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Characterization of relationships between transcriptional units and operon structures in Bacillus subtilis and Escherichia coli.

Okuda S, Kawashima S, Kobayashi K, Ogasawara N, Kanehisa M, Goto S - BMC Genomics (2007)

Bottom Line: Consequently, we found that the levels of gene co-regulation was correlated to intergenic distances and gene expression levels.Most interestingly, we found that functional associations in SOPs were more observed in the environmental and genetic information processes.In addition, such differences may play an important role in the evolution of gene order across genomes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. okuda@kuicr.kyoto-u.ac.jp <okuda@kuicr.kyoto-u.ac.jp>

ABSTRACT

Background: Operon structures play an important role in transcriptional regulation in prokaryotes. However, there have been fewer studies on complicated operon structures in which the transcriptional units vary with changing environmental conditions. Information about such complicated operons is helpful for predicting and analyzing operon structures, as well as understanding gene functions and transcriptional regulation.

Results: We systematically analyzed the experimentally verified transcriptional units (TUs) in Bacillus subtilis and Escherichia coli obtained from ODB and RegulonDB. To understand the relationships between TUs and operons, we defined a new classification system for adjacent gene pairs, divided into three groups according to the level of gene co-regulation: operon pairs (OP) belong to the same TU, sub-operon pairs (SOP) that are at the transcriptional boundaries within an operon, and non-operon pairs (NOP) belonging to different operons. Consequently, we found that the levels of gene co-regulation was correlated to intergenic distances and gene expression levels. Additional analysis revealed that they were also correlated to the levels of conservation across about 200 prokaryotic genomes. Most interestingly, we found that functional associations in SOPs were more observed in the environmental and genetic information processes.

Conclusion: Complicated operon structures were correlated with genome organization and gene expression profiles. Such intricately regulated operons allow functional differences depending on environmental conditions. These regulatory mechanisms are helpful in accommodating the variety of changes that happen around the cell. In addition, such differences may play an important role in the evolution of gene order across genomes.

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Related in: MedlinePlus

Distributions of frequency of correlation coefficients of gene expression profiles between adjacent gene pairs. The upper figures are the distribution of correlation coefficients (A and C) and the bottom figures are their box plots (B and D). Blue, red and green lines indicate OPs, SOPs and NOPs, respectively.
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Figure 4: Distributions of frequency of correlation coefficients of gene expression profiles between adjacent gene pairs. The upper figures are the distribution of correlation coefficients (A and C) and the bottom figures are their box plots (B and D). Blue, red and green lines indicate OPs, SOPs and NOPs, respectively.

Mentions: To investigate the differences in the gene expression of OPs, SOPs and NOPs, we measured the correlation with co-expression data calculated using several microarray data sets (see Materials and Methods). Figure 4 shows the distributions of the correlation coefficients of gene expression profiles between adjacent gene pairs and the boxplots for the three groups in B. subtilis and E. coli. The distribution of OPs shows that they have an obviously higher correlation than NOPs (the blue line in the parts A and C of Figure 4). This result agrees with past studies, and such clear differences have been used to predict operons [8,10]. Interestingly, SOPs also show high correlation, but not as clearly as OPs. All pairs of these three groups were significantly different (p < IE-7 for OP-NOP, SOP-NOP and OP-SOP, wilcoxon rank sum test). These differences are also clear in the box plots in Figure 4 and the median values in Table 2. Both the ranges of quartiles and the median values show that OPs and SOPs are differently distributed. In this study, we found that the co-expression levels of gene pairs within an operon can decrease due to the presence of regulatory elements in their intergenic region.


Characterization of relationships between transcriptional units and operon structures in Bacillus subtilis and Escherichia coli.

Okuda S, Kawashima S, Kobayashi K, Ogasawara N, Kanehisa M, Goto S - BMC Genomics (2007)

Distributions of frequency of correlation coefficients of gene expression profiles between adjacent gene pairs. The upper figures are the distribution of correlation coefficients (A and C) and the bottom figures are their box plots (B and D). Blue, red and green lines indicate OPs, SOPs and NOPs, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1808063&req=5

Figure 4: Distributions of frequency of correlation coefficients of gene expression profiles between adjacent gene pairs. The upper figures are the distribution of correlation coefficients (A and C) and the bottom figures are their box plots (B and D). Blue, red and green lines indicate OPs, SOPs and NOPs, respectively.
Mentions: To investigate the differences in the gene expression of OPs, SOPs and NOPs, we measured the correlation with co-expression data calculated using several microarray data sets (see Materials and Methods). Figure 4 shows the distributions of the correlation coefficients of gene expression profiles between adjacent gene pairs and the boxplots for the three groups in B. subtilis and E. coli. The distribution of OPs shows that they have an obviously higher correlation than NOPs (the blue line in the parts A and C of Figure 4). This result agrees with past studies, and such clear differences have been used to predict operons [8,10]. Interestingly, SOPs also show high correlation, but not as clearly as OPs. All pairs of these three groups were significantly different (p < IE-7 for OP-NOP, SOP-NOP and OP-SOP, wilcoxon rank sum test). These differences are also clear in the box plots in Figure 4 and the median values in Table 2. Both the ranges of quartiles and the median values show that OPs and SOPs are differently distributed. In this study, we found that the co-expression levels of gene pairs within an operon can decrease due to the presence of regulatory elements in their intergenic region.

Bottom Line: Consequently, we found that the levels of gene co-regulation was correlated to intergenic distances and gene expression levels.Most interestingly, we found that functional associations in SOPs were more observed in the environmental and genetic information processes.In addition, such differences may play an important role in the evolution of gene order across genomes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. okuda@kuicr.kyoto-u.ac.jp <okuda@kuicr.kyoto-u.ac.jp>

ABSTRACT

Background: Operon structures play an important role in transcriptional regulation in prokaryotes. However, there have been fewer studies on complicated operon structures in which the transcriptional units vary with changing environmental conditions. Information about such complicated operons is helpful for predicting and analyzing operon structures, as well as understanding gene functions and transcriptional regulation.

Results: We systematically analyzed the experimentally verified transcriptional units (TUs) in Bacillus subtilis and Escherichia coli obtained from ODB and RegulonDB. To understand the relationships between TUs and operons, we defined a new classification system for adjacent gene pairs, divided into three groups according to the level of gene co-regulation: operon pairs (OP) belong to the same TU, sub-operon pairs (SOP) that are at the transcriptional boundaries within an operon, and non-operon pairs (NOP) belonging to different operons. Consequently, we found that the levels of gene co-regulation was correlated to intergenic distances and gene expression levels. Additional analysis revealed that they were also correlated to the levels of conservation across about 200 prokaryotic genomes. Most interestingly, we found that functional associations in SOPs were more observed in the environmental and genetic information processes.

Conclusion: Complicated operon structures were correlated with genome organization and gene expression profiles. Such intricately regulated operons allow functional differences depending on environmental conditions. These regulatory mechanisms are helpful in accommodating the variety of changes that happen around the cell. In addition, such differences may play an important role in the evolution of gene order across genomes.

Show MeSH
Related in: MedlinePlus