Nucleosome Occupancy and Methylome Sequencing (NOMe-seq)

Feeling the force from within - new tools and insights into nuclear mechanotransduction

The ability of cells to sense and respond to mechanical signals is essential for many biological processes that form the basis of cell identity, tissue development and maintenance. This process, known as mechanotransduction, involves crucial feedback between mechanical force and biochemical signals, including epigenomic modifications that establish transcriptional programs. These programs, in turn, reinforce the mechanical properties of the cell and its ability to withstand mechanical perturbation. The nucleus has long been hypothesized to play a key role in mechanotransduction due to its direct exposure to forces transmitted through the cytoskeleton, its role in receiving cytoplasmic signals and its central function in gene regulation. However, parsing out the specific contributions of the nucleus from those of the cell surface and cytoplasm in mechanotransduction remains a substantial challenge. In this Review, we examine the latest evidence on how the nucleus regulates mechanotransduction, both via the nuclear envelope (NE) and through epigenetic and transcriptional machinery elements within the nuclear interior. We also explore the role of nuclear mechanotransduction in establishing a mechanical memory, characterized by a mechanical, epigenetic and transcriptomic cell state that persists after mechanical stimuli cease. Finally, we discuss current challenges in the field of nuclear mechanotransduction and present technological advances that are poised to overcome them.

Study on chromatin regulation patterns of expression vectors in the PhiC31 integration site

The PhiC31 integration system allows for targeted and efficient transgene integration and expression by recognizing pseudo attP sites in mammalian cells and integrating the exogenous genes into the open chromatin regions of active chromatin. In order to investigate the regulatory patterns of efficient gene expression in the open chromatin region of PhiC31 integration, this study utilized Ubiquitous Chromatin Opening Element (UCOE) and activating RNA (saRNA) to modulate the chromatin structure in the promoter region of the PhiC31 integration vector. The study analysed the effects of DNA methylation and nucleosome occupancy changes in the integrated promoter on gene expression levels. The results showed that for the OCT4 promoter with moderate CG density, DNA methylation had a smaller impact on expression compared to changes in nucleosome positioning near the transcription start site, which was crucial for enhancing downstream gene expression. On the other hand, for the SOX2 promoter with high CG density, increased methylation in the CpG island upstream of the transcription start site played a key role in affecting high expression, but the positioning and clustering of nucleosomes also had an important influence. In conclusion, analysing the DNA methylation patterns, nucleosome positioning, and quantity distribution of different promoters can determine whether the PhiC31 integration site possesses the potential to further enhance expression or overcome transgene silencing effects by utilizing chromatin regulatory elements.

Epigenetic pioneering by SWI/SNF family remodelers

In eukaryotic genomes, transcriptional machinery and nucleosomes compete for binding to DNA sequences; thus, a crucial aspect of gene regulatory element function is to modulate chromatin accessibility for transcription factor (TF) and RNA polymerase binding. Recent structural studies have revealed multiple modes of TF engagement with nucleosomes, but how initial "pioneering" results in steady-state DNA accessibility for further TF binding and RNA polymerase II (RNAPII) engagement has been unclear. Even less well understood is how distant sites of open chromatin interact with one another, such as when developmental enhancers activate promoters to release RNAPII for productive elongation. Here, we review evidence for the centrality of the conserved SWI/SNF family of nucleosome remodeling complexes, both in pioneering and in mediating enhancer-promoter contacts. Consideration of the nucleosome unwrapping and ATP hydrolysis activities of SWI/SNF complexes, together with their architectural features, may reconcile steady-state TF occupancy with rapid TF dynamics observed by live imaging.

A single fiber view of the nucleosome organization in eukaryotic chromatin

Eukaryotic cells are thought to arrange nucleosomes into extended arrays with evenly spaced nucleosomes phased at genomic landmarks. Here we tested to what extent this stereotypic organization describes the nucleosome organization in Saccharomyces cerevisiae using Fiber-Seq, a long-read sequencing technique that maps entire nucleosome arrays on individual chromatin fibers in a high throughput manner. With each fiber coming from a different cell, Fiber-Seq uncovers cell-to-cell heterogeneity. The long reads reveal the nucleosome architecture even over repetitive DNA such as the ribosomal DNA repeats. The absolute nucleosome occupancy, a parameter that is difficult to obtain with conventional sequencing approaches, is a direct readout of Fiber-Seq. We document substantial deviations from the stereotypical nucleosome organization with unexpectedly long linker DNAs between nucleosomes, gene bodies missing entire nucleosomes, cell-to-cell heterogeneity in nucleosome occupancy, heterogeneous phasing of arrays and irregular nucleosome spacing. Nucleosome array structures are indistinguishable throughout the gene body and with respect to the direction of transcription arguing against transcription promoting array formation. Acute nucleosome depletion destroyed most of the array organization indicating that nucleosome remodelers cannot efficiently pack nucleosomes under those conditions. Given that nucleosomes are cis-regulatory elements, the cell-to-cell heterogeneity uncovered by Fiber-Seq provides much needed information to understand chromatin structure and function.

Single-Cell Multiomics

Single-cell RNA sequencing methods have led to improved understanding of the heterogeneity and transcriptomic states present in complex biological systems. Recently, the development of novel single-cell technologies for assaying additional modalities, specifically genomic, epigenomic, proteomic, and spatial data, allows for unprecedented insight into cellular biology. While certain technologies collect multiple measurements from the same cells simultaneously, even when modalities are separately assayed in different cells, we can apply novel computational methods to integrate these data. The application of computational integration methods to multimodal paired and unpaired data results in rich information about the identities of the cells present and the interactions between different levels of biology, such as between genetic variation and transcription. In this review, we both discuss the single-cell technologies for measuring these modalities and describe and characterize a variety of computational integration methods for combining the resulting data to leverage multimodal information toward greater biological insight.

Factors and Methods for the Detection of Gene Expression Regulation

Gene-expression regulation involves multiple processes and a range of regulatory factors. In this review, we describe the key factors that regulate gene expression, including transcription factors (TFs), chromatin accessibility, histone modifications, DNA methylation, and RNA modifications. In addition, we also describe methods that can be used to detect these regulatory factors.

Single-cell sequencing: expansion, integration and translation

With the rapid advancement in sequencing technologies, the concept of omics has revolutionized our understanding of cellular behaviors. Conventional omics investigation approaches measure the averaged behaviors of multiple cells, which may easily hide signals represented by a small-cell cohort, urging for the development of techniques with enhanced resolution. Single-cell RNA sequencing, investigating cell transcriptomics at the resolution of a single cell, has been rapidly expanded to investigate other omics such as genomics, proteomics and metabolomics since its invention. The requirement for comprehensive understanding of complex cellular behavior has led to the integration of multi-omics and single-cell sequencing data with other layers of information such as spatial data and the CRISPR screening technique towards gained knowledge or innovative functionalities. The development of single-cell sequencing in both dimensions has rendered it a unique field that offers us a versatile toolbox to delineate complex diseases, including cancers.

ETV2 functions as a pioneer factor to regulate and reprogram the endothelial lineage

The vasculature is an essential organ for the delivery of blood and oxygen to all tissues of the body and is thus relevant to the treatment of ischaemic diseases, injury-induced regeneration and solid tumour growth. Previously, we demonstrated that ETV2 is an essential transcription factor for the development of cardiac, endothelial and haematopoietic lineages. Here we report that ETV2 functions as a pioneer factor that relaxes closed chromatin and regulates endothelial development. By comparing engineered embryonic stem cell differentiation and reprogramming models with multi-omics techniques, we demonstrated that ETV2 was able to bind nucleosomal DNA and recruit BRG1. BRG1 recruitment remodelled chromatin around endothelial genes and helped to maintain an open configuration, resulting in increased H3K27ac deposition. Collectively, these results will serve as a platform for the development of therapeutic initiatives directed towards cardiovascular diseases and solid tumours.

BAF complex-mediated chromatin relaxation is required for establishment of X chromosome inactivation

The process of epigenetic silencing, while fundamentally important, is not yet completely understood. Here we report a replenishable female mouse embryonic stem cell (mESC) system, Xmas, that allows rapid assessment of X chromosome inactivation (XCI), the epigenetic silencing mechanism of one of the two X chromosomes that enables dosage compensation in female mammals. Through a targeted genetic screen in differentiating Xmas mESCs, we reveal that the BAF complex is required to create nucleosome-depleted regions at promoters on the inactive X chromosome during the earliest stages of establishment of XCI. Without this action gene silencing fails. Xmas mESCs provide a tractable model for screen-based approaches that enable the discovery of unknown facets of the female-specific process of XCI and epigenetic silencing more broadly.

Female embryonic stem cells (ESCs) are the ideal model to study X chromosome inactivation (XCI) establishment; however, these cells are challenging to keep in culture. Here the authors create fluorescent ‘Xmas’ reporter mice as a renewable source of ESCs and show nucleosome remodelers Smarcc1 and Smarca4 create a nucleosome-free promoter region prior to the establishment of silencing.

Filtering the Junk: Assigning Function to the Mosquito Non-Coding Genome

The portion of the mosquito genome that does not code for proteins contains regulatory elements that likely underlie variation for important phenotypes including resistance and susceptibility to infection with arboviruses and Apicomplexan parasites. Filtering the non-coding genome to uncover these functional elements is an expanding area of research, though identification of non-coding regulatory elements is challenging due to the lack of an amino acid-like code for the non-coding genome and a lack of sequence conservation across species. This review focuses on three types of non-coding regulatory elements: (1) microRNAs (miRNAs), (2) long non-coding RNAs (lncRNAs), and (3) enhancers, and summarizes current advances in technical and analytical approaches for measurement of each of these elements on a genome-wide scale. The review also summarizes and highlights novel findings following application of these techniques in mosquito-borne disease research. Looking beyond the protein-coding genome is essential for understanding the complexities that underlie differential gene expression in response to arboviral or parasite infection in mosquito disease vectors. A comprehensive understanding of the regulation of gene and protein expression will inform transgenic and other vector control methods rooted in naturally segregating genetic variation.

Self-organizing maps with variable neighborhoods facilitate learning of chromatin accessibility signal shapes associated with regulatory elements

BACKGROUND

Assigning chromatin states genome-wide (e.g. promoters, enhancers, etc.) is commonly performed to improve functional interpretation of these states. However, computational methods to assign chromatin state suffer from the following drawbacks: they typically require data from multiple assays, which may not be practically feasible to obtain, and they depend on peak calling algorithms, which require careful parameterization and often exclude the majority of the genome. To address these drawbacks, we propose a novel learning technique built upon the Self-Organizing Map (SOM), Self-Organizing Map with Variable Neighborhoods (SOM-VN), to learn a set of representative shapes from a single, genome-wide, chromatin accessibility dataset to associate with a chromatin state assignment in which a particular RE is prevalent. These shapes can then be used to assign chromatin state using our workflow.

RESULTS

We validate the performance of the SOM-VN workflow on 14 different samples of varying quality, namely one assay each of A549 and GM12878 cell lines and two each of H1 and HeLa cell lines, primary B-cells, and brain, heart, and stomach tissue. We show that SOM-VN learns shapes that are (1) non-random, (2) associated with known chromatin states, (3) generalizable across sets of chromosomes, and (4) associated with magnitude and multimodality. We compare the accuracy of SOM-VN chromatin states against the Clustering Aggregation Tool (CAGT), an unsupervised method that learns chromatin accessibility signal shapes but does not associate these shapes with REs, and we show that overall precision and recall is increased when learning shapes using SOM-VN as compared to CAGT. We further compare enhancer state assignments from SOM-VN in signals above a set threshold to enhancer state assignments from Predicting Enhancers from ATAC-seq Data (PEAS), a deep learning method that assigns enhancer chromatin states to peaks. We show that the precision-recall area under the curve for the assignment of enhancer states is comparable to PEAS.

CONCLUSIONS

Our work shows that the SOM-VN workflow can learn relationships between REs and chromatin accessibility signal shape, which is an important step toward the goal of assigning and comparing enhancer state across multiple experiments and phenotypic states.

Single-cell chromatin immunocleavage sequencing (scChIC-seq) to profile histone modification

Our method for analyzing histone modifications, scChIC-seq (single-cell chromatin immunocleavage sequencing), involves targeting of the micrococcal nuclease (MNase) to a histone mark of choice by tethering to a specific antibody. Cleaved target sites are then selectively PCR amplified. We show that scChIC-seq reliably detects H3K4me3 and H3K27me3 target sites in single human white blood cells. The resulting data are used for clustering of blood cell types.

New insights into hematopoietic differentiation landscapes from single-cell RNA sequencing

Single-cell transcriptomics has recently emerged as a powerful tool to analyze cellular heterogeneity, discover new cell types, and infer putative differentiation routes. The technique has been rapidly embraced by the hematopoiesis research community, and like other technologies before, single-cell molecular profiling is widely expected to make important contributions to our understanding of the hematopoietic hierarchy. Much of this new interpretation relies on inference of the transcriptomic landscape as a representation of existing cellular states and associated transitions among them. Here we review how this model allows, under certain assumptions, charting of time-resolved differentiation trajectories with unparalleled resolution and how the landscape of multipotent cells may be rather devoid of discrete structures, challenging our preconceptions about stem and progenitor cell types and their organization. Finally, we highlight how promising technological advances may convert static differentiation landscapes into a dynamic cell flux model and thus provide a more holistic understanding of normal hematopoiesis and blood disorders.

Integrated epigenomic analysis stratifies chromatin remodellers into distinct functional groups

Background

ATP-dependent chromatin remodelling complexes are responsible for establishing and maintaining the positions of nucleosomes. Chromatin remodellers are targeted to chromatin by transcription factors and non-coding RNA to remodel the chromatin into functional states. However, the influence of chromatin remodelling on shaping the functional epigenome is not well understood. Moreover, chromatin remodellers have not been extensively explored as a collective group across two-dimensional and three-dimensional epigenomic layers.

Results

Here, we have integrated the genome-wide binding profiles of eight chromatin remodellers together with DNA methylation, nucleosome positioning, histone modification and Hi-C chromosomal contacts to reveal that chromatin remodellers can be stratified into two functional groups. Group 1 (BRG1, SNF2H, CHD3 and CHD4) has a clear preference for binding at ‘actively marked’ chromatin and Group 2 (BRM, INO80, SNF2L and CHD1) for ‘repressively marked’ chromatin. We find that histone modifications and chromatin architectural features, but not DNA methylation, stratify the remodellers into these functional groups.

Conclusions

Our findings suggest that chromatin remodelling events are synchronous and that chromatin remodellers themselves should be considered simultaneously and not as individual entities in isolation or necessarily by structural similarity, as they are traditionally classified. Their coordinated function should be considered by preference for chromatin features in order to gain a more accurate and comprehensive picture of chromatin regulation.

Electronic supplementary material

The online version of this article (10.1186/s13072-019-0258-9) contains supplementary material, which is available to authorized users.