A system biology approach highlights a hormonal enhancer effect on regulation of genes in a nitrate responsive "biomodule"

BackgroundNitrate-induced reprogramming of the transcriptome has recently been shown to be highly context dependent. Herein, a systems biology approach was developed to identify the components and role of cross-talk between nitrate and hormone signals, likely to be involved in the conditional response of NO3- signaling.ResultsBiclustering was used to identify a set of genes that are N-responsive across a range of Nitrogen (N)-treatment backgrounds (i.e. nitrogen treatments under different growth conditions) using a meta-dataset of 76 Affymetrix ATH1 chips from 5 different laboratories. Twenty-one biclusters were found to be N-responsive across subsets of this meta-dataset. N-bicluster 9 (126 genes) was selected for further analysis, as it was shown to be reproducibly responsive to NO3- as a signal, across a wide-variety of background conditions and datasets. N-bicluster 9 genes were then used as "seed" to identify putative cross-talk mechanisms between nitrate and hormone signaling. For this, the 126 nitrate-regulated genes in N-bicluster 9 were biclustered over a meta-dataset of 278 ATH1 chips spanning a variety of hormone treatments. This analysis divided the bicluster 9 genes into two classes: i) genes controlled by NO3- only vs. ii) genes controlled by both NO3- and hormones. The genes in the latter group showed a NO3- response that is significantly enhanced, compared to the former. In silico analysis identified two Cis-Regulatory Elements candidates (CRE) (E2F, HSE) potentially involved the interplay between NO3- and hormonal signals.ConclusionThis systems analysis enabled us to derive a hypothesis in which hormone signals are proposed to enhance the nitrate response, providing a potential mechanistic explanation for the link between nitrate signaling and the control of plant development.

• Publication year

  2009

• Venue

  BMC Systems Biology

• Publication date

  2009-06-06

• Fields of study

  Biology, Medicine, Computer Science, Environmental Science

• Identifiers
  DOI 10.1186/1752-0509-3-59PMID 19500399PMCID 2702358
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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