Mapping nucleosome positions using DNase-seq

Inferring differential protein binding from time-series chromatin accessibility data

Motivation

Due to internal and external factors, the epigenomic landscape is constantly changing in ways that are linked to changes in gene expression. Chromatin accessibility data, such as MNase-seq, provide valuable insights into this landscape and have been used to compute chromatin occupancy profiles. Multiple datasets generated over time or under different conditions can thus be used to study dynamic changes in chromatin occupancy across the genome.

Results

Our existing model, RoboCOP, computes a genome-wide chromatin occupancy profile for nucleosomes and hundreds of transcription factors. Here, we present a new method called DynaCOP that takes multiple chromatin occupancy profiles and uses them to generate a series of nucleosome-guided difference profiles. These profiles identify differentially binding transcription factors and reveal changes in nucleosome occupancy and positioning. We apply DynaCOP to chromatin occupancy profiles derived from deeply sequenced time-series MNase-seq data to study differential chromatin occupancy in the yeast genome under cadmium stress. We find strong correlations between the observed chromatin changes and changes in transcription.

Availability and implementation

https://github.com/HarteminkLab/RoboCOP.

Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation

Epigenetic mechanisms contribute to gene regulation by altering chromatin accessibility through changes in transcription factor (TF) and nucleosome occupancy throughout the genome. Despite numerous studies focusing on changes in gene expression, the intricate chromatin-mediated regulatory code remains largely unexplored on a comprehensive scale. We address this by employing a factor-agnostic, reverse-genetics approach that uses MNase-seq to capture genome-wide TF and nucleosome occupancies in response to the individual deletion of 201 transcriptional regulators in Saccharomyces cerevisiae, thereby assaying nearly one million mutant-gene interactions. We develop a principled approach to identify and quantify chromatin changes genome-wide, observing differences in TF and nucleosome occupancy that recapitulate well-established pathways identified by gene expression data. We also discover distinct chromatin signatures associated with the up- and downregulation of genes, and use these signatures to reveal regulatory mechanisms previously unexplored in expression-based studies. Finally, we demonstrate that chromatin features are predictive of transcriptional activity and leverage these features to reconstruct chromatin-based transcriptional regulatory networks. Overall, these results illustrate the power of an approach combining genetic perturbation with high-resolution epigenomic profiling; the latter enables a close examination of the interplay between TFs and nucleosomes genome-wide, providing a deeper, more mechanistic understanding of the complex relationship between chromatin organization and transcription.

ATAC-seq exposes differences in chromatin accessibility leading to distinct leaf shapes in mulberry

Mulberry leaf shape is an important agronomic trait indicating yield, growth, development, and habitat variation. China was the earliest country in the world to grow mulberry for sericulture, and it is also one of the great contributions of the Chinese nation to human civilization. ATAC-seq (Assay for Transposase Accessible Chromatin using sequencing) is a recently developed technique for genome-wide analysis of chromatin accessibility. The samples used for ATAC sequencing in this study were divided into two groups of whole leaves (CK-1 and CK-2) and lobed leaves (HL-1 and HL-2), with two replicates in each group. The related motif analysis, differential expression motif screening, and functional annotation of mulberry leaf shape differences were performed by raw letter analysis to finally obtain the transcription factors (TFs) that lead to the production of heteromorphic leaves. These transcription factors are common in plants, especially the TCP family, shown to be associated with leaf development and growth in other woody plants and are a potential transcription factor responsible for leaf shape differences in mulberry. Dissecting the regulatory mechanisms of leaf shape of different forms of mulberry leaves by ATAC-seq is an important way to protect mulberry germplasm resources and improve mulberry yield. It is conducive to cultivating mulberry varieties with high resistance to adversity, promoting the sustainable development of sericulture, and protecting and improving the ecological environment.

DeepNup: Prediction of Nucleosome Positioning from DNA Sequences Using Deep Neural Network

Nucleosome positioning is involved in diverse cellular biological processes by regulating the accessibility of DNA sequences to DNA-binding proteins and plays a vital role. Previous studies have manifested that the intrinsic preference of nucleosomes for DNA sequences may play a dominant role in nucleosome positioning. As a consequence, it is nontrivial to develop computational methods only based on DNA sequence information to accurately identify nucleosome positioning, and thus intend to verify the contribution of DNA sequences responsible for nucleosome positioning. In this work, we propose a new deep learning-based method, named DeepNup, which enables us to improve the prediction of nucleosome positioning only from DNA sequences. Specifically, we first use a hybrid feature encoding scheme that combines One-hot encoding and Trinucleotide composition encoding to encode raw DNA sequences; afterwards, we employ multiscale convolutional neural network modules that consist of two parallel convolution kernels with different sizes and gated recurrent units to effectively learn the local and global correlation feature representations; lastly, we use a fully connected layer and a sigmoid unit serving as a classifier to integrate these learned high-order feature representations and generate the final prediction outcomes. By comparing the experimental evaluation metrics on two benchmark nucleosome positioning datasets, DeepNup achieves a better performance for nucleosome positioning prediction than that of several state-of-the-art methods. These results demonstrate that DeepNup is a powerful deep learning-based tool that enables one to accurately identify potential nucleosome sequences.

Nucleosome-Omics: A Perspective on the Epigenetic Code and 3D Genome Landscape

Genetic information is loaded on chromatin, which involves DNA sequence arrangement and the epigenetic landscape. The epigenetic information including DNA methylation, nucleosome positioning, histone modification, 3D chromatin conformation, and so on, has a crucial impact on gene transcriptional regulation. Out of them, nucleosomes, as basal chromatin structural units, play an important central role in epigenetic code. With the discovery of nucleosomes, various nucleosome-level technologies have been developed and applied, pushing epigenetics to a new climax. As the underlying methodology, next-generation sequencing technology has emerged and allowed scientists to understand the epigenetic landscape at a genome-wide level. Combining with NGS, nucleosome-omics (or nucleosomics) provides a fresh perspective on the epigenetic code and 3D genome landscape. Here, we summarized and discussed research progress in technology development and application of nucleosome-omics. We foresee the future directions of epigenetic development at the nucleosome level.

Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data

Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.

Galaxy Dnpatterntools for Computational Analysis of Nucleosome Positioning Sequence Patterns

Nucleosomes are basic units of DNA packing in eukaryotes. Their structure is well conserved from yeast to human and consists of the histone octamer core and 147 bp DNA wrapped around it. Nucleosomes are bound to a majority of the eukaryotic genomic DNA, including its regulatory regions. Hence, they also play a major role in gene regulation. For the latter, their precise positioning on DNA is essential. In the present paper, we describe Galaxy dnpatterntools—software package for nucleosome DNA sequence analysis and mapping. This software will be useful for computational biologists practitioners to conduct more profound studies of gene regulatory mechanisms.

DeNOPA: decoding nucleosome positions sensitively with sparse ATAC-seq data

As the basal bricks, the dynamics and arrangement of nucleosomes orchestrate the higher architecture of chromatin in a fundamental way, thereby affecting almost all nuclear biology processes. Thanks to its rather simple protocol, assay for transposase-accessible chromatin using sequencing (ATAC)-seq has been rapidly adopted as a major tool for chromatin-accessible profiling at both bulk and single-cell levels; however, to picture the arrangement of nucleosomes per se remains a challenge with ATAC-seq. In the present work, we introduce a novel ATAC-seq analysis toolkit, named decoding nucleosome organization profile based on ATAC-seq data (deNOPA), to predict nucleosome positions. Assessments showed that deNOPA outperformed state-of-the-art tools with ultra-sparse ATAC-seq data, e.g. no more than 0.5 fragment per base pair. The remarkable performance of deNOPA was fueled by the short fragment reads, which compose nearly half of sequenced reads in the ATAC-seq libraries and are commonly discarded by state-of-the-art nucleosome positioning tools. However, we found that the short fragment reads enrich information on nucleosome positions and that the linker regions were predicted by reads from both short and long fragments using Gaussian smoothing. Last, using deNOPA, we showed that the dynamics of nucleosome organization may not directly couple with chromatin accessibility in the cis-regulatory regions when human cells respond to heat shock stimulation. Our deNOPA provides a powerful tool with which to analyze the dynamics of chromatin at nucleosome position level with ultra-sparse ATAC-seq data.

High-resolution, genome-wide mapping of positive supercoiling in chromosomes

Supercoiling impacts DNA replication, transcription, protein binding to DNA, and the three-dimensional organization of chromosomes. However, there are currently no methods to directly interrogate or map positive supercoils, so their distribution in genomes remains unknown. Here, we describe a method, GapR-seq, based on the chromatin immunoprecipitation of GapR, a bacterial protein that preferentially recognizes overtwisted DNA, for generating high-resolution maps of positive supercoiling. Applying this method to Escherichia coli and Saccharomyces cerevisiae, we find that positive supercoiling is widespread, associated with transcription, and particularly enriched between convergently oriented genes, consistent with the 'twin-domain' model of supercoiling. In yeast, we also find positive supercoils associated with centromeres, cohesin-binding sites, autonomously replicating sites, and the borders of R-loops (DNA-RNA hybrids). Our results suggest that GapR-seq is a powerful approach, likely applicable in any organism, to investigate aspects of chromosome structure and organization not accessible by Hi-C or other existing methods.

RoboCOP: jointly computing chromatin occupancy profiles for numerous factors from chromatin accessibility data

Chromatin is a tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and occupancy levels of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. In contrast, epigenomic accessibility data like MNase-seq, DNase-seq, and ATAC-seq provide insight into the chromatin landscape of all factors bound along the genome, but with little insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin accessibility data with nucleotide sequence to jointly compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors. We apply RoboCOP to MNase-seq and ATAC-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome, and show that our model makes better predictions than existing methods. We also compute a chromatin occupancy profile of the yeast genome under cadmium stress, revealing chromatin dynamics associated with transcriptional regulation.

Base-resolution models of transcription-factor binding reveal soft motif syntax

The arrangement (syntax) of transcription factor (TF) binding motifs is an important part of the cis-regulatory code, yet remains elusive. We introduce a deep learning model, BPNet, that uses DNA sequence to predict base-resolution chromatin immunoprecipitation (ChIP)-nexus binding profiles of pluripotency TFs. We develop interpretation tools to learn predictive motif representations and identify soft syntax rules for cooperative TF binding interactions. Strikingly, Nanog preferentially binds with helical periodicity, and TFs often cooperate in a directional manner, which we validate using clustered regularly interspaced short palindromic repeat (CRISPR)-induced point mutations. Our model represents a powerful general approach to uncover the motifs and syntax of cis-regulatory sequences in genomics data.

Chromatin accessibility profiling methods

Chromatin accessibility, or the physical access to chromatinized DNA, is a widely studied characteristic of the eukaryotic genome. As active regulatory DNA elements are generally 'accessible', the genome-wide profiling of chromatin accessibility can be used to identify candidate regulatory genomic regions in a tissue or cell type. Multiple biochemical methods have been developed to profile chromatin accessibility, both in bulk and at the single-cell level. Depending on the method, enzymatic cleavage, transposition or DNA methyltransferases are used, followed by high-throughput sequencing, providing a view of genome-wide chromatin accessibility. In this Primer, we discuss these biochemical methods, as well as bioinformatics tools for analysing and interpreting the generated data, and insights into the key regulators underlying developmental, evolutionary and disease processes. We outline standards for data quality, reproducibility and deposition used by the genomics community. Although chromatin accessibility profiling is invaluable to study gene regulation, alone it provides only a partial view of this complex process. Orthogonal assays facilitate the interpretation of accessible regions with respect to enhancer-promoter proximity, functional transcription factor binding and regulatory function. We envision that technological improvements including single-molecule, multi-omics and spatial methods will bring further insight into the secrets of genome regulation.

Plasma DNA Profile Associated with DNASE1L3 Gene Mutations: Clinical Observations, Relationships to Nuclease Substrate Preference, and In Vivo Correction

Plasma DNA fragmentomics is an emerging area in cell-free DNA diagnostics and research. In murine models, it has been shown that the extracellular DNase, DNASE1L3, plays a role in the fragmentation of plasma DNA. In humans, DNASE1L3 deficiency causes familial monogenic systemic lupus erythematosus with childhood onset and anti-dsDNA reactivity. In this study, we found that human patients with DNASE1L3 disease-associated gene variations showed aberrations in size and a reduction of a "CC" end motif of plasma DNA. Furthermore, we demonstrated that DNA from DNASE1L3-digested cell nuclei showed a median length of 153 bp with CC motif frequencies resembling plasma DNA from healthy individuals. Adeno-associated virus-based transduction of Dnase1l3 into Dnase1l3-deficient mice restored the end motif profiles to those seen in the plasma DNA of wild-type mice. Our findings demonstrate that DNASE1L3 is an important player in the fragmentation of plasma DNA, which appears to act in a cell-extrinsic manner to regulate plasma DNA size and motif frequency.

Deacetylation of H4 lysine16 affects acetylation of lysine residues in histone H3 and H4 and promotes transcription of constitutive genes

Histone modification map of H4 N-terminal tail residues in Saccharomyces cerevisiae reveals the prominence of lysine acetylation. Previous reports have indicated the importance of lysine acetylation in maintaining chromatin structure and function. H4K16, a residue with highly regulated acetylation dynamics has unique functions not overlapping with the other H4 N- terminal acetylable residues. The present work unravels the role of H4K16 acetylation in regulating expression of constitutive genes. H4K16 gets distinctly deacetylated over the coding region of constitutively expressed genes. Deacetylation of H4K16 reduces H3K9 acetylation at the cellular and gene level. Reduced H3K9 acetylation however did not negatively correlate with active gene transcription. Significantly, H4K16 deacetylation was found to be associated with hypoacetylated H4K12 throughout the locus of constitutive genes. H4K16 and K12 deacetylation is known to favour active transcription. Sas2, the HAT mutant showed similar patterns of hypoacetylated H3K9 and H4K12 at the active loci, clearly implying that the modifications were associated with deacetylation state of H4K16. Deacetylation of H4K16 was also concurrent with increased H3K56 acetylation in the promoter region and ORF of the constitutive genes. Combination of all these histone modifications significantly reduced H3 occupancy, increased promoter accessibility and enhanced RNAPII recruitment at the constitutively active loci. Consequently, we found that expression of active genes was higher in H4K16R mutant which mimic deacetylated state, but not in H4K16Q mimicking constitutive acetylation. To summarize, H4K16 deacetylation linked with H4K12 and H3K9 hypoacetylation along with H3K56 hyperacetylation generate a chromatin landscape that is conducive for transcription of constitutive genes.

A practical guide for DNase-seq data analysis: from data management to common applications

Deoxyribonuclease I (DNase I)-hypersensitive site sequencing (DNase-seq) has been widely used to determine chromatin accessibility and its underlying regulatory lexicon. However, exploring DNase-seq data requires sophisticated downstream bioinformatics analyses. In this study, we first review computational methods for all of the major steps in DNase-seq data analysis, including experimental design, quality control, read alignment, peak calling, annotation of cis-regulatory elements, genomic footprinting and visualization. The challenges associated with each step are highlighted. Next, we provide a practical guideline and a computational pipeline for DNase-seq data analysis by integrating some of these tools. We also discuss the competing techniques and the potential applications of this pipeline for the analysis of analogous experimental data. Finally, we discuss the integration of DNase-seq with other functional genomics techniques.

NucMap: a database of genome-wide nucleosome positioning map across species

Dynamics of nucleosome positioning affects chromatin state, transcription and all other biological processes occurring on genomic DNA. While MNase-Seq has been used to depict nucleosome positioning map in eukaryote in the past years, nucleosome positioning data is increasing dramatically. To facilitate the usage of published data across studies, we developed a database named nucleosome positioning map (NucMap, http://bigd.big.ac.cn/nucmap). NucMap includes 798 experimental data from 477 samples across 15 species. With a series of functional modules, users can search profile of nucleosome positioning at the promoter region of each gene across all samples and make enrichment analysis on nucleosome positioning data in all genomic regions. Nucleosome browser was built to visualize the profiles of nucleosome positioning. Users can also visualize multiple sources of omics data with the nucleosome browser and make side-by-side comparisons. All processed data in the database are freely available. NucMap is the first comprehensive nucleosome positioning platform and it will serve as an important resource to facilitate the understanding of chromatin regulation.

RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin Occupancy

Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of occupancy of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. On the other hand, epigenomic accessibility data like ATAC-seq, DNase-seq, and MNase-seq provide insight into the chromatin landscape of all factors bound along the genome, but with minimal insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin information from epigenomic accessibility data with nucleotide sequence to compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors at once. RoboCOP can be applied to any epigenomic dataset that provides quantitative insight into chromatin accessibility in any organism, but here we apply it to MNase-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome. Using available protein-binding datasets from the literature, we show that our model more accurately predicts the binding of these factors genome-wide.

A dynamic view of DNA structure within the nucleosome: Biological implications

Most of eukaryotic cellular DNA is packed in nucleosome core particles (NCPs), in which the DNA (DNA_NCP) is wrapped around histones. The influence of this organization on the intrinsic local dynamics of DNA is largely unknown, in particular because capturing such information from experiments remains notoriously challenging. Given the importance of dynamical properties in DNA functions, we addressed this issue using CHARMM36 MD simulations of a nucleosome containing the NCP positioning 601 sequence and four related free dodecamers. Comparison between DNA_NCP and free DNA reveals a limited impact of the dense DNA-histone interface on correlated motions of dinucleotide constituents and on fluctuations of inter base pair parameters. A characteristic feature intimately associated with the DNA_NCP super-helical path is a set of structural periodicities that includes a marked alternation of regions enriched in backbone BI and BII conformers. This observation led to uncover a convincing correspondence between the sequence effect on BI/BII propensities in both DNA_NCP and free DNA, strengthening the idea that the histone preference for particular DNA sequences relies on those intrinsic structural properties. These results offer for the first time a detailed view of the DNA dynamical behavior within NCP. They show in particular that the DNA_NCP dynamics is substantial enough to preserve the ability to structurally adjust to external proteins, for instance remodelers. Also, fresh structural arguments highlight the relevance of relationships between DNA sequence and structural properties for NCP formation. Overall, our work offers a more rational framework to approach the functional, biological roles of NCP.

Genome-wide MNase hypersensitivity assay unveils distinct classes of open chromatin associated with H3K27me3 and DNA methylation in Arabidopsis thaliana

BACKGROUND

Regulation of transcription depends on interactions between cis-regulatory elements (CREs) and regulatory proteins. Active CREs are imbedded in open chromatin that are accessible to nucleases. Several techniques, including DNase-seq, which is based on nuclease DNase I, and ATAC-seq, which is based on transposase Tn5, have been widely used to identify genomic regions associated with open chromatin. These techniques have played a key role in dissecting the regulatory networks in gene expression in both animal and plant species.

RESULTS

We develop a technique, named MNase hypersensitivity sequencing (MH-seq), to identify genomic regions associated with open chromatin in Arabidopsis thaliana. Genomic regions enriched with MH-seq reads are referred as MNase hypersensitive sites (MHSs). MHSs overlap with the majority (~ 90%) of the open chromatin identified previously by DNase-seq and ATAC-seq. Surprisingly, 22% MHSs are not covered by DNase-seq or ATAC-seq reads, which are referred to "specific MHSs" (sMHSs). sMHSs tend to be located away from promoters, and a substantial portion of sMHSs are derived from transposable elements. Most interestingly, genomic regions containing sMHSs are enriched with epigenetic marks, including H3K27me3 and DNA methylation. In addition, sMHSs show a number of distinct characteristics including association with transcriptional repressors. Thus, sMHSs span distinct classes of open chromatin that may not be accessible to DNase I or Tn5. We hypothesize that the small size of the MNase enzyme relative to DNase I or Tn5 allows its access to relatively more condensed chromatin domains.

CONCLUSION

MNase can be used to identify open chromatin regions that are not accessible to DNase I or Tn5. Thus, MH-seq provides an important tool to identify and catalog all classes of open chromatin in plants.

Nucleosomes as allosteric scaffolds for genetic regulation

Nucleosomes are stable yet highly dynamic complexes exhibiting diverse types of motions, such as sliding, DNA unwrapping, and disassembly, encoding a landscape with a large number of metastable states. In this review, describing recent studies on these nucleosome structure changes, we propose that the nucleosome can be viewed as an ideal allosteric scaffold: regulated by effector molecules such as transcription factors and chromatin remodelers, the nucleosome controls the downstream gene activity. Binding of transcription factors to the nucleosome can enhance DNA unwrapping or slide the DNA, altering either the binding or the unbinding of other transcription factors to nearby sites. ATP-dependent chromatin remodelers induce a series of DNA deformations, which allosterically propagate throughout the nucleosome to induce DNA sliding or histone exchange.

Evaluation of a portable nanopore-based sequencer for detection of viruses in water

The newly emerged nanopore sequencing technology such as MinION™ allows for real-time detection of long DNA/RNA fragments on a portable device, yet few have examined its performance for environmental viromes. Here we seeded one RNA virus bacteriophage MS2 and one DNA virus bacteriophage PhiX174 into 10 L well water at three levels ranging from 1 to 21,100 plaque-forming units (PFU)/mL. Two workflows were established to maximize the number of sequencing reads of RNA and DNA viruses using MinION™. With dead-end ultrafiltration, PEG precipitation, and random amplification, MinION™ was capable of detecting MS2 at 155 PFU/mL and PhiX174 at 1-2 PFU/mL. While the DNA workflow only detected PhiX174, the RNA workflow detected both MS2 and PhiX174. The virus concentration, or relative abundance of viral nucleic acids in total nucleic acids, is critical to the proportion of viral reads in sequencing results. Our findings also highlight the importance of including control samples in sequencing runs for environmental water samples with low virus abundance.

Asymmetric repair of UV damage in nucleosomes imposes a DNA strand polarity on somatic mutations in skin cancer

Nucleosomes inhibit excision repair of DNA damage caused by ultraviolet (UV) light, and it has been generally assumed that repair inhibition is equivalent on both sides of the nucleosome dyad. Here, we use genome-wide repair data to show that repair of UV damage in nucleosomes is asymmetric. In yeast, nucleosomes inhibit nucleotide excision repair (NER) of the nontranscribed strand (NTS) of genes in an asymmetric manner, with faster repair of UV damage occurring on the 5′ side of the nucleosomal DNA. Analysis of genomic repair data from UV-irradiated human cells indicates that NER activity along the NTS is also elevated on the 5′ side of nucleosomes, consistent with the repair asymmetry observed in yeast nucleosomes. Among intergenic nucleosomes, repair activity is elevated on the 5′ side of both DNA strands. The distribution of somatic mutations in nucleosomes shows the opposite asymmetry in NER-proficient skin cancers, but not in NER-deficient cancers, indicating that asymmetric repair of nucleosomal DNA imposes a strand polarity on UV mutagenesis. Somatic mutations are enriched on the relatively slow-repairing 3′ side of the nucleosomal DNA, particularly at positions where the DNA minor groove faces away from the histone octamer. Asymmetric repair and mutagenesis are likely caused by differential accessibility of the nucleosomal DNA, a consequence of its left-handed wrapping around the histone octamer.

ZCMM: A Novel Method Using Z-Curve Theory- Based and Position Weight Matrix for Predicting Nucleosome Positioning

Nucleosomes are the basic units of eukaryotes. The accurate positioning of nucleosomes plays a significant role in understanding many biological processes such as transcriptional regulation mechanisms and DNA replication and repair. Here, we describe the development of a novel method, termed ZCMM, based on Z-curve theory and position weight matrix (PWM). The ZCMM was trained and tested using the nucleosomal and linker sequences determined by support vector machine (SVM) in Saccharomyces cerevisiae (S. cerevisiae), and experimental results showed that the sensitivity (Sn), specificity (Sp), accuracy (Acc), and Matthews correlation coefficient (MCC) values for ZCMM were 91.40%, 96.56%, 96.75%, and 0.88, respectively, and the average area under the receiver operating characteristic curve (AUC) value was 0.972. A ZCMM predictor was developed to predict nucleosome positioning in Homo sapiens (H. sapiens), Caenorhabditis elegans (C. elegans), and Drosophila melanogaster (D. melanogaster) genomes, and the accuracy (Acc) values were 77.72%, 85.34%, and 93.62%, respectively. The maximum AUC values of the four species were 0.982, 0.861, 0.912 and 0.911, respectively. Another independent dataset for S. cerevisiae was used to predict nucleosome positioning. Compared with the results of Wu's method, it was found that the Sn, Sp, Acc, and MCC of ZCMM results for S. cerevisiae were all higher, reaching 96.72%, 96.54%, 94.10%, and 0.88. Compared with the Guo's method 'iNuc-PseKNC', the results of ZCMM for D. melanogaster were better. Meanwhile, the ZCMM was compared with some experimental data in vitro and in vivo for S. cerevisiae, and the results showed that the nucleosomes predicted by ZCMM were highly consistent with those confirmed by these experiments. Therefore, it was further confirmed that the ZCMM method has good accuracy and reliability in predicting nucleosome positioning.

Somatic and Germline Mutation Periodicity Follow the Orientation of the DNA Minor Groove around Nucleosomes

Mutation rates along the genome are highly variable and influenced by several chromatin features. Here, we addressed how nucleosomes, the most pervasive chromatin structure in eukaryotes, affect the generation of mutations. We discovered that within nucleosomes, the somatic mutation rate across several tumor cohorts exhibits a strong 10 base pair (bp) periodicity. This periodic pattern tracks the alternation of the DNA minor groove facing toward and away from the histones. The strength and phase of the mutation rate periodicity are determined by the mutational processes active in tumors. We uncovered similar periodic patterns in the genetic variation among human and Arabidopsis populations, also detectable in their divergence from close species, indicating that the same principles underlie germline and somatic mutation rates. We propose that differential DNA damage and repair processes dependent on the minor groove orientation in nucleosome-bound DNA contribute to the 10-bp periodicity in AT/CG content in eukaryotic genomes.

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.

Organization of DNA damage, excision repair, and mutagenesis in chromatin: A genomic perspective

Genomic DNA is constantly assaulted by both endogenous and exogenous damaging agents. The resulting DNA damage, if left unrepaired, can interfere with DNA replication and be converted into mutations. Genomic DNA is packaged into a highly compact yet dynamic chromatin structure, in order to fit into the limited space available in the nucleus of eukaryotic cells. This hierarchical chromatin organization serves as both the target of DNA damaging agents and the context for DNA repair enzymes. Biochemical studies have suggested that both the formation and repair of DNA damage are significantly modulated by chromatin. Our understanding of the impact of chromatin on damage and repair has been significantly enhanced by recent studies. We focus on the nucleosome, the primary building block of chromatin, and discuss how the intrinsic structural properties of nucleosomes, and their associated epigenetic modifications, affect damage formation and DNA repair, as well as subsequent mutagenesis in cancer.

Single-molecule long-read sequencing reveals the chromatin basis of gene expression

Genome-wide chromatin accessibility and nucleosome occupancy profiles have been widely investigated, while the long-range dynamics remain poorly studied at the single-cell level. Here, we present a new experimental approach, methyltransferase treatment followed by single-molecule long-read sequencing (MeSMLR-seq), for long-range mapping of nucleosomes and chromatin accessibility at single DNA molecules and thus achieve comprehensive-coverage characterization of the corresponding heterogeneity. MeSMLR-seq offers direct measurements of both nucleosome-occupied and nucleosome-evicted regions on a single DNA molecule, which is challenging for many existing methods. We applied MeSMLR-seq to haploid yeast, where single DNA molecules represent single cells, and thus we could investigate the combinatorics of many (up to 356) nucleosomes at long range in single cells. We illustrated the differential organization principles of nucleosomes surrounding the transcription start site for silent and actively transcribed genes, at the single-cell level and in the long-range scale. The heterogeneous patterns of chromatin status spanning multiple genes were phased. Together with single-cell RNA-seq data, we quantitatively revealed how chromatin accessibility correlated with gene transcription positively in a highly heterogeneous scenario. Moreover, we quantified the openness of promoters and investigated the coupled chromatin changes of adjacent genes at single DNA molecules during transcription reprogramming. In addition, we revealed the coupled changes of chromatin accessibility for two neighboring glucose transporter genes in response to changes in glucose concentration.

Nucleosome positions establish an extended mutation signature in melanoma

Ultraviolet (UV) light-induced mutations are unevenly distributed across skin cancer genomes, but the molecular mechanisms responsible for this heterogeneity are not fully understood. Here, we assessed how nucleosome structure impacts the positions of UV-induced mutations in human melanomas. Analysis of mutation positions from cutaneous melanomas within strongly positioned nucleosomes revealed a striking ~10 base pair (bp) oscillation in mutation density with peaks occurring at dinucleotides facing away from the histone octamer. Additionally, higher mutation density at the nucleosome dyad generated an overarching “translational curvature” across the 147 bp of DNA that constitutes the nucleosome core particle. This periodicity and curvature cannot be explained by sequence biases in nucleosomal DNA. Instead, our genome-wide map of UV-induced cyclobutane pyrimidine dimers (CPDs) indicates that CPD formation is elevated at outward facing dinucleotides, mirroring the oscillation of mutation density within nucleosome-bound DNA. Nucleotide excision repair (NER) activity, as measured by XR-seq, inversely correlated with the curvature of mutation density associated with the translational setting of the nucleosome. While the 10 bp periodicity of mutations is maintained across nucleosomes regardless of chromatin state, histone modifications, and transcription levels, overall mutation density and curvature across the core particle increased with lower transcription levels. Our observations suggest structural conformations of DNA promote CPD formation at specific sites within nucleosomes, and steric hindrance progressively limits lesion repair towards the nucleosome dyad. Both mechanisms create a unique extended mutation signature within strongly positioned nucleosomes across the human genome.

UV-induced mutations are abundant and heterogeneously distributed across melanoma genomes. Understanding the mechanisms that produce this heterogeneity may help decipher which mutations drive the cancer phenotype. While it is known that mutation density correlates with chromatin compaction on a large scale, recent studies have suggested that local chromatin structure impacts mutation distribution in ways previously undetected. We therefore examined the distribution of melanoma mutations in strongly positioned nucleosomes where we observed a striking oscillatory and curvature pattern. UV lesion formation appeared to be responsible for mutation oscillation, despite active repair occurring in the nucleosome core particle. However, more CPD lesions are removed near the edges of nucleosomes, and thus generated an overall translational curvature in mutation density.

Application of MNase-Seq in the Global Mapping of Nucleosome Positioning in Plants

The precise positioning of nucleosomes along the underlying DNA is critical for a variety of biological processes, especially in regulating transcription. The interplay between nucleosomes and transcription factors for accessing the underlying DNA sequences is one of the key determinants that affect transcriptional regulation. Moreover, nucleosomes with various packing statuses confer distinct functions in regulating gene expressions in response to various internal or external signals. Therefore, global mapping of nucleosome positions is one informative way to elucidate the relationship between patterns of nucleosome positioning/occupancy and transcriptional regulations. MNase digestion coupled with high-throughput sequencing (MNase-seq) has been utilized widely for global mapping of nucleosome positioning in eukaryotes that have a sequenced genome. We have developed a robust MNase-seq procedure in plants. It mainly includes plant nuclei isolation, treatment of purified nuclei with MNase, gel recovery of MNase-trimmed mononucleosomal DNA with an approximate size of 150 bp, MNase-seq library preparation followed by Illumina sequencing, and data analysis. MNase-seq has already been successfully applied to identify genome-wide nucleosome positioning in model plants, rice, and Arabidopsis thaliana.

DMS-Seq for In Vivo Genome-wide Mapping of Protein-DNA Interactions and Nucleosome Centers

Protein-DNA interactions provide the basis for chromatin structure and gene regulation. Comprehensive identification of protein-occupied sites is thus vital to an in-depth understanding of genome function. Dimethyl sulfate (DMS) is a chemical probe that has long been used to detect footprints of DNA-bound proteins in vitro and in vivo. Here, we describe a genomic footprinting method, dimethyl sulfate sequencing (DMS-seq), which exploits the cell-permeable nature of DMS to obviate the need for nuclear isolation. This feature makes DMS-seq simple in practice and removes the potential risk of protein re-localization during nuclear isolation. DMS-seq successfully detects transcription factors bound to cis-regulatory elements and non-canonical chromatin particles in nucleosome-free regions. Furthermore, an unexpected preference of DMS confers on DMS-seq a unique potential to directly detect nucleosome centers without using genetic manipulation. We expect that DMS-seq will serve as a characteristic method for genome-wide interrogation of in vivo protein-DNA interactions.

Major Determinants of Nucleosome Positioning

The compact structure of the nucleosome limits DNA accessibility and inhibits the binding of most sequence-specific proteins. Nucleosomes are not randomly located on the DNA but positioned with respect to the DNA sequence, suggesting models in which critical binding sites are either exposed in the linker, resulting in activation, or buried inside a nucleosome, resulting in repression. The mechanisms determining nucleosome positioning are therefore of paramount importance for understanding gene regulation and other events that occur in chromatin, such as transcription, replication, and repair. Here, we review our current understanding of the major determinants of nucleosome positioning: DNA sequence, nonhistone DNA-binding proteins, chromatin-remodeling enzymes, and transcription. We outline the major challenges for the future: elucidating the precise mechanisms of chromatin opening and promoter activation, identifying the complexes that occupy promoters, and understanding the multiscale problem of chromatin fiber organization.

Changes in chromatin accessibility between Arabidopsis stem cells and mesophyll cells illuminate cell type-specific transcription factor networks

Cell differentiation is driven by changes in the activity of transcription factors (TFs) and subsequent alterations in transcription. To study this process, differences in TF binding between cell types can be deduced by probing chromatin accessibility. We used cell type-specific nuclear purification followed by the assay for transposase-accessible chromatin (ATAC-seq) to delineate differences in chromatin accessibility and TF regulatory networks between stem cells of the shoot apical meristem (SAM) and differentiated leaf mesophyll cells in Arabidopsis thaliana. Chromatin accessibility profiles of SAM stem cells and leaf mesophyll cells were very similar at a qualitative level, yet thousands of regions having quantitatively different chromatin accessibility were also identified. Analysis of the genomic regions preferentially accessible in each cell type identified hundreds of overrepresented TF-binding motifs, highlighting sets of TFs that are probably important for each cell type. Within these sets, we found evidence for extensive co-regulation of target genes by multiple TFs that are preferentially expressed in each cell type. Interestingly, the TFs within each of these cell type-enriched sets also showed evidence of extensively co-regulating each other. We further found that preferentially accessible chromatin regions in mesophyll cells tended to also be substantially accessible in the stem cells, whereas the converse was not true. This observation suggests that the generally higher accessibility of regulatory elements in stem cells might contribute to their developmental plasticity. This work demonstrates the utility of cell type-specific chromatin accessibility profiling for the rapid development of testable models of regulatory control differences between cell types.

Hypomethylated domain-enriched DNA motifs prepattern the accessible nucleosome organization in teleosts

Background

Gene promoters in vertebrate genomes show distinct chromatin features such as stably positioned nucleosome array and DNA hypomethylation. The nucleosomes are known to have certain sequence preferences, and the prediction of nucleosome positioning from DNA sequence has been successful in some organisms such as yeast. However, at gene promoters where nucleosomes are much more stably positioned than in other regions, the sequence-based model has failed to work well, and sequence-independent mechanisms have been proposed.

Results

Using DNase I-seq in medaka embryos, we demonstrated that hypomethylated domains (HMDs) specifically possess accessible nucleosome organization with longer linkers, and we reassessed the DNA sequence preference for nucleosome positioning in these specific regions. Remarkably, we found with a supervised machine learning algorithm, k-mer SVM, that nucleosome positioning in HMDs is accurately predictable from DNA sequence alone. Specific short sequences (6-mers) that contribute to the prediction are specifically enriched in HMDs and distribute periodically with approximately 200-bp intervals which prepattern the position of accessible linkers. Surprisingly, the sequence preference of the nucleosome and linker in HMDs is opposite from that reported previously. Furthermore, the periodicity of specific motifs at hypomethylated promoters was conserved in zebrafish.

Conclusion

This study reveals strong link between nucleosome positioning and DNA sequence at vertebrate promoters, and we propose hypomethylated DNA-specific regulation of nucleosome positioning.

Electronic supplementary material

The online version of this article (doi:10.1186/s13072-017-0152-2) contains supplementary material, which is available to authorized users.

Genome-wide maps of alkylation damage, repair, and mutagenesis in yeast reveal mechanisms of mutational heterogeneity

DNA base damage is an important contributor to genome instability, but how the formation and repair of these lesions is affected by the genomic landscape and contributes to mutagenesis is unknown. Here, we describe genome-wide maps of DNA base damage, repair, and mutagenesis at single nucleotide resolution in yeast treated with the alkylating agent methyl methanesulfonate (MMS). Analysis of these maps revealed that base excision repair (BER) of alkylation damage is significantly modulated by chromatin, with faster repair in nucleosome-depleted regions, and slower repair and higher mutation density within strongly positioned nucleosomes. Both the translational and rotational settings of lesions within nucleosomes significantly influence BER efficiency; moreover, this effect is asymmetric relative to the nucleosome dyad axis and is regulated by histone modifications. Our data also indicate that MMS-induced mutations at adenine nucleotides are significantly enriched on the nontranscribed strand (NTS) of yeast genes, particularly in BER-deficient strains, due to higher damage formation on the NTS and transcription-coupled repair of the transcribed strand (TS). These findings reveal the influence of chromatin on repair and mutagenesis of base lesions on a genome-wide scale and suggest a novel mechanism for transcription-associated mutation asymmetry, which is frequently observed in human cancers.

A computational approach to map nucleosome positions and alternative chromatin states with base pair resolution

Understanding chromatin function requires knowing the precise location of nucleosomes. MNase-seq methods have been widely applied to characterize nucleosome organization in vivo, but generally lack the accuracy to determine the precise nucleosome positions. Here we develop a computational approach leveraging digestion variability to determine nucleosome positions at a base-pair resolution from MNase-seq data. We generate a variability template as a simple error model for how MNase digestion affects the mapping of individual nucleosomes. Applied to both yeast and human cells, this analysis reveals that alternatively positioned nucleosomes are prevalent and create significant heterogeneity in a cell population. We show that the periodic occurrences of dinucleotide sequences relative to nucleosome dyads can be directly determined from genome-wide nucleosome positions from MNase-seq. Alternatively positioned nucleosomes near transcription start sites likely represent different states of promoter nucleosomes during transcription initiation. Our method can be applied to map nucleosome positions in diverse organisms at base-pair resolution.

Nucleosome positioning changes during human embryonic stem cell differentiation

Nucleosomes are the basic unit of chromatin. Nucleosome positioning (NP) plays a key role in transcriptional regulation and other biological processes. To better understand NP we used MNase-seq to investigate changes that occur as human embryonic stem cells (hESCs) transition to nascent mesoderm and then to smooth muscle cells (SMCs). Compared to differentiated cell derivatives, nucleosome occupancy at promoters and other notable genic sites, such as exon/intron junctions and adjacent regions, in hESCs shows a stronger correlation with transcript abundance and is less influenced by sequence content. Upon hESC differentiation, genes being silenced, but not genes being activated, display a substantial change in nucleosome occupancy at their promoters. Genome-wide, we detected a shift of NP to regions of higher G+C content as hESCs differentiate to SMCs. Notably, genomic regions with higher nucleosome occupancy harbor twice as many G↔C changes but fewer than half A↔T changes, compared to regions with lower nucleosome occupancy. Finally, our analysis indicates that the hESC genome is not rearranged and has a sequence mutation rate resembling normal human genomes. Our study reveals another unique feature of hESC chromatin, and sheds light on the relationship between nucleosome occupancy and sequence G+C content.