Histone modification levels are predictive for gene expression. Proc Natl Acad Sci U S A. 2010;107:2926-2931. [PMID: 20133639 DOI: 10.1073/pnas.0909344107]

A wider field of view to predict expression

A sequence-to-expression machine learning model achieves higher accuracy by incorporating information about potential long-range interactions.

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation

Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understanding gene expression patterns. While there are many attempts to develop computational promoter and enhancer identification methods, reliable tools to analyze long genomic sequences are still lacking. Prediction methods often perform poorly on the genome-wide scale because the number of negatives is much higher than that in the training sets. To address this issue, we propose a dynamic negative set updating scheme with a two-model approach, using one model for scanning the genome and the other one for testing candidate positions. The developed method achieves good genome-level performance and maintains robust performance when applied to other vertebrate species, without re-training. Moreover, the unannotated predicted regulatory regions made on the human genome are enriched for disease-associated variants, suggesting them to be potentially true regulatory elements rather than false positives. We validated high scoring "false positive" predictions using reporter assay and all tested candidates were successfully validated, demonstrating the ability of our method to discover novel human regulatory regions.

Differential contribution to gene expression prediction of histone modifications at enhancers or promoters

The ChIP-seq signal of histone modifications at promoters is a good predictor of gene expression in different cellular contexts, but whether this is also true at enhancers is not clear. To address this issue, we develop quantitative models to characterize the relationship of gene expression with histone modifications at enhancers or promoters. We use embryonic stem cells (ESCs), which contain a full spectrum of active and repressed (poised) enhancers, to train predictive models. As many poised enhancers in ESCs switch towards an active state during differentiation, predictive models can also be trained on poised enhancers throughout differentiation and in development. Remarkably, we determine that histone modifications at enhancers, as well as promoters, are predictive of gene expression in ESCs and throughout differentiation and development. Importantly, we demonstrate that their contribution to the predictive models varies depending on their location in enhancers or promoters. Moreover, we use a local regression (LOESS) to normalize sequencing data from different sources, which allows us to apply predictive models trained in a specific cellular context to a different one. We conclude that the relationship between gene expression and histone modifications at enhancers is universal and different from promoters. Our study provides new insight into how histone modifications relate to gene expression based on their location in enhancers or promoters.

Gene expression can be properly predicted by the ChIP-seq signal of histone modifications at promoters, but whether this is also true at enhancers is unclear. In this study we develop predictive models of gene expression that demonstrate the predictive power of histone modifications at enhancers in the context of mouse embryonic stem cells, during differentiation, and in animal development. Moreover, by assessing the contribution of each histone modification, we found that enhancer predictive models and promoter predictive models have different histone modification requirement. Therefore, different histone modifications relate better to enhancer or promoter function(s). Finally, by applying predictive models trained in a specific cellular context to a different one, we concluded that the relationship between gene expression and histone modifications at enhancers is universal.

Differential ATAC-seq and ChIP-seq peak detection using ROTS

Changes in cellular chromatin states fine-tune transcriptional output and ultimately lead to phenotypic changes. Here we propose a novel application of our reproducibility-optimized test statistics (ROTS) to detect differential chromatin states (ATAC-seq) or differential chromatin modification states (ChIP-seq) between conditions. We compare the performance of ROTS to existing and widely used methods for ATAC-seq and ChIP-seq data using both synthetic and real datasets. Our results show that ROTS outperformed other commonly used methods when analyzing ATAC-seq data. ROTS also displayed the most accurate detection of small differences when modeling with synthetic data. We observed that two-step methods that require the use of a separate peak caller often more accurately called enrichment borders, whereas one-step methods without a separate peak calling step were more versatile in calling sub-peaks. The top ranked differential regions detected by the methods had marked correlation with transcriptional differences of the closest genes. Overall, our study provides evidence that ROTS is a useful addition to the available differential peak detection methods to study chromatin and performs especially well when applied to study differential chromatin states in ATAC-seq data.

Epigenetic Deregulation of the Histone Methyltransferase KMT5B Contributes to Malignant Transformation in Glioblastoma

Glioblastoma multiforme (GBM) is the most common and aggressive type of brain tumor in adulthood. Epigenetic mechanisms are known to play a key role in GBM although the involvement of histone methyltransferase KMT5B and its mark H4K20me2 has remained largely unexplored. The present study shows that DNA hypermethylation and loss of DNA hydroxymethylation is associated with KMT5B downregulation and genome-wide reduction of H4K20me2 levels in a set of human GBM samples and cell lines as compared with non-tumoral specimens. Ectopic overexpression of KMT5B induced tumor suppressor-like features in vitro and in a mouse tumor xenograft model, as well as changes in the expression of several glioblastoma-related genes. H4K20me2 enrichment was found immediately upstream of the promoter regions of a subset of deregulated genes, thus suggesting a possible role for KMT5B in GBM through the epigenetic modulation of key target cancer genes.

Influence of the Aryl Hydrocarbon Receptor Activating Environmental Pollutants on Autism Spectrum Disorder

Autism spectrum disorder (ASD) is an umbrella term that includes many different disorders that affect the development, communication, and behavior of an individual. Prevalence of ASD has risen exponentially in the past couple of decades. ASD has a complex etiology and traditionally recognized risk factors only account for a small percentage of incidence of the disorder. Recent studies have examined factors beyond the conventional risk factors (e.g., environmental pollution). There has been an increase in air pollution since the beginning of industrialization. Most environmental pollutants cause toxicities through activation of several cellular receptors, such as the aryl hydrocarbon receptor (AhR)/cytochrome P450 (CYPs) pathway. There is little research on the involvement of AhR in contributing to ASD. Although a few reviews have discussed and addressed the link between increased prevalence of ASD and exposure to environmental pollutants, the mechanism governing this effect, specifically the role of AhR in ASD development and the molecular mechanisms involved, have not been discussed or reviewed before. This article reviews the state of knowledge regarding the impact of the AhR/CYP pathway modulation upon exposure to environmental pollutants on ASD risk, incidence, and development. It also explores the molecular mechanisms involved, such as epigenesis and polymorphism. In addition, the review explores possible new AhR-mediated mechanisms of several drugs used for treatment of ASD, such as sulforaphane, resveratrol, haloperidol, and metformin.

CHIPIN: ChIP-seq inter-sample normalization based on signal invariance across transcriptionally constant genes

Background

Multiple studies rely on ChIP-seq experiments to assess the effect of gene modulation and drug treatments on protein binding and chromatin structure. However, most methods commonly used for the normalization of ChIP-seq binding intensity signals across conditions, e.g., the normalization to the same number of reads, either assume a constant signal-to-noise ratio across conditions or base the estimates of correction factors on genomic regions with intrinsically different signals between conditions. Inaccurate normalization of ChIP-seq signal may, in turn, lead to erroneous biological conclusions.

Results

We developed a new R package, CHIPIN, that allows normalizing ChIP-seq signals across different conditions/samples when spike-in information is not available, but gene expression data are at hand. Our normalization technique is based on the assumption that, on average, no differences in ChIP-seq signals should be observed in the regulatory regions of genes whose expression levels are constant across samples/conditions. In addition to normalizing ChIP-seq signals, CHIPIN provides as output a number of graphs and calculates statistics allowing the user to assess the efficiency of the normalization and qualify the specificity of the antibody used. In addition to ChIP-seq, CHIPIN can be used without restriction on open chromatin ATAC-seq or DNase hypersensitivity data. We validated the CHIPIN method on several ChIP-seq data sets and documented its superior performance in comparison to several commonly used normalization techniques.

Conclusions

The CHIPIN method provides a new way for ChIP-seq signal normalization across conditions when spike-in experiments are not available. The method is implemented in a user-friendly R package available on GitHub: https://github.com/BoevaLab/CHIPIN

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04320-3.

Maternal cecal microbiota transfer rescues early-life antibiotic-induced enhancement of type 1 diabetes in mice

Early-life antibiotic exposure perturbs the intestinal microbiota and accelerates type 1 diabetes (T1D) development in the NOD mouse model. Here, we found that maternal cecal microbiota transfer (CMT) to NOD mice after early-life antibiotic perturbation largely rescued the induced T1D enhancement. Restoration of the intestinal microbiome was significant and persistent, remediating the antibiotic-depleted diversity, relative abundance of particular taxa, and metabolic pathways. CMT also protected against perturbed metabolites and normalized innate and adaptive immune effectors. CMT restored major patterns of ileal microRNA and histone regulation of gene expression. Further experiments suggest a gut-microbiota-regulated T1D protection mechanism centered on Reg3γ, in an innate intestinal immune network involving CD44, TLR2, and Reg3γ. This regulation affects downstream immunological tone, which may lead to protection against tissue-specific T1D injury.

Histone acetylation of 45S rDNA correlates with disrupted nucleolar organization during heat stress response in Zea mays L

The role of the nucleolus in plant response to heat stress remains largely obscure. Our current efforts focused on exploring the underlying mechanism by which nucleolar disorganization is regulated in heat stressed-maize lines. Here, two maize lines, a heat-sensitive line, ZD958, and a heat-tolerant line, ZDH, were submitted to heat stress for investigating their association with the nucleolar disruption. Immunofluorescence staining showed that nucleolar disruption increased with prolonged treatment time. After heat treatment, a significant change in nucleolus organization was observed in the ZD958 line, but the ZDH line showed mild alteration. Moreover, actinomycin D (ActD)-induced nucleolus fission led to inhibition of maize growth under the normal condition. The ZD958 line exhibited a significant increase in the level of H3K9ac and H4K5ac of the 45S rDNA accompanied by a higher transcription of the 5'-external transcribed spacer (ETS) region, while the line ZDH showed a slight increase in histone acetylation levels and the transcriptional initiation at this site after heat treatment. To our knowledge, this is the first report providing a comparative insight between heat stress, rDNA histone modifications, and nucleolus disintegration in a heat-tolerant ZDH compared with a heat-sensitive line ZD958. Our investigation might assist maize breeders in obtaining heat-tolerant lines by targeting nucleoli using epigenetics.

Neuroepigenetic consequences of adolescent ethanol exposure

Adolescence is a critical developmental period characterized by ongoing brain maturation processes including myelination and synaptic pruning. Adolescents experience heightened reward sensitivity, sensation seeking, impulsivity, and diminished inhibitory self-control, which contribute to increased participation in risky behaviors, including the initiation of alcohol use. Ethanol exposure in adolescence alters memory and cognition, anxiety-like behavior, and ethanol sensitivity as well as brain myelination and dendritic spine morphology, with effects lasting into adulthood. Emerging evidence suggests that epigenetic modifications may explain these lasting effects. Focusing on the amygdala, prefrontal cortex and hippocampus, we review studies investigating the epigenetic consequences of adolescent ethanol exposure. Ethanol metabolism globally increases donor substrates for histone acetylation and histone and DNA methylation, and this chapter discusses how this can further impact epigenetic programming of the adolescent brain. Elucidation of the mechanisms through which ethanol can alter the epigenetic code at specific transcripts may provide therapeutic targets for intervention.

Chromatin loop anchors predict transcript and exon usage

Epigenomics and transcriptomics data from high-throughput sequencing techniques such as RNA-seq and ChIP-seq have been successfully applied in predicting gene transcript expression. However, the locations of chromatin loops in the genome identified by techniques such as Chromatin Interaction Analysis with Paired End Tag sequencing (ChIA-PET) have never been used for prediction tasks. Here, we developed machine learning models to investigate if ChIA-PET could contribute to transcript and exon usage prediction. In doing so, we used a large set of transcription factors as well as ChIA-PET data. We developed different Gradient Boosting Trees models according to the different tasks with the integrated datasets from three cell lines, including GM12878, HeLaS3 and K562. We validated the models via 10-fold cross validation, chromosome-split validation and cross-cell validation. Our results show that both transcript and splicing-derived exon usage can be effectively predicted with at least 0.7512 and 0.7459 of accuracy, respectively, on all cell lines from all kinds of validations. Examining the predictive features, we found that RNA Polymerase II ChIA-PET was one of the most important features in both transcript and exon usage prediction, suggesting that chromatin loop anchors are predictive of both transcript and exon usage.

Do Epigenetic Timers Control Petal Development?

Epigenetic modifications include histone modifications and DNA methylation; such modifications can induce heritable changes in gene expression by altering DNA accessibility and chromatin structure. A number of studies have demonstrated that epigenetic factors regulate plant developmental timing in response to environmental changes. However, we still have an incomplete picture of how epigenetic factors can regulate developmental events such as organogenesis. The small number of cell types and the relatively simple developmental progression required to form the Arabidopsis petal makes it a good model to investigate the molecular mechanisms driving plant organogenesis. In this minireview, we summarize recent studies demonstrating the epigenetic control of gene expression during various developmental transitions, and how such regulatory mechanisms can potentially act in petal growth and differentiation.

H3K27Ac modification and gene expression in psoriasis

BACKGROUND

Numerous alterations in gene expression have been described in psoriatic lesions compared to uninvolved or healthy skin. However, the mechanisms which induce this altered expression remain unclear. Epigenetic modifications play a key role in regulating genes' expression. Only three studies compared the whole-genome DNA methylation of psoriasis versus healthy skin. The present is the first study of genome-wide comparison of histone modifications between psoriatic to healthy skins.

OBJECTIVE

Our objective was to explore the pattern of H3K27Ac modifications in psoriatic lesions compared to uninvolved psoriatic and healthy skin, in order to identify new genes involved in the pathogenesis of psoriasis.

METHOD

Using ChIP-seq with anti H3K27Ac we compared the acetylation of lysine 27 on histone 3 (H3K27Ac) modification between psoriatic to healthy skins, combined with mRNA array.

RESULTS

We found a differential H3K27Ac pattern between psoriatic compared to uninvolved or healthy skins. We found that many of the overexpressed and H3K27Ac enriched genes in psoriasis, harbor a putative GRHL transcription factor-binding site.

CONCLUSIONS

In the most overexpressed genes in psoriasis, there is an enrichment of H3K27Ac. However, the loss of H3K27 acetylation modification does not correlate with decreased gene expression. GRHL appears to play an important role in the pathogenesis of psoriasis and therefore, might be a new target for psoriasis therapeutics.

Three functionally redundant plant-specific paralogs are core subunits of the SAGA histone acetyltransferase complex in Arabidopsis

The SAGA (Spt-Ada-Gcn5 acetyltransferase) complex is an evolutionarily conserved histone acetyltransferase complex that has a critical role in histone acetylation, gene expression, and various developmental processes in eukaryotes. However, little is known about the composition and function of the SAGA complex in plants. In this study, we found that the SAGA complex in Arabidopsis thaliana contains not only conserved subunits but also four plant-specific subunits: three functionally redundant paralogs, SCS1, SCS2A, and SCS2B (SCS1/2A/2B), and a TAF-like subunit, TAFL. Mutations in SCS1/2A/2B lead to defective phenotypes similar to those caused by mutations in the genes encoding conserved SAGA subunits HAG1 and ADA2B, including delayed juvenile-to-adult phase transition, late flowering, and increased trichome density. Furthermore, we demonstrated that SCS1/2A/2B are required for the function of the SAGA complex in histone acetylation, thereby promoting the transcription of development-related genes. These results together suggest that SCS1/2A/2B are core subunits of the SAGA complex in Arabidopsis. Compared with SAGA complexes in other eukaryotes, the SAGA complexes in plants have evolved unique features that are necessary for normal growth and development.

Fast detection of differential chromatin domains with SCIDDO

MOTIVATION

The generation of genome-wide maps of histone modifications using chromatin immunoprecipitation sequencing is a standard approach to dissect the complexity of the epigenome. Interpretation and differential analysis of histone datasets remains challenging due to regulatory meaningful co-occurrences of histone marks and their difference in genomic spread. To ease interpretation, chromatin state segmentation maps are a commonly employed abstraction combining individual histone marks. We developed the tool SCIDDO as a fast, flexible and statistically sound method for the differential analysis of chromatin state segmentation maps.

RESULTS

We demonstrate the utility of SCIDDO in a comparative analysis that identifies differential chromatin domains (DCD) in various regulatory contexts and with only moderate computational resources. We show that the identified DCDs correlate well with observed changes in gene expression and can recover a substantial number of differentially expressed genes (DEGs). We showcase SCIDDO's ability to directly interrogate chromatin dynamics, such as enhancer switches in downstream analysis, which simplifies exploring specific questions about regulatory changes in chromatin. By comparing SCIDDO to competing methods, we provide evidence that SCIDDO's performance in identifying DEGs via differential chromatin marking is more stable across a range of cell-type comparisons and parameter cut-offs.

AVAILABILITY AND IMPLEMENTATION

The SCIDDO source code is openly available under github.com/ptrebert/sciddo.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues

Genetic variants which affect complex traits (causal variants) are thought to be found in functional regions of the genome. Identifying causal variants would be useful for predicting complex trait phenotypes in dairy cows, however, functional regions are poorly annotated in the bovine genome. Functional regions can be identified on a genome-wide scale by assaying for post-translational modifications to histone proteins (histone modifications) and proteins interacting with the genome (e.g., transcription factors) using a method called Chromatin immunoprecipitation followed by sequencing (ChIP-seq). In this study ChIP-seq was performed to find functional regions in the bovine genome by assaying for four histone modifications (H3K4Me1, H3K4Me3, H3K27ac, and H3K27Me3) and one transcription factor (CTCF) in 6 tissues (heart, kidney, liver, lung, mammary and spleen) from 2 to 3 lactating dairy cows. Eighty-six ChIP-seq samples were generated in this study, identifying millions of functional regions in the bovine genome. Combinations of histone modifications and CTCF were found using ChromHMM and annotated by comparing with active and inactive genes across the genome. Functional marks differed between tissues highlighting areas which might be particularly important to tissue-specific regulation. Supporting the cis-regulatory role of functional regions, the read counts in some ChIP peaks correlated with nearby gene expression. The functional regions identified in this study were enriched for putative causal variants as seen in other species. Interestingly, regions which correlated with gene expression were particularly enriched for potential causal variants. This supports the hypothesis that complex traits are regulated by variants that alter gene expression. This study provides one of the largest ChIP-seq annotation resources in cattle including, for the first time, in the mammary gland of lactating cows. By linking regulatory regions to expression QTL and trait QTL we demonstrate a new strategy for identifying causal variants in cattle.

Mapping chromatin accessibility and active regulatory elements reveals pathological mechanisms in human gliomas

Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We perform whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we create an atlas of active enhancers and promoters in benign and malignant gliomas. We explore these elements and intersect with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas.

Integrative Ranking of Enhancer Networks Facilitates the Discovery of Epigenetic Markers in Cancer

Regulation of gene expression through multiple epigenetic components is a highly combinatorial process. Alterations in any of these layers, as is commonly found in cancer diseases, can lead to a cascade of downstream effects on tumor suppressor or oncogenes. Hence, deciphering the effects of epigenetic alterations on regulatory elements requires innovative computational approaches that can benefit from the huge amounts of epigenomic datasets that are available from multiple consortia, such as Roadmap or BluePrint. We developed a software tool named IRENE (Integrative Ranking of Epigenetic Network of Enhancers), which performs quantitative analyses on differential epigenetic modifications through an integrated, network-based approach. The method takes into account the additive effect of alterations on multiple regulatory elements of a gene. Applying this tool to well-characterized test cases, it successfully found many known cancer genes from publicly available cancer epigenome datasets.

Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks

Algorithms that accurately predict gene structure from primary sequence alone were transformative for annotating the human genome. Can we also predict the expression levels of genes based solely on genome sequence? Here, we sought to apply deep convolutional neural networks toward that goal. Surprisingly, a model that includes only promoter sequences and features associated with mRNA stability explains 59% and 71% of variation in steady-state mRNA levels in human and mouse, respectively. This model, termed Xpresso, more than doubles the accuracy of alternative sequence-based models and isolates rules as predictive as models relying on chromatic immunoprecipitation sequencing (ChIP-seq) data. Xpresso recapitulates genome-wide patterns of transcriptional activity, and its residuals can be used to quantify the influence of enhancers, heterochromatic domains, and microRNAs. Model interpretation reveals that promoter-proximal CpG dinucleotides strongly predict transcriptional activity. Looking forward, we propose cell-type-specific gene-expression predictions based solely on primary sequences as a grand challenge for the field.

Epigenetics of Sepsis

OBJECTIVES

Recent evidence from the fields of microbiology and immunology, as well as a small number of human sepsis studies, suggest that epigenetic regulation may play a central role in the pathogenesis of sepsis. The term "epigenetics" refers to regulatory mechanisms that control gene expression but are not related to changes in DNA sequence. These include DNA methylation, histone modifications, and regulation of transcription via non-coding RNAs. Epigenetic modifications, occurring in response to external stressors, lead to changes in gene expression, and thus lie at the intersection between genetics and the environment. In this review, we examine data from in vitro studies, animal studies, and the existing human sepsis studies in epigenetics to demonstrate that epigenetic mechanisms are likely central to the pathogenesis of sepsis and that epigenetic therapies may have potential in the treatment of sepsis and its associated organ failures.

DATA SOURCES

Online search of published scientific literature via Pubmed using the term "epigenetics" in combination with the terms "sepsis", "infection", "bacterial infection", "viral infection", "critical illness", "acute respiratory distress syndrome", and "acute lung injury".

STUDY SELECTION

Articles were chosen for inclusion based on their relevance to sepsis, acute inflammation, sepsis-related immune suppression, and sepsis-related organ failure. Reference lists were reviewed to identify additional relevant articles.

DATA EXTRACTION

Relevant data was extracted and synthesized for narrative review.

DATA SYNTHESIS

Epigenetic regulation is a key determinant of gene expression in sepsis. At the onset of infection, host-pathogen interactions often result in epigenetic alterations to host cells that favor pathogen survival. In parallel, the host inflammatory response is characterized by epigenetic modifications in key regulatory genes, including tumor necrosis factor and interleukin-1β. In human sepsis patients, multiple epigenetic modifying enzymes show differential expression in early sepsis, suggesting a role for epigenetics in coordinating the response to infection. In the later stages of sepsis, epigenetic modifications accompany endotoxin tolerance and the immune-suppressed state. In animal models, treatment with epigenetic modifiers can mitigate the effects of sepsis and improve survival as well as reverse sepsis-associated organ injury.

CONCLUSIONS

Epigenetic modifications are associated with key phases of sepsis, from the host-pathogen interaction, to acute inflammation, to immune suppression. Epigenetic markers show promise in the diagnosis and prognosis of sepsis and epigenetic modifying agents show promise as therapeutic tools in animal models of sepsis. Human studies in the area of epigenetics are sorely lacking and should be a priority for sepsis researchers.

Epigenetics, microRNA and Metabolic Syndrome: A Comprehensive Review

Epigenetics refers to the DNA chemistry changes that result in the modification of gene transcription and translation independently of the underlying DNA coding sequence. Epigenetic modifications are reported to involve various molecular mechanisms, including classical epigenetic changes affecting DNA methylation and histone modifications and small RNA-mediated processes, particularly that of microRNAs. Epigenetic changes are reversible and are closely interconnected. They are recognised to play a critical role as mediators of gene regulation, and any alteration in these mechanisms has been identified to mediate various pathophysiological conditions. Moreover, genetic predisposition and environmental factors, including dietary alterations, lifestyle or metabolic status, are identified to interact with the human epigenome, highlighting the importance of epigenetic factors as underlying processes in the aetiology of various diseases such as MetS. This review will reflect on how both the classical and microRNA-regulated epigenetic changes are associated with the pathophysiology of metabolic syndrome. We will then focus on the various aspects of epigenetic-based strategies used to modify MetS outcomes, including epigenetic diet, epigenetic drugs, epigenome editing tools and miRNA-based therapies.

Epigenetics and Heart Development

Epigenetic control of gene expression during cardiac development and disease has been a topic of intense research in recent years. Advances in experimental methods to study DNA accessibility, transcription factor occupancy, and chromatin conformation capture technologies have helped identify regions of chromatin structure that play a role in regulating access of transcription factors to the promoter elements of genes, thereby modulating expression. These chromatin structures facilitate enhancer contacts across large genomic distances and function to insulate genes from cis-regulatory elements that lie outside the boundaries for the gene of interest. Changes in transcription factor occupancy due to changes in chromatin accessibility have been implicated in congenital heart disease. However, the factors controlling this process and their role in changing gene expression during development or disease remain unclear. In this review, we focus on recent advances in the understanding of epigenetic factors controlling cardiac morphogenesis and their role in diseases.

Genome-wide histone acetylation analysis reveals altered transcriptional regulation in the Parkinson's disease brain

BACKGROUND

Parkinson's disease (PD) is a complex, age-related neurodegenerative disorder of largely unknown etiology. PD is strongly associated with mitochondrial respiratory dysfunction, which can lead to epigenetic dysregulation and specifically altered histone acetylation. Nevertheless, and despite the emerging role of epigenetics in age-related brain disorders, the question of whether aberrant histone acetylation is involved in PD remains unresolved.

METHODS

We studied fresh-frozen brain tissue from two independent cohorts of individuals with idiopathic PD (n = 28) and neurologically healthy controls (n = 21). We performed comprehensive immunoblotting to identify histone sites with altered acetylation levels in PD, followed by chromatin immunoprecipitation sequencing (ChIP-seq). RNA sequencing data from the same individuals was used to assess the impact of altered histone acetylation on gene expression.

RESULTS

Immunoblotting analyses revealed increased acetylation at several histone sites in PD, with the most prominent change observed for H3K27, a marker of active promoters and enhancers. ChIP-seq analysis further indicated that H3K27 hyperacetylation in the PD brain is a genome-wide phenomenon with a strong predilection for genes implicated in the disease, including SNCA, PARK7, PRKN and MAPT. Integration of the ChIP-seq with transcriptomic data from the same individuals revealed that the correlation between promoter H3K27 acetylation and gene expression is attenuated in PD patients, suggesting that H3K27 acetylation may be decoupled from transcription in the PD brain. Strikingly, this decoupling was most pronounced among nuclear-encoded mitochondrial genes, corroborating the notion that impaired crosstalk between the nucleus and mitochondria is involved in the pathogenesis of PD. Our findings independently replicated in the two cohorts.

CONCLUSIONS

Our findings strongly suggest that aberrant histone acetylation and altered transcriptional regulation are involved in the pathophysiology of PD. We demonstrate that PD-associated genes are particularly prone to epigenetic dysregulation and identify novel epigenetic signatures associated with the disease.

Environmental Enrichment Induces Epigenomic and Genome Organization Changes Relevant for Cognition

In early development, the environment triggers mnemonic epigenomic programs resulting in memory and learning experiences to confer cognitive phenotypes into adulthood. To uncover how environmental stimulation impacts the epigenome and genome organization, we used the paradigm of environmental enrichment (EE) in young mice constantly receiving novel stimulation. We profiled epigenome and chromatin architecture in whole cortex and sorted neurons by deep-sequencing techniques. Specifically, we studied chromatin accessibility, gene and protein regulation, and 3D genome conformation, combined with predicted enhancer and chromatin interactions. We identified increased chromatin accessibility, transcription factor binding including CTCF-mediated insulation, differential occupancy of H3K36me3 and H3K79me2, and changes in transcriptional programs required for neuronal development. EE stimuli led to local genome re-organization by inducing increased contacts between chromosomes 7 and 17 (inter-chromosomal). Our findings support the notion that EE-induced learning and memory processes are directly associated with the epigenome and genome organization.

ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin

Cell-free DNA (cfDNA) in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells and retain some of the cell-of-origin histone modifications. In this study, we applied chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we showed that we can identify pathology-related changes in hepatocyte transcriptional programs. In patients with metastatic colorectal carcinoma, we detected clinically relevant and patient-specific information, including transcriptionally active human epidermal growth factor receptor 2 (HER2) amplifications. Altogether, cfChIP-seq, using low sequencing depth, provides systemic and genome-wide information and can inform diagnosis and facilitate interrogation of physiological and pathological processes using blood samples.

CRL4DCAF8 dependent opposing stability control over the chromatin remodeler LSH orchestrates epigenetic dynamics in ferroptosis

Despite the emerging evidence on ferroptosis implicated in diverse pathologies, molecular linkage between oxidative inducers and chromatin as epigenetic memory carrier for its propagation remains elusive. Here, we report the identification of two WD40 proteins DCAF8 and WDR76 as substrate adapter and molecular inhibitor respectively of the Cullin-4 RING ubiquitin ligase (CRL4) system for stability control of chromatin remodeler LSH. Degradation analysis and CRL4-DCAF8 complex reconstitution demonstrate that CRL4^DCAF8 is a bona fide E3 ligase for LSH. In contrast, WDR76 antagonizes DCAF8-targeted LSH proteolysis through competitive inhibition of the holo-CRL4^DCAF8-LSH complex assembly. Importantly, this opposing regulatory strategy is utilized in lipid hydroperoxide induced ferroptosis, where we identify key redox homeostasis genes significantly regulated by the DCAF8/WDR76/LSH axis through transcriptomic epistasis analysis. This regulation is mechanistically attributed to DNA hydroxymethylation fostered WDR76 interaction with LSH and increased ratio of DCAF8 to WDR76 for antagonistic LSH association accompanying decreased DNA oxidation along with ROS overproduction. Evaluation of epigenetic dynamics at ferroptosis gene promoters reveals linker histone H1- and LSH-associated transcriptional repression is coordinately removed upon lipid peroxidation stress. Together with the phenotypes driven by WDR76 and DCAF8 manipulations, these data identify DCAF8- and WDR76-adapted oxidative damage sensing through DNA hydroxymethylation for LSH degradation control as a crucial nexus in epigenetic regulation of ferroptosis.

CpG content-dependent associations between transcription factors and histone modifications

Understanding the factors that underlie the epigenetic regulation of genes is crucial to understand the gene regulatory machinery as a whole. Several experimental and computational studies examined the relationship between different factors involved. Here we investigate the relationship between transcription factors (TFs) and histone modifications (HMs), based on ChIP-seq data in cell lines. As it was shown that gene regulation by TFs differs depending on the CpG class of a promoter, we study the impact of the CpG content in promoters on the associations between TFs and HMs. We suggest an approach based on sparse linear regression models to infer associations between TFs and HMs with respect to CpG content. A study of the partial correlation of HMs for the two classes of high and low CpG content reveals possible CpG dependence and potential candidates for confounding factors in our models. We show that the models are accurate, inferred associations reflect known biological relationships, and we give new insight into associations with respect to CpG content. Moreover, analysis of a ChIP-seq dataset in HepG2 cells of the HM H3K122ac, an HM about little is known, reveals novel TF associations and supports a previously established link to active transcription.

Genome-wide analysis of primary microRNA expression using H3K36me3 ChIP-seq data

MicroRNAs are key players in gene regulatory networks controlling cell homeostasis. Their altered expression has been previously linked to disease outcomes and microRNAs thus serve as biomarkers for disease diagnostics. However, their synthesis and its transcriptional regulation have been challenging to investigate. In this study, we validated the use of H3K36me3 histone modification for the quantification of microRNA transcription levels using data from the ENCODE Consortium and then applied this approach to provide new insight into the cell-type-specific regulation in tissues, cell line models and cardiac disease. In cardiomyocytes derived from patients suffering from septal defects, carrying a G296S mutation in the transcription factor GATA4, we show that microRNA gene transcription is altered in cardiomyocytes carrying this mutation and coincides with novel super-enhancers formed within regulatory domains defined using chromatin interaction profiles. The most prominently elevated primary transcript encodes for let-7a and miR-100 that may target genes in the Hippo signaling pathway. Collectively, our work presents a methodology to quantify microRNA gene expression using histone marker data and paves the way for functional studies of cell-type-specific transcriptional regulation occurring in disease pathology.

Single-cell dynamics of chromatin activity during cell lineage differentiation in Caenorhabditis elegans embryos

Elucidating the chromatin dynamics that orchestrate embryogenesis is a fundamental question in developmental biology. Here, we exploit position effects on expression as an indicator of chromatin activity and infer the chromatin activity landscape in every lineaged cell during Caenorhabditis elegans early embryogenesis. Systems-level analyses reveal that chromatin activity distinguishes cellular states and correlates with fate patterning in the early embryos. As cell lineage unfolds, chromatin activity diversifies in a lineage-dependent manner, with switch-like changes accompanying anterior-posterior fate asymmetry and characteristic landscapes being established in different cell lineages. Upon tissue differentiation, cellular chromatin from distinct lineages converges according to tissue types but retains stable memories of lineage history, contributing to intra-tissue cell heterogeneity. However, the chromatin landscapes of cells organized in a left-right symmetric pattern are predetermined to be analogous in early progenitors so as to pre-set equivalent states. Finally, genome-wide analysis identifies many regions exhibiting concordant chromatin activity changes that mediate the co-regulation of functionally related genes during differentiation. Collectively, our study reveals the developmental and genomic dynamics of chromatin activity at the single-cell level.

Epigenetic Element-Based Transcriptome-Wide Association Study Identifies Novel Genes for Bipolar Disorder

Since the bipolar disorder (BD) signals identified by genome-wide association study (GWAS) often reside in the non-coding regions, understanding the biological relevance of these genetic loci has proven to be complicated. Transcriptome-wide association studies (TWAS) providing a powerful approach to identify novel disease risk genes and uncover possible causal genes at loci identified previously by GWAS. However, these methods did not consider the importance of epigenetic regulation in gene expression. Here, we developed a novel epigenetic element-based transcriptome-wide association study (ETWAS) that tested the effects of genetic variants on gene expression levels with the epigenetic features as prior and further mediated the association between predicted expression and BD. We conducted an ETWAS consisting of 20 352 cases and 31 358 controls and identified 44 transcriptome-wide significant hits. We found 14 conditionally independent genes, and 10 genes that did not previously implicate with BD were regarded as novel candidate genes, such as ASB16 in the cerebellar hemisphere (P = 9.29 × 10-8). We demonstrated that several genome-wide significant signals from the BD GWAS driven by genetically regulated expression, and NEK4 explained 90.1% of the GWAS signal. Additionally, ETWAS identified genes could explain heritability beyond that explained by GWAS-associated SNPs (P = 5.60 × 10-66). By querying the SNPs in the final models of identified genes in phenome databases, we identified several phenotypes previously associated with BD, such as schizophrenia and depression. In conclusion, ETWAS is a powerful method, and we identified several novel candidate genes associated with BD.

Detection of H3K4me3 Identifies NeuroHIV Signatures, Genomic Effects of Methamphetamine and Addiction Pathways in Postmortem HIV+ Brain Specimens that Are Not Amenable to Transcriptome Analysis

Human postmortem specimens are extremely valuable resources for investigating translational hypotheses. Tissue repositories collect clinically assessed specimens from people with and without HIV, including age, viral load, treatments, substance use patterns and cognitive functions. One challenge is the limited number of specimens suitable for transcriptional studies, mainly due to poor RNA quality resulting from long postmortem intervals. We hypothesized that epigenomic signatures would be more stable than RNA for assessing global changes associated with outcomes of interest. We found that H3K27Ac or RNA Polymerase (Pol) were not consistently detected by Chromatin Immunoprecipitation (ChIP), while the enhancer H3K4me3 histone modification was abundant and stable up to the 72 h postmortem. We tested our ability to use HeK4me3 in human prefrontal cortex from HIV+ individuals meeting criteria for methamphetamine use disorder or not (Meth +/-) which exhibited poor RNA quality and were not suitable for transcriptional profiling. Systems strategies that are typically used in transcriptional metadata were applied to H3K4me3 peaks revealing consistent genomic activity differences in regions where addiction and neuronal synapses pathway genes are represented, including genes of the dopaminergic system, as well as inflammatory pathways. The resulting comparisons mirrored previously observed effects of Meth on suppressing gene expression and provided insights on neurological processes affected by Meth. The results suggested that H3K4me3 detection in chromatin may reflect transcriptional patterns, thus providing opportunities for analysis of larger numbers of specimens from cases with substance use and neurological deficits. In conclusion, the detection of H3K4me3 in isolated chromatin can be an alternative to transcriptome strategies to increase the power of association using specimens with long postmortem intervals and low RNA quality.

Functional annotations of three domestic animal genomes provide vital resources for comparative and agricultural research

Gene regulatory elements are central drivers of phenotypic variation and thus of critical importance towards understanding the genetics of complex traits. The Functional Annotation of Animal Genomes consortium was formed to collaboratively annotate the functional elements in animal genomes, starting with domesticated animals. Here we present an expansive collection of datasets from eight diverse tissues in three important agricultural species: chicken (Gallus gallus), pig (Sus scrofa), and cattle (Bos taurus). Comparative analysis of these datasets and those from the human and mouse Encyclopedia of DNA Elements projects reveal that a core set of regulatory elements are functionally conserved independent of divergence between species, and that tissue-specific transcription factor occupancy at regulatory elements and their predicted target genes are also conserved. These datasets represent a unique opportunity for the emerging field of comparative epigenomics, as well as the agricultural research community, including species that are globally important food resources.

Seasonal plasticity: how do butterfly wing pattern traits evolve environmental responsiveness?

Phenotypic plasticity in response to environmental cues is common in butterflies, and is a major driver of butterfly wing pattern diversity. The endocrine signal ecdysone has been revealed as a major modulator of plasticity in butterflies. External cues such as day length or temperature are translated internally into variation in ecdysone titers, which in turn lead to alternate phenotypes such as seasonal wing patterns. Here we review the evidence showing that ecdysone-mediated plasticity of different wing pattern features such as wing color and eyespot size can evolve independently. Recent studies show that ecdysone regulates gene expression in Drosophila melanogaster via a chromatin remodeling mechanism. We thus propose that environmentally responsive ecdysone titers in butterflies may also function via chromatin regulation to promote different seasonal phenotypes. We present a model of ecdysone response evolution that integrates both gene regulatory architecture and organismal development, and propose a set of testable mechanistic hypotheses for how plastic response profiles of specific genes can evolve.

Telomerase Regulation: A Role for Epigenetics

Simple Summary

Maintenance of telomeres is a fundamental step in human carcinogenesis and is primarily regulated by telomerase and the human telomerase reverse transcriptase gene (TERT). Improved understanding of the transcriptional control of this gene may provide potential therapeutic targets. Epigenetic modifications are a prominent mechanism to control telomerase activity and regulation of the TERT gene. TERT-targeting miRNAs have been widely studied and their function explained through pre-clinical in vivo model-based validation studies. Further, histone deacetylase inhibitors are now in pre and early clinical trials with significant clinical success. Importantly, TERT downregulation through epigenetic modifications including TERT promoter methylation, histone deacetylase inhibitors, and miRNA activity might contribute to clinical study design. This review provides an overview of the epigenetic mechanisms involved in the regulation of TERT expression and telomerase activity.

Abstract

Telomerase was first described by Greider and Blackburn in 1984, a discovery ultimately recognized by the Nobel Prize committee in 2009. The three decades following on from its discovery have been accompanied by an increased understanding of the fundamental mechanisms of telomerase activity, and its role in telomere biology. Telomerase has a clearly defined role in telomere length maintenance and an established influence on DNA replication, differentiation, survival, development, apoptosis, tumorigenesis, and a further role in therapeutic resistance in human stem and cancer cells including those of breast and cervical origin. TERT encodes the catalytic subunit and rate-limiting factor for telomerase enzyme activity. The mechanisms of activation or silencing of TERT remain open to debate across somatic, cancer, and stem cells. Promoter mutations upstream of TERT may promote dysregulated telomerase activation in tumour cells but additional factors including epigenetic, transcriptional and posttranscriptional modifications also have a role to play. Previous systematic analysis indicated methylation and mutation of the TERT promoter in 53% and 31%, respectively, of TERT expressing cancer cell lines supporting the concept of a key role for epigenetic alteration associated with TERT dysregulation and cellular transformation. Epigenetic regulators including DNA methylation, histone modification, and non-coding RNAs are now emerging as drivers in the regulation of telomeres and telomerase activity. Epigenetic regulation may be responsible for reversible silencing of TERT in several biological processes including development and differentiation, and increased TERT expression in cancers. Understanding the epigenetic mechanisms behind telomerase regulation holds important prospects for cancer treatment, diagnosis and prognosis. This review will focus on the role of epigenetics in telomerase regulation.

Conservation and trans-regulation of histone modification in the A and B subgenomes of polyploid wheat during domestication and ploidy transition

BACKGROUND

Polyploidy has played a prominent role in the evolution of plants and many other eukaryotic lineages. However, how polyploid genomes adapt to the abrupt presence of two or more sets of chromosomes via genome regulation remains poorly understood. Here, we analyzed genome-wide histone modification and gene expression profiles in relation to domestication and ploidy transition in the A and B subgenomes of polyploid wheat.

RESULTS

We found that epigenetic modification patterns by two typical euchromatin histone markers, H3K4me3 and H3K27me3, for the great majority of homoeologous triad genes in A and B subgenomes were highly conserved between wild and domesticated tetraploid wheats and remained stable in the process of ploidy transitions from hexaploid to extracted tetraploid and then back to resynthesized hexaploid. However, a subset of genes was differentially modified during tetraploid and hexaploid wheat domestication and in response to ploidy transitions, and these genes were enriched for particular gene ontology (GO) terms. The extracted tetraploid wheat manifested higher overall histone modification levels than its hexaploid donor, and which were reversible and restored to normal levels in the resynthesized hexaploid. Further, while H3K4me3 marks were distally distributed along each chromosome and significantly correlated with subgenome expression as expected, H3K27me3 marks showed only a weak distal bias and did not show a significant correlation with gene expression.

CONCLUSIONS

Our results reveal overall high stability of histone modification patterns in the A and B subgenomes of polyploid wheat during domestication and in the process of ploidy transitions. However, modification levels of a subset of functionally relevant genes in the A and B genomes were trans-regulated by the D genome in hexaploid wheat.

MACMIC Reveals A Dual Role of CTCF in Epigenetic Regulation of Cell Identity Genes

Numerous studies of relationship between epigenomic features have focused on their strong correlation across the genome, likely because such relationship can be easily identified by many established methods for correlation analysis. However, two features with little correlation may still colocalize at many genomic sites to implement important functions. There is no bioinformatic tool for researchers to specifically identify such feature pairs. Here, we develop a method to identify feature pairs in which two features have maximal colocalization minimal correlation (MACMIC) across the genome. By MACMIC analysis of 3306 feature pairs in 16 human cell types, we reveal a dual role of CCCTC-binding factor (CTCF) in epigenetic regulation of cell identity genes. Although super-enhancers are associated with activation of target genes, only a subset of super-enhancers colocalized with CTCF regulate cell identity genes. At super-enhancers colocalized with CTCF, CTCF is required for the active marker H3K27ac in cell types requiring the activation, and also required for the repressive marker H3K27me3 in other cell types requiring repression. Our work demonstrates the biological utility of the MACMIC analysis and reveals a key role for CTCF in epigenetic regulation of cell identity. The code for MACMIC is available at https://github.com/bxia888/MACMIC.

Methods for ChIP-seq analysis: A practical workflow and advanced applications

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a central method in epigenomic research. Genome-wide analysis of histone modifications, such as enhancer analysis and genome-wide chromatin state annotation, enables systematic analysis of how the epigenomic landscape contributes to cell identity, development, lineage specification, and disease. In this review, we first present a typical ChIP-seq analysis workflow, from quality assessment to chromatin-state annotation. We focus on practical, rather than theoretical, approaches for biological studies. Next, we outline various advanced ChIP-seq applications and introduce several state-of-the-art methods, including prediction of gene expression level and chromatin loops from epigenome data and data imputation. Finally, we discuss recently developed single-cell ChIP-seq analysis methodologies that elucidate the cellular diversity within complex tissues and cancers.

NF-Y plays essential roles in flavonoid biosynthesis by modulating histone modifications in tomato

NF-Y transcription factors are reported to play diverse roles in a wide range of biological processes in plants. However, only a few active NF-Y complexes are known in plants and the precise functions of NF-Y complexes in flavonoid biosynthesis have not been determined. Using various molecular, genetic and biochemical approaches, we found that NF-YB8a, NF-YB8b and NF-YB8c - a NF-YB subgroup - can interact with a specific subgroup of NF-YC and then recruit either of two distinct NF-YAs to form NF-Y complexes that bind the CCAAT element in the CHS1 promoter. Furthermore, suppressing the expression of particular NF-YB genes increased the levels of H3K27me3 at the CHS1 locus and significantly suppressed the expression of CHS1 during tomato fruit ripening, which led to the development of pink-coloured fruit with colourless peels. Altogether, by demonstrating that NF-Y transcription factors play essential roles in flavonoid biosynthesis and by providing significant molecular insight into the regulatory mechanisms that drive the development of pink-coloured tomato fruit, we provide a major advance to our fundamental knowledge and information that has considerable practical value for horticulture.

Iterative epigenomic analyses in the same single cell

Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors, and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracellular cues. However, the predictive ability of epigenomic analysis is still limited for mechanistic research at a single cell level. To overcome this limitation, it would be useful to acquire reliable signals from multiple epigenetic marks in the same single cell. Here, we propose a new approach and a new method for analysis of several components of the epigenome in the same single cell. The new method allows reanalysis of the same single cell. We found that reanalysis of the same single cell is feasible, provides confirmation of the epigenetic signals, and allows application of statistical analysis to identify reproduced reads using data sets generated only from the single cell. Reanalysis of the same single cell is also useful to acquire multiple epigenetic marks from the same single cells. The method can acquire at least five epigenetic marks: H3K27ac, H3K27me3, mediator complex subunit 1, a DNA modification, and a DNA-interacting protein. We can predict active signaling pathways in K562 single cells using the epigenetic data and confirm that the predicted results strongly correlate with actual active signaling pathways identified by RNA-seq results. These results suggest that the new method provides mechanistic insights for cellular phenotypes through multilayered epigenome analysis in the same single cells.

Potential applications of deep learning in single-cell RNA sequencing analysis for cell therapy and regenerative medicine

When used in cell therapy and regenerative medicine strategies, stem cells have potential to treat many previously incurable diseases. However, current application methods using stem cells are underdeveloped, as these cells are used directly regardless of their culture medium and subgroup. For example, when using mesenchymal stem cells (MSCs) in cell therapy, researchers do not consider their source and culture method nor their application angle and function (soft tissue regeneration, hard tissue regeneration, suppression of immune function, or promotion of immune function). By combining machine learning methods (such as deep learning) with data sets obtained through single-cell RNA sequencing (scRNA-seq) technology, we can discover the hidden structure of these cells, predict their effects more accurately, and effectively use subpopulations with differentiation potential for stem cell therapy. scRNA-seq technology has changed the study of transcription, because it can express single-cell genes with single-cell anatomical resolution. However, this powerful technology is sensitive to biological and technical noise. The subsequent data analysis can be computationally difficult for a variety of reasons, such as denoising single cell data, reducing dimensionality, imputing missing values, and accounting for the zero-inflated nature. In this review, we discussed how deep learning methods combined with scRNA-seq data for research, how to interpret scRNA-seq data in more depth, improve the follow-up analysis of stem cells, identify potential subgroups, and promote the implementation of cell therapy and regenerative medicine measures.

The histone modification H3K4me3 is altered at the ANK1 locus in Alzheimer's disease brain

Several epigenome-wide association studies of DNA methylation have highlighted altered DNA methylation in the ANK1 gene in Alzheimer's disease (AD) brain samples. However, no study has specifically examined ANK1 histone modifications in the disease. We use chromatin immunoprecipitation-qPCR to quantify tri-methylation at histone 3 lysine 4 (H3K4me3) and 27 (H3K27me3) in the ANK1 gene in entorhinal cortex from donors with high (n = 59) or low (n = 29) Alzheimer's disease pathology. We demonstrate decreased levels of H3K4me3, a marker of active gene transcription, with no change in H3K27me3, a marker of inactive genes. H3K4me3 is negatively correlated with DNA methylation in specific regions of the ANK1 gene. Our study suggests that the ANK1 gene shows altered epigenetic marks indicative of reduced gene activation in Alzheimer's disease.

Cis-acting variation is common across regulatory layers but is often buffered during embryonic development

Precise patterns of gene expression are driven by interactions between transcription factors, regulatory DNA sequences, and chromatin. How DNA mutations affecting any one of these regulatory "layers" are buffered or propagated to gene expression remains unclear. To address this, we quantified allele-specific changes in chromatin accessibility, histone modifications, and gene expression in F1 embryos generated from eight Drosophila crosses at three embryonic stages, yielding a comprehensive data set of 240 samples spanning multiple regulatory layers. Genetic variation (allelic imbalance) impacts gene expression more frequently than chromatin features, with metabolic and environmental response genes being most often affected. Allelic imbalance in cis-regulatory elements (enhancers) is common and highly heritable, yet its functional impact does not generally propagate to gene expression. When it does, genetic variation impacts RNA levels through two alternative mechanisms involving either H3K4me3 or chromatin accessibility and H3K27ac. Changes in RNA are more predictive of variation in H3K4me3 than vice versa, suggesting a role for H3K4me3 downstream from transcription. The impact of a substantial proportion of genetic variation is consistent across embryonic stages, with 50% of allelic imbalanced features at one stage being also imbalanced at subsequent developmental stages. Crucially, buffering, as well as the magnitude and evolutionary impact of genetic variants, is influenced by regulatory complexity (i.e., number of enhancers regulating a gene), with transcription factors being most robust to cis-acting, but most influenced by trans-acting, variation.

MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

Although genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities based on H3K4me3 and H3K27ac enrichment, from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

Impaired Regulation of Histone Methylation and Acetylation Underlies Specific Neurodevelopmental Disorders

Epigenetic processes are critical for governing the complex spatiotemporal patterns of gene expression in neurodevelopment. One such mechanism is the dynamic network of post-translational histone modifications that facilitate recruitment of transcription factors or even directly alter chromatin structure to modulate gene expression. This is a tightly regulated system, and mutations affecting the function of a single histone-modifying enzyme can shift the normal epigenetic balance and cause detrimental developmental consequences. In this review, we will examine select neurodevelopmental conditions that arise from mutations in genes encoding enzymes that regulate histone methylation and acetylation. The methylation-related conditions discussed include Wiedemann-Steiner, Kabuki, and Sotos syndromes, and the acetylation-related conditions include Rubinstein-Taybi, KAT6A, genitopatellar/Say-Barber-Biesecker-Young-Simpson, and brachydactyly mental retardation syndromes. In particular, we will discuss the clinical/phenotypic and genetic basis of these conditions and the model systems that have been developed to better elucidate cellular and systemic pathological mechanisms.

Müller Glia-Mediated Retinal Regeneration

Müller glia originate from neuroepithelium and are the principal glial cells in the retina. During retinal development, Müller glia are one of the last cell types to be born. In lower vertebrates, such as zebrafish, Müller glia possess a remarkable capacity for retinal regeneration following various forms of injury through a reprogramming process in which endogenous Müller glia proliferate and differentiate into all types of retinal cells. In mammals, Müller glia become reactive in response to damage to protect or to further impair retinal function. Although mammalian Müller glia have regenerative potential, it is limited as far as repairing damaged retina. Lessons learned from zebrafish will help reveal the critical mechanisms involved in Müller glia reprogramming. Progress has been made in triggering Müller glia to reprogram and generate functional neurons to restore vision in mammals indicating that Müller glia reprogramming may be a promising therapeutic strategy for human retinal diseases. This review comprehensively summarizes the mechanisms related to retinal regeneration in model animals and the critical advanced progress made in Müller glia reprogramming in mammals.

Intragenic DNA methylation regulates insect gene expression and reproduction through the MBD/Tip60 complex

DNA methylation is an important epigenetic modification. However, the regulations and functions of insect intragenic DNA methylation remain unknown. Here, we demonstrate that a regulatory mechanism involving intragenic DNA methylation controls ovarian and embryonic developmental processes in Bombyx mori. In B. mori, DNA methylation is found near the transcription start site (TSS) of ovarian genes. By promoter activity analysis, we observed that 5′ UTR methylation enhances gene expression. Moreover, methyl-DNA-binding domain protein 2/3 (MBD2/3) binds to the intragenic methyl-CpG fragment and recruits acetyltransferase Tip60 to promote histone H3K27 acetylation and gene expression. Additionally, genome-wide analyses showed that the peak of H3K27 acetylation appears near the TSS of methyl-modified genes, and DNA methylation is enriched in genes involved in protein synthesis in the B. mori ovary, with MBD2/3 knockdown resulting in decreased fecundity. These data uncover a mechanism of gene body methylation for regulating insect gene expression and reproduction.

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Insect intragenic 5mC enhances gene expression through histone H3K27 acetylation

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MBD2/3 binds the intragenic 5mC and recruits Tip60 to promote H3K27 acetylation

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Intragenic 5mCs modify protein synthesis-related genes in insect ovaries

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The intragenic 5mC plays a role in insect reproduction

Histone modifications during the life cycle of the brown alga Ectocarpus

BACKGROUND

Brown algae evolved complex multicellularity independently of the animal and land plant lineages and are the third most developmentally complex phylogenetic group on the planet. An understanding of developmental processes in this group is expected to provide important insights into the evolutionary events necessary for the emergence of complex multicellularity. Here, we focus on mechanisms of epigenetic regulation involving post-translational modifications of histone proteins.

RESULTS

A total of 47 histone post-translational modifications are identified, including a novel mark H2AZR38me1, but Ectocarpus lacks both H3K27me3 and the major polycomb complexes. ChIP-seq identifies modifications associated with transcription start sites and gene bodies of active genes and with transposons. H3K79me2 exhibits an unusual pattern, often marking large genomic regions spanning several genes. Transcription start sites of closely spaced, divergently transcribed gene pairs share a common nucleosome-depleted region and exhibit shared histone modification peaks. Overall, patterns of histone modifications are stable through the life cycle. Analysis of histone modifications at generation-biased genes identifies a correlation between the presence of specific chromatin marks and the level of gene expression.

CONCLUSIONS

The overview of histone post-translational modifications in the brown alga presented here will provide a foundation for future studies aimed at understanding the role of chromatin modifications in the regulation of brown algal genomes.

intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data

BACKGROUND

RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy.

RESULTS

Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization.

CONCLUSION

intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset.

Prediction of histone post-translational modifications using deep learning

Motivation

Histone post-translational modifications (PTMs) are involved in a variety of essential regulatory processes in the cell, including transcription control. Recent studies have shown that histone PTMs can be accurately predicted from the knowledge of transcription factor binding or DNase hypersensitivity data. Similarly, it has been shown that one can predict PTMs from the underlying DNA primary sequence.

Results

In this study, we introduce a deep learning architecture called DeepPTM for predicting histone PTMs from transcription factor binding data and the primary DNA sequence. Extensive experimental results show that our deep learning model outperforms the prediction accuracy of the model proposed in Benveniste et al. (PNAS 2014) and DeepHistone (BMC Genomics 2019). The competitive advantage of our framework lies in the synergistic use of deep learning combined with an effective pre-processing step. Our classification framework has also enabled the discovery that the knowledge of a small subset of transcription factors (which are histone-PTM and cell-type-specific) can provide almost the same prediction accuracy that can be obtained using all the transcription factors data.

Availabilityand implementation

https://github.com/dDipankar/DeepPTM.

Supplementary information

Supplementary data are available at Bioinformatics online.

Epigenetic regulation by polyphenols in diabetes and related complications

Diabetes mellitus (DM) is a chronic metabolic disorder and one of the most challenging health problems worldwide. Left untreated, it may progress causing serious complications. Genetics, epigenetics, and environmental factors are known to play an overlapping role in the pathogenesis of DM. Growing evidence suggests the hypothesis that the environment induces changes in the early phases of growth and development, influencing health and disease in the adulthood through the alteration in genetic expression of an individual, at least in part. DNA methylation, histone modifications and miRNAs are three mechanisms responsible for epigenetic alterations. The daily diet contains a number of secondary metabolites, with polyphenols being highest in abundance, which contribute to overall health and may prevent or delay the onset of many chronic diseases. Polyphenols have the ability to alter metabolic and signaling pathways at various levels, such as gene expression, epigenetic regulation, protein expression and enzyme activity. The potential efficacy of polyphenolic compounds on glucose homeostasis has been evidenced from in vitro, in vivo and clinical studies. The present review is designed to focus on epigenetic regulation exerted by polyphenolic compounds in DM and their complications, as well as to summarize clinical trials involving polyphenols in DM.