Sequence-based prediction of single nucleosome positioning and genome-wide nucleosome occupancy

Specific DNA binding of archaeal histones HMfA and HMfB

In archaea, histones play a role in genome compaction and are involved in transcription regulation. Whereas archaeal histones bind DNA without sequence specificity, they bind preferentially to DNA containing repeats of alternating A/T and G/C motifs. These motifs are also present on the artificial sequence "Clone20," a high-affinity model sequence for binding of the histones from Methanothermus fervidus. Here, we investigate the binding of HMfA and HMfB to Clone20 DNA. We show that specific binding at low protein concentrations (<30 nM) yields a modest level of DNA compaction, attributed to tetrameric nucleosome formation, whereas nonspecific binding strongly compacts DNA. We also demonstrate that histones impaired in hypernucleosome formation are still able to recognize the Clone20 sequence. Histone tetramers indeed exhibit a higher binding affinity for Clone20 than nonspecific DNA. Our results indicate that a high-affinity DNA sequence does not act as a nucleation site, but is bound by a tetramer which we propose is geometrically different from the hypernucleosome. Such a mode of histone binding might permit sequence-driven modulation of hypernucleosome size. These findings might be extrapolated to histone variants that do not form hypernucleosomes. Versatile binding modes of histones could provide a platform for functional interplay between genome compaction and transcription.

Beyond Sequence: Internucleosomal Interactions Dominate Array Assembly

The organization of the nucleosome array is a critical component of the chromatin assembly into higher order structure as well as its function. Here, we investigated the contributions of the DNA sequence and internucleosomal interactions on the organization of the nucleosomal arrays in compact structures using atomic force microscopy. We assembled nucleosomes on DNA substrates allowing for the formation of tetranucleosomes. We found that nucleosomes are capable of close positioning with no discernible space between them, even in the case of assembled dinucleosomes. This morphology of the array is in contrast with that observed for arrays assembled with repeats of the nucleosome positioning motifs separated by uniform spacers. Simulated assembly of tetranucleosomes by random placement along the substrates revealed that nucleosome array compaction is promoted by the interaction of the nucleosomes. We developed a theoretical model to account for the role of DNA sequence and internucleosomal interactions in the formation of the nucleosome structures. These findings suggest that, in the chromatin assembly, the affinity of the nucleosomes to the DNA sequence and the strengths of the internucleosomal interactions are the two major factors defining the compactness of the chromatin.

Comprehensive computational analysis of epigenetic descriptors affecting CRISPR-Cas9 off-target activity

BACKGROUND

A common issue in CRISPR-Cas9 genome editing is off-target activity, which prevents the widespread use of CRISPR-Cas9 in medical applications. Among other factors, primary chromatin structure and epigenetics may influence off-target activity.

METHODS

In this work, we utilize crisprSQL, an off-target database, to analyze the effect of 19 epigenetic descriptors on CRISPR-Cas9 off-target activity. Termed as 19 epigenetic features/scores, they consist of 6 experimental epigenetic and 13 computed nucleosome organization-related features. In terms of novel features, 15 of the epigenetic scores are newly considered. The 15 newly considered scores consist of 13 freshly computed nucleosome occupancy/positioning scores and 2 experimental features (MNase and DRIP). The other 4 existing scores are experimental features (CTCF, DNase I, H3K4me3, RRBS) commonly used in deep learning models for off-target activity prediction. For data curation, MNase was aggregated from existing experimental nucleosome occupancy data. Based on the sequence context information available in crisprSQL, we also computed nucleosome occupancy/positioning scores for off-target sites.

RESULTS

To investigate the relationship between the 19 epigenetic features and off-target activity, we first conducted Spearman and Pearson correlation analysis. Such analysis shows that some computed scores derived from training-based models and training-free algorithms outperform all experimental epigenetic features. Next, we evaluated the contribution of all epigenetic features in two successful machine/deep learning models which predict off-target activity. We found that some computed scores, unlike all 6 experimental features, significantly contribute to the predictions of both models. As a practical research contribution, we make the off-target dataset containing all 19 epigenetic features available to the research community.

CONCLUSIONS

Our comprehensive computational analysis helps the CRISPR-Cas9 community better understand the relationship between epigenetic features and CRISPR-Cas9 off-target activity.

Reconstituted TAD-size chromatin fibers feature heterogeneous nucleosome clusters

Large topologically associated domains (TADs) contain irregularly spaced nucleosome clutches, and interactions between such clutches are thought to aid the compaction of these domains. Here, we reconstituted TAD-sized chromatin fibers containing hundreds of nucleosomes on native source human and lambda-phage DNA and compared their mechanical properties at the single-molecule level with shorter ‘601’ arrays with various nucleosome repeat lengths. Fluorescent imaging showed increased compaction upon saturation of the DNA with histones and increasing magnesium concentration. Nucleosome clusters and their structural fluctuations were visualized in confined nanochannels. Force spectroscopy revealed not only similar mechanical properties of the TAD-sized fibers as shorter fibers but also large rupture events, consistent with breaking the interactions between distant clutches of nucleosomes. Though the arrays of native human DNA, lambda-phage and ‘601’ DNA featured minor differences in reconstitution yield and nucleosome stability, the fibers’ global structural and mechanical properties were similar, including the interactions between nucleosome clutches. These single-molecule experiments quantify the mechanical forces that stabilize large TAD-sized chromatin domains consisting of disordered, dynamically interacting nucleosome clutches and their effect on the condensation of large chromatin domains.

Nucleosome sliding can influence the spreading of histone modifications

Nucleosomes are the fundamental building blocks of chromatin that not only help in the folding of chromatin, but also in carrying epigenetic information. It is known that nucleosome sliding is responsible for dynamically organizing chromatin structure and the resulting gene regulation. Since sliding can move two neighboring nucleosomes physically close or away, can it play a role in the spreading of histone modifications? We investigate this by simulating a stochastic model that couples nucleosome dynamics with the kinetics of histone modifications. We show that the sliding of nucleosomes can affect the modification pattern as well as the time it takes to modify a given region of chromatin. Exploring different nucleosome densities and modification kinetic parameters, we show that nucleosome sliding can be important for creating histone modification domains. Our model predicts that nucleosome density coupled with sliding dynamics can create an asymmetric histone modification profile around regulatory regions. We also compute the probability distribution of modified nucleosomes and relaxation kinetics of modifications. Our predictions are comparable with known experimental results.

The lane-switch mechanism for nucleosome repositioning by DNA translocase

Translocases such as DNA/RNA polymerases, replicative helicases, and exonucleases are involved in eukaryotic DNA transcription, replication, and repair. Since eukaryotic genomic DNA wraps around histone octamers and forms nucleosomes, translocases inevitably encounter nucleosomes. A previous study has shown that a nucleosome repositions downstream when a translocase collides with the nucleosome. However, the molecular mechanism of the downstream repositioning remains unclear. In this study, we identified the lane-switch mechanism for downstream repositioning with molecular dynamics simulations and validated it with restriction enzyme digestion assays and deep sequencing assays. In this mechanism, after a translocase unwraps nucleosomal DNA up to the site proximal to the dyad, the remaining wrapped DNA switches its binding lane to that vacated by the unwrapping, and the downstream DNA rewraps, completing downstream repositioning. This mechanism may have broad implications for transcription through nucleosomes, histone recycling, and nucleosome remodeling.

Comparative analysis and prediction of nucleosome positioning using integrative feature representation and machine learning algorithms

Background

Nucleosome plays an important role in the process of genome expression, DNA replication, DNA repair and transcription. Therefore, the research of nucleosome positioning has invariably received extensive attention. Considering the diversity of DNA sequence representation methods, we tried to integrate multiple features to analyze its effect in the process of nucleosome positioning analysis. This process can also deepen our understanding of the theoretical analysis of nucleosome positioning.

Results

Here, we not only used frequency chaos game representation (FCGR) to construct DNA sequence features, but also integrated it with other features and adopted the principal component analysis (PCA) algorithm. Simultaneously, support vector machine (SVM), extreme learning machine (ELM), extreme gradient boosting (XGBoost), multilayer perceptron (MLP) and convolutional neural networks (CNN) are used as predictors for nucleosome positioning prediction analysis, respectively. The integrated feature vector prediction quality is significantly superior to a single feature. After using principal component analysis (PCA) to reduce the feature dimension, the prediction quality of H. sapiens dataset has been significantly improved.

Conclusions

Comparative analysis and prediction on H. sapiens, C. elegans, D. melanogaster and S. cerevisiae datasets, demonstrate that the application of FCGR to nucleosome positioning is feasible, and we also found that integrative feature representation would be better.

Nucleosome-induced homology recognition in chromatin

One of the least understood properties of chromatin is the ability of its similar regions to recognize each other through weak interactions. Theories based on electrostatic interactions between helical macromolecules suggest that the ability to recognize sequence homology is an innate property of the non-ideal helical structure of DNA. However, this theory does not account for the nucleosomal packing of DNA. Can homologous DNA sequences recognize each other while wrapped up in the nucleosomes? Can structural homology arise at the level of nucleosome arrays? Here, we present a theoretical model for the recognition potential well between chromatin fibres sliding against each other. This well is different from the one predicted for bare DNA; the minima in energy do not correspond to literal juxtaposition, but are shifted by approximately half the nucleosome repeat length. The presence of this potential well suggests that nucleosome positioning may induce mutual sequence recognition between chromatin fibres and facilitate the formation of chromatin nanodomains. This has implications for nucleosome arrays enclosed between CTCF-cohesin boundaries, which may form stiffer stem-like structures instead of flexible entropically favourable loops. We also consider switches between chromatin states, e.g. through acetylation/deacetylation of histones, and discuss nucleosome-induced recognition as a precursory stage of genetic recombination.

A deformation energy model reveals sequence-dependent property of nucleosome positioning

We present a deformation energy model for predicting nucleosome positioning, in which a position-dependent structural parameter set derived from crystal structures of nucleosomes was used to calculate the DNA deformation energy. The model is successful in predicting nucleosome occupancy genome-wide in budding yeast, nucleosome free energy, and rotational positioning of nucleosomes. Our model also indicates that the genomic regions underlying the MNase-sensitive nucleosomes in budding yeast have high deformation energy and, consequently, low nucleosome-forming ability, while the MNase-sensitive non-histone particles are characterized by much lower DNA deformation energy and high nucleosome preference. In addition, we also revealed that remodelers, SNF2 and RSC8, are likely to act in chromatin remodeling by binding to broad nucleosome-depleted regions that are intrinsically favorable for nucleosome positioning. Our data support the important role of position-dependent physical properties of DNA in nucleosome positioning.

On the role of transcription in positioning nucleosomes

Nucleosome positioning is crucial for the genome’s function. Though the role of DNA sequence in positioning nucleosomes is well understood, a detailed mechanistic understanding on the impact of transcription remains lacking. Using numerical simulations, we investigated the dependence of nucleosome density profiles on transcription level across multiple species. We found that the low nucleosome affinity of yeast, but not mouse, promoters contributes to the formation of phased nucleosomes arrays for inactive genes. For the active genes, a heterogeneous distribution of +1 nucleosomes, caused by a tug-of-war between two types of remodeling enzymes, is essential for reproducing their density profiles. In particular, while positioning enzymes are known to remodel the +1 nucleosome and align it toward the transcription start site (TSS), spacer enzymes that use a pair of nucleosomes as their substrate can shift the nucleosome array away from the TSS. Competition between these enzymes results in two types of nucleosome density profiles with well- and ill-positioned +1 nucleosome. Finally, we showed that Pol II assisted histone exchange, if occurring at a fast speed, can abolish the impact of remodeling enzymes. By elucidating the role of individual factors, our study reconciles the seemingly conflicting results on the overall impact of transcription in positioning nucleosomes across species.

Nucleosome positioning plays a key role in the genome’s function by regulating the accessibility of protein binding sites as well as higher-order chromatin organization. Though significant progress has been made towards studying the role of DNA sequence in positioning the nucleosomes, our understanding on the impact of transcription lags behind. Our study uses kinetic simulations to explore the role of DNA sequence specificity, transcription factor binding, enzyme remodeling, and Pol II elongation in positioning nucleosomes. It suggests that the differences in nucleosome density profiles observed at various transcription levels in yeast and mouse embryonic stem cells can be understood from a tug-of-war between two types of remodeling enzymes.

Sensitive Automated Measurement of Histone-DNA Affinities in Nucleosomes

The DNA of eukaryotes is wrapped around histone octamers to form nucleosomes. Although it is well established that the DNA sequence significantly influences nucleosome formation, its precise contribution has remained controversial, partially owing to the lack of quantitative affinity data. Here, we present a method to measure DNA-histone binding free energies at medium throughput and with high sensitivity. Competitive nucleosome formation is achieved through automation, and a modified epifluorescence microscope is used to rapidly and accurately measure the fractions of bound/unbound DNA based on fluorescence anisotropy. The procedure allows us to obtain full titration curves with high reproducibility. We applied this technique to measure the histone-DNA affinities for 47 DNA sequences and analyzed how the affinities correlate with relevant DNA sequence features. We found that the GC content has a significant impact on nucleosome-forming preferences, but 10 bp dinucleotide periodicities and the presence of poly(dA:dT) stretches do not.

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Robotics permits full titration series to measure histone-DNA binding affinities

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Fluorescence anisotropy used as a fast, sensitive readout of bound/unbound DNA

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Free energies span three orders of magnitude, less for naturally occurring sequences

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GC content is a major determinant of measured binding free energies

Q-Nuc: a bioinformatics pipeline for the quantitative analysis of nucleosomal profiles

Nucleosomal profiling is an effective method to determine the positioning and occupancy of nucleosomes, which is essential to understand their roles in genomic processes. However, the positional randomness across the genome and its relationship with nucleosome occupancy remains poorly understood. Here we present a computational method that segments the profile into nucleosomal domains and quantifies their randomness and relative occupancy level. Applying this method to published data, we find on average ~ 3-fold differences in the degree of positional randomness between regions typically considered "well-ordered", as well as an unexpected predominance of only two types of domains of positional randomness in yeast cells. Further, we find that occupancy levels between domains actually differ maximally by ~ 2-3-fold in both cells, which has not been described before. We also developed a procedure by which one can estimate the sequencing depth that is required to identify nucleosomal positions even when regional positional randomness is high. Overall, we have developed a pipeline to quantitatively characterize domain-level features of nucleosome randomness and occupancy genome-wide, enabling the identification of otherwise unknown features in nucleosomal organization.

DNA Sequence Is a Major Determinant of Tetrasome Dynamics

Eukaryotic genomes are hierarchically organized into protein-DNA assemblies for compaction into the nucleus. Nucleosomes, with the (H3-H4)2 tetrasome as a likely intermediate, are highly dynamic in nature by way of several different mechanisms. We have recently shown that tetrasomes spontaneously change the direction of their DNA wrapping between left- and right-handed conformations, which may prevent torque buildup in chromatin during active transcription or replication. DNA sequence has been shown to strongly affect nucleosome positioning throughout chromatin. It is not known, however, whether DNA sequence also impacts the dynamic properties of tetrasomes. To address this question, we examined tetrasomes assembled on a high-affinity DNA sequence using freely orbiting magnetic tweezers. In this context, we also studied the effects of mono- and divalent salts on the flipping dynamics. We found that neither DNA sequence nor altered buffer conditions affect overall tetrasome structure. In contrast, tetrasomes bound to high-affinity DNA sequences showed significantly altered flipping kinetics, predominantly via a reduction in the lifetime of the canonical state of left-handed wrapping. Increased mono- and divalent salt concentrations counteracted this behavior. Thus, our study indicates that high-affinity DNA sequences impact not only the positioning of the nucleosome but that they also endow the subnucleosomal tetrasome with enhanced conformational plasticity. This may provide a means to prevent histone loss upon exposure to torsional stress, thereby contributing to the integrity of chromatin at high-affinity sites.

Theory of Active Chromatin Remodeling

Nucleosome positioning controls the accessible regions of chromatin and plays essential roles in DNA-templated processes. ATP driven remodeling enzymes are known to be crucial for its establishment in vivo, but their nonequilibrium nature has hindered the development of a unified theoretical framework for nucleosome positioning. Using a perturbation theory, we show that the effect of these enzymes can be well approximated by effective equilibrium models with rescaled temperatures and interactions. Numerical simulations support the accuracy of the theory in predicting both kinetic and steady-state quantities, including the effective temperature and the radial distribution function, in biologically relevant regimes. The energy landscape view emerging from our study provides an intuitive understanding for the impact of remodeling enzymes in either reinforcing or overwriting intrinsic signals for nucleosome positioning, and may help improve the accuracy of computational models for its prediction in silico.

Inference of the human polyadenylation code

Motivation

Processing of transcripts at the 3′-end involves cleavage at a polyadenylation site followed by the addition of a poly(A)-tail. By selecting which site is cleaved, the process of alternative polyadenylation enables genes to produce transcript isoforms with different 3′-ends. To facilitate the identification and treatment of disease-causing mutations that affect polyadenylation and to understand the sequence determinants underlying this regulatory process, a computational model that can accurately predict polyadenylation patterns from genomic features is desirable.

Results

Previous works have focused on identifying candidate polyadenylation sites and classifying tissue-specific sites. By training on how multiple sites in genes are competitively selected for polyadenylation from 3′-end sequencing data, we developed a deep learning model that can predict the tissue-specific strength of a polyadenylation site in the 3′ untranslated region of the human genome given only its genomic sequence. We demonstrate the model’s broad utility on multiple tasks, without any application-specific training. The model can be used to predict which polyadenylation site is more likely to be selected in genes with multiple sites. It can be used to scan the 3′ untranslated region to find candidate polyadenylation sites. It can be used to classify the pathogenicity of variants near annotated polyadenylation sites in ClinVar. It can also be used to anticipate the effect of antisense oligonucleotide experiments to redirect polyadenylation. We provide analysis on how different features affect the model’s predictive performance and a method to identify sensitive regions of the genome at the single-based resolution that can affect polyadenylation regulation.

Supplementary information

Supplementary data are available at Bioinformatics online.

LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks

Motivation

Nucleosome positioning plays significant roles in proper genome packing and its accessibility to execute transcription regulation. Despite a multitude of nucleosome positioning resources available on line including experimental datasets of genome-wide nucleosome occupancy profiles and computational tools to the analysis on these data, the complex language of eukaryotic Nucleosome positioning remains incompletely understood.

Results

Here, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) to understand nucleosome positioning. We combined Inception-like networks with a gating mechanism for the response of multiple patterns and long term association in DNA sequences. We developed the open-source package LeNup based on the CNN to predict nucleosome positioning in Homo sapiens, Caenorhabditis elegans, Drosophila melanogaster as well as Saccharomyces cerevisiae genomes. We trained LeNup on four benchmark datasets. LeNup achieved greater predictive accuracy than previously published methods.

Availability and implementation

LeNup is freely available as Python and Lua script source code under a BSD style license from https://github.com/biomedBit/LeNup.

Supplementary information

Supplementary data are available at Bioinformatics online.

Deep learning architectures for prediction of nucleosome positioning from sequences data

Background

Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several biological studies have shown that the nucleosome positioning influences the regulation of cell type-specific gene activities. Moreover, computational studies have shown evidence of sequence specificity concerning the DNA fragment wrapped into nucleosomes, clearly underlined by the organization of particular DNA substrings. As the main consequence, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using a sequence features representation.

Results

In this work, we propose a deep learning model for nucleosome identification. Our model stacks convolutional layers and Long Short-term Memories to automatically extract features from short- and long-range dependencies in a sequence. Using this model we are able to avoid the feature extraction and selection steps while improving the classification performances.

Conclusions

Results computed on eleven data sets of five different organisms, from Yeast to Human, show the superiority of the proposed method with respect to the state of the art recently presented in the literature.

Chromatin remodelers couple inchworm motion with twist-defect formation to slide nucleosomal DNA

ATP-dependent chromatin remodelers are molecular machines that control genome organization by repositioning, ejecting, or editing nucleosomes, activities that confer them essential regulatory roles on gene expression and DNA replication. Here, we investigate the molecular mechanism of active nucleosome sliding by means of molecular dynamics simulations of the Snf2 remodeler translocase in complex with a nucleosome. During its inchworm motion driven by ATP consumption, the translocase overwrites the original nucleosome energy landscape via steric and electrostatic interactions to induce sliding of nucleosomal DNA unidirectionally. The sliding is initiated at the remodeler binding location via the generation of a pair of twist defects, which then spontaneously propagate to complete sliding throughout the entire nucleosome. We also reveal how remodeler mutations and DNA sequence control active nucleosome repositioning, explaining several past experimental observations. These results offer a detailed mechanistic picture of remodeling important for the complete understanding of these key biological processes.

Nucleosomes are the protein-DNA complexes underlying Eukaryotic genome organization, and serve as regulators of gene expression by occluding DNA to other proteins. This regulation requires the precise positioning of nucleosomes along DNA. Chromatin remodelers are the molecular machines that consume ATP to slide nucleosome at their correct locations, but the mechanisms of remodeling are still unclear. Based on the static structural information of a remodeler bound on nucleosome, we performed molecular dynamics computer simulations revealing the details of how remodelers slide nucleosomal DNA: the inchworm-like motion of remodelers create small DNA deformations called twist defects, which then spontaneously propagate throughout the nucleosome to induce sliding. These simulations explain several past experimental findings and are important for our understanding of genome organization.

A unified computational framework for modeling genome-wide nucleosome landscape

Nucleosomes form the fundamental building blocks of eukaryotic chromatin, and previous attempts to understand the principles governing their genome-wide distribution have spurred much interest and debate in biology. In particular, the precise role of DNA sequence in shaping local chromatin structure has been controversial. This paper rigorously quantifies the contribution of hitherto-debated sequence features-including G+C content, 10.5 bp periodicity, and poly(dA:dT) tracts-to three distinct aspects of genome-wide nucleosome landscape: occupancy, translational positioning and rotational positioning. Our computational framework simultaneously learns nucleosome number and nucleosome-positioning energy from genome-wide nucleosome maps. In contrast to other previous studies, our model can predict both in vitro and in vivo nucleosome maps in Saccharomyces cerevisiae. We find that although G+C content is the primary determinant of MNase-derived nucleosome occupancy, MNase digestion biases may substantially influence this GC dependence. By contrast, poly(dA:dT) tracts are seen to deter nucleosome formation, regardless of the experimental method used. We further show that the 10.5 bp nucleotide periodicity facilitates rotational but not translational positioning. Applying our method to in vivo nucleosome maps demonstrates that, for a subset of genes, the regularly-spaced nucleosome arrays observed around transcription start sites can be partially recapitulated by DNA sequence alone. Finally, in vivo nucleosome occupancy derived from MNase-seq experiments around transcription termination sites can be mostly explained by the genomic sequence. Implications of these results and potential extensions of the proposed computational framework are discussed.

DNA physical properties outperform sequence compositional information in classifying nucleosome-enriched and -depleted regions

The nucleosome is the fundamental structural unit of eukaryotic chromatin and plays an essential role in the epigenetic regulation of cellular processes, such as DNA replication, recombination, and transcription. Hence, it is important to identify nucleosome positions in the genome. Our previous model based on DNA deformation energy, in which a set of DNA physical descriptors was used, performed well in predicting nucleosome dyad positions and occupancy. In this study, we established a machine-learning model for predicting nucleosome occupancy in order to further verify the physical descriptors. Results showed that (1) our model outperformed several other sequence compositional information-based models, indicating a stronger dependence of nucleosome positioning on DNA physical properties; (2) nucleosome-enriched and -depleted regions have distinct features in terms of DNA physical descriptors like sequence-dependent flexibility and equilibrium structure parameters; (3) gene transcription start sites and termination sites can be well characterized with the distribution patterns of the physical descriptors, indicating the regulatory role of DNA physical properties in gene transcription. In addition, we developed a web server for the model, which is freely accessible at http://lin-group.cn/server/iNuc-force/.

The implication of DNA bending energy for nucleosome positioning and sliding

Nucleosome not only directly affects cellular processes, such as DNA replication, recombination, and transcription, but also severs as a fundamentally important target of epigenetic modifications. Our previous study indicated that the bending property of DNA is important in nucleosome formation, particularly in predicting the dyad positions of nucleosomes on a DNA segment. Here, we investigated the role of bending energy in nucleosome positioning and sliding in depth to decipher sequence-directed mechanism. The results show that bending energy is a good physical index to predict the free energy in the process of nucleosome reconstitution in vitro. Our data also imply that there are at least 20% of the nucleosomes in budding yeast do not adopt canonical positioning, in which underlying sequences wrapped around histones are structurally symmetric. We also revealed distinct patterns of bending energy profile for distinctly organized chromatin structures, such as well-positioned nucleosomes, fuzzy nucleosomes, and linker regions and discussed nucleosome sliding in terms of bending energy. We proposed that the stability of a nucleosome is positively correlated with the strength of the bending anisotropy of DNA segment, and both accessibility and directionality of nucleosome sliding is likely to be modulated by diverse patterns of DNA bending energy profile.

Coupling of replisome movement with nucleosome dynamics can contribute to the parent-daughter information transfer

Positioning of nucleosomes along the genomic DNA is crucial for many cellular processes that include gene regulation and higher order packaging of chromatin. The question of how nucleosome-positioning information from a parent chromatin gets transferred to the daughter chromatin is highly intriguing. Accounting for experimentally known coupling between replisome movement and nucleosome dynamics, we propose a model that can obtain de novo nucleosome assembly similar to what is observed in recent experiments. Simulating nucleosome dynamics during replication, we argue that short pausing of the replication fork, associated with nucleosome disassembly, can be a event crucial for communicating nucleosome positioning information from parent to daughter. We show that the interplay of timescales between nucleosome disassembly (τ_p) at the replication fork and nucleosome sliding behind the fork (τ_s) can give rise to a rich ‘phase diagram’ having different inherited patterns of nucleosome organization. Our model predicts that only when τ_p ≥ τ_s the daughter chromatin can inherit nucleosome positioning of the parent.

Single-molecule compaction of megabase-long chromatin molecules by multivalent cations

To gain insight into the conformational properties and compaction of megabase-long chromatin molecules, we reconstituted chromatin from T4 phage DNA (165 kb) and recombinant human histone octamers (HO). The unimolecular compaction, induced by divalent Mg2+ or tetravalent spermine4+ cations, studied by single-molecule fluorescence microscopy (FM) and dynamic light scattering (DLS) techniques, resulted in the formation of 250-400 nm chromatin condensates. The compaction on this scale of DNA size is comparable to that of chromatin topologically associated domains (TAD) in vivo. Variation of HO loading revealed a number of unique features related to the efficiency of chromatin compaction by multivalent cations, the mechanism of compaction, and the character of partly compact chromatin structures. The observations may be relevant for how DNA accessibility in chromatin is maintained. Compaction of saturated chromatin, in turn, is accompanied by an intra-chain segregation at the level of single chromatin molecules, suggesting an intriguing scenario of selective activation/deactivation of DNA as a result of chromatin fiber heterogeneity due to the nucleosome positioning. We suggest that this chromatin, reconstituted on megabase-long DNA because of its large size, is a useful model of eukaryotic chromatin.

Toehold-enhanced LNA probes for selective pull down and single-molecule analysis of native chromatin

The organization of DNA into chromatin is thought to regulate gene expression in eukaryotes. To study its structure in vitro, there is a need for techniques that can isolate specific chromosomal loci of natively assembled chromatin. Current purification methods often involve chemical cross-linking to preserve the chromatin composition. However, such cross-linking may affect the native structure. It also impedes single molecule force spectroscopy experiments, which have been instrumental to probe chromatin folding. Here we present a method for the incorporation of affinity tags, such as biotin, into native nucleoprotein fragments based on their DNA sequence, and subsequent single molecule analysis by magnetic tweezers. DNA oligos with several Locked Nucleic Acid (LNA) nucleotides are shown to selectively bind to target DNA at room temperature, mediated by a toehold end in the target, allowing for selective purification of DNA fragments. The stability of the probe-target hybrid is sufficient to withstand over 65 pN of force. We employ these probes to obtain force-extension curves of native chromatin fragments of the 18S ribosomal DNA from the yeast Saccharomyces cerevisiae. These experiments yield valuable insights in the heterogeneity in structure and composition of natively assembled chromatin at the single-molecule level.

DNA mutation motifs in the genes associated with inherited diseases

Mutations in human genes can be responsible for inherited genetic disorders and cancer. Mutations can arise due to environmental factors or spontaneously. It has been shown that certain DNA sequences are more prone to mutate. These sites are termed hotspots and exhibit a higher mutation frequency than expected by chance. In contrast, DNA sequences with lower mutation frequencies than expected by chance are termed coldspots. Mutation hotspots are usually derived from a mutation spectrum, which reflects particular population where an effect of a common ancestor plays a role. To detect coldspots/hotspots unaffected by population bias, we analysed the presence of germline mutations obtained from HGMD database in the 5-nucleotide segments repeatedly occurring in genes associated with common inherited disorders, in particular, the PAH, LDLR, CFTR, F8, and F9 genes. Statistically significant sequences (mutational motifs) rarely associated with mutations (coldspots) and frequently associated with mutations (hotspots) exhibited characteristic sequence patterns, e.g. coldspots contained purine tract while hotspots showed alternating purine-pyrimidine bases, often with the presence of CpG dinucleotide. Using molecular dynamics simulations and free energy calculations, we analysed the global bending properties of two selected coldspots and two hotspots with a G/T mismatch. We observed that the coldspots were inherently more flexible than the hotspots. We assume that this property might be critical for effective mismatch repair as DNA with a mutation recognized by MutSα protein is noticeably bent.

Nucleosome dynamics: Sequence matters

About three quarter of all eukaryotic DNA is wrapped around protein cylinders, forming nucleosomes. Even though the histone proteins that make up the core of nucleosomes are highly conserved in evolution, nucleosomes can be very different from each other due to posttranslational modifications of the histones. Another crucial factor in making nucleosomes unique has so far been underappreciated: the sequence of their DNA. This review provides an overview of the experimental and theoretical progress that increasingly points to the importance of the nucleosomal base pair sequence. Specifically, we discuss the role of the underlying base pair sequence in nucleosome positioning, sliding, breathing, force-induced unwrapping, dissociation and partial assembly and also how the sequence can influence higher-order structures. A new view emerges: the physical properties of nucleosomes, especially their dynamical properties, are determined to a large extent by the mechanical properties of their DNA, which in turn depends on DNA sequence.

A deformation energy-based model for predicting nucleosome dyads and occupancy

Nucleosome plays an essential role in various cellular processes, such as DNA replication, recombination, and transcription. Hence, it is important to decode the mechanism of nucleosome positioning and identify nucleosome positions in the genome. In this paper, we present a model for predicting nucleosome positioning based on DNA deformation, in which both bending and shearing of the nucleosomal DNA are considered. The model successfully predicted the dyad positions of nucleosomes assembled in vitro and the in vitro map of nucleosomes in Saccharomyces cerevisiae. Applying the model to Caenorhabditis elegans and Drosophila melanogaster, we achieved satisfactory results. Our data also show that shearing energy of nucleosomal DNA outperforms bending energy in nucleosome occupancy prediction and the ability to predict nucleosome dyad positions is attributed to bending energy that is associated with rotational positioning of nucleosomes.

Theoretical estimates of exposure timescales of protein binding sites on DNA regulated by nucleosome kinetics

It is being increasingly realized that nucleosome organization on DNA crucially regulates DNA-protein interactions and the resulting gene expression. While the spatial character of the nucleosome positioning on DNA has been experimentally and theoretically studied extensively, the temporal character is poorly understood. Accounting for ATPase activity and DNA-sequence effects on nucleosome kinetics, we develop a theoretical method to estimate the time of continuous exposure of binding sites of non-histone proteins (e.g. transcription factors and TATA binding proteins) along any genome. Applying the method to Saccharomyces cerevisiae, we show that the exposure timescales are determined by cooperative dynamics of multiple nucleosomes, and their behavior is often different from expectations based on static nucleosome occupancy. Examining exposure times in the promoters of GAL1 and PHO5, we show that our theoretical predictions are consistent with known experiments. We apply our method genome-wide and discover huge gene-to-gene variability of mean exposure times of TATA boxes and patches adjacent to TSS (+1 nucleosome region); the resulting timescale distributions have non-exponential tails.

Categorical spectral analysis of periodicity in nucleosomal DNA

DNA helical twist imposes geometric constraints on the location of histone–DNA interaction sites along nucleosomal DNA. Certain 10.5-bp periodic nucleotides in phase with these geometric constraints have been suggested to facilitate nucleosome positioning. However, the extent of nucleotide periodicity in nucleosomal DNA and its significance in directing nucleosome positioning still remain unclear. We clarify these issues by applying categorical spectral analysis to high-resolution nucleosome maps in two yeast species. We find that only a small fraction of nucleosomal sequences contain significant 10.5-bp periodicity. We further develop a spectral decomposition method to show that the previously observed periodicity in aligned nucleosomal sequences mainly results from proper phasing among nucleosomal sequences, and not from a preponderant occurrence of periodicity within individual sequences. Importantly, we show that this phasing may arise from the histones’ proclivity for putting preferred nucleotides at some of the evenly spaced histone–DNA contact points with respect to the dyad axis. We demonstrate that 10.5-bp periodicity, when present, significantly facilitates rotational, but not translational, nucleosome positioning. Finally, although periodicity only moderately affects nucleosome occupancy genome wide, reduced periodicity is an evolutionarily conserved signature of nucleosome-depleted regions around transcription start/termination sites.

Prediction of fine-tuned promoter activity from DNA sequence

The quantitative prediction of transcriptional activity of genes using promoter sequence is fundamental to the engineering of biological systems for industrial purposes and understanding the natural variation in gene expression. To catalyze the development of new algorithms for this purpose, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized a community challenge seeking predictive models of promoter activity given normalized promoter activity data for 90 ribosomal protein promoters driving expression of a fluorescent reporter gene. By developing an unbiased modeling approach that performs an iterative search for predictive DNA sequence features using the frequencies of various k-mers, inferred DNA mechanical properties and spatial positions of promoter sequences, we achieved the best performer status in this challenge. The specific predictive features used in the model included the frequency of the nucleotide G, the length of polymeric tracts of T and TA, the frequencies of 6 distinct trinucleotides and 12 tetranucleotides, and the predicted protein deformability of the DNA sequence. Our method accurately predicted the activity of 20 natural variants of ribosomal protein promoters (Spearman correlation r = 0.73) as compared to 33 laboratory-mutated variants of the promoters (r = 0.57) in a test set that was hidden from participants. Notably, our model differed substantially from the rest in 2 main ways: i) it did not explicitly utilize transcription factor binding information implying that subtle DNA sequence features are highly associated with gene expression, and ii) it was entirely based on features extracted exclusively from the 100 bp region upstream from the translational start site demonstrating that this region encodes much of the overall promoter activity. The findings from this study have important implications for the engineering of predictable gene expression systems and the evolution of gene expression in naturally occurring biological systems.

Incorporating chromatin accessibility data into sequence-to-expression modeling

Prediction of gene expression levels from regulatory sequences is one of the major challenges of genomic biology today. A particularly promising approach to this problem is that taken by thermodynamics-based models that interpret an enhancer sequence in a given cellular context specified by transcription factor concentration levels and predict precise expression levels driven by that enhancer. Such models have so far not accounted for the effect of chromatin accessibility on interactions between transcription factor and DNA and consequently on gene-expression levels. Here, we extend a thermodynamics-based model of gene expression, called GEMSTAT (Gene Expression Modeling Based on Statistical Thermodynamics), to incorporate chromatin accessibility data and quantify its effect on accuracy of expression prediction. In the new model, called GEMSTAT-A, accessibility at a binding site is assumed to affect the transcription factor's binding strength at the site, whereas all other aspects are identical to the GEMSTAT model. We show that this modification results in significantly better fits in a data set of over 30 enhancers regulating spatial expression patterns in the blastoderm-stage Drosophila embryo. It is important to note that the improved fits result not from an overall elevated accessibility in active enhancers but from the variation of accessibility levels within an enhancer. With whole-genome DNA accessibility measurements becoming increasingly popular, our work demonstrates how such data may be useful for sequence-to-expression models. It also calls for future advances in modeling accessibility levels from sequence and the transregulatory context, so as to predict accurately the effect of cis and trans perturbations on gene expression.

The nucleosome landscape of Plasmodium falciparum reveals chromatin architecture and dynamics of regulatory sequences

In eukaryotes, the chromatin architecture has a pivotal role in regulating all DNA-associated processes and it is central to the control of gene expression. For Plasmodium falciparum, a causative agent of human malaria, the nucleosome positioning profile of regulatory regions deserves particular attention because of their extreme AT-content. With the aid of a highly controlled MNase-seq procedure we reveal how positioning of nucleosomes provides a structural and regulatory framework to the transcriptional unit by demarcating landmark sites (transcription/translation start and end sites). In addition, our analysis provides strong indications for the function of positioned nucleosomes in splice site recognition. Transcription start sites (TSSs) are bordered by a small nucleosome-depleted region, but lack the stereotypic downstream nucleosome arrays, highlighting a key difference in chromatin organization compared to model organisms. Furthermore, we observe transcription-coupled eviction of nucleosomes on strong TSSs during intraerythrocytic development and demonstrate that nucleosome positioning and dynamics can be predictive for the functionality of regulatory DNA elements. Collectively, the strong nucleosome positioning over splice sites and surrounding putative transcription factor binding sites highlights the regulatory capacity of the nucleosome landscape in this deadly human pathogen.

Nucleosome positioning: resources and tools online

Nucleosome positioning is an important process required for proper genome packing and its accessibility to execute the genetic program in a cell-specific, timely manner. In the recent years hundreds of papers have been devoted to the bioinformatics, physics and biology of nucleosome positioning. The purpose of this review is to cover a practical aspect of this field, namely, to provide a guide to the multitude of nucleosome positioning resources available online. These include almost 300 experimental datasets of genome-wide nucleosome occupancy profiles determined in different cell types and more than 40 computational tools for the analysis of experimental nucleosome positioning data and prediction of intrinsic nucleosome formation probabilities from the DNA sequence. A manually curated, up to date list of these resources will be maintained at http://generegulation.info.

Conditions for positioning of nucleosomes on DNA

Positioning of nucleosomes along a eukaryotic genome plays an important role in its organization and regulation. There are many different factors affecting the location of nucleosomes. Some can be viewed as preferential binding of a single nucleosome to different locations along the DNA and some as interactions between neighboring nucleosomes. In this study, we analyze positioning of nucleosomes and derive conditions for their good positioning. Using analytic and numerical approaches we find that, if the binding preferences are very weak, an interplay between the interactions and the binding preferences is essential for a good positioning of nucleosomes, especially on correlated energy landscapes. Analyzing the empirical energy landscape, we conclude that good positioning of nucleosomes in vivo is possible only if they strongly interact. In this case, our model, predicting long-length-scale fluctuations of nucleosomes' occupancy along the DNA, accounts well for the empirical observations.

Sequence structure of Lowary/Widom clones forming strong nucleosomes

Lowary and Widom selected from random sequences those which form exceptionally stable nucleosomes, including clone 601, the current champion of strong nucleosome (SN) sequences. This unique sequence database (LW sequences) carries sequence elements which confer stability on the nucleosomes formed on the sequences, and, thus, may serve as source of information on the structure of "ideal" or close to ideal nucleosome DNA sequence. An important clue is also provided by crystallographic study of Vasudevan and coauthors on clone 601 nucleosomes. It demonstrated that YR·YR dinucleotide stacks (primarily TA·TA) follow one another at distances 10 or 11 bases or multiples thereof, such that they all are located on the interface between DNA and histone octamer. Combining this important information with alignment of the YR-containing 10-mers and 11-mers from LW sequences, the bendability matrices of the stable nucleosome DNA are derived. The matrices suggest that the periodically repeated TA (YR), RR, and YY dinucleotides are the main sequence features of the SNs. This consensus coincides with the one for recently discovered SNs with visibly periodic DNA sequences. Thus, the experimentally observed stable LW nucleosomes and SNs derived computationally appear to represent the same entity - exceptionally stable SNs.

Ubiquitous human 'master' origins of replication are encoded in the DNA sequence via a local enrichment in nucleosome excluding energy barriers

As the elementary building block of eukaryotic chromatin, the nucleosome is at the heart of the compromise between the necessity of compacting DNA in the cell nucleus and the required accessibility to regulatory proteins. The recent availability of genome-wide experimental maps of nucleosome positions for many different organisms and cell types has provided an unprecedented opportunity to elucidate to what extent the DNA sequence conditions the primary structure of chromatin and in turn participates in the chromatin-mediated regulation of nuclear functions, such as gene expression and DNA replication. In this study, we use in vivo and in vitro genome-wide nucleosome occupancy data together with the set of nucleosome-free regions (NFRs) predicted by a physical model of nucleosome formation based on sequence-dependent bending properties of the DNA double-helix, to investigate the role of intrinsic nucleosome occupancy in the regulation of the replication spatio-temporal programme in human. We focus our analysis on the so-called replication U/N-domains that were shown to cover about half of the human genome in the germline (skew-N domains) as well as in embryonic stem cells, somatic and HeLa cells (mean replication timing U-domains). The 'master' origins of replication (MaOris) that border these megabase-sized U/N-domains were found to be specified by a few hundred kb wide regions that are hyper-sensitive to DNase I cleavage, hypomethylated, and enriched in epigenetic marks involved in transcription regulation, the hallmarks of localized open chromatin structures. Here we show that replication U/N-domain borders that are conserved in all considered cell lines have an environment highly enriched in nucleosome-excluding-energy barriers, suggesting that these ubiquitous MaOris have been selected during evolution. In contrast, MaOris that are cell-type-specific are mainly regulated epigenetically and are no longer favoured by a local abundance of intrinsic NFRs encoded in the DNA sequence. At the smaller few hundred bp scale of gene promoters, CpG-rich promoters of housekeeping genes found nearby ubiquitous MaOris as well as CpG-poor promoters of tissue-specific genes found nearby cell-type-specific MaOris, both correspond to in vivo NFRs that are not coded as nucleosome-excluding-energy barriers. Whereas the former promoters are likely to correspond to high occupancy transcription factor binding regions, the latter are an illustration that gene regulation in human is typically cell-type-specific.

Prediction of nucleosome rotational positioning in yeast and human genomes based on sequence-dependent DNA anisotropy

BACKGROUND

An organism's DNA sequence is one of the key factors guiding the positioning of nucleosomes within a cell's nucleus. Sequence-dependent bending anisotropy dictates how DNA is wrapped around a histone octamer. One of the best established sequence patterns consistent with this anisotropy is the periodic occurrence of AT-containing dinucleotides (WW) and GC-containing dinucleotides (SS) in the nucleosomal locations where DNA is bent in the minor and major grooves, respectively. Although this simple pattern has been observed in nucleosomes across eukaryotic genomes, its use for prediction of nucleosome positioning was not systematically tested.

RESULTS

We present a simple computational model, termed the W/S scheme, implementing this pattern, without using any training data. This model accurately predicts the rotational positioning of nucleosomes both in vitro and in vivo, in yeast and human genomes. About 65 - 75% of the experimentally observed nucleosome positions are predicted with the precision of one to two base pairs. The program is freely available at http://people.rit.edu/fxcsbi/WS_scheme/. We also introduce a simple and efficient way to compare the performance of different models predicting the rotational positioning of nucleosomes.

CONCLUSIONS

This paper presents the W/S scheme to achieve accurate prediction of rotational positioning of nucleosomes, solely based on the sequence-dependent anisotropic bending of nucleosomal DNA. This method successfully captures DNA features critical for the rotational positioning of nucleosomes, and can be further improved by incorporating additional terms related to the translational positioning of nucleosomes in a species-specific manner.

A Novel Wavelet-Based Approach for Predicting Nucleosome Positions Using DNA Structural Information

Nucleosomes are basic elements of chromatin structure. The positioning of nucleosomes along a genome is very important to dictate eukaryotic DNA compaction and access. Current computational methods have focused on the analysis of nucleosome occupancy and the positioning of well-positioned nucleosomes. However, fuzzy nucleosomes require more complex configurations and are more difficult to predict their positions. We analyzed the positioning of well-positioned and fuzzy nucleosomes from a novel structural perspective, and proposed WaveNuc, a computational approach for inferring their positions based on continuous wavelet transformation. The comparative analysis demonstrates that these two kinds of nucleosomes exhibit different propeller twist structural characteristics. Well-positioned nucleosomes tend to locate at sharp peaks of the propeller twist profile, whereas fuzzy nucleosomes correspond to broader peaks. The sharpness of these peaks shows that the propeller twist profile may contain nucleosome positioning information. Exploiting this knowledge, we applied WaveNuc to detect the two different kinds of peaks of the propeller twist profile along the genome. We compared the performance of our method with existing methods on real data sets. The results show that the proposed method can accurately resolve complex configurations of fuzzy nucleosomes, which leads to better performance of nucleosome positioning prediction on the whole genome.

Coregulation of transcription factor binding and nucleosome occupancy through DNA features of mammalian enhancers

Transcription factors (TFs) preferentially bind sites contained in regions of computationally predicted high nucleosomal occupancy, suggesting that nucleosomes are gatekeepers of TF binding sites. However, because of their complexity mammalian genomes contain millions of randomly occurring, unbound TF consensus binding sites. We hypothesized that the information controlling nucleosome assembly may coincide with the information that enables TFs to bind cis-regulatory elements while ignoring randomly occurring sites. Hence, nucleosomes would selectively mask genomic sites that can be contacted by TFs and thus be potentially functional. The hematopoietic pioneer TF Pu.1 maintained nucleosome depletion at macrophage-specific enhancers that displayed a broad range of nucleosome occupancy in other cell types and in reconstituted chromatin. We identified a minimal set of DNA sequence and shape features that accurately predicted both Pu.1 binding and nucleosome occupancy genome-wide. These data reveal a basic organizational principle of mammalian cis-regulatory elements whereby TF recruitment and nucleosome deposition are controlled by overlapping DNA sequence features.

Training-free atomistic prediction of nucleosome occupancy

Nucleosomes alter gene expression by preventing transcription factors from occupying binding sites along DNA. DNA methylation can affect nucleosome positioning and so alter gene expression epigenetically (without changing DNA sequence). Conventional methods to predict nucleosome occupancy are trained on observed DNA sequence patterns or known DNA oligonucleotide structures. They are statistical and lack the physics needed to predict subtle epigenetic changes due to DNA methylation. The training-free method presented here uses physical principles and state-of-the-art all-atom force fields to predict both nucleosome occupancy along genomic sequences as well as binding to known positioning sequences. Our method calculates the energy of both nucleosomal and linear DNA of the given sequence. Based on the DNA deformation energy, we accurately predict the in vitro occupancy profile observed experimentally for a 20,000-bp genomic region as well as the experimental locations of nucleosomes along 13 well-established positioning sequence elements. DNA with all C bases methylated at the 5 position shows less variation of nucleosome binding: Strong binding is weakened and weak binding is strengthened compared with normal DNA. Methylation also alters the preference of nucleosomes for some positioning sequences but not others.

Principles of nucleation of H3K27 methylation during embryonic development

During embryonic development, maintenance of cell identity and lineage commitment requires the Polycomb-group PRC2 complex, which catalyzes histone H3 lysine 27 trimethylation (H3K27me3). However, the developmental origins of this regulation are unknown. Here we show that H3K27me3 enrichment increases from blastula stages onward in embryos of the Western clawed frog (Xenopus tropicalis) within constrained domains strictly defined by sequence. Strikingly, although PRC2 also binds widely to active enhancers, H3K27me3 is only deposited at a small subset of these sites. Using a Support Vector Machine algorithm, these sequences can be predicted accurately on the basis of DNA sequence alone, with a sequence signature conserved between humans, frogs, and fish. These regions correspond to the subset of blastula-stage DNA methylation-free domains that are depleted for activating promoter motifs, and enriched for motifs of developmental factors. These results imply a genetic-default model in which a preexisting absence of DNA methylation is the major determinant of H3K27 methylation when not opposed by transcriptional activation. The sequence and motif signatures reveal the hierarchical and genetically inheritable features of epigenetic cross-talk that impose constraints on Polycomb regulation and guide H3K27 methylation during the exit of pluripotency.

NCS: incorporating positioning data to quantify nucleosome stability in yeast

MOTIVATION

With the spreading technique of mass sequencing, nucleosome positions and scores for their intensity have become available through several previous studies in yeast, but relatively few studies have specifically aimed to determine the score of nucleosome stability. Based on mass sequencing data, we proposed a nucleosome center score (NCS) for quantifying nucleosome stability by measuring shifts of the nucleosome center, and then mapping NCS scores to nucleosome positions in Brogaard et al.'s study.

RESULTS

We demonstrated the efficiency of NCS by known preference of A/T-based tracts for nucleosome formation, and showed that central nucleosomal DNA is more sensitive to A/T-based tracts than outer regions, which corresponds to the central histone tetramer-dominated region. We also found significant flanking preference around nucleosomal DNA for A/T-based dinucleotides, suggesting that neighboring sequences could affect nucleosome stability. Finally, the difference between results of NCS and Brogaard et al.'s scores was addressed and discussed.

CONTACTS

jchiang@mail.ncku.edu.tw

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Nucleosome positioning and kinetics near transcription-start-site barriers are controlled by interplay between active remodeling and DNA sequence

We investigate how DNA sequence, ATP-dependent chromatin remodeling and nucleosome-depleted ‘barriers’ co-operate to determine the kinetics of nucleosome organization, in a stochastic model of nucleosome positioning and dynamics. We find that ‘statistical’ positioning of nucleosomes against ‘barriers’, hypothesized to control chromatin structure near transcription start sites, requires active remodeling and therefore cannot be described using equilibrium statistical mechanics. We show that, unlike steady-state occupancy, DNA site exposure kinetics near a barrier is dominated by DNA sequence rather than by proximity to the barrier itself. The timescale for formation of positioning patterns near barriers is proportional to the timescale for active nucleosome eviction. We also show that there are strong gene-to-gene variations in nucleosome positioning near barriers, which are eliminated by averaging over many genes. Our results suggest that measurement of nucleosome kinetics can reveal information about sequence-dependent regulation that is not apparent in steady-state nucleosome occupancy.

A comparative evaluation on prediction methods of nucleosome positioning

Nucleosome positioning plays an essential role in cellular processes by modulating accessibility of DNA to proteins. Many computational models have been developed to predict genome-wide nucleosome positions from DNA sequences. Comparative analysis of predicted and experimental nucleosome positioning maps facilitates understanding the regulatory mechanisms of transcription and DNA replication. Therefore, a comprehensive evaluation of existing computational methods is important and useful for biologists to choose appropriate ones in their research. In this article, we carried out a performance comparison among eight widely used computational methods on four species including yeast, fruitfly, mouse and human. In particular, we compared these methods on different regions of each species such as gene sequences, promoters and 5'UTR exons. The experimental results show that the performances of the two latest versions of the thermodynamic model are relatively steadier than the other four methods. Moreover, these methods are workable on four species, but their performances decrease gradually from yeast to human, indicating that the fundamental mechanism of nucleosome positioning is conserved through the evolution process, but more and more factors participate in the determination of nucleosome positions, which leads to sophisticated regulation mechanisms.