Abstract

BackgroundWith the advent of microarray technology, it has become feasible to identify virtually all genes in an organism that are induced by developmental or environmental changes. However, relying solely on gene expression data may be of limited value if the aim is to infer the underlying genetic networks. Development of computational methods to combine microarray data with other information sources is therefore necessary. Here we describe one such method.ResultsBy means of our method, previously published Arabidopsis microarray data from cold acclimated plants at six different time points, promoter motif sequence data extracted from ~24,000 Arabidopsis promoters and known transcription factor binding sites were combined to construct a putative genetic regulatory interaction network. The inferred network includes both previously characterised and hitherto un-described regulatory interactions between transcription factor (TF) genes and genes that encode other TFs or other proteins. Part of the obtained transcription factor regulatory network is presented here. More detailed information is available in the additional files.ConclusionThe rule-based method described here can be used to infer genetic networks by combining data from microarrays, promoter sequences and known promoter binding sites. This method should in principle be applicable to any biological system. We tested the method on the cold acclimation process in Arabidopsis and could identify a more complex putative genetic regulatory network than previously described. However, it should be noted that information on specific binding sites for individual TFs were in most cases not available. Thus, gene targets for the entire TF gene families were predicted. In addition, the networks were built solely by a bioinformatics approach and experimental verifications will be necessary for their final validation. On the other hand, since our method highlights putative novel interactions, more directed experiments could now be performed.

Highlights

  • With the advent of microarray technology, it has become feasible to identify virtually all genes in an organism that are induced by developmental or environmental changes

  • Transcriptome analysis using microarray technology is a very powerful tool to identify cold responsive genes [2,3,4]. Amongst these are genes encoding transcription factors (TFs), signal transduction components, osmo-regulatory proteins, membrane stabilisation proteins, regulatory factors for protein folding, ice nucleation proteins and enzymes involved in the biosynthesis of various kinds of small molecules like polyhydroxilated sugar alcohols, amino acids and derivatives, tertiary sulphonium compounds and quaternary ammonium compounds [1,5,6,7,8]

  • Molecular and genomic analyses have shown that the CBF (C-repeat Binding Factor) TFs have a prominent role in the cold acclimation process

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Summary

Introduction

With the advent of microarray technology, it has become feasible to identify virtually all genes in an organism that are induced by developmental or environmental changes. Transcriptome analysis using microarray technology is a very powerful tool to identify cold responsive genes [2,3,4]. Amongst these are genes encoding transcription factors (TFs), signal transduction components, osmo-regulatory proteins, membrane stabilisation proteins, regulatory factors for protein folding, ice nucleation proteins and enzymes involved in the biosynthesis of various kinds of small molecules like polyhydroxilated sugar alcohols, amino acids and derivatives, tertiary sulphonium compounds and quaternary ammonium compounds [1,5,6,7,8]. A further identification and characterization of genes involved in the molecular regulation of cold acclimation may enable us to develop plant varieties with improved tolerance to cold [1]

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