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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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Dynamic properties of transcription factors (TFs) within the hierarchical framework. Distribution of TF values in each of the three layers of the inferred hierarchy for transcript abundance (mRNA molecules per cell) (A), transcript half-life (min) (B), protein abundance (protein molecules per cell) (C), protein half-life (min) (D), and noise in protein abundance (variability in protein levels in a cell population) (F). (E) Percentages of TFs in each of the three hierarchical layers containing a TATA-box. The expected percentage is shown as a broken line (22%). The y axis in (F) denotes protein noise measured as the distance from median co-efficient of variation of all proteins (DM; see Materials and methods).
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f5: Dynamic properties of transcription factors (TFs) within the hierarchical framework. Distribution of TF values in each of the three layers of the inferred hierarchy for transcript abundance (mRNA molecules per cell) (A), transcript half-life (min) (B), protein abundance (protein molecules per cell) (C), protein half-life (min) (D), and noise in protein abundance (variability in protein levels in a cell population) (F). (E) Percentages of TFs in each of the three hierarchical layers containing a TATA-box. The expected percentage is shown as a broken line (22%). The y axis in (F) denotes protein noise measured as the distance from median co-efficient of variation of all proteins (DM; see Materials and methods).

Mentions: We next investigated whether TFs within each hierarchical layer have different dynamic properties in terms of their abundance and degradation rates. Integrating information on transcript abundance (Holstege et al, 1998) and half-life (Wang et al, 2002) with the hierarchical structure revealed that mRNA molecules coding for core-layer TFs are relatively more abundant than that of top- and bottom-layer TFs (Figure 5A). The abundance of transcripts coding for core-layer TFs is statistically higher than that coding for bottom-layer TFs (P<10−3; Wilcoxon's rank-sum test), but not top-layer TFs (P<0.136; Wilcoxon's rank-sum test). Transcripts of TFs from all three layers have similar half-life (Figure 5B). As transcript degradation rates are comparable, this suggested that the core-layer TFs are likely to be transcribed at a higher rate than the top- or bottom-layer TFs. We then investigated if the availability of TFs may be regulated at the protein level.


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)

Dynamic properties of transcription factors (TFs) within the hierarchical framework. Distribution of TF values in each of the three layers of the inferred hierarchy for transcript abundance (mRNA molecules per cell) (A), transcript half-life (min) (B), protein abundance (protein molecules per cell) (C), protein half-life (min) (D), and noise in protein abundance (variability in protein levels in a cell population) (F). (E) Percentages of TFs in each of the three hierarchical layers containing a TATA-box. The expected percentage is shown as a broken line (22%). The y axis in (F) denotes protein noise measured as the distance from median co-efficient of variation of all proteins (DM; see Materials and methods).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f5: Dynamic properties of transcription factors (TFs) within the hierarchical framework. Distribution of TF values in each of the three layers of the inferred hierarchy for transcript abundance (mRNA molecules per cell) (A), transcript half-life (min) (B), protein abundance (protein molecules per cell) (C), protein half-life (min) (D), and noise in protein abundance (variability in protein levels in a cell population) (F). (E) Percentages of TFs in each of the three hierarchical layers containing a TATA-box. The expected percentage is shown as a broken line (22%). The y axis in (F) denotes protein noise measured as the distance from median co-efficient of variation of all proteins (DM; see Materials and methods).
Mentions: We next investigated whether TFs within each hierarchical layer have different dynamic properties in terms of their abundance and degradation rates. Integrating information on transcript abundance (Holstege et al, 1998) and half-life (Wang et al, 2002) with the hierarchical structure revealed that mRNA molecules coding for core-layer TFs are relatively more abundant than that of top- and bottom-layer TFs (Figure 5A). The abundance of transcripts coding for core-layer TFs is statistically higher than that coding for bottom-layer TFs (P<10−3; Wilcoxon's rank-sum test), but not top-layer TFs (P<0.136; Wilcoxon's rank-sum test). Transcripts of TFs from all three layers have similar half-life (Figure 5B). As transcript degradation rates are comparable, this suggested that the core-layer TFs are likely to be transcribed at a higher rate than the top- or bottom-layer TFs. We then investigated if the availability of TFs may be regulated at the protein level.

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