into networks and the functional context of genes are provided, because factors determining expression patterns are reflected in correlations. Our findings demonstrate that transcript co-response analysis presents a valuable resource to uncover common regulatory patterns of genes. Different data matrices in CSB.DB allow examination of specific biological questions. All matrices are publicly available through CSB.DB. This work presents one possible roadmap to use the CSB.DB resources.