PMID:15130539
| Citation |
Riva, A, Delorme, MO, Chevalier, T, Guilhot, N, Hénaut, C and Hénaut, A (2004) The difficult interpretation of transcriptome data: the case of the GATC regulatory network. Comput Biol Chem 28:109-18 |
|---|---|
| Abstract |
Genomic analyses on part of Escherichia coli's chromosome had suggested the existence of a GATC regulated network. This has recently been confirmed through a transcriptome analysis. Two hypotheses about the molecular control mechanism have been proposed-(i) the GATC network regulation is caused by the presence of GATC clusters within the coding sequences; the regulation is the direct consequence of the clusters' hemi-methylation and therefore their elevated melting temperature, (ii) the regulation is caused by the presence of GATCs in the non-coding 500 bp upstream regions of the affected genes; it is the consequence of an interaction with a regulatory protein like Fnr or CAP. An analysis of the transcriptome data has not allowed us to decide between the two hypotheses. We have therefore taken a classic genomic approach, analyzing the statistical distribution of GATC along the chromosome, using a realistic model of the chromosome as theoretical reference. We observe no particular distribution of GATC in the non-coding upstream regions; however, we confirm the presence of GATC clusters within the genes. In order to verify that the particular distribution observed in E. coli is not a statistical artefact, but has a physiological role, we have carried out the same analysis on Salmonella, making the hypothesis that the genes containing a GATC clusters should be largely the same in the two bacteria. This has been indeed observed, showing that the genes containing a GATC cluster are part of a regulation network. The present is a case study, which demonstrates that the analysis of transcriptome data does not always permit to identify the primary cause of a phenomenon observed; on the other hand, a classic genomic approach linked with a comparative study of related genomes may allow this identification. |
| Links |
PubMed Online version:10.1016/j.compbiolchem.2003.12.004 |
| Keywords |
Computational Biology; Escherichia coli/genetics; Genomics; Genotype; Methyltransferases/genetics; Microsatellite Repeats/genetics; Microsatellite Repeats/physiology; Salmonella/genetics; Statistics as Topic; Temperature; Transcription, Genetic |
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