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Transcription stochasticity of complex gene regulation models.

ABSTRACT: Transcription is regulated by a multitude of factors that concertedly induce genes to switch between activity states. Eukaryotic transcription involves a multitude of complexes that sequentially assemble on chromatin under the influence of transcription factors and the dynamic state of chromatin. Prokaryotic transcription depends on transcription factors, sigma-factors, and, in some cases, on DNA looping. We present a stochastic model of transcription that considers these complex regulatory mechanisms. We coarse-grain the molecular details in such a way that the model can describe a broad class of gene-regulation mechanisms. We solve this model analytically for various measures of stochastic transcription and compare alternative gene-regulation designs. We find that genes with complex multiprotein regulation can have peaked burst-size distributions in contrast to the geometric distributions found for simple models of transcription regulation. Burst-size distributions are, in addition, shaped by mRNA degradation during transcription bursts. We derive the stochastic properties of genes in the limit of deterministic switch times. These genes typically have reduced transcription noise. Severe timescale separation between gene regulation and transcription initiation enhances noise and leads to bimodal mRNA copy number distributions. In general, complex mechanisms for gene regulation lead to nonexponential waiting-time distributions for gene switching and transcription initiation, which typically reduce noise in mRNA copy numbers and burst size. Finally, we discuss that qualitatively different gene regulation models can often fit the same experimental data on single-cell mRNA abundance even though they have qualitatively different burst-size statistics and regulatory parameters.

SUBMITTER: Schwabe A

PROVIDER: S-EPMC3446772 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Transcription stochasticity of complex gene regulation models.

Schwabe Anne A Rybakova Katja N KN Bruggeman Frank J FJ

Biophysical journal 20120901 6

Transcription is regulated by a multitude of factors that concertedly induce genes to switch between activity states. Eukaryotic transcription involves a multitude of complexes that sequentially assemble on chromatin under the influence of transcription factors and the dynamic state of chromatin. Prokaryotic transcription depends on transcription factors, sigma-factors, and, in some cases, on DNA looping. We present a stochastic model of transcription that considers these complex regulatory mech ...[more]

PMID: 22995487

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Project description:Recent discovery that much of the mammalian genome does not encode protein-coding genes (PCGs) has brought widespread attention to long noncoding RNAs (lncRNAs) as a novel layer of biological regulation. Enhancer lnc (elnc) RNAs from the enhancer regions of the genome carry the capacity to regulate PCGs in cis or in trans. Spotted fever rickettsioses represent the consequence of host infection with Gram-negative, obligate intracellular bacteria in the Genus Rickettsia. Despite being implicated in the pathways of infection and inflammation, the roles of lncRNAs in host response to Rickettsia species have remained a mystery. We have profiled the expression of host lncRNAs during infection of susceptible mice with R. conorii as a model closely mimicking the pathogenesis of human spotted fever rickettsioses. RNA sequencing on the lungs of infected hosts yielded reads mapping to 74,964 non-coding RNAs, 206 and 277 of which were determined to be significantly up- and down-regulated, respectively, in comparison to uninfected controls. Following removal of short non-coding RNAs and ambiguous transcripts, remaining transcripts underwent in-depth analysis of mouse lung epigenetic signatures H3K4Me1 and H3K4Me3, active transcript markers (POLR2A, p300, CTCF), and DNaseI hypersensitivity sites to identify two potentially active and highly up-regulated elncRNAs NONMMUT013718 and NONMMUT024103. Using Hi-3C sequencing resource, we further determined that genomic loci of NONMMUT013718 and NONMMUT024103 might interact with and regulate the expression of nearby PCGs, namely Id2 (inhibitor of DNA binding 2) and Apol10b (apolipoprotein 10b), respectively. Heterologous reporter assays confirmed the activity of elncRNAs as the inducers of their predicted PCGs. In the lungs of infected mice, expression of both elncRNAs and their targets was significantly higher than mock-infected controls. Induced expression of NONMMUT013718/Id2 in murine macrophages and NONMMUT024103/Apol10b in endothelial cells was also clearly evident during R. conorii infection in vitro. Finally, shRNA mediated knock-down of NONMMUT013718 and NONMMUT024103 elncRNAs resulted in reduced expression of endogenous Id2 and Apl10b, demonstrating the regulatory roles of these elncRNAs on their target PCGs. Our results provide very first experimental evidence suggesting altered expression of pulmonary lncRNAs and elncRNA-mediated regulation of PCGs involved in immunity and during host interactions with pathogenic rickettsiae.

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Transcription stochasticity of complex gene regulation models.

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Transcription stochasticity of complex gene regulation models.

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