Systematic assessment of ISWI subunits shows that NURF creates local accessibility for CTCF.

Catalytic activity of the imitation switch (ISWI) family of remodelers is critical for nucleosomal organization and DNA binding of certain transcription factors, including the insulator protein CTCF. Here we define the contribution of individual subcomplexes by deriving a panel of isogenic mouse stem cell lines, each lacking one of six ISWI accessory subunits. Individual deletions of subunits of either CERF, RSF, ACF, WICH or NoRC subcomplexes only moderately affect the chromatin landscape, while removal of the NURF-specific subunit BPTF leads to a strong reduction in chromatin accessibility and SNF2H ATPase localization around CTCF sites. This affects adjacent nucleosome occupancy and CTCF binding. At a group of sites with reduced chromatin accessibility, CTCF binding persists but cohesin occupancy is reduced, resulting in decreased insulation. These results suggest that CTCF binding can be separated from its function as an insulator in nuclear organization and identify a specific role for NURF in mediating SNF2H localization and chromatin opening at bound CTCF sites.

The kinetic landscape of nucleosome assembly: A coarse-grained molecular dynamics study.

The organization of nucleosomes along the Eukaryotic genome is maintained over time despite disruptive events such as replication. During this complex process, histones and DNA can form a variety of non-canonical nucleosome conformations, but their precise molecular details and roles during nucleosome assembly remain unclear. In this study, employing coarse-grained molecular dynamics simulations and Markov state modeling, we characterized the complete kinetics of nucleosome assembly. On the nucleosome-positioning 601 DNA sequence, we observe a rich transition network among various canonical and non-canonical tetrasome, hexasome, and nucleosome conformations. A low salt environment makes nucleosomes stable, but the kinetic landscape becomes more rugged, so that the system is more likely to be trapped in off-pathway partially assembled intermediates. Finally, we find that the co-operativity between DNA bending and histone association enables positioning sequence motifs to direct the assembly process, with potential implications for the dynamic organization of nucleosomes on real genomic sequences.

UltraPrep is a scalable, cost-effective, bead-based method for purifying cell-free DNA.

UltraPrep is an open-source, two-step method for purification of cell-free DNA that entails extraction of total DNA followed by size-selective enrichment of the smaller fragments that are characteristic of DNA originating from fragmentation between nucleosome. The advantages of the two related protocols that are described are that they can easily accommodate a wide range of sample input volumes, they rely on simple, magnetic bead-based technology, the yields of cfDNA are directly comparable to the most popular methods for cfDNA purification, and they dramatically reduce the cost of cfDNA isolation relative to currently available commercial methods. We provide a framework for physical and molecular quality analysis of purified cfDNA and demonstrate that the cfDNA generated by UltraPrep meets or exceeds the quality metrics of the most commonly used procedure. In addition, our method removes high molecular weight genomic DNA (hmwgDNA) that can interfere with downstream assay results, thereby addressing one of the primary concerns for preanalytical collection of blood samples.

Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data.

Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. In this study we use characteristics of the NOMe (nucleosome occupancy and methylation)-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using hidden Markov models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations.

DNMHMM: An approach to identify the differential nucleosome regions in multiple cell types based on a Hidden Markov Model.

Nucleosome occupancy changes across cell types and environmental conditions and such changes often have profound influence in transcription. It's of importance to identify the differential nucleosome regions (DNRs) where the nucleosome occupancy level differs across cell types. Here we developed DNMHMM, a Hidden Markov Model (HMM) based algorithm, to detect the DNRs with nucleosomal DNA sequenced dataset. The performance evaluation indicates that DNMHMM is advisable for multi-cell type comparison. Upon testing this model in yeast mutants, where the modifiable histone residues were mutated into alanine, we found that DNA sequences of the dynamic nucleosomes lack 10-11 bp periodicities and harbor binding motifs of the nucleosome remodelling complex. Moreover, the highly expressed genes have more dynamic nucleosomes at promoters. We further compared nucleosome occupancy between resting and activated human CD4+ T cells with this model. It was revealed that during the activation of CD4+ T cells, dynamic nucleosomes are enriched at regulatory sites, hence, up to some extent can affect the gene expression level. Taken together, DNMHMM offers the possibility to access precise nucleosome dynamics among multiple cell types and also can describe the closer association between nucleosome and transcription.

Nucleosome Turnover Regulates Histone Methylation Patterns over the Genome.

Recent studies have indicated that nucleosome turnover is rapid, occurring several times per cell cycle. To access the effect of nucleosome turnover on the epigenetic landscape, we investigated H3K79 methylation, which is produced by a single methyltransferase (Dot1l) with no known demethylase. Using chemical-induced proximity (CIP), we find that the valency of H3K79 methylation (mono-, di-, and tri-) is determined by nucleosome turnover rates. Furthermore, propagation of this mark is predicted by nucleosome turnover simulations over the genome and accounts for the asymmetric distribution of H3K79me toward the transcriptional unit. More broadly, a meta-analysis of other conserved histone modifications demonstrates that nucleosome turnover models predict both valency and chromosomal propagation of methylation marks. Based on data from worms, flies, and mice, we propose that the turnover of modified nucleosomes is a general means of propagation of epigenetic marks and a determinant of methylation valence.

Bottom-up modeling of chromatin segregation due to epigenetic modifications.

We use a chromosome-scale simulation to show that the preferential binding of heterochromatin protein 1 (HP1) to regions high in histone methylation (specifically H3K9me3) results in phase segregation and reproduces features of the observed Hi-C contact map. Specifically, we perform Monte Carlo simulations with one computational bead per nucleosome and an H3K9me3 pattern based on published ChIP-seq signals. We implement a binding model in which HP1 preferentially binds to trimethylated histone tails and then oligomerizes to bridge together nucleosomes. We observe a phase reminiscent of heterochromatin-dense and high in H3K9me3-and another reminiscent of euchromatin-less dense and lacking H3K9me3. This segregation results in a plaid contact probability map that matches the general shape and position of published Hi-C data. Analysis suggests that a roughly 20-kb segment of H3K9me3 enrichment is required to drive segregation into the heterochromatic phase.

Multi-scale chromatin state annotation using a hierarchical hidden Markov model.

Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.

Multiplexing Genetic and Nucleosome Positioning Codes: A Computational Approach.

Eukaryotic DNA is strongly bent inside fundamental packaging units: the nucleosomes. It is known that their positions are strongly influenced by the mechanical properties of the underlying DNA sequence. Here we discuss the possibility that these mechanical properties and the concomitant nucleosome positions are not just a side product of the given DNA sequence, e.g. that of the genes, but that a mechanical evolution of DNA molecules might have taken place. We first demonstrate the possibility of multiplexing classical and mechanical genetic information using a computational nucleosome model. In a second step we give evidence for genome-wide multiplexing in Saccharomyces cerevisiae and Schizosacharomyces pombe. This suggests that the exact positions of nucleosomes play crucial roles in chromatin function.

Survey of cryptic unstable transcripts in yeast.

BACKGROUND: Cryptic unstable transcripts (CUTs) are a largely unexplored class of nuclear exosome degraded, non-coding RNAs in budding yeast. It is highly debated whether CUT transcription has a functional role in the cell or whether CUTs represent noise in the yeast transcriptome. We sought to ascertain the extent of conserved CUT expression across a variety of Saccharomyces yeast strains to further understand and characterize the nature of CUT expression. RESULTS: We sequenced the WT and rrp6Δ transcriptomes of three S.cerevisiae strains: S288c, Σ1278b, JAY291 and the S.paradoxus strain N17 and utilized a hidden Markov model to annotate CUTs in these four strains. Utilizing a four-way genomic alignment we identified a large population of CUTs with conserved syntenic expression across all four strains. By identifying configurations of gene-CUT pairs, where CUT expression originates from the gene 5' or 3' nucleosome free region, we observed distinct gene expression trends specific to these configurations which were most prevalent in the presence of conserved CUT expression. Divergent pairs correlate with higher expression of genes, and convergent pairs correlate with reduced gene expression. CONCLUSIONS: Our RNA-seq based method has greatly expanded upon previous CUT annotations in S.cerevisiae underscoring the extensive and pervasive nature of unstable transcription. Furthermore we provide the first assessment of conserved CUT expression in yeast and globally demonstrate possible modes of CUT-based regulation of gene expression.

Using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling.

Genome-wide mapping of nucleosomes has revealed a great deal about the relationships between chromatin structure and control of gene expression. Recent next generation CHIP-chip and CHIP-Seq technologies have accelerated our understanding of basic principles of chromatin organization. These technologies have taught us that nucleosomes play a crucial role in gene regulation by allowing physical access to transcription factors. Recent methods and experimental advancements allow the determination of nucleosome positions for a given genome area. However, most of these methods estimate the number of nucleosomes either by an EM algorithm using a BIC criterion or an effective heuristic strategy. Here, we introduce a Bayesian method for identifying nucleosome positions. The proposed model is based on a Multinomial-Dirichlet classification and a hierarchical mixture distributions. The number and the positions of nucleosomes are estimated using a reversible jump Markov chain Monte Carlo simulation technique. We compare the performance of our method on simulated data and MNase-Seq data from Saccharomyces cerevisiae against PING and NOrMAL methods.

Solution-state conformation and stoichiometry of yeast Sir3 heterochromatin fibres.

Heterochromatin is a repressive chromatin compartment essential for maintaining genomic integrity. A hallmark of heterochromatin is the presence of specialized nonhistone proteins that alter chromatin structure to inhibit transcription and recombination. It is generally assumed that heterochromatin is highly condensed. However, surprisingly little is known about the structure of heterochromatin or its dynamics in solution. In budding yeast, formation of heterochromatin at telomeres and the homothallic silent mating type loci require the Sir3 protein. Here, we use a combination of sedimentation velocity, atomic force microscopy and nucleosomal array capture to characterize the stoichiometry and conformation of Sir3 nucleosomal arrays. The results indicate that Sir3 interacts with nucleosomal arrays with a stoichiometry of two Sir3 monomers per nucleosome. We also find that Sir3 fibres are less compact than canonical magnesium-induced 30 nm fibres. We suggest that heterochromatin proteins promote silencing by 'coating' nucleosomal arrays, stabilizing interactions between nucleosomal histones and DNA.

Flexible and dynamic nucleosome fiber in living mammalian cells.

Genomic DNA is organized three dimensionally within cells as chromatin and is searched and read by various proteins by an unknown mechanism; this mediates diverse cell functions. Recently, several pieces of evidence, including our cryomicroscopy and synchrotron X-ray scattering analyses, have demonstrated that chromatin consists of irregularly folded nucleosome fibers without a 30-nm chromatin fiber (i.e., a polymer melt-like structure). This melt-like structure implies a less physically constrained and locally more dynamic state, which may be crucial for protein factors to scan genomic DNA. Using a combined approach of fluorescence correlation spectroscopy, Monte Carlo computer simulations, and single nucleosome imaging, we demonstrated the flexible and dynamic nature of the nucleosome fiber in living mammalian cells. We observed local nucleosome fluctuation (~50 nm movement/30 ms) caused by Brownian motion. Our in vivo/in silico results suggest that local nucleosome dynamics facilitate chromatin accessibility and play a critical role in the scanning of genome information.

Quantitative models of the mechanisms that control genome-wide patterns of animal transcription factor binding.

Animal transcription factors drive complex spatial and temporal patterns of gene expression during development by binding to a wide array of genomic regions. While the in vivo DNA binding landscape and in vitro DNA binding affinities of many such proteins have been characterized, our understanding of the forces that determine where, when, and the extent to which these transcription factors bind DNA in cells remains primitive. In this chapter, we describe computational thermodynamic models that predict the genome-wide DNA binding landscape of transcription factors in vivo and evaluate the contribution of biophysical determinants, such as protein-protein interactions and chromatin accessibility, on DNA occupancy. We show that predictions based only on DNA sequence and in vitro DNA affinity data achieve a mild correlation (r=0.4) with experimental measurements of in vivo DNA binding. However, by incorporating direct measurements of DNA accessibility in chromatin, it is possible to obtain much higher accuracy (r=0.6-0.9) for various transcription factors across known target genes. Thus, a combination of experimental DNA accessibility data and computational modeling of transcription factor DNA binding may be sufficient to predict the binding landscape of any animal transcription factor with reasonable accuracy.

Assessment of circulating biomarkers for potential pharmacodynamic utility in patients with lymphoma.

PURPOSE: Treatment efficacy and toxicity are difficult to predict in lymphoma patients. In this study, the utility of circulating biomarkers in predicting and/or monitoring treatment efficacy/toxicity were investigated. PATIENTS AND METHODS: Circulating biomarkers of cell death (nucleosomal DNA (nDNA) and cytokeratin 18 (CK18)), and circulating FLT3 ligand, a potential biomarker of myelosuppression, were assessed before and serially after standard chemotherapy in 49 patients with Hodgkin and non-Hodgkin lymphoma. Cytokeratin 18 is not expressed in lymphoma cells so is a potential biomarker of epithelial toxicity in this setting. Tumour response was assessed before and after completion of chemotherapy by 2D and 3D computed tomography radiological response. RESULTS: Baseline nDNA level was significantly higher in all lymphoma subtypes compared with 61 healthy controls and was prognostic for progression-free survival in diffuse large B-cell lymphoma (DLBCL). Decreases in nDNA levels were observed in the first week after chemotherapy; in FL, early falls in nDNA predicted for long remission following therapy. In DLBCL, elevations in nDNA occurred in cases with progressive disease. Circulating CK18 increased within 48 h of chemotherapy and was significantly higher in patients experiencing epithelial toxicity graded >3 by Common Terminology for Classification of Adverse Events criteria. FLT3 ligand was elevated within 3-8 days of chemotherapy initiation and predicted those patients who subsequently developed neutropenic sepsis. CONCLUSION: These data suggest circulating biomarkers contribute useful information regarding tumour response and toxicity in patients receiving standard chemotherapy and have potential utility in the development of individualised treatment approaches in lymphoma. These biomarkers are now being tested within multicentre phase III trials to progress their qualification.

A continuous-index Bayesian hidden Markov model for prediction of nucleosome positioning in genomic DNA.

Nucleosomes are units of chromatin structure, consisting of DNA sequence wrapped around proteins called "histones." Nucleosomes occur at variable intervals throughout genomic DNA and prevent transcription factor (TF) binding by blocking TF access to the DNA. A map of nucleosomal locations would enable researchers to detect TF binding sites with greater efficiency. Our objective is to construct an accurate genomic map of nucleosome-free regions (NFRs) based on data from high-throughput genomic tiling arrays in yeast. These high-volume data typically have a complex structure in the form of dependence on neighboring probes as well as underlying DNA sequence, variable-sized gaps, and missing data. We propose a novel continuous-index model appropriate for non-equispaced tiling array data that simultaneously incorporates DNA sequence features relevant to nucleosome formation. Simulation studies and an application to a yeast nucleosomal assay demonstrate the advantages of using the new modeling framework, as well as its robustness to distributional misspecifications. Our results reinforce the previous biological hypothesis that higher-order nucleotide combinations are important in distinguishing nucleosomal regions from NFRs.

Genomic studies and computational predictions of nucleosome positions and formation energies.

Chromatin is a complex of DNA, RNA, and proteins whose primary function is to package genomic DNA into the tight confines of a cell nucleus. A fundamental repeating unit of chromatin is the nucleosome, an octamer of histone proteins around which 147 base pairs of DNA are wound in almost two turns of a left-handed superhelix. Chromatin is a dynamic structure that exerts profound influence on regulation of gene expression and other cellular functions. These chromatin-directed processes are facilitated by optimizing nucleosome positions throughout the genome and by remodeling nucleosomes in response to various external and internal signals such as environmental perturbations. Here we discuss the large-scale maps of nucleosome positions made available through recent advances in parallel high-throughput sequencing and microarray technologies. We show that these maps reveal common features of nucleosome organization in eukaryotic genomes. We also survey the computational models designed to predict nucleosome formation scores or energies and demonstrate how these predictions can be used to position multiple nucleosomes on the genome without steric overlap.

Chromatin-dependent transcription factor accessibility rather than nucleosome remodeling predominates during global transcriptional restructuring in Saccharomyces cerevisiae.

Several well-studied promoters in yeast lose nucleosomes upon transcriptional activation and gain them upon repression, an observation that has prompted the model that transcriptional activation and repression requires nucleosome remodeling of regulated promoters. We have examined global nucleosome positioning before and after glucose-induced transcriptional reprogramming, a condition under which more than half of all yeast genes significantly change expression. The majority of induced and repressed genes exhibit no change in promoter nucleosome arrangement, although promoters that do undergo nucleosome remodeling tend to contain a TATA box. Rather, we found multiple examples where the pre-existing accessibility of putative transcription factor binding sites before glucose addition determined whether the corresponding gene would change expression in response to glucose addition. These results suggest that selection of appropriate transcription factor binding sites may be dictated to a large extent by nucleosome prepositioning but that regulation of expression through these sites is dictated not by nucleosome repositioning but by changes in transcription factor activity.

Preferentially quantized linker DNA lengths in Saccharomyces cerevisiae.

The exact lengths of linker DNAs connecting adjacent nucleosomes specify the intrinsic three-dimensional structures of eukaryotic chromatin fibers. Some studies suggest that linker DNA lengths preferentially occur at certain quantized values, differing one from another by integral multiples of the DNA helical repeat, approximately 10 bp; however, studies in the literature are inconsistent. Here, we investigate linker DNA length distributions in the yeast Saccharomyces cerevisiae genome, using two novel methods: a Fourier analysis of genomic dinucleotide periodicities adjacent to experimentally mapped nucleosomes and a duration hidden Markov model applied to experimentally defined dinucleosomes. Both methods reveal that linker DNA lengths in yeast are preferentially periodic at the DNA helical repeat ( approximately 10 bp), obeying the forms 10n+5 bp (integer n). This 10 bp periodicity implies an ordered superhelical intrinsic structure for the average chromatin fiber in yeast.

Nucleosome positioning from tiling microarray data.

MOTIVATION: The packaging of DNA around nucleosomes in eukaryotic cells plays a crucial role in regulation of gene expression, and other DNA-related processes. To better understand the regulatory role of nucleosomes, it is important to pinpoint their position in a high (5-10 bp) resolution. Toward this end, several recent works used dense tiling arrays to map nucleosomes in a high-throughput manner. These data were then parsed and hand-curated, and the positions of nucleosomes were assessed. RESULTS: In this manuscript, we present a fully automated algorithm to analyze such data and predict the exact location of nucleosomes. We introduce a method, based on a probabilistic graphical model, to increase the resolution of our predictions even beyond that of the microarray used. We show how to build such a model and how to compile it into a simple Hidden Markov Model, allowing for a fast and accurate inference of nucleosome positions. We applied our model to nucleosomal data from mid-log yeast cells reported by Yuan et al. and compared our predictions to those of the original paper; to a more recent method that uses five times denser tiling arrays as explained by Lee et al.; and to a curated set of literature-based nucleosome positions. Our results suggest that by applying our algorithm to the same data used by Yuan et al. our fully automated model traced 13% more nucleosomes, and increased the overall accuracy by about 20%. We believe that such an improvement opens the way for a better understanding of the regulatory mechanisms controlling gene expression, and how they are encoded in the DNA.