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The loose evolutionary relationships between transcription factors and other gene products across prokaryotes.

del Grande M, Moreno-Hagelsieb G - BMC Res Notes (2014)

Bottom Line: In most prokaryotes, genes coding for TFs showed lower co-occurrences when compared to other genes.We also show that genes coding for TFs tend to have lower Codon Adaptation Indexes compared to other genes.The Codon Adaptation Index analyses suggest quick gene exchange and rewiring of transcriptional regulation across prokaryotes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Wilfrid Laurier University, 75 University Ave, W,, N2L 3C5 Waterloo, Ontario, Canada. gmoreno@wlu.ca.

ABSTRACT

Background: Tests for the evolutionary conservation of associations between genes coding for transcription factors (TFs) and other genes have been limited to a few model organisms due to the lack of experimental information of functional associations in other organisms. We aimed at surmounting this limitation by using the most co-occurring gene pairs as proxies for the most conserved functional interactions available for each gene in a genome. We then used genes predicted to code for TFs to compare their most conserved interactions against the most conserved interactions for the rest of the genes within each prokaryotic genome available.

Results: We plotted profiles of phylogenetic profiles, p-cubic, to compare the maximally scoring interactions of TFs against those of other genes. In most prokaryotes, genes coding for TFs showed lower co-occurrences when compared to other genes. We also show that genes coding for TFs tend to have lower Codon Adaptation Indexes compared to other genes.

Conclusions: The co-occurrence tests suggest that transcriptional regulation evolves quickly in most, if not all, prokaryotes. The Codon Adaptation Index analyses suggest quick gene exchange and rewiring of transcriptional regulation across prokaryotes.

No MeSH data available.


Comparing manually curated, and predicted transcription factors (TFs). Manually-curated TFs were obtained from RegulonDB [6] for E. coli K12, and from DBTBS [16] for B. subtilis 168. Predictions were based on matches to Pfam and Superfamily DNA-binding domains reported at the DBD [17]. (A, D) Venn diagrams comparing curated and predicted TFs. (B, E) P-cubic of curated TFs. (C, F) P-cubic of predicted TF-coding genes. The p-cubic of any set of TF-coding genes is below the p-cubic of the corresponding set of other genes, showing that TF-coding genes have lower co-occurrences than other genes. Since predicted TF-coding genes behave similarly to curated TF-coding genes, predicted TF-coding genes might be enough to test if TF-coding genes in other prokaryotes have lower co-occurrences than genes coding for proteins other than TFs.
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Fig1: Comparing manually curated, and predicted transcription factors (TFs). Manually-curated TFs were obtained from RegulonDB [6] for E. coli K12, and from DBTBS [16] for B. subtilis 168. Predictions were based on matches to Pfam and Superfamily DNA-binding domains reported at the DBD [17]. (A, D) Venn diagrams comparing curated and predicted TFs. (B, E) P-cubic of curated TFs. (C, F) P-cubic of predicted TF-coding genes. The p-cubic of any set of TF-coding genes is below the p-cubic of the corresponding set of other genes, showing that TF-coding genes have lower co-occurrences than other genes. Since predicted TF-coding genes behave similarly to curated TF-coding genes, predicted TF-coding genes might be enough to test if TF-coding genes in other prokaryotes have lower co-occurrences than genes coding for proteins other than TFs.

Mentions: In our two model organisms, E. coli K12 MG1655 and B. subtilis 168, the highest MI of genes coding for manually-curated TFs shows a lower p-cubic than that for other genes (Figure 1B and 1E). The same was true when we used the genes coding for predicted TFs in the same genomes (Figure 1C and 1F). This suggests that, even though our predicted TFs do not completely agree with the curated datasets (Figure 1A and 1D), they still provide enough information to test the conservation of TF interactions against the interactions of other genes. Our previous study on the evolutionary conservation of functional interactions of E. coli K12 had found that the most conserved regulon-related interaction was between TFs and their TGs [3]. Here we found that the top-scoring interactions for TFs have better conservation than the TF to TG interactions (Figure 1). Being a rather small set, the p-cubic curves for known TF/TG pairs is too noisy to allow confident conclusions. Still, it is possible that top-scoring interactions represent interactions beyond those mediated by transcriptional regulation. However, top-scoring interactions for TFs were still lower than those for other genes, suggesting that TFs have more generic evolutionary plasticity than other genes in these model organisms.Figure 1


The loose evolutionary relationships between transcription factors and other gene products across prokaryotes.

del Grande M, Moreno-Hagelsieb G - BMC Res Notes (2014)

Comparing manually curated, and predicted transcription factors (TFs). Manually-curated TFs were obtained from RegulonDB [6] for E. coli K12, and from DBTBS [16] for B. subtilis 168. Predictions were based on matches to Pfam and Superfamily DNA-binding domains reported at the DBD [17]. (A, D) Venn diagrams comparing curated and predicted TFs. (B, E) P-cubic of curated TFs. (C, F) P-cubic of predicted TF-coding genes. The p-cubic of any set of TF-coding genes is below the p-cubic of the corresponding set of other genes, showing that TF-coding genes have lower co-occurrences than other genes. Since predicted TF-coding genes behave similarly to curated TF-coding genes, predicted TF-coding genes might be enough to test if TF-coding genes in other prokaryotes have lower co-occurrences than genes coding for proteins other than TFs.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4300776&req=5

Fig1: Comparing manually curated, and predicted transcription factors (TFs). Manually-curated TFs were obtained from RegulonDB [6] for E. coli K12, and from DBTBS [16] for B. subtilis 168. Predictions were based on matches to Pfam and Superfamily DNA-binding domains reported at the DBD [17]. (A, D) Venn diagrams comparing curated and predicted TFs. (B, E) P-cubic of curated TFs. (C, F) P-cubic of predicted TF-coding genes. The p-cubic of any set of TF-coding genes is below the p-cubic of the corresponding set of other genes, showing that TF-coding genes have lower co-occurrences than other genes. Since predicted TF-coding genes behave similarly to curated TF-coding genes, predicted TF-coding genes might be enough to test if TF-coding genes in other prokaryotes have lower co-occurrences than genes coding for proteins other than TFs.
Mentions: In our two model organisms, E. coli K12 MG1655 and B. subtilis 168, the highest MI of genes coding for manually-curated TFs shows a lower p-cubic than that for other genes (Figure 1B and 1E). The same was true when we used the genes coding for predicted TFs in the same genomes (Figure 1C and 1F). This suggests that, even though our predicted TFs do not completely agree with the curated datasets (Figure 1A and 1D), they still provide enough information to test the conservation of TF interactions against the interactions of other genes. Our previous study on the evolutionary conservation of functional interactions of E. coli K12 had found that the most conserved regulon-related interaction was between TFs and their TGs [3]. Here we found that the top-scoring interactions for TFs have better conservation than the TF to TG interactions (Figure 1). Being a rather small set, the p-cubic curves for known TF/TG pairs is too noisy to allow confident conclusions. Still, it is possible that top-scoring interactions represent interactions beyond those mediated by transcriptional regulation. However, top-scoring interactions for TFs were still lower than those for other genes, suggesting that TFs have more generic evolutionary plasticity than other genes in these model organisms.Figure 1

Bottom Line: In most prokaryotes, genes coding for TFs showed lower co-occurrences when compared to other genes.We also show that genes coding for TFs tend to have lower Codon Adaptation Indexes compared to other genes.The Codon Adaptation Index analyses suggest quick gene exchange and rewiring of transcriptional regulation across prokaryotes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Wilfrid Laurier University, 75 University Ave, W,, N2L 3C5 Waterloo, Ontario, Canada. gmoreno@wlu.ca.

ABSTRACT

Background: Tests for the evolutionary conservation of associations between genes coding for transcription factors (TFs) and other genes have been limited to a few model organisms due to the lack of experimental information of functional associations in other organisms. We aimed at surmounting this limitation by using the most co-occurring gene pairs as proxies for the most conserved functional interactions available for each gene in a genome. We then used genes predicted to code for TFs to compare their most conserved interactions against the most conserved interactions for the rest of the genes within each prokaryotic genome available.

Results: We plotted profiles of phylogenetic profiles, p-cubic, to compare the maximally scoring interactions of TFs against those of other genes. In most prokaryotes, genes coding for TFs showed lower co-occurrences when compared to other genes. We also show that genes coding for TFs tend to have lower Codon Adaptation Indexes compared to other genes.

Conclusions: The co-occurrence tests suggest that transcriptional regulation evolves quickly in most, if not all, prokaryotes. The Codon Adaptation Index analyses suggest quick gene exchange and rewiring of transcriptional regulation across prokaryotes.

No MeSH data available.