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Regulatory network structure as a dominant determinant of transcription factor evolutionary rate.

ABSTRACT: The evolution of transcriptional regulatory networks has thus far mostly been studied at the level of cis-regulatory elements. To gain a complete understanding of regulatory network evolution we must also study the evolutionary role of trans-factors, such as transcription factors (TFs). Here, we systematically assess genomic and network-level determinants of TF evolutionary rate in yeast, and how they compare to those of generic proteins, while carefully controlling for differences of the TF protein set, such as expression level. We found significantly distinct trends relating TF evolutionary rate to mRNA expression level, codon adaptation index, the evolutionary rate of physical interaction partners, and, confirming previous reports, to protein-protein interaction degree and regulatory in-degree. We discovered that for TFs, the dominant determinants of evolutionary rate lie in the structure of the regulatory network, such as the median evolutionary rate of target genes and the fraction of species-specific target genes. Decomposing the regulatory network by edge sign, we found that this modular evolution of TFs and their targets is limited to activating regulatory relationships. We show that fast evolving TFs tend to regulate other TFs and niche-specific processes and that their targets show larger evolutionary expression changes than targets of other TFs. We also show that the positive trend relating TF regulatory in-degree and evolutionary rate is likely related to the species-specificity of the transcriptional regulation modules. Finally, we discuss likely causes for TFs' different evolutionary relationship to the physical interaction network, such as the prevalence of transient interactions in the TF subnetwork. This work suggests that positive and negative regulatory networks follow very different evolutionary rules, and that transcription factor evolution is best understood at a network- or systems-level.

SUBMITTER: Coulombe-Huntington J

PROVIDER: S-EPMC3475661 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Regulatory network structure as a dominant determinant of transcription factor evolutionary rate.

Coulombe-Huntington Jasmin J Xia Yu Y

PLoS computational biology 20121018 10

The evolution of transcriptional regulatory networks has thus far mostly been studied at the level of cis-regulatory elements. To gain a complete understanding of regulatory network evolution we must also study the evolutionary role of trans-factors, such as transcription factors (TFs). Here, we systematically assess genomic and network-level determinants of TF evolutionary rate in yeast, and how they compare to those of generic proteins, while carefully controlling for differences of the TF pro ...[more]

PMID: 23093926

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Project description:BACKGROUND: MicroRNA (miRNA) is a class of small RNAs of ~22nt which play essential roles in many crucial biological processes and numerous human diseases at post-transcriptional level of gene expression. It has been revealed that miRNA genes tend to be clustered, and the miRNAs organized into one cluster are usually transcribed coordinately. This implies a coordinated regulation mode exerted by clustered miRNAs. However, how the clustered miRNAs coordinate their regulations on large scale gene expression is still unclear. RESULTS: We constructed the miRNA-transcription factor regulatory network that contains the interactions between transcription factors (TFs), miRNAs and non-TF protein-coding genes, and made a genome-wide study on the regulatory coordination of clustered miRNAs. We found that there are two types of miRNA clusters, i.e. homo-clusters that contain miRNAs of the same family and hetero-clusters that contain miRNAs of various families. In general, the homo-clustered as well as the hetero-clustered miRNAs both exhibit coordinated regulation since the miRNAs belonging to one cluster tend to be involved in the same network module, which performs a relatively isolated biological function. However, the homo-clustered miRNAs show a direct regulatory coordination that is realized by one-step regulation (i.e. the direct regulation of the coordinated targets), whereas the hetero-clustered miRNAs show an indirect regulatory coordination that is realized by a regulation comprising at least three steps (e.g. the regulation on the coordinated targets by a miRNA through a sequential action of two TFs). The direct and indirect regulation target different categories of genes, the former predominantly regulating genes involved in emergent responses, the latter targeting genes that imply long-term effects. CONCLUSION: The genomic clustering of miRNAs is closely related to the coordinated regulation in the gene regulatory network. The pattern of regulatory coordination is dependent on the composition of the miRNA cluster. The homo-clustered miRNAs mainly coordinate their regulation rapidly, while the hetero-clustered miRNAs exert control with a delay. The diverse pattern of regulatory coordination suggests distinct roles of the homo-clustered and the hetero-clustered miRNAs in biological processes.

Project description:BackgroundInflammation triggered by infection or injury is tightly controlled by glucocorticoid hormones which signal via a dedicated transcription factor, the Glucocorticoid Receptor (GR), to regulate hundreds of genes. However, the hierarchy of transcriptional responses to GR activation and the molecular basis of their oftentimes non-linear dynamics are not understood.ResultsWe investigated early glucocorticoid-driven transcriptional events in macrophages, a cell type highly responsive to both pro- and anti-inflammatory stimuli. Using whole transcriptome analyses in resting and acutely lipopolysaccharide (LPS)-stimulated macrophages, we show that early GR target genes form dense networks with the majority of control nodes represented by transcription factors. The expression dynamics of several glucocorticoid-responsive genes are consistent with feed forward loops (FFL) and coincide with rapid GR recruitment. Notably, GR binding sites in genes encoding members of the KLF transcription factor family colocalize with KLF binding sites. Moreover, our gene expression, transcription factor binding and computational data are consistent with the existence of the GR-KLF9-KLF2 incoherent FFL. Analysis of LPS-downregulated genes revealed striking enrichment in multimerized Zn-fingers- and KRAB domain-containing proteins known to bind nucleic acids and repress transcription by propagating heterochromatin. This raises an intriguing possibility that an increase in chromatin accessibility in inflammatory macrophages results from broad downregulation of negative chromatin remodelers.ConclusionsPro- and anti-inflammatory stimuli alter the expression of a vast array of transcription factors and chromatin remodelers. By regulating multiple transcription factors, which propagate the initial hormonal signal, GR acts as a coordinating hub in anti-inflammatory responses. As several KLFs promote the anti-inflammatory program in macrophages, we propose that GR and KLFs functionally cooperate to curb inflammation.

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Regulatory network structure as a dominant determinant of transcription factor evolutionary rate.

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Regulatory network structure as a dominant determinant of transcription factor evolutionary rate.

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