Chromatin Features Research Articles

Distinct structural and functional heterochromatin partitioning of lamin B1 and lamin B2 revealed using genome-wide nicking enzyme epitope targeted DNA sequencing.

Gene expression is regulated by chromatin DNA methylation and other features, including histone post-translational modifications (PTMs), chromatin remodelers and transcription factor occupancy. A complete understanding of gene regulation will require the mapping of these chromatin features in small cell number samples. Here we describe a novel genome-wide chromatin profiling technology, named as Nicking Enzyme Epitope targeted DNA sequencing (NEED-seq). NEED-seq offers antibody-targeted controlled nicking by Nt.CviPII-pGL fusion to study specific protein-DNA complexes in formaldehyde fixed cells, allowing for both visual and genomic resolution of epitope bound chromatin. When applied to nuclei, NEED-seq yielded genome-wide profile of chromatin-associated proteins and histone PTMs. Additionally, NEED-seq of lamin B1 and B2 demonstrated their association with heterochromatin. Lamin B1- and B2-associated domains (LAD) segregated to three different states, and states with stronger LAD correlated with heterochromatic marks. Hi-C analysis displayed A and B compartment with equal lamin B1 and B2 distribution, although methylated DNA remained high in B compartment. LAD clustering with Hi-C resulted in subcompartments, with lamin B1 and B2 partitioning to facultative and constitutive heterochromatin, respectively, and were associated with neuronal development. Thus, lamin B1 and B2 show structural and functional partitioning in mammalian nucleus.

Cryopreservation of stallion sperm does not change sperm chromatin and RNAs characteristics

Cryopreservation of stallion sperm does not change sperm chromatin and RNAs characteristics

A hitchhiker's guide to single-cell epigenomics: Methods and applications for cancer research.

Genetic mutations are well known to influence tumorigenesis, tumor progression, treatment response and relapse, but the role of epigenetic variation in cancer progression is still largely unexplored. The lack of epigenetic understanding in cancer evolution is in part due to the limited availability of methods to examine such a heterogeneous disease. However, in the last decade the development of several single-cell methods to profile diverse chromatin features (chromatin accessibility, histone modifications, DNA methylation, etc.) has propelled the study of cancer epigenomics. In this review, we detail the current landscape of single-omic and multi-omic single-cell methods with a particular focus on the examination of histone modifications. Furthermore, we provide recommendations on both the application of these methods to cancer research and how to perform initial computational analyses. Together, this review serves as a referential framework for incorporating single-cell methods as an important tool for tumor biology.

Chromatin loops gather targets of upstream regulators together for efficient gene transcription regulation during vernalization in wheat

BackgroundPlants respond to environmental stimuli by altering gene transcription that is highly related with chromatin status, including histone modification, chromatin accessibility, and three-dimensional chromatin interaction. Vernalization is essential for the transition to reproductive growth for winter wheat. How wheat reshapes its chromatin features, especially chromatin interaction during vernalization, remains unknown.ResultsCombinatory analysis of gene transcription and histone modifications in winter wheat under different vernalization conditions identifies 17,669 differential expressed genes and thousands of differentially enriched peaks of H3K4me3, H3K27me3, and H3K9ac. We find dynamic gene expression across the vernalization process is highly associated with H3K4me3. More importantly, the dynamic H3K4me3- and H3K9ac-associated chromatin-chromatin interactions demonstrate that vernalization leads to increased chromatin interactions and gene activation. Remarkably, spatially distant targets of master regulators like VRN1 and VRT2 are gathered together by chromatin loops to achieve efficient transcription regulation, which is designated as a “shepherd” model. Furthermore, by integrating gene regulatory network for vernalization and natural variation of flowering time, TaZNF10 is identified as a negative regulator for vernalization-related flowering time in wheat.ConclusionsWe reveal dynamic gene transcription network during vernalization and find that the spatially distant genes can be recruited together via chromatin loops associated with active histone mark thus to be more efficiently found and bound by upstream regulator. It provides new insights into understanding vernalization and response to environmental stimuli in wheat and other plants.

Genome-wide profiling and functional study of short N-terminal H2B variants in Arabidopsis.

Nucleosomes harboring specific histone variants show distinct chromatin localization patterns and regulatory functions, thereby playing crucial roles in epigenetic regulation. Compared to the well-understood variants of H2A and H3, the study about H2B variants is emerging. Deciphering the roles and regulatory mechanisms of H2B variants in plants will provide more knowledges about epigenetic regulations in plant biology. Using the model plant Arabidopsis thaliana as the research subject, we systematically analyzed histone H2B variants, four short N-terminal histone H2B variants (snH2Bs) were identified. The genomic distribution characteristics of these snH2Bs, their impact on plant growth, and the potential regulatory mechanisms were studied. By integrating whole-genome chromatin immunoprecipitation sequencing (ChIP-seq) and fluorescence microscopy localization analysis, the distribution of snH2Bs across the genome was identified. Single, double, and triple knock-out mutants were constructed using CRISPR-Cas9 to further explore the functions of snH2Bs in the growth process of Arabidopsis thaliana, the possible mechanisms were also discussed. These snH2B variants are preferentially expressed in reproductive tissues and are detected in the nuclei of pollen grains. Further genome-wide profiling indicates that the snH2Bs distribute at active chromatin regions and are positively correlated with gene expression. By creating knock-out single, double, and triple mutants for these snH2Bs, we demonstrate that H2B.5 influences vegetative to reproductive transition. We also show that H2B.5 is required for proper accumulation of H3 lysine 9 acetylation and H2B mono-ubiquitination. Overall, our study not only provide insights into the functions and chromatin characteristics of plant snH2Bs, but also supplies examples that illustrate the interplay between histone variants and histone modification. These findings contribute to the understanding of the fundamental principles of epigenetic regulation in eukaryotes and also highlight potential targets for crop improvement.

Evaluating the Impact of Rapid Thermoresistance (RTT) on Membrane and Chromatin Features in Post-Thawed Bovine Semen

This work aims to evaluate the effects of rapid thermoresistance on the morphofunctional aspects of membranes using flow cytometry, as well as the quality of sperm chromatin using the Toluidine Blue technique, both before and after the thermoresistance test.Six sets of frozen semen from ten bulls were used. The samples were thawed in a water bath at 36ºC and separated into two aliquots. The first aliquot, control group (C), was kept in a test tube previously heated to 36ºC with subsequent evaluations using microscopy, cytometry, and chromatin analyses. The second aliquot, experimental group (E), underwent the rapid thermoresistance test (RTT) in a water bath preheated at 46ºC for 30 minutes with subsequent evaluations using microscopy, cytometry, and chromatin analyses. For statistical analysis, the paired T test, significance (P<0.05), was used.

High-throughput capture of transcription factor-driven epigenome dynamics using PHILO ChIP-seq.

Assessing the dynamics of chromatin features and transcription factor (TF) binding at scale remains a significant challenge in plants. Here, we present PHILO (Plant HIgh-throughput LOw input) ChIP-seq, a high-throughput ChIP-seq platform that enables the cost-effective and extensive capture of TF binding and genome-wide distributions of histone modifications. The PHILO ChIP-seq pipeline is adaptable to many plant species, requires very little starting material (1mg), and provides the option to use MNase (micrococcal nuclease) for chromatin fragmentation. By employing H3K9ac PHILO ChIP-seq on eight Arabidopsis thaliana jasmonic acid (JA) pathway mutants, with the simultaneous processing of over 100 samples, we not only recapitulated but also expanded the current understanding of the intricate interplay between the master TFs MYC2/3/4 and various chromatin regulators. Additionally, our analyses brought to light previously unknown histone acetylation patterns within the regulatory regions of MYC2 target genes in Arabidopsis, which is also conserved in tomato (Solanum lycopersicum). In summary, our PHILO ChIP-seq platform demonstrates its high effectiveness in investigating TF binding and chromatin dynamics on a large scale in plants, paving the way for the cost-efficient realization of complex experimental setups.

LOGOWheat: deep learning-based prediction of regulatory effects for noncoding variants in wheats.

Identifying the regulatory effects of noncoding variants presents a significant challenge. Recently, the accumulation of epigenomic profiling data in wheat has provided an opportunity to model the functional impacts of these variants. In this study, we introduce Language of Genome for Wheat (LOGOWheat), a deep learning-based tool designed to predict the regulatory effects of noncoding variants in wheat. LOGOWheat initially employs a self-attention-based, contextualized pretrained language model to acquire bidirectional representations of the unlabeled wheat reference genome. Epigenomic profiling data are also collected and utilized to fine-tune the model, enabling it to discern the regulatory code inherent in genomic sequences. The test results suggest that LOGOWheat is highly effective in predicting multiple chromatin features, achieving an average area under the receiver operating characteristic (AUROC) of 0.8531 and an average area under the precision-recall curve (AUPRC) of 0.7633. Two case studies illustrate and demonstrate the main functions provided by LOGOWheat: assigning scores and prioritizing causal variants within a given variant set and constructing a saturated mutagenesis map in silico to discover high-impact sites or functional motifs in a given sequence. Finally, we propose the concept of extracting potential functional variations from the wheat population by integrating evolutionary conservation information. LOGOWheat is available at http://logowheat.cn/.

Chromatin architecture mapping by multiplex proximity tagging.

Chromatin plays a pivotal role in genome expression, maintenance, and replication. To better understand chromatin organization, we developed a novel proximity-tagging method which assigns unique DNA barcodes to molecules that associate in 3D space. Using this method - Proximity Copy Paste (PCP) - we mapped the connectivity of individual nucleosomes in Saccharomyces cerevisiae . We show that chromatin is predominantly organized into regularly spaced nucleosome arrays whose properties differ according to transcriptional activity. Additionally, by mapping long-range, multi-way interactions we provide evidence that metaphase chromosomes are compacted by arrayed cohesin hubs. Using single-molecule nuclease footprinting data we define distinct chromatin states within a mixed population to show that noncanonical nucleosomes are a stable feature of chromatin. PCP is a versatile method allowing the connectivity of individual molecules to be mapped at high-resolution.

Studying the structure and function of nucleosomes by atomic force microscopy

Chromatin is an epigenetic platform for the implementation of DNA-dependent processes. The nucleosome, as the basic level of chromatin compaction, largely determines its properties and structure. When studying the structure and functions of nucleosomes, physicochemical tools are actively used, such as magnetic and optical “tweezers,” “DNA curtains,” nuclear magnetic resonance, X-ray diffraction analysis and cryoelectron microscopy, as well as optical methods based on FRET. Despite the fact that these approaches make it possible to determine a wide range of structural and functional characteristics of chromatin and nucleosomes with high spatial and temporal resolution, atomic-force microscopy (AFM) complements the capabilities of these methods. This review presents the results of structural studies of nucleosomes in view of the development of the AFM method. The capabilities of AFM are considered in the context of the use of other physicochemical approaches.

Distinct H3K9me3 heterochromatin maintenance dynamics govern different gene programmes and repeats in pluripotent cells.

H3K9me3 heterochromatin, established by lysine methyltransferases (KMTs) and compacted by heterochromatin protein 1 (HP1) isoforms, represses alternative lineage genes and DNA repeats. Our understanding of H3K9me3 heterochromatin stability is presently limited to individual domains and DNA repeats. Here we engineered Suv39h2-knockout mouse embryonic stem cells to degrade remaining two H3K9me3 KMTs within 1 hour and found that both passive dilution and active removal contribute to H3K9me3 decay within 12-24 hours. We discovered four different H3K9me3 decay rates across the genome and chromatin features and transcription factor binding patterns that predict the stability classes. A 'binary switch' governs heterochromatin compaction, with HP1 rapidly dissociating from heterochromatin upon KMT depletion and a particular threshold level of HP1 limiting pioneer factor binding, chromatin opening and exit from pluripotency within 12 h. Unexpectedly, receding H3K9me3 domains unearth residual HP1β peaks enriched with heterochromatin-inducing proteins. Our findings reveal distinct H3K9me3 heterochromatin maintenance dynamics governing gene networks and repeats that together safeguard pluripotency.

Global chromatin reorganization and regulation of genes with specific evolutionary ages during differentiation and cancer.

Cancer cells are highly plastic, allowing them to adapt to changing conditions. Genes related to basic cellular processes evolved in ancient species, while more specialized genes appeared later with multicellularity (metazoan genes) or even after mammals evolved. Transcriptomic analyses have shown that ancient genes are up-regulated in cancer, while metazoan-origin genes are inactivated. Despite the importance of these observations, the underlying mechanisms remain unexplored. Here, we study local and global epigenomic mechanisms that may regulate genes from specific evolutionary periods. Using evolutionary gene age data, we characterize the epigenomic landscape, gene expression regulation, and chromatin organization in three cell types: human embryonic stem cells, normal B-cells, and primary cells from Chronic Lymphocytic Leukemia, a B-cell malignancy. We identify topological changes in chromatin organization during differentiation observing patterns in Polycomb repression and RNA Polymerase II pausing, which are reversed during oncogenesis. Beyond the non-random organization of genes and chromatin features in the 3D epigenome, we suggest that these patterns lead to preferential interactions among ancient, intermediate, and recent genes, mediated by RNA Polymerase II, Polycomb, and the lamina, respectively. Our findings shed light on gene regulation according to evolutionary age and suggest this organization changes across differentiation and oncogenesis.

Predicting genome-wide tissue-specific enhancers via combinatorial transcription factor genomic occupancy analysis.

Enhancers are non-coding cis-regulatory elements crucial for transcriptional regulation. Mutations in enhancers can disrupt gene regulation, leading to disease phenotypes. Identifying enhancers and their tissue-specific activity is challenging due to their lack of stereotyped sequences. This study presents a sequence-based computational model that uses combinatorial transcription factor (TF) genomic occupancy to predict tissue-specific enhancers. Trained on diverse datasets, including ENCODE and Vista enhancer browser data, the model predicted 25 000 forebrain-specific cis-regulatory modules (CRMs) in the human genome. Validation using biochemical features, disease-associated SNPs, and in vivo zebrafish analysis confirmed its effectiveness. This model aids in predicting enhancers lacking well-characterized chromatin features, complementing experimental approaches in tissue-specific enhancer discovery.

The chromatin tapestry as a framework for neurodevelopment.

The neuronal nucleus houses a meticulously organized genome. Within this structure, genetic material is not simply compacted but arranged into a precise and functional 3D chromatin landscape essential for cellular regulation. This mini-review highlights the importance of this chromatin landscape in healthy neurodevelopment, as well as the diseases that occur with aberrant chromatin architecture. We discuss insights into the fundamental mechanistic relationship between histone modifications, DNA methylation, and genome organization. We then discuss findings that reveal how these epigenetic features change throughout normal neurodevelopment. Finally, we highlight single-gene neurodevelopmental disorders that illustrate the interdependence of epigenetic features, showing how disruptions in DNA methylation or genome architecture can ripple across the entire epigenome. As such, we emphasize the importance of measuring multiple chromatin architectural aspects, as the disruption of one mechanism can likely impact others in the intricate epigenetic network. This mini-review underscores the vast gaps in our understanding of chromatin structure in neurodevelopmental diseases and the substantial research needed to understand the interplay between chromatin features and neurodevelopment.

Integration of scHi-C and scRNA-seq data defines distinct 3D-regulated and biological-context dependent cell subpopulations

An integration of 3D chromatin structure and gene expression at single-cell resolution has yet been demonstrated. Here, we develop a computational method, a multiomic data integration (MUDI) algorithm, which integrates scHi-C and scRNA-seq data to precisely define the 3D-regulated and biological-context dependent cell subpopulations or topologically integrated subpopulations (TISPs). We demonstrate its algorithmic utility on the publicly available and newly generated scHi-C and scRNA-seq data. We then test and apply MUDI in a breast cancer cell model system to demonstrate its biological-context dependent utility. We find the newly defined topologically conserved associating domain (CAD) is the characteristic single-cell 3D chromatin structure and better characterizes chromatin domains in single-cell resolution. We further identify 20 TISPs uniquely characterizing 3D-regulated breast cancer cellular states. We reveal two of TISPs are remarkably resemble to high cycling breast cancer persister cells and chromatin modifying enzymes might be functional regulators to drive the alteration of the 3D chromatin structures. Our comprehensive integration of scHi-C and scRNA-seq data in cancer cells at single-cell resolution provides mechanistic insights into 3D-regulated heterogeneity of developing drug-tolerant cancer cells.

Multiplexed spatial mapping of chromatin features, transcriptome, and proteins in tissues.

The phenotypic and functional states of a cell are modulated by a complex interactive molecular hierarchy of multiple omics layers, involving the genome, epigenome, transcriptome, proteome, and metabolome. Spatial omics approaches have enabled the capture of information from different molecular layers directly in the tissue context. However, current technologies are limited to map one to two modalities at the same time, providing an incomplete representation of cellular identity. Such data is inadequate to fully understand complex biological systems and their underlying regulatory mechanisms. Here we present spatial-Mux-seq, a multi-modal spatial technology that allows simultaneous profiling of five different modalities, including genome-wide profiles of two histone modifications and open chromatin, whole transcriptome, and a panel of proteins at tissue scale and cellular level in a spatially resolved manner. We applied this technology to generate multi-modal tissue maps in mouse embryos and mouse brains, which discriminated more cell types and states than unimodal data. We investigated the spatiotemporal relationship between histone modifications, chromatin accessibility, gene and protein expression in neuron differentiation revealing the relationship between tissue organization, function, and gene regulatory networks. We were able to identify a radial glia spatial niche and revealed spatially changing gradient of epigenetic signals in this region. Moreover, we revealed previously unappreciated involvement of repressive histone marks in the mouse hippocampus. Collectively, the spatial multi-omics approach heralds a new era for characterizing tissue and cellular heterogeneity that single modality studies alone could not reveal.

Distinct H3K9me3 heterochromatin maintenance dynamics govern different gene programs and repeats in pluripotent cells.

H3K9me3-heterochromatin, established by lysine methyltransferases (KMTs) and compacted by HP1 isoforms, represses alternative lineage genes and DNA repeats. Our understanding of H3K9me3-heterochromatin stability is presently limited to individual domains and DNA repeats. We engineered Suv39h2 KO mouse embryonic stem cells to degrade remaining two H3K9me3-KMTs within one hour and found that both passive dilution and active removal contribute to H3K9me3 decay within 12-24 hours. We discovered four different H3K9me3 decay rates across the genome and chromatin features and transcription factor binding patterns that predict the stability classes. A "binary switch" governs heterochromatin compaction, with HP1 rapidly dissociating from heterochromatin upon KMTs' depletion and a particular threshold level of HP1 limiting pioneer factor binding, chromatin opening, and exit from pluripotency within 12 hr. Unexpectedly, receding H3K9me3 domains unearth residual HP1β peaks enriched with heterochromatin-inducing proteins. Our findings reveal distinct H3K9me3-heterochromatin maintenance dynamics governing gene networks and repeats that together safeguard pluripotency.

H3.3K122A results in a neomorphic phenotype in mouse embryonic stem cells.

The histone variant H3.3 acts in coordination with histone posttranslational modifications and other chromatin features to facilitate appropriate transcription. Canonical histone H3 and histone variant H3.3 are post-translationally modified with the genomic distribution of these marks denoting different features and with more recent evidence suggesting that these modifications may influence transcription. While the majority of posttranslational modifications occur on histone tails, there are defined modifications within the globular domain, such as acetylation of H3K122/H3.3K122. To understand the function of the residue H3.3K122 in transcriptional regulation, we attempted to generate H3.3K122A mouse embryonic stem (mES) cells but were unsuccessful. Through multi-omic profiling of mutant cell lines harboring two or three of four H3.3 targeted alleles, we have uncovered that H3.3K122A is neomorphic and results in lethality. This is surprising as prior studies demonstrate H3.3-null mES cells are viable and pluripotent, albeit with reduced differentiation capacity. Together, these studies have uncovered a novel dependence of a globular domain residue of H3.3 for viability and broadened our understanding of how histone variants contribute to transcription regulation and pluripotency in mES cells.

Artificial Intelligence in Chromatin Analysis: A Random Forest Model Enhanced by Fractal and Wavelet Features

In this study, we propose an innovative concept that applies an AI-based approach using the random forest algorithm integrated with fractal and discrete wavelet transform features of nuclear chromatin. This strategy could be employed to identify subtle structural changes in cells that are in the early stages of programmed cell death. The code for the random forest model is developed using the Scikit-learn library in Python and includes hyperparameter tuning and cross-validation to optimize performance. The suggested input data for the model are chromatin fractal dimension, fractal lacunarity, and three wavelet coefficient energies obtained through high-pass and low-pass filtering. Additionally, the code contains several methods to assess the performance metrics of the model. This model holds potential as a starting point for designing simple yet advanced AI biosensors capable of detecting apoptotic cells that are not discernible through conventional microscopy techniques.

Comprehensive Transcriptome Analysis Expands lncRNA Functional Profiles in Breast Cancer.

Breast cancer is a heterogeneous disease that arises as a multi-stage process involving multiple cell types. Patients diagnosed with the same clinical stage and pathological classification may have different prognoses and therapeutic responses due to alterations in molecular genetics. As an essential marker for the molecular subtyping of breast cancer, long non-coding RNAs (lncRNAs) play a crucial role in gene expression regulation, cell differentiation, and the maintenance of genomic stability. Here, we developed a modular framework for lncRNA identification and applied it to a breast cancer cohort to identify novel lncRNAs not previously annotated. To investigate the potential biological function, regulatory mechanisms, and clinical relevance of the novel lncRNAs, we elucidated the genomic and chromatin features of these lncRNAs, along with the associated protein-coding genes and putative enhancers involved in the breast cancer regulatory networks. Furthermore, we uncovered that the expression patterns of novel and annotated lncRNAs identified in breast cancer were related to the hormone response in the PAM50 subtyping criterion, as well as the immune response and progression states of breast cancer across different immune cells and immune checkpoint genes. Collectively, the comprehensive identification and functional analysis of lncRNAs revealed that these lncRNAs play an essential role in breast cancer by altering gene expression and participating in the regulatory networks, contributing to a better insight into breast cancer heterogeneity and potential avenues for therapeutic intervention.