Antagonising Chromatin Remodelling Activities in the Regulation of Mammalian Ribosomal Transcription

Ribosomal transcription constitutes the major energy consuming process in cells and is regulated in response to proliferation, differentiation and metabolic conditions by several signalling pathways. These act on the transcription machinery but also on chromatin factors and ncRNA. The many ribosomal gene repeats are organised in a number of different chromatin states; active, poised, pseudosilent and repressed gene repeats. Some of these chromatin states are unique to the 47rRNA gene repeat and do not occur at other locations in the genome, such as the active state organised with the HMG protein UBF whereas other chromatin state are nucleosomal, harbouring both active and inactive histone marks. The number of repeats in a certain state varies on developmental stage and cell type; embryonic cells have more rRNA gene repeats organised in an open chromatin state, which is replaced by heterochromatin during differentiation, establishing different states depending on cell type. The 47S rRNA gene transcription is regulated in different ways depending on stimulus and chromatin state of individual gene repeats. This review will discuss the present knowledge about factors involved, such as chromatin remodelling factors NuRD, NoRC, CSB, B-WICH, histone modifying enzymes and histone chaperones, in altering gene expression and switching chromatin states in proliferation, differentiation, metabolic changes and stress responses.

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Universal annotation of the human genome through integration of over a thousand epigenomic datasets

10.1101/2020.11.17.387134 ◽

2020 ◽

Author(s):

Ha Vu ◽

Jason Ernst

Keyword(s):

Human Genome ◽

Large Scale ◽

Cell Types ◽

Chromatin State ◽

Open Chromatin ◽

Cell Type ◽

Chromatin States ◽

Modeling Approach ◽

Cell Type Specific ◽

Stack Model

AbstractGenome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative ‘stacked modeling’ approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges. In this paper, using a version of ChromHMM enhanced for large-scale applications, we applied the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, denoted the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we used in characterizing each state. Compared to cell-type-specific annotations, the full-stack annotation directly differentiates constitutive from cell-type-specific activity and is more predictive of locations of external genomic annotations. Overall, the full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing cell-type-specific annotations for studying the non-coding human genome.

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Universal annotation of the human genome through integration of over a thousand epigenomic datasets

Genome Biology ◽

10.1186/s13059-021-02572-z ◽

2022 ◽

Vol 23 (1) ◽

Author(s):

Ha Vu ◽

Jason Ernst

Keyword(s):

Human Genome ◽

Large Scale ◽

Cell Types ◽

Chromatin State ◽

Small Scale ◽

Open Chromatin ◽

Cell Type ◽

Chromatin States ◽

Modeling Approach ◽

Stack Model

Abstract Background Genome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative “stacked modeling” approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges. Results Using a version of ChromHMM enhanced for large-scale applications, we apply the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, with the learned model denoted as the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we use in characterizing each state. Compared to per-cell-type annotations, the full-stack annotations directly differentiate constitutive from cell type-specific activity and is more predictive of locations of external genomic annotations. Conclusions The full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing per-cell-type annotations for studying the non-coding human genome.

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Inferring time series chromatin states for promoter-enhancer pairs based on Hi-C data

BMC Genomics ◽

10.1186/s12864-021-07373-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Henriette Miko ◽

Yunjiang Qiu ◽

Bjoern Gaertner ◽

Maike Sander ◽

Uwe Ohler

Keyword(s):

Time Series ◽

Histone Modifications ◽

Gene Activation ◽

Expectation Maximization Algorithm ◽

Chromatin State ◽

Open Chromatin ◽

Multiple Time ◽

Enhancer Activity ◽

Chromatin States ◽

Multiple Time Points

Abstract Background Co-localized combinations of histone modifications (“chromatin states”) have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points (“chromatin state trajectories”) have previously been analyzed at promoter and enhancers separately. With the advent of time series Hi-C data it is now possible to connect promoters and enhancers and to analyze chromatin state trajectories at promoter-enhancer pairs. Results We present TimelessFlex, a framework for investigating chromatin state trajectories at promoters and enhancers and at promoter-enhancer pairs based on Hi-C information. TimelessFlex extends our previous approach Timeless, a Bayesian network for clustering multiple histone modification data sets at promoter and enhancer feature regions. We utilize time series ATAC-seq data measuring open chromatin to define promoters and enhancer candidates. We developed an expectation-maximization algorithm to assign promoters and enhancers to each other based on Hi-C interactions and jointly cluster their feature regions into paired chromatin state trajectories. We find jointly clustered promoter-enhancer pairs showing the same activation patterns on both sides but with a stronger trend at the enhancer side. While the promoter side remains accessible across the time series, the enhancer side becomes dynamically more open towards the gene activation time point. Promoter cluster patterns show strong correlations with gene expression signals, whereas Hi-C signals get only slightly stronger towards activation. The code of the framework is available at https://github.com/henriettemiko/TimelessFlex. Conclusions TimelessFlex clusters time series histone modifications at promoter-enhancer pairs based on Hi-C and it can identify distinct chromatin states at promoter and enhancer feature regions and their changes over time.

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Prediction of condition-specific regulatory maps in Arabidopsis using integrated genomic data

10.1101/565119 ◽

2019 ◽

Author(s):

Qi Song ◽

Jiyoung Lee ◽

Shamima Akter ◽

Ruth Grene ◽

Song Li

Keyword(s):

Stress Responses ◽

Abiotic Stresses ◽

Individual Cell ◽

Genomic Data ◽

Cell Types ◽

Root Cell ◽

Specific Gene ◽

Open Chromatin ◽

Cell Type ◽

Cell Type Specific

AbstractRecent advances in genomic technologies have generated large-scale protein-DNA interaction data and open chromatic regions for multiple plant species. To predict condition specific gene regulatory networks using these data, we developed the Condition Specific Regulatory network inference engine (ConSReg), which combines heterogeneous genomic data using sparse linear model followed by feature selection and stability selection to select key regulatory genes. Using Arabidopsis as a model system, we constructed maps of gene regulation under more than 50 experimental conditions including abiotic stresses, cell type-specific expression, and stress responses in individual cell types. Our results show that ConSReg accurately predicted gene expressions (average auROC of 0.84) across multiple testing datasets. We found that, (1) including open chromatin information from ATAC-seq data significantly improves the performance of ConSReg across all tested datasets; (2) choice of negative training samples and length of promoter regions are two key factors that affect model performance. We applied ConSReg to Arabidopsis single cell RNA-seq data of two root cell types (endodermis and cortex) and identified five regulators in two root cell types. Four out of the five regulators have additional experimental evidence to support their roles in regulating gene expression in Arabidopsis roots. By comparing regulatory maps in abiotic stress responses and cell type-specific experiments, we revealed that transcription factors that regulate tissue levels abiotic stresses tend to also regulate stress responses in individual cell types in plants.

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Multi-scale annotations of chromatin states in 127 human cell-types

10.1101/2020.12.22.424078 ◽

2020 ◽

Author(s):

Yan Kai ◽

Stephanos Tsoucas ◽

Shengbao Suo ◽

Guo-Cheng Yuan

Keyword(s):

Human Cell ◽

Biological Function ◽

Cell Types ◽

Chromatin State ◽

Cell Type ◽

Chromatin States ◽

Multi Scale ◽

Public Data ◽

Domain State ◽

Cell Type Specific

AbstractGenome-wide profiling of chromatin states has been widely used to characterize the biological function of non-coding genomic sequences in a cell-type specific manner. However, the systematic, comprehensive annotations of chromatin states from experimental data are challenging and require not just extensive biological knowledge but also sophisticated computational modeling. Previously we developed a hierarchical hidden Markov model, named diHMM, to systematically annotate chromatin states at multiple scales based on the combination of histone mark and chromatin regulator binding profiles. Here, we have improved the method by optimizing computational efficiency and using an ensemble-clustering approach to achieve a unified annotation by integrating information from cell-type-specific models. We then applied this improved method to generate a unified multi-scale chromatin state map in 127 human cell types, based on public data generated by the Epigenome Roadmap and ENCODE consortia. We found cell types with similar origin are typically associated with similar chromatin states, but cultured cell lines have distinct structures than primary cells. The contribution of enhancer elements to gene regulation is mediated by the broader context of domain-state organization. Distinct domain-state patterns are associated with various 3D chromatin structures. As such, we have demonstrated the utility of the multi-scale chromatin state map in characterizing the biological function of the human genome.

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CENP-B creates alternative epigenetic chromatin states permissive for CENP-A or heterochromatin assembly

Journal of Cell Science ◽

10.1242/jcs.243303 ◽

2020 ◽

Vol 133 (15) ◽

pp. jcs243303 ◽

Cited By ~ 6

Author(s):

Koichiro Otake ◽

Jun-ichirou Ohzeki ◽

Nobuaki Shono ◽

Kazuto Kugou ◽

Koei Okazaki ◽

...

Keyword(s):

De Novo ◽

Artificial Chromosome ◽

Human Artificial Chromosome ◽

Open Chromatin ◽

Histone Chaperones ◽

Satellite Dnas ◽

Chromatin States ◽

Heterochromatin Formation ◽

Acidic Domain ◽

Alphoid Dna

ABSTRACTCENP-B binds to CENP-B boxes on centromeric satellite DNAs (known as alphoid DNA in humans). CENP-B maintains kinetochore function through interactions with CENP-A nucleosomes and CENP-C. CENP-B binding to transfected alphoid DNA can induce de novo CENP-A assembly, functional centromere and kinetochore formation, and subsequent human artificial chromosome (HAC) formation. Furthermore, CENP-B also facilitates H3K9 (histone H3 lysine 9) trimethylation on alphoid DNA, mediated by Suv39h1, at ectopic alphoid DNA integration sites. Excessive heterochromatin invasion into centromere chromatin suppresses CENP-A assembly. It is unclear how CENP-B controls such different chromatin states. Here, we show that the CENP-B acidic domain recruits histone chaperones and many chromatin modifiers, including the H3K36 methylase ASH1L, as well as the heterochromatin components Suv39h1 and HP1 (HP1α, β and γ, also known as CBX5, CBX1 and CBX3, respectively). ASH1L facilitates the formation of open chromatin competent for CENP-A assembly on alphoid DNA. These results indicate that CENP-B is a nexus for histone modifiers that alternatively promote or suppress CENP-A assembly by mutually exclusive mechanisms. Besides the DNA-binding domain, the CENP-B acidic domain also facilitates CENP-A assembly de novo on transfected alphoid DNA. CENP-B therefore balances CENP-A assembly and heterochromatin formation on satellite DNA.

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Profiling of accessible chromatin regions across multiple plant species and cell types reveals common gene regulatory principles and new control modules

10.1101/167932 ◽

2017 ◽

Cited By ~ 1

Author(s):

Kelsey A. Maher ◽

Marko Bajic ◽

Kaisa Kajala ◽

Mauricio Reynoso ◽

Germain Pauluzzi ◽

...

Keyword(s):

Hair Cell ◽

Plant Species ◽

Stress Responses ◽

Binding Sites ◽

Cell Types ◽

Regulatory Elements ◽

Open Chromatin ◽

Cell Type ◽

Cell Type Specific ◽

Accessible Chromatin

ABSTRACTThe transcriptional regulatory structure of plant genomes remains poorly defined relative to animals. It is unclear how many cis-regulatory elements exist, where these elements lie relative to promoters, and how these features are conserved across plant species. We employed the Assay for Transposase-Accessible Chromatin (ATAC-seq) in four plant species (Arabidopsis thaliana, Medicago truncatula, Solanum lycopersicum, and Oryza sativa) to delineate open chromatin regions and transcription factor (TF) binding sites across each genome. Despite 10-fold variation in intergenic space among species, the majority of open chromatin regions lie within 3 kb upstream of a transcription start site in all species. We find a common set of four TFs that appear to regulate conserved gene sets in the root tips of all four species, suggesting that TF-gene networks are generally conserved. Comparative ATAC-seq profiling of Arabidopsis root hair and non-hair cell types revealed extensive similarity as well as many cell type-specific differences. Analyzing TF binding sites in differentially accessible regions identified a MYB-driven regulatory module unique to the hair cell, which appears to control both cell fate regulators and abiotic stress responses. Our analyses revealed common regulatory principles among species and shed light on the mechanisms producing cell type-specific transcriptomes during development.

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Single-cell epigenomics reveals mechanisms of human cortical development

Nature ◽

10.1038/s41586-021-03209-8 ◽

2021 ◽

Vol 598 (7879) ◽

pp. 205-213

Author(s):

Ryan S. Ziffra ◽

Chang N. Kim ◽

Jayden M. Ross ◽

Amy Wilfert ◽

Tychele N. Turner ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Cortical Development ◽

Chromatin Accessibility ◽

Chromatin State ◽

Open Chromatin ◽

Cell Fate Specification ◽

Cell Type ◽

Fate Specification ◽

Cell Type Specific

AbstractDuring mammalian development, differences in chromatin state coincide with cellular differentiation and reflect changes in the gene regulatory landscape1. In the developing brain, cell fate specification and topographic identity are important for defining cell identity2 and confer selective vulnerabilities to neurodevelopmental disorders3. Here, to identify cell-type-specific chromatin accessibility patterns in the developing human brain, we used a single-cell assay for transposase accessibility by sequencing (scATAC-seq) in primary tissue samples from the human forebrain. We applied unbiased analyses to identify genomic loci that undergo extensive cell-type- and brain-region-specific changes in accessibility during neurogenesis, and an integrative analysis to predict cell-type-specific candidate regulatory elements. We found that cerebral organoids recapitulate most putative cell-type-specific enhancer accessibility patterns but lack many cell-type-specific open chromatin regions that are found in vivo. Systematic comparison of chromatin accessibility across brain regions revealed unexpected diversity among neural progenitor cells in the cerebral cortex and implicated retinoic acid signalling in the specification of neuronal lineage identity in the prefrontal cortex. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development.

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Non-Coding, RNAPII-Dependent Transcription at the Promoters of rRNA Genes Regulates Their Chromatin State in S. cerevisiae

Non-Coding RNA ◽

10.3390/ncrna7030041 ◽

2021 ◽

Vol 7 (3) ◽

pp. 41

Author(s):

Emma Lesage ◽

Jorge Perez-Fernandez ◽

Sophie Queille ◽

Christophe Dez ◽

Olivier Gadal ◽

...

Keyword(s):

Rna Polymerase ◽

Rna Polymerase Ii ◽

Tandem Repeats ◽

Chromatin State ◽

Rrna Genes ◽

Rdna Genes ◽

Regulatory Pathways ◽

Chromatin States ◽

Non Coding Rnas ◽

Pervasive Transcription

Pervasive transcription is widespread in eukaryotes, generating large families of non-coding RNAs. Such pervasive transcription is a key player in the regulatory pathways controlling chromatin state and gene expression. Here, we describe long non-coding RNAs generated from the ribosomal RNA gene promoter called UPStream-initiating transcripts (UPS). In yeast, rDNA genes are organized in tandem repeats in at least two different chromatin states, either transcribed and largely depleted of nucleosomes (open) or assembled in regular arrays of nucleosomes (closed). The production of UPS transcripts by RNA Polymerase II from endogenous rDNA genes was initially documented in mutants defective for rRNA production by RNA polymerase I. We show here that UPS are produced in wild-type cells from closed rDNA genes but are hidden within the enormous production of rRNA. UPS levels are increased when rDNA chromatin states are modified at high temperatures or entering/leaving quiescence. We discuss their role in the regulation of rDNA chromatin states and rRNA production.

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Annotation of chromatin states in 66 complete mouse epigenomes during development

Communications Biology ◽

10.1038/s42003-021-01756-4 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Arjan van der Velde ◽

Kaili Fan ◽

Junko Tsuji ◽

Jill E. Moore ◽

Michael J. Purcaro ◽

...

Keyword(s):

Target Genes ◽

Cell Types ◽

Developmental Trajectory ◽

Phase Iii ◽

Chromatin State ◽

Mammalian Development ◽

Chromatin States ◽

Transcription Start Sites ◽

Repressive Mark ◽

Distinct Cell

AbstractThe morphologically and functionally distinct cell types of a multicellular organism are maintained by their unique epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 11.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by polycomb repressive complex proteins, and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.

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