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CpG domains downstream of TSSs promote high levels of gene expression.

ABSTRACT: CpG dinucleotides are known to play a crucial role in regulatory domains, affecting gene expression in their natural context. Here, we demonstrate that intragenic CpG frequency and distribution impacts transgene and genomic gene expression levels in mammalian cells. As shown for the Macrophage Inflammatory Protein 1?, de novo RNA synthesis correlates with the number of CpG dinucleotides, whereas RNA splicing, stability, nuclear export and translation are not affected by the sequence modification. Differences in chromatin accessibility in vivo and altered nucleosome positioning in vitro suggest that increased CpG levels destabilize the chromatin structure. Moreover, enriched CpG levels correlate with increased RNA polymerase II elongation rates in vivo. Interestingly, elevated CpG levels particularly at the 5' end of the gene promote efficient transcription. We show that this is a genome-wide feature of highly expressed genes, by identifying a domain of ?700 bp with high CpG content downstream of the transcription start site, correlating with high levels of transcription. We suggest that these 5' CpG domains are required to distort the chromatin structure and to increase gene activity.

SUBMITTER: Krinner S

PROVIDER: S-EPMC3973331 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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CpG domains downstream of TSSs promote high levels of gene expression.

Krinner Simone S Heitzer Asli P AP Diermeier Sarah D SD Obermeier Ingrid I Längst Gernot G Wagner Ralf R

Nucleic acids research 20140109 6

CpG dinucleotides are known to play a crucial role in regulatory domains, affecting gene expression in their natural context. Here, we demonstrate that intragenic CpG frequency and distribution impacts transgene and genomic gene expression levels in mammalian cells. As shown for the Macrophage Inflammatory Protein 1α, de novo RNA synthesis correlates with the number of CpG dinucleotides, whereas RNA splicing, stability, nuclear export and translation are not affected by the sequence modification ...[more]

PMID: 24413563

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Project description:Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.

Dataset Information

CpG domains downstream of TSSs promote high levels of gene expression.

Publications

CpG domains downstream of TSSs promote high levels of gene expression.

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