Nucleosome positioning by genomic excluding-energy barriers

Universitè Claude Bernard Lyon 1, Université de Lyon, F-69000 Lyon, France.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 12/2009; 106(52):22257-62. DOI: 10.1073/pnas.0909511106
Source: PubMed


Recent genome-wide nucleosome mappings along with bioinformatics studies have confirmed that the DNA sequence plays a more important role in the collective organization of nucleosomes in vivo than previously thought. Yet in living cells, this organization also results from the action of various external factors like DNA-binding proteins and chromatin remodelers. To decipher the code for intrinsic chromatin organization, there is thus a need for in vitro experiments to bridge the gap between computational models of nucleosome sequence preferences and in vivo nucleosome occupancy data. Here we combine atomic force microscopy in liquid and theoretical modeling to demonstrate that a major sequence signaling in vivo are high-energy barriers that locally inhibit nucleosome formation rather than favorable positioning motifs. We show that these genomic excluding-energy barriers condition the collective assembly of neighboring nucleosomes consistently with equilibrium statistical ordering principles. The analysis of two gene promoter regions in Saccharomyces cerevisiae and the human genome indicates that these genomic barriers direct the intrinsic nucleosome occupancy of regulatory sites, thereby contributing to gene expression regulation.

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Available from: Philippe Bouvet
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    • "Nucleosome exclusion by specific DNA sequences such as poly(dA–dT) tracts [30] [31] or by protein such as the transcription factor Abf1 [22] [29] contributes to recruit ORC. In turn, ORC shapes a pattern of nucleosome positioning around the origin that contributes to initiation [26] [29]. "
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    ABSTRACT: Eukaryotic replication origins are activated at different times during the S phase of the cell cycle, following a temporal program that is stably transmitted to daughter cells. Although the mechanisms that control initiation at the level of individual origins are now well understood, much less is known on how cells coordinate replication at hundreds of origins distributed on the chromosomes. In this review, we discuss recent advances shedding new light on how this complex process is regulated in the budding yeast S. cerevisiae. The picture that emerges from these studies is that replication timing is regulated in cis by mechanisms modulating the chromatin structure and the sub-nuclear organization of origins. These mechanisms do not affect the licensing of replication origins but determine their ability to compete for limiting initiation factors, which are recycled from early to late origins throughout the length of the S phase.
    Preview · Article · Sep 2013 · Journal of Molecular Biology
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    • "Eukaryotic chromatin can be viewed as a succession of superimposed organizational steps including the nucleosomal array, its condensation into the 30 nm chromatin fiber and the formation of chromatin loops, up to a full extent of condensation in metaphase chromosomes (van Holde 1988;Wolffe 1998;Calladine & Drew 1999;Alberts et al. 2002;Felsenfeld & Groudine 2003). If specific chromatin configurations may be dictated by the DNA sequence itself (Satchwell et al. 1986;Ioshikhes et al. 1996;Widom 2001;Segal et al. 2006;St-Jean et al. 2008;Milani et al. 2009;Arneodo et al. 2011;Chevereau et al. 2011;Travers et al. 2012;Struhl & Segal 2013), the chromatin structure is subject to various epigenetic modifications in any given cell type, including DNA methylation, histone modifications, histone variant incorporation and DNA-binding proteins (Kouzarides 2007;Zhou et al. 2011;Zentner & Henikoff 2013). Recent technical advances in genomics and epigenomics including the combination of chromatin immunoprecipitation (ChIP) with massive parallel sequencing (ChIP-Seq) () have made available a wealth of genome-wide data in various eukaryotic organisms, from budding yeast, to plants, worm, fly and mammals (Bernstein et al. 2007;The ENCODE Project Consortium 2007;Rando & Chang 2009;Roudier et al. 2009;Gerstein et al. 2010;Kharchenko et al. 2010;The modENCODE Consortium 2010;Feng & Jacobsen 2011;The ENCODE Project Consortium 2011). "
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    ABSTRACT: Increasing knowledge of chromatin structure in various cell types raises the challenge of deciphering the contribution of epigenetic modifications to the regulation of nuclear functions in mammals. In a recent study, we have analysed the genome-wide distributions of thirteen epigenetic marks in the human cell line K562 at 100 kb resolution of Mean Replication Timing (MRT) data. Using classical clustering techniques, we have shown that the combinatorial complexity of these epigenetic data can be reduced to four predominant chromatin states that replicate at different periods of the S-phase. C1 is an early replicating transcriptionally active euchromatin state, C2 a mid-S repressive type of chromatin associated with Polycomb complexes, C3 a silent chromatin with lack of chromatin marks that replicates later than C2 but before C4, a HP1-associated heterochromatin state that replicates at the end of S-phase. These four chromatin states display remarkable similarities with those recently reported in fly, worm and plants at higher ∼ 1 kb resolution of gene expression data. Here, we extend our integrative analysis of epigenetic data in the K562 human cell line to this smaller scale by focusing on gene promoters (±3 kb around transcription start sites). We show that these promoters can similarly be classified into four main chromatin states: P1 regroups all the marks of transcriptionally active chromatin and corresponds to CpG rich promoters of highly expressed genes; P2 is notably associated with the histone modification H3K27me3 that is the mark of a polycomb repressed chromatin state; P3 corresponds to promoters that are not enriched for any available marks as the signature of a ‘null’ or ‘black’ silent heterochromatin state and P4 characterizes the few gene promoters that contain only the constitutive heterochromatin histone modification H3K9me3. When investigating the coherence between promoter activity (P1, P2, P3 or P4) and the large-scale chromatin environment (C1, C2, C3 or C4), we find that the higher the gene density in a considered 100 kb-window, the higher (resp. the lower) the probability of a P1 active promoter (resp. silent P2, P3 and P4 promoters) to be surrounded by an open euchromatin C1 (resp. facultative C2, black C3 or HP1-associated C4 heterochromatin) environment. From large to small scales, it is mainly C4 and to a lesser extent C3 heterochromatin environments both corresponding to gene poor regions, that strongly conditions promoters to belong to the inactive P3 and P4 classes. If C1 (resp. C2) environment surrounds a majority of corresponding active P1 (resp. P2) promoters, it also contains a non-negligible proportion of inactive P2 and P3 (resp. active P1 and inactive P3) promoters. When further investigating the large-scale organization of human genes with respect to ‘master’ replication origins that were shown to border megabase-sized U-shaped MRT domains, we reveal some significant enrichment of highly expressed P1 genes in a closed neighbourhood of these early initiation zones consistently with the gradient of chromatin states observed from C1 at U-domain borders followed by C2, C3 and C4 at U-domain centers. On the contrary to P2 promoters that are mainly found in the C2 environment at finite distance (∼200–300 kb) from U-domain borders, the inactive P3 and P4 promoters are distributed rather homogeneously inside U-domains. The generalization of our study to different cell types including ES, somatic and cancer cells is likely to provide new insight on the global reorganization of replication domains during differentiation (or disease) in relation to coordinated changes in chromatin environment and gene expression.
    Preview · Article · Jun 2013 · Frontiers in Life Science
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    • "Besides those features such as the propeller twist and free energy which overlap with previous computational studies, we also find that the DNA denaturation, DNA-bending stiffness, Stacking energy and Z-DNA are effective in capturing nucleosome occupancy. These structural features capture more accurately in vivo nucleosome occupancy than sequence compositional features, consistent with a previous analysis which indicated that a major sequence signaling in vivo is a high-energy barrier rather than favorable sequence motifs [48]. Furthermore, we proposed a novel computational method, DLaNe, to detect peaks (valleys) of structural profiles to locate nucleosome positions. "
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    ABSTRACT: Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene expression regulation. The results indicated that our proposed methods are effective in predicting nucleosome occupancy and positions and that these structural features are highly predictive of nucleosome organization.The implementation of our DLaNe method based on structural features is available online.
    Full-text · Article · Mar 2012 · BMC Bioinformatics
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