PING 2.0: an R/Bioconductor package for nucleosome positioning using next-generation sequencing data

Mapping nucleosome and chromatin architectures: A survey of computational methods

With ever-growing genomic sequencing data, the data variabilities and the underlying biases of the sequencing technologies pose significant computational challenges ranging from the need for accurately detecting the nucleosome positioning or chromatin interaction to the need for developing normalization methods to eliminate systematic biases. This review mainly surveys the computational methods for mapping the higher-resolution nucleosome and higher-order chromatin architectures. While a detailed discussion of the underlying algorithms is beyond the scope of our survey, we have discussed the methods and tools that can detect the nucleosomes in the genome, then demonstrated the computational methods for identifying 3D chromatin domains and interactions. We further illustrated computational approaches for integrating multi-omics data with Hi-C data and the advance of single-cell (sc)Hi-C data analysis. Our survey provides a comprehensive and valuable resource for biomedical scientists interested in studying nucleosome organization and chromatin structures as well as for computational scientists who are interested in improving upon them.

MeCP2 regulates gene expression through recognition of H3K27me3

MeCP2 plays a multifaceted role in gene expression regulation and chromatin organization. Interaction between MeCP2 and methylated DNA in the regulation of gene expression is well established. However, the widespread distribution of MeCP2 suggests it has additional interactions with chromatin. Here we demonstrate, by both biochemical and genomic analyses, that MeCP2 directly interacts with nucleosomes and its genomic distribution correlates with that of H3K27me3. In particular, the methyl-CpG-binding domain of MeCP2 shows preferential interactions with H3K27me3. We further observe that the impact of MeCP2 on transcriptional changes correlates with histone post-translational modification patterns. Our findings indicate that MeCP2 interacts with genomic loci via binding to DNA as well as histones, and that interaction between MeCP2 and histone proteins plays a key role in gene expression regulation.

Gcn4 Binding in Coding Regions Can Activate Internal and Canonical 5' Promoters in Yeast

Gcn4 is a yeast transcriptional activator induced by amino acid starvation. ChIP-seq analysis revealed 546 genomic sites occupied by Gcn4 in starved cells, representing ∼30% of Gcn4-binding motifs. Surprisingly, only ∼40% of the bound sites are in promoters, of which only ∼60% activate transcription, indicating extensive negative control over Gcn4 function. Most of the remaining ∼300 Gcn4-bound sites are within coding sequences (CDSs), with ∼75 representing the only bound sites near Gcn4-induced genes. Many such unconventional sites map between divergent antisense and sub-genic sense transcripts induced within CDSs adjacent to induced TBP peaks, consistent with Gcn4 activation of cryptic bidirectional internal promoters. Mutational analysis confirms that Gcn4 sites within CDSs can activate sub-genic and full-length transcripts from the same or adjacent genes, showing that functional Gcn4 binding is not confined to promoters. Our results show that internal promoters can be regulated by an activator that functions at conventional 5'-positioned promoters.

Precise genome-wide mapping of single nucleosomes and linkers in vivo

We developed a chemical cleavage method that releases single nucleosome dyad-containing fragments, allowing us to precisely map both single nucleosomes and linkers with high accuracy genome-wide in yeast. Our single nucleosome positioning data reveal that nucleosomes occupy preferred positions that differ by integral multiples of the DNA helical repeat. By comparing nucleosome dyad positioning maps to existing genomic and transcriptomic data, we evaluated the contributions of sequence, transcription, and histones H1 and H2A.Z in defining the chromatin landscape. We present a biophysical model that neglects DNA sequence and shows that steric occlusion suffices to explain the salient features of nucleosome positioning.

Profiling Nucleosome Occupancy by MNase-seq: Experimental Protocol and Computational Analysis

Nucleosomes are the basic repeating units of eukaryotic chromatin. They play important roles in chromatin compaction and gene regulation. Therefore, it is important to profile the in vivo locations of nucleosomes in the genome. Here we illustrate how to profile nucleosome occupancy at genome-wide scale using micrococcal nuclease (MNase) digestion combined with high throughput Illumina sequencing (MNase-seq). Nucleosome-associated DNA is relatively insensitive to digestion by micrococcal nuclease (MNase). Upon mild MNase treatment, the undigested nucleosomal DNA can be purified and sequenced allowing a precise localization of in vivo nucleosomes at a genome-wide level.

NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Background

Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them.

Results

Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs).

Conclusions

The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3580-2) contains supplementary material, which is available to authorized users.

DChIPRep, an R/Bioconductor package for differential enrichment analysis in chromatin studies

The genome-wide study of epigenetic states requires the integrative analysis of histone modification ChIP-seq data. Here, we introduce an easy-to-use analytic framework to compare profiles of enrichment in histone modifications around classes of genomic elements, e.g. transcription start sites (TSS). Our framework is available via the user-friendly R/Bioconductor package DChIPRep. DChIPRep uses biological replicate information as well as chromatin Input data to allow for a rigorous assessment of differential enrichment. DChIPRep is available for download through the Bioconductor project at http://bioconductor.org/packages/DChIPRep. Contact. DChIPRep@gmail.com.

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.

Chromatin-dependent regulation of RNA polymerases II and III activity throughout the transcription cycle

The particular behaviour of eukaryotic RNA polymerases along different gene regions and amongst distinct gene functional groups is not totally understood. To cast light onto the alternative active or backtracking states of RNA polymerase II, we have quantitatively mapped active RNA polymerases at a high resolution following a new biotin-based genomic run-on (BioGRO) technique. Compared with conventional profiling with chromatin immunoprecipitation, the analysis of the BioGRO profiles in Saccharomyces cerevisiae shows that RNA polymerase II has unique activity profiles at both gene ends, which are highly dependent on positioned nucleosomes. This is the first demonstration of the in vivo influence of positioned nucleosomes on transcription elongation. The particular features at the 5' end and around the polyadenylation site indicate that this polymerase undergoes extensive specific-activity regulation in the initial and final transcription elongation phases. The genes encoding for ribosomal proteins show distinctive features at both ends. BioGRO also provides the first nascentome analysis for RNA polymerase III, which indicates that transcription of tRNA genes is poorly regulated at the individual copy level. The present study provides a novel perspective of the transcription cycle that incorporates inactivation/reactivation as an important aspect of RNA polymerase dynamics.

Nucleosome regulatory dynamics in response to TGFβ

Nucleosomes play important roles in a cell beyond their basal functionality in chromatin compaction. Their placement affects all steps in transcriptional regulation, from transcription factor (TF) binding to messenger ribonucleic acid (mRNA) synthesis. Careful profiling of their locations and dynamics in response to stimuli is important to further our understanding of transcriptional regulation by the state of chromatin. We measured nucleosome occupancy in human hepatic cells before and after treatment with transforming growth factor beta 1 (TGFβ1), using massively parallel sequencing. With a newly developed method, SuMMIt, for precise positioning of nucleosomes we inferred dynamics of the nucleosomal landscape. Distinct nucleosome positioning has previously been described at transcription start site and flanking TF binding sites. We found that the average pattern is present at very few sites and, in case of TF binding, the double peak surrounding the sites is just an artifact of averaging over many loci. We systematically searched for depleted nucleosomes in stimulated cells compared to unstimulated cells and identified 24 318 loci. Depending on genomic annotation, 44–78% of them were over-represented in binding motifs for TFs. Changes in binding affinity were verified for HNF4α by qPCR. Strikingly many of these loci were associated with expression changes, as measured by RNA sequencing.

Next-generation technologies and data analytical approaches for epigenomics

Epigenetics refers to the collection of heritable features that modulate the genome-environment interaction without being encoded in the actual DNA sequence. While being mitotically and sometimes even meiotically transmitted, epigenetic traits often demonstrate extensive flexibility. This allows cells to acquire diverse gene expression patterns during differentiation, but also to adapt to a changing environment. However, epigenetic alterations are not always beneficial to the organism, as they are, for example, frequently identified in human diseases such as cancer. Accurate and cost-efficient genome-scale profiling of epigenetic features is thus of major importance to pinpoint these "epimutations," for example, to monitor the epigenetic impact of environmental exposure. Over the last decade, the field of epigenetics has been revolutionized by several innovative "epigenomics" technologies exactly addressing this need. In this review, we discuss and compare widely used next-generation methods to assess DNA methylation and hydroxymethylation, noncoding RNA expression, histone modifications, and nucleosome positioning. Although recent methods are typically based on "second-generation" sequencing, we also pay attention to still commonly used array- and PCR-based methods, and look forward to the additional advantages of single-molecule sequencing. As the current bottleneck in epigenomics research is the analysis rather than generation of data, the basic difficulties and problem-solving strategies regarding data preprocessing and statistical analysis are introduced for the different technologies. Finally, we also consider the complications associated with epigenomic studies of species with yet unsequenced genomes and possible solutions.