116 research outputs found

    Forces driving the three-dimensional folding of eukaryotic genomes

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    The last decade has radically renewed our understanding of higher order chromatin folding in the eukaryotic nucleus. As a result, most current models are in support of a mostly hierarchical and relatively stable folding of chromosomes dividing chromosomal territories into A- (active) and B- (inactive) compartments, which are then further partitioned into topologically associating domains (TADs), each of which is made up from multiple loops stabilized mainly by the CTCF and cohesin chromatin-binding complexes. Nonetheless, the structure-to-function relationship of eukaryotic genomes is still not well understood. Here, we focus on recent work highlighting the biophysical and regulatory forces that contribute to the spatial organization of genomes, and we propose that the various conformations that chromatin assumes are not so much the result of a linear hierarchy, but rather of both converging and conflicting dynamic forces that act on it

    The 4-D landscape of the inflammatory response

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    Enhancers and silencers: an integrated and simple model for their function

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    Regulatory DNA elements such as enhancers, silencers and insulators are embedded in metazoan genomes, and they control gene expression during development. Although they fulfil different roles, they share specific properties. Herein we discuss some examples and a parsimonious model for their function is proposed. All are transcription units that tether their target promoters close to, or distant from, transcriptional hot spots (or 'factories')

    A dynamical model reveals gene co-localizations in nucleus

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    Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency-or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes

    Exploiting native forces to capture chromosome conformation in mammalian cell nuclei

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    Mammalian interphase chromosomes fold into a multitude of loops to fit the confines of cell nuclei, and looping is tightly linked to regulated function. Chromosome conformation capture (3C) technology has significantly advanced our understanding of this structure-to-function relationship. However, all 3C-based methods rely on chemical cross-linking to stabilize spatial interactions. This step remains a “black box” as regards the biases it may introduce, and some discrepancies between microscopy and 3C studies have now been reported. To address these concerns, we developed “i3C”

    Transcription factories in the context of the nuclear and genome organization

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    In the eukaryotic nucleus, genes are transcribed in transcription factories. In the present review, we re-evaluate the models of transcription factories in the light of recent and older data. Based on this analysis, we propose that transcription factories result from the aggregation of RNA polymerase II-containing pre-initiation complexes assembled next to each other in the nuclear space. Such an aggregation can be triggered by the phosphorylation of the C-terminal domain of RNA polymerase II molecules and their interaction with various transcription factors. Individual transcription factories would thus incorporate tissue-specific, co-regulated as well as housekeeping genes based only on their initial proximity to each other in the nuclear space. Targeting genes to be transcribed to protein-dense factories that contain all factors necessary for transcription initiation and elongation through chromatin templates clearly favors a more economical utilization and better recycling of the transcription machinery

    The proteomes of transcription factories containing RNA polymerases I, II or III

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    Human nuclei contain three RNA polymerases (I, II and III) that transcribe different groups of genes; the active forms of all three are difficult to isolate because they are bound to the substructure. Here we describe a purification approach for isolating active RNA polymerase complexes from mammalian cells. After isolation, we analyzed their protein content by mass spectrometry. Each complex represents part of the core of a transcription factory. For example, the RNA polymerase II complex contains subunits unique to RNA polymerase II plus various transcription factors but shares a number of ribonucleoproteins with the other polymerase complexes; it is also rich in polymerase II transcripts. We also describe a native chromosome conformation capture method to confirm that the complexes remain attached to the same pairs of DNA templates found in vivo
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