ArticleNucleic acids research2006
The distinctive signatures of promoter regions and operon junctions across prokaryotes.
Article in Nucleic acids research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The pseudogenes of Mycobacterium leprae reveal the functional relevance of gene order within operons.Nucleic acids research · 2011Article
- Relationship between operon preference and functional properties of persistent genes in bacterial genomes.BMC genomics · 2010Article
- Biochemical features and functional implications of the RNA-based T-box regulatory mechanism.Microbiology and molecular biology reviews : MMBR · 2009Review
- Structure and evolution of gene regulatory networks in microbial genomes.Research in microbiology · 2007Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Here we show that regions upstream of first transcribed genes have oligonucleotide signatures that distinguish them from regions upstream of genes in the middle of operons. Databases of experimentally confirmed transcription units do not exist for most genomes. Thus, to expand the analyses into genomes with no experimentally confirmed data, we used genes conserved adjacent in evolutionarily distant genomes as representatives of genes inside operons. Likewise, we used divergently transcribed genes as representative examples of first transcribed genes. In model organisms, the trinucleotide signatures of regions upstream of these representative genes allow for operon predictions with accuracies close to those obtained with known operon data (0.8). Signature-based operon predictions have more similar phylogenetic profiles and higher proportions of genes in the same pathways than predicted transcription unit boundaries (TUBs). These results confirm that we are separating genes with related functions, as expected for operons, from genes not necessarily related, as expected for genes in different transcription units. We also test the quality of the predictions using microarray data in six genomes and show that the signature-predicted operons tend to have high correlations of expression. Oligonucleotide signatures should expand the number of tools available to identify operons even in poorly characterized genomes.
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Registered trials
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