Limits...
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.

Show MeSH
Network representation of a transcriptional regulatory cascade. Transcription factors (TFs), denoted as nodes in a network (red and green circles), represent several entities (gene, mRNA, and protein) and events (transcription, translation, degradation, etc) that are compressed in both space and time. Although a series of regulatory events can be conveniently represented as a node in the network, the dynamics of the entities and the biological processes that make up the node are not captured.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2736650&req=5

f1: Network representation of a transcriptional regulatory cascade. Transcription factors (TFs), denoted as nodes in a network (red and green circles), represent several entities (gene, mRNA, and protein) and events (transcription, translation, degradation, etc) that are compressed in both space and time. Although a series of regulatory events can be conveniently represented as a node in the network, the dynamics of the entities and the biological processes that make up the node are not captured.

Mentions: Although transcriptional regulatory interactions are conveniently represented as nodes and edges in a network, it is important to note that each node in the network represents several entities (gene, mRNA, and protein) and events (transcription, translation, degradation, etc) that are compressed in both space and time (see Figure 1). Consequently, the dynamic nature of these events (synthesis and degradation of mRNA and protein molecules) and entities (steady-state levels of mRNA and protein molecules) are expected to affect the regulatory interactions in the network. Although we have a good understanding of the topology of regulatory networks, the dynamics of nodes (TFs and TGs) in these networks and their role in systems behavior remain largely unexplored. In this regard, several fundamental questions remain unanswered: for example, do TFs in the regulatory network have distinct dynamic properties (e.g., abundance, half-life, etc) characterizing their role in a regulatory cascade? More generally, does the position of a TF in the network structure relate to its dynamics? Although the richness of this detail is lost in the network representation, such questions can be addressed by integrating diverse genomic datasets encapsulating the dynamics of transcription and translation.


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)

Network representation of a transcriptional regulatory cascade. Transcription factors (TFs), denoted as nodes in a network (red and green circles), represent several entities (gene, mRNA, and protein) and events (transcription, translation, degradation, etc) that are compressed in both space and time. Although a series of regulatory events can be conveniently represented as a node in the network, the dynamics of the entities and the biological processes that make up the node are not captured.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f1: Network representation of a transcriptional regulatory cascade. Transcription factors (TFs), denoted as nodes in a network (red and green circles), represent several entities (gene, mRNA, and protein) and events (transcription, translation, degradation, etc) that are compressed in both space and time. Although a series of regulatory events can be conveniently represented as a node in the network, the dynamics of the entities and the biological processes that make up the node are not captured.
Mentions: Although transcriptional regulatory interactions are conveniently represented as nodes and edges in a network, it is important to note that each node in the network represents several entities (gene, mRNA, and protein) and events (transcription, translation, degradation, etc) that are compressed in both space and time (see Figure 1). Consequently, the dynamic nature of these events (synthesis and degradation of mRNA and protein molecules) and entities (steady-state levels of mRNA and protein molecules) are expected to affect the regulatory interactions in the network. Although we have a good understanding of the topology of regulatory networks, the dynamics of nodes (TFs and TGs) in these networks and their role in systems behavior remain largely unexplored. In this regard, several fundamental questions remain unanswered: for example, do TFs in the regulatory network have distinct dynamic properties (e.g., abundance, half-life, etc) characterizing their role in a regulatory cascade? More generally, does the position of a TF in the network structure relate to its dynamics? Although the richness of this detail is lost in the network representation, such questions can be addressed by integrating diverse genomic datasets encapsulating the dynamics of transcription and translation.

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