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]

Heritable dysregulation of DNA methylation may underlie the diabetogenic effects of paternal preconception exposure to inorganic arsenic in C57BL/6J mice

Chronic exposure to inorganic arsenic (iAs) has been linked with the development of diabetes mellitus (DM). We recently showed that parental exposure to iAs (200 ppb) prior to mating was associated with diabetic phenotypes in offspring and altered gene expression in parents and offspring. The goal of the present study was to determine if DNA methylation underlies the differential gene expression in the livers of offspring. DNA methylation was assessed in paternal (G0) sperm and livers of their offspring (G1) using a genome wide DNA methylation array. We found that iAs exposure significantly altered CpG methylation (p < 0.05) in 54.3 %, 49.4 %, and 63.7 % of the differentially expressed genes in G0 sperm, G1 female livers, and G1 male livers, respectively. Importantly, a subset of differentially methylated CpG sites were shared across generations. Sensitivity analyses (FDR < 0.1) of imprinted and DM-associated genes revealed differential methylation of 74 imprinted genes and 100 DM-associated genes in the livers of G1 males. These male-specific results are intriguing given the prior findings of diabetic phenotypes found exclusively in male offspring from parents exposed to iAs. In summary, these data demonstrate that heritable changes in DNA methylation through the paternal germline may underlie the diabetogenic effects of preconception iAs exposure.

Insights into toxicological mechanisms of per-/polyfluoroalkyl substances by using omics-centered approaches

The extensive presence of per-/polyfluoroalkyl substances (PFASs) in the environment and their adverse effects on organisms have garnered increasing concern. With the shift of industrial development from legacy to emerging PFASs, expanding the understanding of molecular responses to legacy and emerging PFASs is essential to accurately assess their risks to organisms. Compared with traditional toxicological approaches, omics technologies including transcriptomics, proteomics, metabolomics/lipidomics, and microbiomics allow comprehensive analysis of the molecular changes that occur in organisms after PFAS exposure. This paper comprehensively reviews the insights of omics approaches, especially the multi-omics approach, on the toxic mechanisms of both legacy and emerging PFASs in recent five years, focusing on hepatotoxicity, developmental toxicity, immunotoxicity, reproductive toxicity, neurotoxicity, and the endocrine-disrupting effect. PFASs exert various toxic effects via lipid and amino acid metabolism disruption, perturbations in several cell signal pathways, and binding to nuclear receptors. Notably, integrating multi-omics offers a thorough insight into the mechanisms of toxicity associated with PFASs. The gut microbiota plays an essential regulatory role in the toxic mechanisms of PFAS-induced hepatotoxicity. Finally, further research directions for PFAS toxicology based on omics technologies are prospected.

Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular states

To understand the complex relationship between histone mark activity and gene expression, recent advances have used in silico predictions based on large-scale machine learning models. However, these approaches have omitted key contributing factors like cell state, histone mark function or distal effects, which impact the relationship, limiting their findings. Moreover, downstream use of these models for new biological insight is lacking. Here, we present the most comprehensive study of this relationship to date - investigating seven histone marks in eleven cell types across a diverse range of cell states. We used convolutional and attention-based models to predict transcription from histone mark activity at promoters and distal regulatory elements. Our work shows that histone mark function, genomic distance and cellular states collectively influence a histone mark's relationship with transcription. We found that no individual histone mark is consistently the strongest predictor of gene expression across all genomic and cellular contexts. This highlights the need to consider all three factors when determining the effect of histone mark activity on transcriptional state. Furthermore, we conducted in silico histone mark perturbation assays, uncovering functional and disease related loci and highlighting frameworks for the use of chromatin deep learning models to uncover new biological insight.

Unveiling the Therapeutic Promise of Epigenetics in Vascular Cognitive Impairment and Vascular Dementia

Vascular dementia (VaD) is a progressive neurodegenerative disease characterized by cognitive decline and memory deficits. Despite its significant prevalence and impact, the pathophysiology of VaD remains poorly understood, and current treatments are limited to symptom management. Emerging evidence highlights the importance of lifestyle-associated risk factors in VaD, emphasizing the role of gene-environment interactions, particularly in the realm of epigenetics. While preclinical studies using animal models have provided valuable insights into epigenetic mechanisms, the translatability of these findings to human clinical settings remains limited, and research into VaD-specific epigenetics is still in its infancy. This review aims to elucidate the intricate interplay between epigenetics and VaD, shedding light on potential therapeutic interventions rooted in epigenetic mechanisms. By synthesizing insights from existing literature, we also discuss the challenges and opportunities in translating preclinical findings into clinically viable treatments, underscoring the need for further research to bridge the gap between animal models and human applications.

Histone H4 lysine 20 monomethylation is not a mark of transcriptional silencers

Transcriptional silencers are cis-regulatory elements that downregulate the expression of target genes. Although thousands of silencers have been identified experimentally, a predictive chromatin signature of silencers has not been found. H4K20me1 previously was reported to be highly enriched among human silencers, but our reanalysis of those data using an appropriate background revealed that the enrichment is only marginal. We generated H4K20me1 ChIP-seq profiles in Drosophila S2 cells, which similarly showed that H4K20me1 does not mark Drosophila silencers and instead is associated with active transcription. Silencers remain a poorly annotated, difficult to predict class of cis-regulatory elements whose specific chromatin features remain to be identified.

Phosphoinositide signaling in the nucleus: Impacts on chromatin and transcription regulation

Phosphoinositides also called Polyphosphoinositides (PPIns) are small lipid messengers with established key roles in organelle trafficking and cell signaling in response to physiological and environmental inputs. Besides their well-described functions in the cytoplasm, accumulating evidences pointed to PPIns involvement in transcription and chromatin regulation. Through the description of previous and recent advances of PPIns implication in transcription, this review highlights key discoveries on how PPIns modulate nuclear factors activity and might impact chromatin to modify gene expression. Finally, we discuss how PPIns nuclear and cytosolic metabolisms work jointly in orchestrating key transduction cascades that end in the nucleus to modulate gene expression.

The GTE4-EML chromatin reader complex concurrently recognizes histone acetylation and H3K4 trimethylation in Arabidopsis

Histone acetylation and H3K4 trimethylation (H3K4me3) are associated with active transcription. However, how they cooperate to regulate transcription in plants remains largely unclear. Our study revealed that GLOBAL TRANSCRIPTION FACTOR GROUP E 4 (GTE4) binds to acetylated histones and forms a complex with the functionally redundant H3K4me3-binding EMSY-like proteins EML1 or EML2 (EML1/2) in Arabidopsis thaliana. The eml1 eml2 (eml1/2) double mutant exhibits a similar morphological phenotype to gte4, and most of the differentially expressed genes in gte4 were coregulated in eml1/2. Through chromatin immunoprecipitation followed by deep sequencing, we found that GTE4 and EML2 co-occupy protein-coding genes enriched with both histone acetylation and H3K4me3, exerting a synergistic effect on the association of the GTE4-EML complex with chromatin. The association of GTE4 with chromatin requires both its bromodomain and EML-interacting domain. This study identified a complex and uncovered how it concurrently recognizes histone acetylation and H3K4me3 to facilitate gene transcription at the whole-genome level in Arabidopsis.

Kidney toxicology of a novel compound Lithium Bis(trifluoromethanesulfonyl)imide (LiTFSI, ie. HQ-115) used in energy applications: An epigenetic perspective

Exposure to emerging energy-based environmental contaminants such as lithium bis(trifluoromethanesulfonyl)imide (LiTFSI, trade name HQ-115), poses a significant threat to human health, yet its impact on kidney function and epigenetic regulation remains poorly understood. Here, we investigated the effects of LiTFSI exposure on kidney-related biochemical indicators, renal injuries, and epigenetic alterations in male CD-1 mice under both 14-day and 30-day exposure durations. Our study revealed that LiTFSI exposure led to changes in kidney-related markers, notably affecting serum bicarbonate levels, while relative kidney weight remained unaffected. Histological analysis revealed tubule dilation, inflammation, and loss of kidney structure in LiTFSI-exposed mice, alongside dysregulated expression of genes associated with inflammation, renal function, and uric acid metabolism. Epigenetic analysis further identified widespread DNA methylation changes in the two exposure regimes. Functional analysis revealed that differentially methylated regions are implicated in cell apoptosis and cancer-related pathways and are enriched with development-related transcription factor binding motifs, suggesting a potential mechanism of action underlying exposure induced kidney damage. These findings underscore the intricate interplay between environmental exposures, epigenetic modulation, and kidney health, emphasizing the need for additional research to unravel precise mechanisms and develop targeted interventions to mitigate the adverse effects of LiTFSI and exposure of similar clean energy compounds on human health.

Mapping protein-DNA interactions with DiMeLo-seq

We recently developed directed methylation with long-read sequencing (DiMeLo-seq) to map protein-DNA interactions genome wide. DiMeLo-seq is capable of mapping multiple interaction sites on single DNA molecules, profiling protein binding in the context of endogenous DNA methylation, identifying haplotype-specific protein-DNA interactions and mapping protein-DNA interactions in repetitive regions of the genome that are difficult to study with short-read methods. With DiMeLo-seq, adenines in the vicinity of a protein of interest are methylated in situ by tethering the Hia5 methyltransferase to an antibody using protein A. Protein-DNA interactions are then detected by direct readout of adenine methylation with long-read, single-molecule DNA sequencing platforms such as Nanopore sequencing. Here we present a detailed protocol and practical guidance for performing DiMeLo-seq. This protocol can be run on nuclei from fresh, lightly fixed or frozen cells. The protocol requires 1-2 d for performing in situ targeted methylation, 1-5 d for library preparation depending on desired fragment length and 1-3 d for Nanopore sequencing depending on desired sequencing depth. The protocol requires basic molecular biology skills and equipment, as well as access to a Nanopore sequencer. We also provide a Python package, dimelo, for analysis of DiMeLo-seq data.

Predicting the effect of CRISPR-Cas9-based epigenome editing

Epigenetic regulation orchestrates mammalian transcription, but functional links between them remain elusive. To tackle this problem, we use epigenomic and transcriptomic data from 13 ENCODE cell types to train machine learning models to predict gene expression from histone post-translational modifications (PTMs), achieving transcriptome-wide correlations of ~ 0.70 - 0.79 for most cell types. Our models recapitulate known associations between histone PTMs and expression patterns, including predicting that acetylation of histone subunit H3 lysine residue 27 (H3K27ac) near the transcription start site (TSS) significantly increases expression levels. To validate this prediction experimentally and investigate how natural vs. engineered deposition of H3K27ac might differentially affect expression, we apply the synthetic dCas9-p300 histone acetyltransferase system to 8 genes in the HEK293T cell line and to 5 genes in the K562 cell line. Further, to facilitate model building, we perform MNase-seq to map genome-wide nucleosome occupancy levels in HEK293T. We observe that our models perform well in accurately ranking relative fold-changes among genes in response to the dCas9-p300 system; however, their ability to rank fold-changes within individual genes is noticeably diminished compared to predicting expression across cell types from their native epigenetic signatures. Our findings highlight the need for more comprehensive genome-scale epigenome editing datasets, better understanding of the actual modifications made by epigenome editing tools, and improved causal models that transfer better from endogenous cellular measurements to perturbation experiments. Together these improvements would facilitate the ability to understand and predictably control the dynamic human epigenome with consequences for human health.

Translation of genome-wide association study: from genomic signals to biological insights

Since the turn of the 21st century, genome-wide association study (GWAS) have successfully identified genetic signals associated with a myriad of common complex traits and diseases. As we transition from establishing robust genetic associations with diverse phenotypes, the central challenge is now focused on characterizing the underlying functional mechanisms driving these signals. Previous GWAS efforts have revealed multiple variants, each conferring relatively subtle susceptibility, collectively contributing to the pathogenesis of various common diseases. Such variants can further exhibit associations with multiple other traits and differ across ancestries, plus disentangling causal variants from non-causal due to linkage disequilibrium complexities can lead to challenges in drawing direct biological conclusions. Combined with cellular context considerations, such challenges can reduce the capacity to definitively elucidate the biological significance of GWAS signals, limiting the potential to define mechanistic insights. This review will detail current and anticipated approaches for functional interpretation of GWAS signals, both in terms of characterizing the underlying causal variants and the corresponding effector genes.

DeepCBA: A deep learning framework for gene expression prediction in maize based on DNA sequences and chromatin interactions

Chromatin interactions create spatial proximity between distal regulatory elements and target genes in the genome, which has an important impact on gene expression, transcriptional regulation, and phenotypic traits. To date, several methods have been developed for predicting gene expression. However, existing methods do not take into consideration the effect of chromatin interactions on target gene expression, thus potentially reducing the accuracy of gene expression prediction and mining of important regulatory elements. In this study, we developed a highly accurate deep learning-based gene expression prediction model (DeepCBA) based on maize chromatin interaction data. Compared with existing models, DeepCBA exhibits higher accuracy in expression classification and expression value prediction. The average Pearson correlation coefficients (PCCs) for predicting gene expression using gene promoter proximal interactions, proximal-distal interactions, and both proximal and distal interactions were 0.818, 0.625, and 0.929, respectively, representing an increase of 0.357, 0.16, and 0.469 over the PCCs obtained with traditional methods that use only gene proximal sequences. Some important motifs were identified through DeepCBA; they were enriched in open chromatin regions and expression quantitative trait loci and showed clear tissue specificity. Importantly, experimental results for the maize flowering-related gene ZmRap2.7 and the tillering-related gene ZmTb1 demonstrated the feasibility of DeepCBA for exploration of regulatory elements that affect gene expression. Moreover, promoter editing and verification of two reported genes (ZmCLE7 and ZmVTE4) demonstrated the utility of DeepCBA for the precise design of gene expression and even for future intelligent breeding. DeepCBA is available at http://www.deepcba.com/ or http://124.220.197.196/.

Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state regulatory potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbor distinctive transcription factor binding motifs that are similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we show that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

CatLearning: highly accurate gene expression prediction from histone mark

Histone modifications, known as histone marks, are pivotal in regulating gene expression within cells. The vast array of potential combinations of histone marks presents a considerable challenge in decoding the regulatory mechanisms solely through biological experimental approaches. To overcome this challenge, we have developed a method called CatLearning. It utilizes a modified convolutional neural network architecture with a specialized adaptation Residual Network to quantitatively interpret histone marks and predict gene expression. This architecture integrates long-range histone information up to 500Kb and learns chromatin interaction features without 3D information. By using only one histone mark, CatLearning achieves a high level of accuracy. Furthermore, CatLearning predicts gene expression by simulating changes in histone modifications at enhancers and throughout the genome. These findings help comprehend the architecture of histone marks and develop diagnostic and therapeutic targets for diseases with epigenetic changes.

GENet: A Graph-Based Model Leveraging Histone Marks and Transcription Factors for Enhanced Gene Expression Prediction

Understanding the regulatory mechanisms of gene expression is a crucial objective in genomics. Although the DNA sequence near the transcription start site (TSS) offers valuable insights, recent methods suggest that analyzing only the surrounding DNA may not suffice to accurately predict gene expression levels. We developed GENet (Gene Expression Network from Histone and Transcription Factor Integration), a novel approach that integrates essential regulatory signals from transcription factors and histone modifications into a graph-based model. GENet extends beyond simple DNA sequence analysis by incorporating additional layers of genetic control, which are vital for determining gene expression. Our method markedly enhances the prediction of mRNA levels compared to previous models that depend solely on DNA sequence data. The results underscore the significance of including comprehensive regulatory information in gene expression studies. GENet emerges as a promising tool for researchers, with potential applications extending from fundamental biological research to the development of medical therapies.

Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma

Cancer cells show remarkable plasticity and can switch lineages in response to the tumor microenvironment. Cellular plasticity drives invasiveness and metastasis and helps cancer cells to evade therapy by developing resistance to radiation and cytotoxic chemotherapy. Increased understanding of cell fate determination through epigenetic reprogramming is critical to discover how cancer cells achieve transcriptomic and phenotypic plasticity. Glioblastoma is a perfect example of cancer evolution where cells retain an inherent level of plasticity through activation or maintenance of progenitor developmental programs. However, the principles governing epigenetic drivers of cellular plasticity in glioblastoma remain poorly understood. Here, using machine learning (ML) we employ cross-patient prediction of transcript expression using a combination of epigenetic features (ATAC-seq, CTCF ChIP-seq, RNAPII ChIP-seq, H3K27Ac ChIP-seq, and RNA-seq) of glioblastoma stem cells (GSCs). We investigate different ML and deep learning (DL) models for this task and build our final pipeline using XGBoost. The model trained on one patient generalizes to another one suggesting that the epigenetic signals governing gene transcription are consistent across patients even if GSCs can be very different. We demonstrate that H3K27Ac is the epigenetic feature providing the most significant contribution to cross-patient prediction of gene expression. In addition, using H3K27Ac signals from patients-derived GSCs, we can predict gene expression of human neural crest stem cells suggesting a shared developmental epigenetic trajectory between subpopulations of these malignant and benign stem cells. Our cross-patient ML/DL models determine weighted patterns of influence of epigenetic marks on gene expression across patients with glioblastoma and between GSCs and neural crest stem cells. We propose that broader application of this analysis could reshape our view of glioblastoma tumor evolution and inform the design of new epigenetic targeting therapies.

Whole-genome landscape of histone H3K4me3 modification during sperm cell lineage development in tomato

BACKGROUND

During male gametogenesis of flowering plants, sperm cell lineage (microspores, generative cells, and sperm cells) differentiated from somatic cells and acquired different cell fates. Trimethylation of histone H3 on lysine 4 (H3K4me3) epigenetically contributes to this process, however, it remained unclear how H3K4me3 influences the gene expression in each cell type. Here, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) to obtain a genome-wide landscape of H3K4me3 during sperm cell lineage development in tomato (Solanum lycopersicum).

RESULTS

We show that H3K4me3 peaks were mainly enriched in the promoter regions, and intergenic H3K4me3 peaks expanded as sperm cell lineage differentiated from somatic cells. H3K4me3 was generally positively associated with transcript abundance and served as a better indicator of gene expression in somatic and vegetative cells, compared to sperm cell lineage. H3K4me3 was mutually exclusive with DNA methylation at 3' proximal of the transcription start sites. The microspore maintained the H3K4me3 features of somatic cells, while generative cells and sperm cells shared an almost identical H3K4me3 pattern which differed from that of the vegetative cell. After microspore division, significant loss of H3K4me3 in genes related to brassinosteroid and cytokinin signaling was observed in generative cells and vegetative cells, respectively.

CONCLUSIONS

Our results suggest the asymmetric division of the microspore significantly reshapes the genome-wide distribution of H3K4me3. Selective loss of H3K4me3 in genes related to hormone signaling may contribute to functional differentiation of sperm cell lineage. This work provides new resource data for the epigenetic studies of gametogenesis in plants.

Acetylation of histones and non-histone proteins is not a mere consequence of ongoing transcription

In all eukaryotes, acetylation of histone lysine residues correlates with transcription activation. Whether histone acetylation is a cause or consequence of transcription is debated. One model suggests that transcription promotes the recruitment and/or activation of acetyltransferases, and histone acetylation occurs as a consequence of ongoing transcription. However, the extent to which transcription shapes the global protein acetylation landscapes is not known. Here, we show that global protein acetylation remains virtually unaltered after acute transcription inhibition. Transcription inhibition ablates the co-transcriptionally occurring ubiquitylation of H2BK120 but does not reduce histone acetylation. The combined inhibition of transcription and CBP/p300 further demonstrates that acetyltransferases remain active and continue to acetylate histones independently of transcription. Together, these results show that histone acetylation is not a mere consequence of transcription; acetyltransferase recruitment and activation are uncoupled from the act of transcription, and histone and non-histone protein acetylation are sustained in the absence of ongoing transcription.

Effect of genomic and cellular environments on gene expression noise

BACKGROUND

Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome.

RESULTS

To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci.

CONCLUSIONS

Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.

Adolescent binge ethanol impacts H3K9me3-occupancy at synaptic genes and the regulation of oligodendrocyte development

Introduction

Binge drinking in adolescence can disrupt myelination and cause brain structural changes that persist into adulthood. Alcohol consumption at a younger age increases the susceptibility of these changes. Animal models to understand ethanol's actions on myelin and white matter show that adolescent binge ethanol can alter the developmental trajectory of oligodendrocytes, myelin structure, and myelin fiber density. Oligodendrocyte differentiation is epigenetically regulated by H3K9 trimethylation (H3K9me3). Prior studies have shown that adolescent binge ethanol dysregulates H3K9 methylation and decreases H3K9-related gene expression in the PFC.

Methods

Here, we assessed ethanol-induced changes to H3K9me3 occupancy at genomic loci in the developing adolescent PFC. We further assessed ethanol-induced changes at the transcription level with qPCR time course approaches in oligodendrocyte-enriched cells to assess changes in oligodendrocyte progenitor and oligodendrocytes specifically.

Results

Adolescent binge ethanol altered H3K9me3 regulation of synaptic-related genes and genes specific for glutamate and potassium channels in a sex-specific manner. In PFC tissue, we found an early change in gene expression in transcription factors associated with oligodendrocyte differentiation that may lead to the later significant decrease in myelin-related gene expression. This effect appeared stronger in males.

Conclusion

Further exploration in oligodendrocyte cell enrichment time course and dose response studies could suggest lasting dysregulation of oligodendrocyte maturation at the transcriptional level. Overall, these studies suggest that binge ethanol may impede oligodendrocyte differentiation required for ongoing myelin development in the PFC by altering H3K9me3 occupancy at synaptic-related genes. We identify potential genes that may be contributing to adolescent binge ethanol-related myelin loss.

Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

Transgenerational Effects of Arsenic Exposure on Learning and Memory in Rats: Crosstalk between Arsenic Methylation, Hippocampal Metabolism, and Histone Modifications

Arsenic (As) is widely present in the natural environment, and exposure to it can lead to learning and memory impairment. However, the underlying epigenetic mechanisms are still largely unclear. This study aimed to reveal the role of histone modifications in environmental levels of arsenic (sodium arsenite) exposure-induced learning and memory dysfunction in male rats, and the inter/transgenerational effects of paternal arsenic exposure were also investigated. It was found that arsenic exposure impaired the learning and memory ability of F0 rats and down-regulated the expression of cognition-related genes Bdnf, c-Fos, mGlur1, Nmdar1, and Gria2 in the hippocampus. We also observed that inorganic arsenite was methylated to DMA and histone modification-related metabolites were altered, contributing to the dysregulation of H3K4me1/2/3, H3K9me1/2/3, and H3K4ac in rat hippocampus after exposure. Therefore, it is suggested that arsenic methylation and hippocampal metabolism changes attenuated H3K4me1/2/3 and H3K4ac while enhancing H3K9me1/2/3, which repressed the key gene expressions, leading to cognitive impairment in rats exposed to arsenic. In addition, paternal arsenic exposure induced transgenerational effects of learning and memory disorder in F2 male rats through the regulation of H3K4me2 and H3K9me1/2/3, which inhibited c-Fos, mGlur1, and Nmdar1 expression. These results provide novel insights into the molecular mechanism of arsenic-induced neurotoxicity and highlight the risk of neurological deficits in offspring with paternal exposure to arsenic.

Quantifying transcriptome diversity: a review

Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.

An epigenetic timer regulates the transition from cell division to cell expansion during Arabidopsis petal organogenesis

A number of studies have demonstrated that epigenetic factors regulate plant developmental timing in response to environmental changes. However, we still have an incomplete view of how epigenetic factors can regulate developmental events such as organogenesis, and the transition from cell division to cell expansion, in plants. 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 study, we investigated how the RABBIT EARS (RBE) transcriptional repressor maintains the downregulation of its downstream direct target, TCP5, long after RBE expression dissipates. We showed that RBE recruits the Groucho/Tup1-like corepressor TOPLESS (TPL) to repress TCP5 transcription in petal primordia. This process involves multiple layers of changes such as remodeling of chromatin accessibility, alteration of RNA polymerase activity, and histone modifications, resulting in an epigenetic memory that is maintained through multiple cell divisions. This memory functions to maintain cell divisions during the early phase of petal development, and its attenuation in a cell division-dependent fashion later in development enables the transition from cell division to cell expansion. Overall, this study unveils a novel mechanism by which the memory of an epigenetic state, and its cell-cycle regulated decay, acts as a timer to precisely control organogenesis.

Deep learning models incorporating endogenous factors beyond DNA sequences improve the prediction accuracy of base editing outcomes

Adenine base editors (ABEs) and cytosine base editors (CBEs) enable the single nucleotide editing of targeted DNA sites avoiding generation of double strand breaks, however, the genomic features that influence the outcomes of base editing in vivo still remain to be characterized. High-throughput datasets from lentiviral integrated libraries were used to investigate the sequence features affecting base editing outcomes, but the effects of endogenous factors beyond the DNA sequences are still largely unknown. Here the base editing outcomes of ABE and CBE were evaluated in mammalian cells for 5012 endogenous genomic sites and 11,868 genome-integrated target sequences, with 4654 genomic sites sharing the same target sequences. The comparative analyses revealed that the editing outcomes of ABE and CBE at endogenous sites were substantially different from those obtained using genome-integrated sequences. We found that the base editing efficiency at endogenous target sites of both ABE and CBE was influenced by endogenous factors, including epigenetic modifications and transcriptional activity. A deep-learning algorithm referred as BE_Endo, was developed based on the endogenous factors and sequence information from our genomic datasets, and it yielded unprecedented accuracy in predicting the base editing outcomes. These findings along with the developed computational algorithms may facilitate future application of BEs for scientific research and clinical gene therapy.

Machine learning unveils RNA polymerase II binding as a predictor for SMAD2-dependent transcription dynamics in response to Actvin signalling

The transforming growth factor-β (TGF-β) superfamily, including Nodal and Activin, plays a critical role in various cellular processes. Understanding the intricate regulation and gene expression dynamics of TGF-β signalling is of interest due to its diverse biological roles. A machine learning approach is used to predict gene expression patterns induced by Activin using features, such as histone modifications, RNA polymerase II binding, SMAD2-binding, and mRNA half-life. RNA sequencing and ChIP sequencing datasets were analysed and differentially expressed SMAD2-binding genes were identified. These genes were classified into activated and repressed categories based on their expression patterns. The predictive power of different features and combinations was evaluated using logistic regression models and their performances were assessed. Results showed that RNA polymerase II binding was the most informative feature for predicting the expression patterns of SMAD2-binding genes. The authors provide insights into the interplay between transcriptional regulation and Activin signalling and offers a computational framework for predicting gene expression patterns in response to cell signalling.

MAE-seq refines regulatory elements across the genome

Proper cell fate determination relies on precise spatial and temporal genome-wide cooperation between regulatory elements (REs) and their targeted genes. However, the lengths of REs defined using different methods vary, which indicates that there is sequence redundancy and that the context of the genome may be unintelligible. We developed a method called MAE-seq (Massive Active Enhancers by Sequencing) to experimentally identify functional REs at a 25-bp scale. In this study, MAE-seq was used to identify 626879, 541617 and 554826 25-bp enhancers in mouse embryonic stem cells (mESCs), C2C12 and HEK 293T, respectively. Using ∼1.6 trillion 25 bp DNA fragments and screening 12 billion cells, we identified 626879 as active enhancers in mESCs as an example. Comparative analysis revealed that most of the histone modification datasets were annotated by MAE-Seq loci. Furthermore, 33.85% (212195) of the identified enhancers were identified as de novo ones with no epigenetic modification. Intriguingly, distinct chromatin states dictate the requirement for dissimilar cofactors in governing novel and known enhancers. Validation results show that these 25-bp sequences could act as a functional unit, which shows identical or similar expression patterns as the previously defined larger elements, Enhanced resolution facilitated the identification of numerous cell-specific enhancers and their accurate annotation as super enhancers. Moreover, we characterized novel elements capable of augmenting gene activity. By integrating with high-resolution Hi-C data, over 55.64% of novel elements may have a distal association with different targeted genes. For example, we found that the Cdh1 gene interacts with one novel and two known REs in mESCs. The biological effects of these interactions were investigated using CRISPR-Cas9, revealing their role in coordinating Cdh1 gene expression and mESC proliferation. Our study presents an experimental approach to refine the REs at 25-bp resolution, advancing the precision of genome annotation and unveiling the underlying genome context. This novel approach not only advances our understanding of gene regulation but also opens avenues for comprehensive exploration of the genomic landscape.

JMnorm: a novel joint multi-feature normalization method for integrative and comparative epigenomics

Combinatorial patterns of epigenetic features reflect transcriptional states and functions of genomic regions. While many epigenetic features have correlated relationships, most existing data normalization approaches analyze each feature independently. Such strategies may distort relationships between functionally correlated epigenetic features and hinder biological interpretation. We present a novel approach named JMnorm that simultaneously normalizes multiple epigenetic features across cell types, species, and experimental conditions by leveraging information from partially correlated epigenetic features. We demonstrate that JMnorm-normalized data can better preserve cross-epigenetic-feature correlations across different cell types and enhance consistency between biological replicates than data normalized by other methods. Additionally, we show that JMnorm-normalized data can consistently improve the performance of various downstream analyses, which include candidate cis-regulatory element clustering, cross-cell-type gene expression prediction, detection of transcription factor binding and changes upon perturbations. These findings suggest that JMnorm effectively minimizes technical noise while preserving true biologically significant relationships between epigenetic datasets. We anticipate that JMnorm will enhance integrative and comparative epigenomics.

Epigenomic Characterization of Lymphoid Neoplasms

Lymphoid neoplasms represent a heterogeneous group of disease entities and subtypes with markedly different molecular and clinical features. Beyond genetic alterations, lymphoid tumors also show widespread epigenomic changes. These severely affect the levels and distribution of DNA methylation, histone modifications, chromatin accessibility, and three-dimensional genome interactions. DNA methylation stands out as a tracer of cell identity and memory, as B cell neoplasms show epigenetic imprints of their cellular origin and proliferative history, which can be quantified by an epigenetic mitotic clock. Chromatin-associated marks are informative to uncover altered regulatory regions and transcription factor networks contributing to the development of distinct lymphoid tumors. Tumor-intrinsic epigenetic and genetic aberrations cooperate and interact with microenvironmental cells to shape the transcriptome at different phases of lymphoma evolution, and intraclonal heterogeneity can now be characterized by single-cell profiling. Finally, epigenetics offers multiple clinical applications, including powerful diagnostic and prognostic biomarkers as well as therapeutic targets.

Pig H3K4me3, H3K27ac, and gene expression profiles reveal reproductive tissue-specific activity of transposable elements

Regulatory sequences and transposable elements (TEs) account for a large proportion of the genomic sequences of species; however, their roles in gene transcription, especially tissue-specific expression, remain largely unknown. Pigs serve as an excellent animal model for studying genomic sequence biology due to the extensive diversity among their wild and domesticated populations. Here, we conducted an integrated analysis using H3K27ac ChIP-seq, H3K4me3 ChIP-seq, and RNA-seq data from 10 different tissues of seven fetuses and eight closely related adult pigs. We aimed to annotate the regulatory elements and TEs to elucidate their associations with histone modifications and mRNA expression across different tissues and developmental stages. Based on correlation analysis between mRNA expression and H3K27ac and H3K4me3 peak activity, results indicated that H3K27ac exhibited stronger associations with gene expression than H3K4me3. Furthermore, 1.45% of TEs overlapped with either the H3K27ac or H3K4me3 peaks, with the majority displaying tissue-specific activity. Notably, a TE subfamily (LTR4C_SS), containing binding motifs for SIX1 and SIX4, showed specific enrichment in the H3K27ac peaks of the adult and fetal ovaries. RNA-seq analysis also revealed widespread expression of TEs in the exons or promoters of genes, including 4 688 TE-containing transcripts with distinct development stage-specific and tissue-specific expression. Of note, 1 967 TE-containing transcripts were enriched in the testes. We identified a long terminal repeat (LTR), MLT1F1, acting as a testis-specific alternative promoter in SRPK2 (a cell cycle-related protein kinase) in our pig dataset. This element was also conserved in humans and mice, suggesting either an ancient integration of TEs in genes specifically expressed in the testes or parallel evolutionary patterns. Collectively, our findings demonstrate that TEs are deeply embedded in the genome and exhibit important tissue-specific biological functions, particularly in the reproductive organs.

Chromatin activity identifies differential gene regulation across human ancestries

BACKGROUND

Current evidence suggests that cis-regulatory elements controlling gene expression may be the predominant target of natural selection in humans and other species. Detecting selection acting on these elements is critical to understanding evolution but remains challenging because we do not know which mutations will affect gene regulation.

RESULTS

To address this, we devise an approach to search for lineage-specific selection on three critical steps in transcriptional regulation: chromatin activity, transcription factor binding, and chromosomal looping. Applying this approach to lymphoblastoid cells from 831 individuals of either European or African descent, we find strong signals of differential chromatin activity linked to gene expression differences between ancestries in numerous contexts, but no evidence of functional differences in chromosomal looping. Moreover, we show that enhancers rather than promoters display the strongest signs of selection associated with sites of differential transcription factor binding.

CONCLUSIONS

Overall, our study indicates that some cis-regulatory adaptation may be more easily detected at the level of chromatin than DNA sequence. This work provides a vast resource of genomic interaction data from diverse human populations and establishes a novel selection test that will benefit future study of regulatory evolution in humans and other species.

Epigenomic analysis of the myometrium during late implantation revealed regulatory elements in genes related to the cellular zinc homeostasis pathway in pigs

The myometrium, composed of the inner circular muscle (CM) and outer longitudinal muscle (LM), is crucial in establishing and maintaining early pregnancy. However, the molecular mechanisms involved are not well understood. In this study, we identified the transcriptomic features of the CM and LM collected from the mesometrial (M) and anti-mesometrial (AM) sides of the pig uterus on day 18 of pregnancy during the placentation initiation phase. Some genes in the cellular zinc ion level regulatory pathways (MT-1A, MT-1D, MT-2B, SLC30A2, and SLC39A2) were spatially and highly enriched in uterine CM at the mesometrial side. In addition, the histone modification profiles of H3K27ac and H3K4me3 in uterine CM and LM collected from the mesometrial side were characterized. Genomic regions associated with the expression of genes regulating the cellular zinc ion level were detected. Moreover, six highly linked variants in the H3K27ac-enriched region of the pig SLC30A2 gene were identified and found to be significantly associated with the total number born at the second parity (P < 0.05). In conclusion, the genes in the pathways of cellular zinc homeostasis and their regulatory elements identified have implications for pig reproduction trait improvement and warrant further investigations.

Summary of ChIP-Seq Methods and Description of an Optimized ChIP-Seq Protocol

Chromatin immunoprecipitation (ChIP) is an invaluable method to characterize interactions between proteins and genomic DNA, such as the genomic localization of transcription factors and post-translational modification of histones. DNA and proteins are reversibly and covalently crosslinked using formaldehyde. Then the cells are lysed to release the chromatin. The chromatin is fragmented into smaller sizes either by micrococcal nuclease (MN) or sonication and then purified from other cellular components. The protein-DNA complexes are enriched by immunoprecipitation (IP) with antibodies that target the epitope of interest. The DNA is released from the proteins by heat and protease treatment, followed by degradation of contaminating RNAs with RNase. The resulting DNA is analyzed using various methods, including polymerase chain reaction (PCR), quantitative PCR (qPCR), or sequencing. This protocol outlines each of these steps for both yeast and human cells. This chapter includes a contextual discussion of the combination of ChIP with DNA analysis methods such as ChIP-on-Chip, ChIP-qPCR, and ChIP-Seq, recent updates on ChIP-Seq data analysis pipelines, complementary methods for identification of binding sites of DNA binding proteins, and additional protocol information about ChIP-qPCR and ChIP-Seq.

Novel stripe rust effector boosts the transcription of a host susceptibility factor through affecting histone modification to promote infection in wheat

Regulation of host gene expression to promote disease is a common strategy for plant pathogens. However, it remains unclear whether or not fungal pathogens manipulate host gene expression directly through secreted effectors with transcriptional activity. Here, we identified a fungal effector PstGTA1 from Puccinia striiformis f. sp. tritici (Pst), which has partial homology to the subunit of global transcriptional activator SNF2 from oyster. The transcriptional activating activity of PstGTA1 was validated in yeast, and the potential role of PstGTA1 in pathogenicity was assessed using gene silenced and overexpression transgenic wheat plants. Candidate targets regulated by PstGTA1 were screened by transcriptomic analysis, and the specific promoter region binding to PstGTA1 was further determined. PstGTA1 can be delivered to the wheat cell nucleus and contributes to the full virulence of Pst by targeting the promoter of TaSIG, a gene negatively regulating wheat immunity, and possibly activates its transcription by affecting the histone H3K4 acetylation level. Our study provides the first direct evidence for a fungal effector with transactivation activity modulating the transcription of a host specific susceptibility gene through promoter binding and histone acetylation.

The SMYD3-dependent H3K4me3 status of IGF2 intensifies local Th2 differentiation in CRSwNP via positive feedback

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous and common upper airway disease divided into various inflammatory endotypes. Recent epidemiological findings showed a T helper 2 (Th2)-skewed dominance in CRSwNP patients. Histone modification alterations can regulate transcriptional and translational expression, resulting in abnormal pathogenic changes and the occurrence of diseases. Trimethylation of histone H3 lysine 4 (H3K4me3) is considered an activator of gene expression through modulation of accessibility for transcription, which is closely related to CRSwNP. H3K4me3 levels in the human nasal epithelium may change under Th2-biased inflammatory conditions, resulting in exaggerated local nasal Th2 responses via the regulation of naïve CD4+ T-cell differentiation. Here, we revealed that the level of SET and MYND domain-containing protein 3 (SMYD3)-mediated H3K4me3 was increased in NPs from Th2 CRSwNP patients compared with those from healthy controls. We demonstrated that SMYD3-mediated H3K4me3 is increased in human nasal epithelial cells under Th2-biased inflammatory conditions via S-adenosyl-L-methionine (SAM) production and further found that the H3K4me3high status of insulin-like growth factor 2 (IGF2) produced in primary human nasal epithelial cells could promote naïve CD4+ T-cell differentiation into Th2 cells. Moreover, we found that SAM production was dependent on the c-Myc/methionine adenosyltransferase 2A (MAT2A) axis in the nasal epithelium. Understanding histone modifications in the nasal epithelium has immense potential utility in the development of novel classes of therapeutics targeting Th2 polarization in Th2 CRSwNP. Video Abstract.

MiREx: mRNA levels prediction from gene sequence and miRNA target knowledge

Messenger RNA (mRNA) has an essential role in the protein production process. Predicting mRNA expression levels accurately is crucial for understanding gene regulation, and various models (statistical and neural network-based) have been developed for this purpose. A few models predict mRNA expression levels from the DNA sequence, exploiting the DNA sequence and gene features (e.g., number of exons/introns, gene length). Other models include information about long-range interaction molecules (i.e., enhancers/silencers) and transcriptional regulators as predictive features, such as transcription factors (TFs) and small RNAs (e.g., microRNAs - miRNAs). Recently, a convolutional neural network (CNN) model, called Xpresso, has been proposed for mRNA expression level prediction leveraging the promoter sequence and mRNAs' half-life features (gene features). To push forward the mRNA level prediction, we present miREx, a CNN-based tool that includes information about miRNA targets and expression levels in the model. Indeed, each miRNA can target specific genes, and the model exploits this information to guide the learning process. In detail, not all miRNAs are included, only a selected subset with the highest impact on the model. MiREx has been evaluated on four cancer primary sites from the genomics data commons (GDC) database: lung, kidney, breast, and corpus uteri. Results show that mRNA level prediction benefits from selected miRNA targets and expression information. Future model developments could include other transcriptional regulators or be trained with proteomics data to infer protein levels.

Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models

The data explosion driven by advancements in genomic research, such as high-throughput sequencing techniques, is constantly challenging conventional methods used in genomics. In parallel with the urgent demand for robust algorithms, deep learning has succeeded in various fields such as vision, speech, and text processing. Yet genomics entails unique challenges to deep learning, since we expect a superhuman intelligence that explores beyond our knowledge to interpret the genome from deep learning. A powerful deep learning model should rely on the insightful utilization of task-specific knowledge. In this paper, we briefly discuss the strengths of different deep learning models from a genomic perspective so as to fit each particular task with proper deep learning-based architecture, and we remark on practical considerations of developing deep learning architectures for genomics. We also provide a concise review of deep learning applications in various aspects of genomic research and point out current challenges and potential research directions for future genomics applications. We believe the collaborative use of ever-growing diverse data and the fast iteration of deep learning models will continue to contribute to the future of genomics.

Wolf-Hirschhorn syndrome candidate 1 (Whsc1) methyltransferase signals via a Pitx2-miR-23/24 axis to effect tooth development

Wolf-Hirschhorn syndrome (WHS) is a developmental disorder attributed to a partial deletion on the short arm of chromosome 4. WHS patients suffer from oral manifestations including cleft lip and palate, hypodontia, and taurodontism. WHS candidate 1 (WHSC1) gene is a H3K36-specific methyltransferase that is deleted in every reported case of WHS. Mutation in this gene also results in tooth anomalies in patients. However, the correlation between genetic abnormalities and the tooth anomalies has remained controversial. In our study, we aimed to clarify the role of WHSC1 in tooth development. We profiled the Whsc1 expression pattern during mouse incisor and molar development by immunofluorescence staining and found Whsc1 expression is reduced as tooth development proceeds. Using real-time quantitative reverse transcription PCR, Western blot, chromatin immunoprecipitation, and luciferase assays, we determined that Whsc1 and Pitx2, the initial transcription factor involved in tooth development, positively and reciprocally regulate each other through their gene promoters. miRNAs are known to regulate gene expression posttranscriptionally during development. We previously reported miR-23a/b and miR-24-1/2 were highly expressed in the mature tooth germ. Interestingly, we demonstrate here that these two miRs directly target Whsc1 and repress its expression. Additionally, this miR cluster is also negatively regulated by Pitx2. We show the expression of these two miRs and Whsc1 are inversely correlated during mouse mandibular development. Taken together, our results provide new insights into the potential role of Whsc1 in regulating tooth development and a possible molecular mechanism underlying the dental defects in WHS.

Lineage commitment of dermal fibroblast progenitors is controlled by Kdm6b-mediated chromatin demethylation

Dermal Fibroblast Progenitors (DFPs) differentiate into distinct fibroblast lineages during skin development. However, the epigenetic mechanisms that regulate DFP differentiation are not known. Our objective was to use multimodal single-cell approaches, epigenetic assays, and allografting techniques to define a DFP state and the mechanism that governs its differentiation potential. Our initial results indicated that the overall transcription profile of DFPs is repressed by H3K27me3 and has inaccessible chromatin at lineage-specific genes. Surprisingly, the repressive chromatin profile of DFPs renders them unable to reform the skin in allograft assays despite their multipotent potential. We hypothesized that chromatin derepression was modulated by the H3K27me3 demethylase, Kdm6b/Jmjd3. Dermal fibroblast-specific deletion of Kdm6b/Jmjd3 in mice resulted in adipocyte compartment ablation and inhibition of mature dermal papilla functions, confirmed by additional single-cell RNA-seq, ChIP-seq, and allografting assays. We conclude that DFPs are functionally derepressed during murine skin development by Kdm6b/Jmjd3. Our studies therefore reveal a multimodal understanding of how DFPs differentiate into distinct fibroblast lineages and provide a novel publicly available multiomics search tool.

Genome-wide binding sites of Plasmodium falciparum mini chromosome maintenance protein MCM6 show new insights into parasite DNA replication

Multiple rounds of DNA replication take place in various stages of the life cycle in the human malaria parasite Plasmodium falciparum. Previous bioinformatics analysis has shown the presence of putative Autonomously Replicating Sequence (ARS) like sequences in the Plasmodium genome. However, the actual sites and frequency of replication origins in the P. falciparum genome based on experimental data still remain elusive. Minichromosome maintenance (MCM) proteins are recruited by the Origin recognition complex (ORC) to the origins of replication in eukaryotes including P. falciparum. We used PfMCM6 for chromatin immunoprecipitation followed by sequencing (ChIP-seq) in the quest for identification of putative replication origins in the parasite. PfMCM6 DNA binding sites annotation revealed high enrichment at exon regions. This is contrary to higher eukaryotes that show an inclination of origin sites towards transcriptional start sites. ChIP-seq results were further validated by ChIP-qPCR results as well as nascent strand abundance assay at the selected PfMCM6 enriched sites that also showed preferential binding of PfORC1 suggesting potential of these sites as origin sites. Further, PfMCM6 ChIP-seq data showed a positive correlation with previously published histone H4K8Ac genome-wide binding sites but not with H3K9Ac sites suggesting epigenetic control of replication initiation sites in the parasites. Overall, our data show the genome-wide distribution of PfMCM6 binding sites with their potential as replication origins in this deadly human pathogen that not only broadens our knowledge of parasite DNA replication and its unique biology, it may help to find new avenues for intervention processes.

Allele specific binding of histone modifications and a transcription factor does not predict allele specific expression in correlated ChIP-seq peak-exon pairs

Allele specific expression (ASE) is widespread in many species including cows. Therefore, regulatory regions which control gene expression should show cis-regulatory variation which mirrors this differential expression within the animal. ChIP-seq peaks for histone modifications and transcription factors measure activity at functional regions and the height of some peaks have been shown to correlate across tissues with the expression of particular genes, suggesting these peaks are putative regulatory regions. In this study we identified ASE in the bovine genome in multiple tissues and investigated whether ChIP-seq peaks for four histone modifications and the transcription factor CTCF show allele specific binding (ASB) differences in the same tissues. We then investigate whether peak height and gene expression, which correlates across tissues, also correlates within the animal by investigating whether the direction of ASB in putative regulatory regions, mirrors that of the ASE in the genes they are putatively regulating. We found that ASE and ASB were widespread in the bovine genome but vary in extent between tissues. However, even when the height of a peak was positively correlated across tissues with expression of an exon, ASE of the exon and ASB of the peak were in the same direction only half the time. A likely explanation for this finding is that the correlations between peak height and exon expression do not indicate that the height of the peak causes the extent of exon expression, at least in some cases.

Chromosome-Wide Distribution and Characterization of H3K36me3 and H3K27Ac in the Marine Model Diatom Phaeodactylum tricornutum

Histone methylation and acetylation play a crucial role in response to developmental cues and environmental changes. Previously, we employed mass spectrometry to identify histone modifications such as H3K27ac and H3K36me3 in the model diatom Phaeodactylum tricornutum, which have been shown to be important for transcriptional activation in animal and plant species. To further investigate their evolutionary implications, we utilized chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) and explored their genome-wide distribution in P. tricornutum. Our study aimed to determine their role in transcriptional regulation of genes and transposable elements (TEs) and their co-occurrence with other histone marks. Our results revealed that H3K27ac and H3K36me3 were predominantly localized in promoters and genic regions indicating a high conservation pattern with studies of the same marks in plants and animals. Furthermore, we report the diversity of genes encoding H3 lysine 36 (H3K36) trimethylation-specific methyltransferase in microalgae leveraging diverse sequencing resources including the Marine Microbial Eukaryote Transcriptome Sequencing Project database (MMETSP). Our study expands the repertoire of epigenetic marks in a model microalga and provides valuable insights into the evolutionary context of epigenetic-mediated gene regulation. These findings shed light on the intricate interplay between histone modifications and gene expression in microalgae, contributing to our understanding of the broader epigenetic landscape in eukaryotic organisms.

ZSCAN4 Regulates Zygotic Genome Activation and Telomere Elongation in Porcine Parthenogenetic Embryos

Zinc finger and SCAN domain-containing 4 (ZSCAN4), a DNA-binding protein, maintains telomere length and plays a key role in critical aspects of mouse embryonic stem cells, including maintaining genomic stability and defying cellular senescence. However, the effect of ZSCAN4 in porcine parthenogenetic embryos remains unclear. To investigate the function of ZSCAN4 and the underlying mechanism in porcine embryo development, ZSCAN4 was knocked down via dsRNA injection in the one-cell stage. ZSCAN4 was highly expressed in the four- and five- to eight-cell stages in porcine embryos. The percentage of four-cell stage embryos, five- to eight-cell stage embryos, and blastocysts was lower in the ZSCAN4 knockdown group than in the control group. Notably, depletion of ZSCAN4 induced the protein expression of DNMT1 and 5-Methylcytosine (5mC, a methylated form of the DNA base cytosine) in the four-cell stage. The H3K27ac level and ZGA genes expression decreased following ZSCAN4 knockdown. Furthermore, ZSCAN4 knockdown led to DNA damage and shortened telomere compared with the control. Additionally, DNMT1-dsRNA was injected to reduce DNA hypermethylation in ZSCAN4 knockdown embryos. DNMT1 knockdown rescued telomere shortening and developmental defects caused by ZSCAN4 knockdown. In conclusion, ZSCAN4 is involved in the regulation of transcriptional activity and is essential for maintaining telomere length by regulating DNMT1 expression in porcine ZGA.

JARID2 and EZH2, The Eminent Epigenetic Drivers In Human Cancer

Cancer has become a prominent cause of death, accounting for approximately 10 million death worldwide as per the World Health Organization reports 2020. Epigenetics deal with the alterations of heritable phenotypes, except for DNA alterations. Currently, we are trying to comprehend the role of utmost significant epigenetic genes involved in the burgeoning of human cancer. A sundry of studies reported the Enhancer of Zeste Homologue2 (EZH2) as a prime catalytic subunit of Polycomb Repressive Complex2, which is involved in several pivotal activities, including embryogenesis. In addition, EZH2 has detrimental effects leading to the onset and metastasis of several cancers. Jumonji AT Rich Interacting Domain2 (JARID2), an undebated crucial nuclear factor, has strong coordination with the PRC2 family. In this review, we discuss various epigenetic entities, primarily focusing on the possible role and mechanism of EZH2 and the significant contribution of JARID2 in human cancers.

Epigenetic Mechanisms Contribute to Intraindividual Variations of Drug Metabolism Mediated by Cytochrome P450 Enzymes

Significant interindividual and intraindividual variations on cytochrome P450 (CYP)-mediated drug metabolism exist in the general population globally. Genetic polymorphisms are one of the major contribution factors for interindividual variations, but epigenetic mechanisms mainly contribute to intraindividual variations, including DNA methylation, histone modifications, microRNAs, and long non-coding RNAs. The current review provides analysis of advanced knowledge in the last decade on contributions of epigenetic mechanisms to intraindividual variations on CYP-mediated drug metabolism in several situations, including (1) ontogeny, the developmental changes of CYP expression in individuals from neonates to adults; (2) increased activities of CYP enzymes induced by drug treatment; (3) increased activities of CYP enzymes in adult ages induced by drug treatment at neonate ages; and (4) decreased activities of CYP enzymes in individuals with drug-induced liver injury (DILI). Furthermore, current challenges, knowledge gaps, and future perspective of the epigenetic mechanisms in development of CYP pharmacoepigenetics are discussed. In conclusion, epigenetic mechanisms have been proven to contribute to intraindividual variations of drug metabolism mediated by CYP enzymes in age development, drug induction, and DILI conditions. The knowledge has helped understanding how intraindividual variation are generated. Future studies are needed to develop CYP-based pharmacoepigenetics to guide clinical applications for precision medicine with improved therapeutic efficacy and reduced risk of adverse drug reactions and toxicity. SIGNIFICANCE STATEMENT: Understanding epigenetic mechanisms in contribution to intraindividual variations of CYP-mediated drug metabolism may help to develop CYP-based pharmacoepigenetics for precision medicine to improve therapeutic efficacy and reduce adverse drug reactions and toxicity for drugs metabolized by CYP enzymes.

Tracking Targets of Dynamic Super-Enhancers in Vitro to Better Characterize Osteoclastogenesis and to Evaluate the Effect of Diuron on the Maturation of Human Bone Cells

BACKGROUND

Osteoclasts are major actors in the maintenance of bone homeostasis. The full functional maturation of osteoclasts from monocyte lineage cells is essential for the degradation of old/damaged bone matrix. Diuron is one of the most frequently encountered herbicides, particularly in water sources. However, despite a reported delayed ossification in vivo, its impact on bone cells remains largely unknown.

OBJECTIVES

The objectives of this study were to first better characterize osteoclastogenesis by identifying genes that drive the differentiation of CD14+ monocyte progenitors into osteoclasts and to evaluate the toxicity of diuron on osteoblastic and osteoclastic differentiation in vitro.

METHODS

We performed chromatin immunoprecipitation (ChIP) against H3K27ac followed by ChIP-sequencing (ChIP-Seq) and RNA-sequencing (RNA-Seq) at different stages of differentiation of CD14+ monocytes into active osteoclasts. Differentially activated super-enhancers and their potential target genes were identified. Then to evaluate the toxicity of diuron on osteoblasts and osteoclasts, we performed RNA-Seq and functional tests during in vitro osteoblastic and osteoclastic differentiation by exposing cells to different concentrations of diuron.

RESULTS

The combinatorial study of the epigenetic and transcriptional remodeling taking place during differentiation has revealed a very dynamic epigenetic profile that supports the expression of genes vital for osteoclast differentiation and function. In total, we identified 122 genes induced by dynamic super-enhancers at late days. Our data suggest that high concentration of diuron (50μM) affects viability of mesenchymal stem cells (MSCs) in vitro associated with a decrease of bone mineralization. At a lower concentration (1μM), an inhibitory effect was observed in vitro on the number of osteoclasts derived from CD14+ monocytes without affecting cell viability. Among the diuron-affected genes, our analysis suggests a significant enrichment of genes targeted by pro-differentiation super-enhancers, with an odds ratio of 5.12 (ρ=2.59×10-5).

DISCUSSION

Exposure to high concentrations of diuron decreased the viability of MSCs and could therefore affect osteoblastic differentiation and bone mineralization. This pesticide also disrupted osteoclasts maturation by impairing the expression of cell-identity determining genes. Indeed, at sublethal concentrations, differences in the expression of these key genes were mild during the course of in vitro osteoclast differentiation. Taken together our results suggest that high exposure levels of diuron could have an effect on bone homeostasis. https://doi.org/10.1289/EHP11690.

Dynamic modulation of genomic enhancer elements in the suprachiasmatic nucleus, the site of the mammalian circadian clock

The mammalian suprachiasmatic nucleus (SCN), located in the ventral hypothalamus, synchronizes and maintains daily cellular and physiological rhythms across the body, in accordance with environmental and visceral cues. Consequently, the systematic regulation of spatiotemporal gene transcription in the SCN is vital for daily timekeeping. So far, the regulatory elements assisting circadian gene transcription have only been studied in peripheral tissues, lacking the critical neuronal dimension intrinsic to the role of the SCN as central brain pacemaker. By using histone-ChIP-seq, we identified SCN-enriched gene regulatory elements that associated with temporal gene expression. Based on tissue-specific H3K27ac and H3K4me3 marks, we successfully produced the first-ever SCN gene-regulatory map. We found that a large majority of SCN enhancers not only show robust 24-h rhythmic modulation in H3K27ac occupancy, peaking at distinct times of day, but also possess canonical E-box (CACGTG) motifs potentially influencing downstream cycling gene expression. To establish enhancer-gene relationships in the SCN, we conducted directional RNA-seq at six distinct times across the day and night, and studied the association between dynamically changing histone acetylation and gene transcript levels. About 35% of the cycling H3K27ac sites were found adjacent to rhythmic gene transcripts, often preceding the rise in mRNA levels. We also noted that enhancers encompass noncoding, actively transcribing enhancer RNAs (eRNAs) in the SCN, which in turn oscillate, along with cyclic histone acetylation, and correlate with rhythmic gene transcription. Taken together, these findings shed light on genome-wide pretranscriptional regulation operative in the central clock that confers its precise and robust oscillation necessary to orchestrate daily timekeeping in mammals.

Acetylation of histone H2B marks active enhancers and predicts CBP/p300 target genes

Chromatin features are widely used for genome-scale mapping of enhancers. However, discriminating active enhancers from other cis-regulatory elements, predicting enhancer strength and identifying their target genes is challenging. Here we establish histone H2B N-terminus multisite lysine acetylation (H2BNTac) as a signature of active enhancers. H2BNTac prominently marks candidate active enhancers and a subset of promoters and discriminates them from ubiquitously active promoters. Two mechanisms underlie the distinct H2BNTac specificity: (1) unlike H3K27ac, H2BNTac is specifically catalyzed by CBP/p300; (2) H2A-H2B, but not H3-H4, are rapidly exchanged through transcription-induced nucleosome remodeling. H2BNTac-positive candidate enhancers show a high validation rate in orthogonal enhancer activity assays and a vast majority of endogenously active enhancers are marked by H2BNTac and H3K27ac. Notably, H2BNTac intensity predicts enhancer strength and outperforms current state-of-the-art models in predicting CBP/p300 target genes. These findings have broad implications for generating fine-grained enhancer maps and modeling CBP/p300-dependent gene regulation.

A computational pipeline to learn gene expression predictive models from epigenetic information at enhancers or promoters

Here, we present a computational pipeline to obtain quantitative models that characterize the relationship of gene expression with the epigenetic marking at enhancers or promoters in mouse embryonic stem cells. Our protocol consists of (i) generating predictive models of gene expression from epigenetic information (such as histone modification ChIP-seq) at enhancers or promoters and (ii) assessing the performance of these predictive models. This protocol could be applied to other biological scenarios or other types of epigenetic data. For complete details on the use and execution of this protocol, please refer to Gonzalez-Ramirez et al. (2021).1.

Methylation of histone H3 lysine 4 is required for maintenance of beta cell function in adult mice

AIMS/HYPOTHESIS

Beta cells control glucose homeostasis via regulated production and secretion of insulin. This function arises from a highly specialised gene expression programme that is established during development and then sustained, with limited flexibility, in terminally differentiated cells. Dysregulation of this programme is seen in type 2 diabetes but mechanisms that preserve gene expression or underlie its dysregulation in mature cells are not well resolved. This study investigated whether methylation of histone H3 lysine 4 (H3K4), a marker of gene promoters with unresolved functional importance, is necessary for the maintenance of mature beta cell function.

METHODS

Beta cell function, gene expression and chromatin modifications were analysed in conditional Dpy30 knockout mice, in which H3K4 methyltransferase activity is impaired, and in a mouse model of diabetes.

RESULTS

H3K4 methylation maintains expression of genes that are important for insulin biosynthesis and glucose responsiveness. Deficient methylation of H3K4 leads to a less active and more repressed epigenome profile that locally correlates with gene expression deficits but does not globally reduce gene expression. Instead, developmentally regulated genes and genes in weakly active or suppressed states particularly rely on H3K4 methylation. We further show that H3K4 trimethylation (H3K4me3) is reorganised in islets from the Lepr^db/db mouse model of diabetes in favour of weakly active and disallowed genes at the expense of terminal beta cell markers with broad H3K4me3 peaks.

CONCLUSIONS/INTERPRETATION

Sustained methylation of H3K4 is critical for the maintenance of beta cell function. Redistribution of H3K4me3 is linked to gene expression changes that are implicated in diabetes pathology.