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Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Jothi R, Balaji S, Wuster A, Grochow JA, Gsponer J, Przytycka TM, Aravind L, Babu MM - Mol. Syst. Biol. (2009)

Bottom Line: At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs.Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation.We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

View Article: PubMed Central - PubMed

Affiliation: Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA. jothi@mail.nih.gov

ABSTRACT
Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

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Static properties of transcription factors (TFs) within the hierarchical framework. (A) Average number of target genes (TGs) regulated or co-regulated by TFs (left), percentage of TFs in each layer that are hubs (middle), and degree distribution of TFs (right). (B) Break-down of combinatorial regulatory patterns from a TG's perspective showing the percentage of TGs regulated by a combinatorial set of TFs from one or more layers. Less than 1% of TGs are jointly regulated by the top- and bottom-layer TFs. Values marked with red and green texts and arrows indicate that the corresponding subgroups are statistically under- or over-represented, respectively, compared with those in random networks of same size and degree distribution as the yeast regulatory network (see Results and Materials and methods). The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (C) Break-down of feed-forward loop (FFL) motifs showing the composition of all FFL motifs in the yeast regulatory network. Top panel shows FFL motifs where all the three nodes involve TFs, and the bottom panel shows FFL motifs involving two TFs and a TG. About 94% of all FFL motifs involve only the core- and/or top-layer TFs. Statistically over-represented FFL patterns are indicated by a green arrow, P<1.6 × 10−3. The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (D) Percentages of TFs that are essential in each of the three layers of the hierarchy. (E) Distribution of TF conservation levels (presence/absence of orthologs) across 15 fungal genomes in each of the three layers of the hierarchy. (F) Distribution of number of gene ontology (GO) biological processes a TF is associated with.
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f4: Static properties of transcription factors (TFs) within the hierarchical framework. (A) Average number of target genes (TGs) regulated or co-regulated by TFs (left), percentage of TFs in each layer that are hubs (middle), and degree distribution of TFs (right). (B) Break-down of combinatorial regulatory patterns from a TG's perspective showing the percentage of TGs regulated by a combinatorial set of TFs from one or more layers. Less than 1% of TGs are jointly regulated by the top- and bottom-layer TFs. Values marked with red and green texts and arrows indicate that the corresponding subgroups are statistically under- or over-represented, respectively, compared with those in random networks of same size and degree distribution as the yeast regulatory network (see Results and Materials and methods). The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (C) Break-down of feed-forward loop (FFL) motifs showing the composition of all FFL motifs in the yeast regulatory network. Top panel shows FFL motifs where all the three nodes involve TFs, and the bottom panel shows FFL motifs involving two TFs and a TG. About 94% of all FFL motifs involve only the core- and/or top-layer TFs. Statistically over-represented FFL patterns are indicated by a green arrow, P<1.6 × 10−3. The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (D) Percentages of TFs that are essential in each of the three layers of the hierarchy. (E) Distribution of TF conservation levels (presence/absence of orthologs) across 15 fungal genomes in each of the three layers of the hierarchy. (F) Distribution of number of gene ontology (GO) biological processes a TF is associated with.

Mentions: First, we examined the local and global topological properties of TFs in relation to the above-established hierarchy. We noticed that, on an average (median values are reported), the TFs in the top layer regulate 54 TGs, the TFs in the core layer regulate 144 TGs, and the TFs in the bottom layer regulate 14 TGs (left panel in Figure 4A). The distribution of regulatory hubs (32 TFs constituting the top 20% of the highly connected TFs) within the hierarchy is striking (middle panel in Figure 4A). The hubs are rarely seen at the top of the hierarchy but are present predominantly in the core layer. In all, 27 out of the 32 TF hubs are present in the core layer, which accounts for 42% of all TFs in the core layer (P<1.7 × 10−8; hypergeometric test). The bottom layer contains no regulatory hubs (P<3.3 × 10−8; hypergeometric test). This shows that though the core layer contains the majority of the regulatory hubs, the inherent hierarchical structure is such that the top layer TFs, which are likely to trigger regulatory cascades down the hierarchy, are not enriched in regulatory hubs.


Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Jothi R, Balaji S, Wuster A, Grochow JA, Gsponer J, Przytycka TM, Aravind L, Babu MM - Mol. Syst. Biol. (2009)

Static properties of transcription factors (TFs) within the hierarchical framework. (A) Average number of target genes (TGs) regulated or co-regulated by TFs (left), percentage of TFs in each layer that are hubs (middle), and degree distribution of TFs (right). (B) Break-down of combinatorial regulatory patterns from a TG's perspective showing the percentage of TGs regulated by a combinatorial set of TFs from one or more layers. Less than 1% of TGs are jointly regulated by the top- and bottom-layer TFs. Values marked with red and green texts and arrows indicate that the corresponding subgroups are statistically under- or over-represented, respectively, compared with those in random networks of same size and degree distribution as the yeast regulatory network (see Results and Materials and methods). The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (C) Break-down of feed-forward loop (FFL) motifs showing the composition of all FFL motifs in the yeast regulatory network. Top panel shows FFL motifs where all the three nodes involve TFs, and the bottom panel shows FFL motifs involving two TFs and a TG. About 94% of all FFL motifs involve only the core- and/or top-layer TFs. Statistically over-represented FFL patterns are indicated by a green arrow, P<1.6 × 10−3. The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (D) Percentages of TFs that are essential in each of the three layers of the hierarchy. (E) Distribution of TF conservation levels (presence/absence of orthologs) across 15 fungal genomes in each of the three layers of the hierarchy. (F) Distribution of number of gene ontology (GO) biological processes a TF is associated with.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC2736650&req=5

f4: Static properties of transcription factors (TFs) within the hierarchical framework. (A) Average number of target genes (TGs) regulated or co-regulated by TFs (left), percentage of TFs in each layer that are hubs (middle), and degree distribution of TFs (right). (B) Break-down of combinatorial regulatory patterns from a TG's perspective showing the percentage of TGs regulated by a combinatorial set of TFs from one or more layers. Less than 1% of TGs are jointly regulated by the top- and bottom-layer TFs. Values marked with red and green texts and arrows indicate that the corresponding subgroups are statistically under- or over-represented, respectively, compared with those in random networks of same size and degree distribution as the yeast regulatory network (see Results and Materials and methods). The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (C) Break-down of feed-forward loop (FFL) motifs showing the composition of all FFL motifs in the yeast regulatory network. Top panel shows FFL motifs where all the three nodes involve TFs, and the bottom panel shows FFL motifs involving two TFs and a TG. About 94% of all FFL motifs involve only the core- and/or top-layer TFs. Statistically over-represented FFL patterns are indicated by a green arrow, P<1.6 × 10−3. The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (D) Percentages of TFs that are essential in each of the three layers of the hierarchy. (E) Distribution of TF conservation levels (presence/absence of orthologs) across 15 fungal genomes in each of the three layers of the hierarchy. (F) Distribution of number of gene ontology (GO) biological processes a TF is associated with.
Mentions: First, we examined the local and global topological properties of TFs in relation to the above-established hierarchy. We noticed that, on an average (median values are reported), the TFs in the top layer regulate 54 TGs, the TFs in the core layer regulate 144 TGs, and the TFs in the bottom layer regulate 14 TGs (left panel in Figure 4A). The distribution of regulatory hubs (32 TFs constituting the top 20% of the highly connected TFs) within the hierarchy is striking (middle panel in Figure 4A). The hubs are rarely seen at the top of the hierarchy but are present predominantly in the core layer. In all, 27 out of the 32 TF hubs are present in the core layer, which accounts for 42% of all TFs in the core layer (P<1.7 × 10−8; hypergeometric test). The bottom layer contains no regulatory hubs (P<3.3 × 10−8; hypergeometric test). This shows that though the core layer contains the majority of the regulatory hubs, the inherent hierarchical structure is such that the top layer TFs, which are likely to trigger regulatory cascades down the hierarchy, are not enriched in regulatory hubs.

Bottom Line: At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs.Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation.We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

View Article: PubMed Central - PubMed

Affiliation: Biostatistics Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA. jothi@mail.nih.gov

ABSTRACT
Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

Show MeSH
Related in: MedlinePlus