Abstract:
:By applying graph representations to biochemical pathways, a new computational pipeline is proposed to find potential operons in microbial genomes. The algorithm relies on the fact that enzyme genes in operons tend to catalyze successive reactions in metabolic pathways. We applied this algorithm to 42 microbial genomes to identify putative operon structures. The predicted operons from Escherichia coli were compared with a selected metabolism-related operon dataset from the RegulonDB database, yielding a prediction sensitivity (89%) and specificity (87%) relative to this dataset. Several examples of detected operons are given and analyzed. Modular gene cluster transfer and operon fusion are observed. A further use of predicted operon data to assign function to putative genes was suggested and, as an example, a previous putative gene (MJ1604) from Methanococcus jannaschii is now annotated as a phosphofructokinase, which was regarded previously as a missing enzyme in this organism. GC content changes in the operon region and nonoperon region were examined. The results reveal a clear GC content transition at the boundaries of putative operons. We looked further into the conservation of operons across genomes. A trp operon alignment is analyzed in depth to show gene loss and rearrangement in different organisms during operon evolution.
journal_name
Genome Resjournal_title
Genome researchauthors
Zheng Y,Szustakowski JD,Fortnow L,Roberts RJ,Kasif Sdoi
10.1101/gr.200602subject
Has Abstractpub_date
2002-08-01 00:00:00pages
1221-30issue
8eissn
1088-9051issn
1549-5469journal_volume
12pub_type
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