Reconfiguration of nucleosome-depleted regions at distal regulatory elements accompanies DNA methylation of enhancers and insulators in cancer

Emergence of enhancers at late DNA replicating regions

Enhancers are fast-evolving genomic sequences that control spatiotemporal gene expression patterns. By examining enhancer turnover across mammalian species and in multiple tissue types, we uncover a relationship between the emergence of enhancers and genome organization as a function of germline DNA replication time. While enhancers are most abundant in euchromatic regions, enhancers emerge almost twice as often in late compared to early germline replicating regions, independent of transposable elements. Using a deep learning sequence model, we demonstrate that new enhancers are enriched for mutations that alter transcription factor (TF) binding. Recently evolved enhancers appear to be mostly neutrally evolving and enriched in eQTLs. They also show more tissue specificity than conserved enhancers, and the TFs that bind to these elements, as inferred by binding sequences, also show increased tissue-specific gene expression. We find a similar relationship with DNA replication time in cancer, suggesting that these observations may be time-invariant principles of genome evolution. Our work underscores that genome organization has a profound impact in shaping mammalian gene regulation.

Increased chromatin accessibility facilitates intron retention in specific cell differentiation states

Dynamic intron retention (IR) in vertebrate cells is of widespread biological importance. Aberrant IR is associated with numerous human diseases including several cancers. Despite consistent reports demonstrating that intrinsic sequence features can help introns evade splicing, conflicting findings about cell type- or condition-specific IR regulation by trans-regulatory and epigenetic mechanisms demand an unbiased and systematic analysis of IR in a controlled experimental setting. We integrated matched mRNA sequencing (mRNA-Seq), whole-genome bisulfite sequencing (WGBS), nucleosome occupancy methylome sequencing (NOMe-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq) data from primary human myeloid and lymphoid cells. Using these multi-omics data and machine learning, we trained two complementary models to determine the role of epigenetic factors in the regulation of IR in cells of the innate immune system. We show that increased chromatin accessibility, as revealed by nucleosome-free regions, contributes substantially to the retention of introns in a cell-specific manner. We also confirm that intrinsic characteristics of introns are key for them to evade splicing. This study suggests an important role for chromatin architecture in IR regulation. With an increasing appreciation that pathogenic alterations are linked to RNA processing, our findings may provide useful insights for the development of novel therapeutic approaches that target aberrant splicing.

Nucleosome-Omics: A Perspective on the Epigenetic Code and 3D Genome Landscape

Genetic information is loaded on chromatin, which involves DNA sequence arrangement and the epigenetic landscape. The epigenetic information including DNA methylation, nucleosome positioning, histone modification, 3D chromatin conformation, and so on, has a crucial impact on gene transcriptional regulation. Out of them, nucleosomes, as basal chromatin structural units, play an important central role in epigenetic code. With the discovery of nucleosomes, various nucleosome-level technologies have been developed and applied, pushing epigenetics to a new climax. As the underlying methodology, next-generation sequencing technology has emerged and allowed scientists to understand the epigenetic landscape at a genome-wide level. Combining with NGS, nucleosome-omics (or nucleosomics) provides a fresh perspective on the epigenetic code and 3D genome landscape. Here, we summarized and discussed research progress in technology development and application of nucleosome-omics. We foresee the future directions of epigenetic development at the nucleosome level.

Epigenomic alterations in cancer: mechanisms and therapeutic potential

The human cell requires ways to specify its transcriptome without altering the essential sequence of DNA; this is achieved through mechanisms which govern the epigenetic state of DNA and epitranscriptomic state of RNA. These alterations can be found as modified histone proteins, cytosine DNA methylation, non-coding RNAs, and mRNA modifications, such as N6-methyladenosine (m6A). The different aspects of epigenomic and epitranscriptomic modifications require protein complexes to write, read, and erase these chemical alterations. Reflecting these important roles, many of these reader/writer/eraser proteins are either frequently mutated or differentially expressed in cancer. The disruption of epigenetic regulation in the cell can both contribute to cancer initiation and progression, and increase the likelihood of developing resistance to chemotherapies. Development of therapeutics to target proteins involved in epigenomic/epitranscriptomic modifications has been intensive, but further refinement is necessary to achieve ideal treatment outcomes without too many off-target effects for cancer patients. Therefore, further integration of clinical outcomes combined with large-scale genomic analyses is imperative for furthering understanding of epigenomic mechanisms in cancer.

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

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

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

Whole-genome methods to define DNA and histone accessibility and long-range interactions in chromatin

Defining the genome-wide chromatin landscape has been a goal of experimentalists for decades. Here we review highlights of these efforts, from seminal experiments showing discontinuities in chromatin structure related to gene activation to extensions of these methods elucidating general features of chromatin related to gene states by exploiting deep sequencing methods. We also review chromatin conformational capture methods to identify patterns in long-range interactions between genomic loci.

Computational characterization of domain-segregated 3D chromatin structure and segmented DNA methylation status in carcinogenesis

The high-order chromatin structure, together with DNA methylation and other epigenetic marks, plays a vital role in gene regulation and displays abnormal status in cancer cells. Theoretical analyses are expected to provide a more unified understanding of the multi-omics data on the large variety of samples, and hopefully a common picture of carcinogenesis. In particular, we are interested in the question of whether an underlying origin DNA sequence exists for these epigenetic alterations. The human genome consists of two types of megabase-sized domain based on the distribution of CpG islands (CGIs) that show distinct structural, epigenetic, and transcriptional properties: CGI-rich and CGI-poor domains. Through an integrated analysis of chromatin structure, DNA methylation, and RNA sequencing data, we found that, in carcinogenesis, the two different types of domain display different structural changes and have an increased number of DNA methylation differences and transcriptional-level differences, compared with in noncancer cells. We also compared the structural features among carcinogenesis, senescence, and mitosis, showing the possible connection between chromatin structure and cell state, which could affect vital cancer-related properties. In summary, chromatin structure, DNA methylation, and gene expression, as well as their changes observed in several types of cancers, show a dependence on multiscale DNA sequence heterogeneity.

Panobinostat reverses HepaCAM gene expression and suppresses proliferation by increasing histone acetylation in prostate cancer

Increased expression of histone deacetylases (HDACs) affiliated to the epigenetic regulation is common aberration in prostate cancer (PCa). We have confirmed that hepatocyte cell adhesion molecule (hepaCAM), acting as a tumor suppressor gene, is rarely expressed in PCa previously, However, the mechanisms of which is still unknown. The level of histone acetylation reportedly may involve anti-oncogene transcription and expression. In this study, we investigated the effect of panobinostat, the broad-spectrum histone deacetylases inhibitor, on PCa LNCaP and DU145 cell growth, and observed re-expression of hepaCAM when treated with panobinostat. We demonstrated that intranuclear acetylation of lys9 of histone H3 (Ac-H3K9) were increased, while that of both mRNA and protein of HDAC1, HDAC3, and HDAC4 were decreased when the treating concentration of panobinostat increased. We confirmed the relationship between histone acetylation and the expression of hepaCAM and AR in prostate cancer tissues. We also confirmed that panobinostat could overcome the resistance for androgen deprivation therapy (ADT). Further, we combined panobinostat with Ad-hepaCAM, which resulted in significantly increased antitumor activity and significant attenuation of the proliferation-associated genes CCND1 and PCNA compared to each single treatment. In conclusion, panobinostat may enhance the acetylation of lys9 of histone 3 and reverse the hepaCAM expression through its inhibitory effect on HDACs activity in PCa LNCaP and DU145 cells; Ad-hepaCAM combined with panobinostat may synergistically inhibit the growth of LNCaP and DU145 cells, via a potential mechanism associated with the down-regulation of the expression of CCND1 and PCNA. These findings suggest that this therapeutic strategy should be further developed in clinical trials.

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

BACKGROUND

Genome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative "stacked modeling" approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges.

RESULTS

Using a version of ChromHMM enhanced for large-scale applications, we apply the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, with the learned model denoted as the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we use in characterizing each state. Compared to per-cell-type annotations, the full-stack annotations directly differentiate constitutive from cell type-specific activity and is more predictive of locations of external genomic annotations.

CONCLUSIONS

The full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing per-cell-type annotations for studying the non-coding human genome.

Deoxyribonucleic Acid 5-Hydroxymethylation in Cell-Free Deoxyribonucleic Acid, a Novel Cancer Biomarker in the Era of Precision Medicine

Aberrant methylation has been regarded as a hallmark of cancer. 5-hydroxymethylcytosine (5hmC) is recently identified as the ten-eleven translocase (ten-eleven translocase)-mediated oxidized form of 5-methylcytosine, which plays a substantial role in DNA demethylation. Cell-free DNA has been introduced as a promising tool in the liquid biopsy of cancer. There are increasing evidence indicating that 5hmC in cell-free DNA play an active role during carcinogenesis. However, it remains unclear whether 5hmC could surpass classical markers in cancer detection, treatment, and prognosis. Here, we systematically reviewed the recent advances in the clinic and basic research of DNA 5-hydroxymethylation in cancer, especially in cell-free DNA. We further discuss the mechanisms underlying aberrant 5hmC patterns and carcinogenesis. Synergistically, 5-hydroxymethylation may act as a promising biomarker, unleashing great potential in early cancer detection, prognosis, and therapeutic strategies in precision oncology.

HiC1Dmetrics: framework to extract various one-dimensional features from chromosome structure data

Eukaryotic genomes are organized in a three-dimensional spatial structure. In this regard, the development of chromosome conformation capture methods has enabled studies of chromosome organization on a genomic scale. Hi-C, the high-throughput chromosome conformation capture method, can reveal a population-averaged, hierarchical chromatin structure. The typical Hi-C analysis uses a two-dimensional (2D) contact matrix that indicates contact frequencies between all possible genomic position pairs. Oftentimes, however, such a 2D matrix is not amenable to handling quantitative comparisons, visualizations and integrations across multiple datasets. Although several one-dimensional (1D) metrics have been proposed to depict structural information in Hi-C data, their effectiveness is still underappreciated. Here, we first review the currently available 1D metrics for individual Hi-C samples or two-sample comparisons and then discuss their validity and suitable analysis scenarios. We also propose several new 1D metrics to identify additional unique features of chromosome structures. We highlight that the 1D metrics are reproducible and robust for comparing and visualizing multiple Hi-C samples. Moreover, we show that 1D metrics can be easily combined with epigenome tracks to annotate chromatin states in greater details. We develop a new framework, called HiC1Dmetrics, to summarize all 1D metrics discussed in this study. HiC1Dmetrics is open-source (github.com/wangjk321/HiC1Dmetrics) and can be accessed from both command-line and web-based interfaces. Our tool constitutes a useful resource for the community of chromosome-organization researchers.

Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine

The recent deluge of genome-wide technologies for the mapping of the epigenome and resulting data in cancer samples has provided the opportunity for gaining insights into and understanding the roles of epigenetic processes in cancer. However, the complexity, high-dimensionality, sparsity, and noise associated with these data pose challenges for extensive integrative analyses. Machine Learning (ML) algorithms are particularly suited for epigenomic data analyses due to their flexibility and ability to learn underlying hidden structures. We will discuss four overlapping but distinct major categories under ML: dimensionality reduction, unsupervised methods, supervised methods, and deep learning (DL). We review the preferred use cases of these algorithms in analyses of cancer epigenomics data with the hope to provide an overview of how ML approaches can be used to explore fundamental questions on the roles of epigenome in cancer biology and medicine.

Head and Neck Cancers Are Not Alike When Tarred with the Same Brush: An Epigenetic Perspective from the Cancerization Field to Prognosis

Simple Summary

Squamous cell carcinomas affect different head and neck subsites and, although these tumors arise from the same epithelial lining and share risk factors, they differ in terms of clinical behavior and molecular carcinogenesis mechanisms. Differences between HPV-negative and HPV-positive tumors are those most frequently explored, but further data suggest that the molecular heterogeneity observed among head and neck subsites may go beyond HPV infection. In this review, we explore how alterations of DNA methylation and microRNA expression contribute to head and neck squamous cell carcinoma (HNSCC) development and progression. The association of these epigenetic alterations with risk factor exposure, early carcinogenesis steps, transformation risk, and prognosis are described. Finally, we discuss the potential application of the use of epigenetic biomarkers in HNSCC.

Abstract

Head and neck squamous cell carcinomas (HNSCC) are among the ten most frequent types of cancer worldwide and, despite all efforts, are still diagnosed at late stages and show poor overall survival. Furthermore, HNSCC patients often experience relapses and the development of second primary tumors, as a consequence of the field cancerization process. Therefore, a better comprehension of the molecular mechanisms involved in HNSCC development and progression may enable diagnosis anticipation and provide valuable tools for prediction of prognosis and response to therapy. However, the different biological behavior of these tumors depending on the affected anatomical site and risk factor exposure, as well as the high genetic heterogeneity observed in HNSCC are major obstacles in this pursue. In this context, epigenetic alterations have been shown to be common in HNSCC, to discriminate the tumor anatomical subsites, to be responsive to risk factor exposure, and show promising results in biomarker development. Based on this, this review brings together the current knowledge on alterations of DNA methylation and microRNA expression in HNSCC natural history, focusing on how they contribute to each step of the process and on their applicability as biomarkers of exposure, HNSCC development, progression, and response to therapy.

Epigenetic remodelling of enhancers in response to estrogen deprivation and re-stimulation

Estrogen hormones are implicated in a majority of breast cancers and estrogen receptor alpha (ER), the main nuclear factor mediating estrogen signaling, orchestrates a complex molecular circuitry that is not yet fully elucidated. Here, we investigated genome-wide DNA methylation, histone acetylation and transcription after estradiol (E2) deprivation and re-stimulation to better characterize the ability of ER to coordinate gene regulation. We found that E2 deprivation mostly resulted in DNA hypermethylation and histone deacetylation in enhancers. Transcriptome analysis revealed that E2 deprivation leads to a global down-regulation in gene expression, and more specifically of TET2 demethylase that may be involved in the DNA hypermethylation following short-term E2 deprivation. Further enrichment analysis of transcription factor (TF) binding and motif occurrence highlights the importance of ER connection mainly with two partner TF families, AP-1 and FOX. These interactions take place in the proximity of E2 deprivation-mediated differentially methylated and histone acetylated enhancers. Finally, while most deprivation-dependent epigenetic changes were reversed following E2 re-stimulation, DNA hypermethylation and H3K27 deacetylation at certain enhancers were partially retained. Overall, these results show that inactivation of ER mediates rapid and mostly reversible epigenetic changes at enhancers, and bring new insight into early events, which may ultimately lead to endocrine resistance.

DNA methylation is required to maintain both DNA replication timing precision and 3D genome organization integrity

DNA replication timing and three-dimensional (3D) genome organization are associated with distinct epigenome patterns across large domains. However, whether alterations in the epigenome, in particular cancer-related DNA hypomethylation, affects higher-order levels of genome architecture is still unclear. Here, using Repli-Seq, single-cell Repli-Seq, and Hi-C, we show that genome-wide methylation loss is associated with both concordant loss of replication timing precision and deregulation of 3D genome organization. Notably, we find distinct disruption in 3D genome compartmentalization, striking gains in cell-to-cell replication timing heterogeneity and loss of allelic replication timing in cancer hypomethylation models, potentially through the gene deregulation of DNA replication and genome organization pathways. Finally, we identify ectopic H3K4me3-H3K9me3 domains from across large hypomethylated domains, where late replication is maintained, which we purport serves to protect against catastrophic genome reorganization and aberrant gene transcription. Our results highlight a potential role for the methylome in the maintenance of 3D genome regulation.

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

Oct4-Mediated Inhibition of Lsd1 Activity Promotes the Active and Primed State of Pluripotency Enhancers

An aberrant increase in pluripotency gene (PpG) expression due to enhancer reactivation could induce stemness and enhance the tumorigenicity of cancer stem cells. Silencing of PpG enhancers (PpGe) during embryonic stem cell differentiation involves Lsd1-mediated H3K4me1 demethylation and DNA methylation. Here, we observed retention of H3K4me1 and DNA hypomethylation at PpGe associated with a partial repression of PpGs in F9 embryonal carcinoma cells (ECCs) post-differentiation. H3K4me1 demethylation in F9 ECCs could not be rescued by Lsd1 overexpression. Given our observation that H3K4me1 demethylation is accompanied by strong Oct4 repression in P19 ECCs, we tested if Oct4 interaction with Lsd1 affects its catalytic activity. Our data show a dose-dependent inhibition of Lsd1 activity by Oct4 and retention of H3K4me1 at PpGe in Oct4-overexpressing P19 ECCs. These data suggest that Lsd1-Oct4 interaction in cancer stem cells could establish a "primed" enhancer state that is susceptible to reactivation, leading to aberrant PpG expression.

Genome-Wide Epigenetic Landscape of Lung Adenocarcinoma Links HOXB9 DNA Methylation to Intrinsic EGFR-TKI Resistance and Heterogeneous Responses

PURPOSE

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) show efficacy in treating patients with lung adenocarcinoma with EGFR-activating mutations. However, a significant subset of targeted patients fail to respond. Unlike acquired resistance (AR), intrinsic resistance (IR) remains poorly understood. We investigated whether epigenomic factors contribute to patient-to-patient heterogeneity in the EGFR-TKI response and aimed to characterize the IR subpopulation that obtains no benefit from EGFR-TKIs.

PATIENTS AND METHODS

We conducted genome-wide DNA methylation profiling of 79 tumors sampled from patients with advanced lung adenocarcinoma before they received EGFR-TKI treatment and analyzed the patient responses. Pyrosequencing was performed in a validation cohort of 163 patients with EGFR-activating mutations.

RESULTS

A DNA methylation landscape of 216 CpG sites with differential methylation was established to elucidate the association of DNA methylation with the characteristics and EGFR-TKI response status of the patients. Functional analysis of 37 transcription-repressive sites identified the enrichment of transcription factors, notably homeobox (HOX) genes. DNA methylation of HOXB9 (cg13643585) in the enhancer region yielded 88% sensitivity for predicting drug response (odds ratio [OR], 6.64; 95% CI, 1.98 to 25.23; P = .0009). Pyrosequencing validated that HOXB9 gained methylation in patients with a poor EGFR-TKI response (OR, 3.06; 95% CI, 1.13 to 8.19; P = .019).

CONCLUSION

Our data suggest that homeobox DNA methylation could be a novel tumor cellular state that can aid the precise categorization of tumor heterogeneity in the study of IR to EGFR-TKIs. We identified, for the first time, an epigenomic factor that can potentially complement DNA mutation status in discriminating patients with lung adenocarcinoma who are less likely to benefit from EGFR-TKI treatment, thereby leading to improved patient management in precision medicine.

BRG1 knockdown inhibits proliferation through multiple cellular pathways in prostate cancer

Background

BRG1 (encoded by SMARCA4) is a catalytic component of the SWI/SNF chromatin remodelling complex, with key roles in modulating DNA accessibility. Dysregulation of BRG1 is observed, but functionally uncharacterised, in a wide range of malignancies. We have probed the functions of BRG1 on a background of prostate cancer to investigate how BRG1 controls gene expression programmes and cancer cell behaviour.

Results

Our investigation of SMARCA4 revealed that BRG1 is over-expressed in the majority of the 486 tumours from The Cancer Genome Atlas prostate cohort, as well as in a complementary panel of 21 prostate cell lines. Next, we utilised a temporal model of BRG1 depletion to investigate the molecular effects on global transcription programmes. Depleting BRG1 had no impact on alternative splicing and conferred only modest effect on global expression. However, of the transcriptional changes that occurred, most manifested as down-regulated expression. Deeper examination found the common thread linking down-regulated genes was involvement in proliferation, including several known to increase prostate cancer proliferation (KLK2, PCAT1 and VAV3). Interestingly, the promoters of genes driving proliferation were bound by BRG1 as well as the transcription factors, AR and FOXA1. We also noted that BRG1 depletion repressed genes involved in cell cycle progression and DNA replication, but intriguingly, these pathways operated independently of AR and FOXA1. In agreement with transcriptional changes, depleting BRG1 conferred G1 arrest.

Conclusions

Our data have revealed that BRG1 promotes cell cycle progression and DNA replication, consistent with the increased cell proliferation associated with oncogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01023-7.

The Role of H3K4 Trimethylation in CpG Islands Hypermethylation in Cancer

CpG methylation in transposons, exons, introns and intergenic regions is important for long-term silencing, silencing of parasitic sequences and alternative promoters, regulating imprinted gene expression and determining X chromosome inactivation. Promoter CpG islands, although rich in CpG dinucleotides, are unmethylated and remain so during all phases of mammalian embryogenesis and development, except in specific cases. The biological mechanisms that contribute to the maintenance of the unmethylated state of CpG islands remain elusive, but the modification of established DNA methylation patterns is a common feature in all types of tumors and is considered as an event that intrinsically, or in association with genetic lesions, feeds carcinogenesis. In this review, we focus on the latest results describing the role that the levels of H3K4 trimethylation may have in determining the aberrant hypermethylation of CpG islands in tumors.

Challenges and Opportunities of Genomic Approaches in Therapeutics Development

The magnitude of all therapeutic responses is significantly determined by genome structure, variation, and functional interactions. This determination occurs at many levels which are discussed in the current review. Well-established examples of structural variation between individuals are known to dictate an individual's response to numerous drugs, as clearly illustrated by warfarin. The exponential rate of genomic-based interrogation is coupled with an expanding repertoire of genomic technologies and applications. This is leading to an ever more sophisticated appreciation of how structural variation, regulation of transcription and genomic structure, both individually and collectively, define cell therapeutic responses.

svMIL: predicting the pathogenic effect of TAD boundary-disrupting somatic structural variants through multiple instance learning

Motivation

Despite the fact that structural variants (SVs) play an important role in cancer, methods to predict their effect, especially for SVs in non-coding regions, are lacking, leaving them often overlooked in the clinic. Non-coding SVs may disrupt the boundaries of Topologically Associated Domains (TADs), thereby affecting interactions between genes and regulatory elements such as enhancers. However, it is not known when such alterations are pathogenic. Although machine learning techniques are a promising solution to answer this question, representing the large number of interactions that an SV can disrupt in a single feature matrix is not trivial.

Results

We introduce svMIL: a method to predict pathogenic TAD boundary-disrupting SV effects based on multiple instance learning, which circumvents the need for a traditional feature matrix by grouping SVs into bags that can contain any number of disruptions. We demonstrate that svMIL can predict SV pathogenicity, measured through same-sample gene expression aberration, for various cancer types. In addition, our approach reveals that somatic pathogenic SVs alter different regulatory interactions than somatic non-pathogenic SVs and germline SVs.

Availability and implementation

All code for svMIL is publicly available on GitHub: https://github.com/UMCUGenetics/svMIL.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genomic retargeting of p53 and CTCF is associated with transcriptional changes during oncogenic HRas-induced transformation

Gene transcription is regulated by distant regulatory elements via combinatorial binding of transcription factors. It is increasingly recognized that alterations in chromatin state and transcription factor binding in these distant regulatory elements may have key roles in cancer development. Here we focused on the first stages of oncogene-induced carcinogenic transformation, and characterized the regulatory network underlying transcriptional changes associated with this process. Using Hi-C data, we observe spatial coupling between differentially expressed genes and their differentially accessible regulatory elements and reveal two candidate transcription factors, p53 and CTCF, as determinants of transcriptional alterations at the early stages of oncogenic HRas-induced transformation in human mammary epithelial cells. Strikingly, the malignant transcriptional reprograming is promoted by redistribution of chromatin binding of these factors without major variation in their expression level. Our results demonstrate that alterations in the regulatory landscape have a major role in driving oncogene-induced transcriptional reprogramming.

Nuclear role for human Argonaute-1 as an estrogen-dependent transcription coactivator

In mammals, argonaute (AGO) proteins have been characterized for their roles in small RNA-mediated posttranscriptional and also in transcriptional gene silencing. Here, we report a different role for AGO1 in estradiol-triggered transcriptional activation in human cells. We show that in MCF-7 mammary gland cells, AGO1 associates with transcriptional enhancers of estrogen receptor α (ERα) and that this association is up-regulated by treating the cells with estrogen (E2), displaying a positive correlation with the activation of these enhancers. Moreover, we show that AGO1 interacts with ERα and that this interaction is also increased by E2 treatment, but occurs in the absence of RNA. We show that AGO1 acts positively as a coactivator in estradiol-triggered transcription regulation by promoting ERα binding to its enhancers. Consistently, AGO1 depletion decreases long-range contacts between ERα enhancers and their target promoters. Our results point to a role of AGO1 in transcriptional regulation in human cells that is independent from small RNA binding.

Dissecting the epigenomic dynamics of human fetal germ cell development at single-cell resolution

Proper development of fetal germ cells (FGCs) is vital for the precise transmission of genetic and epigenetic information through generations. The transcriptional landscapes of human FGC development have been revealed; however, the epigenetic reprogramming process of FGCs remains elusive. Here, we profiled the genome-wide DNA methylation and chromatin accessibility of human FGCs at different phases as well as gonadal niche cells at single-cell resolution. First, we found that DNA methylation levels of FGCs changed in a temporal manner, whereas FGCs at different phases in the same embryo exhibited comparable DNA methylation levels and patterns. Second, we revealed the phase-specific chromatin accessibility signatures at the promoter regions of a large set of critical transcription factors and signaling pathway genes. We also identified potential distal regulatory elements including enhancers in FGCs. Third, compared with other hominid-specific retrotransposons, SVA_D might have a broad spectrum of binding capacity for transcription factors, including SOX15 and SOX17. Finally, using an in vitro culture system of human FGCs, we showed that the BMP signaling pathway promoted the cell proliferation of FGCs, and regulated the WNT signaling pathway by orchestrating the chromatin accessibility of its ligand genes. Our single-cell epigenomic atlas and functional assays provide valuable insights for understanding the strongly heterogeneous, unsynchronized, yet highly robust nature of human germ cell development.

DNA methylation repels binding of hypoxia-inducible transcription factors to maintain tumor immunotolerance

BACKGROUND

Hypoxia is pervasive in cancer and other diseases. Cells sense and adapt to hypoxia by activating hypoxia-inducible transcription factors (HIFs), but it is still an outstanding question why cell types differ in their transcriptional response to hypoxia.

RESULTS

We report that HIFs fail to bind CpG dinucleotides that are methylated in their consensus binding sequence, both in in vitro biochemical binding assays and in vivo studies of differentially methylated isogenic cell lines. Based on in silico structural modeling, we show that 5-methylcytosine indeed causes steric hindrance in the HIF binding pocket. A model wherein cell-type-specific methylation landscapes, as laid down by the differential expression and binding of other transcription factors under normoxia, control cell-type-specific hypoxia responses is observed. We also discover ectopic HIF binding sites in repeat regions which are normally methylated. Genetic and pharmacological DNA demethylation, but also cancer-associated DNA hypomethylation, expose these binding sites, inducing HIF-dependent expression of cryptic transcripts. In line with such cryptic transcripts being more prone to cause double-stranded RNA and viral mimicry, we observe low DNA methylation and high cryptic transcript expression in tumors with high immune checkpoint expression, but not in tumors with low immune checkpoint expression, where they would compromise tumor immunotolerance. In a low-immunogenic tumor model, DNA demethylation upregulates cryptic transcript expression in a HIF-dependent manner, causing immune activation and reducing tumor growth.

CONCLUSIONS

Our data elucidate the mechanism underlying cell-type-specific responses to hypoxia and suggest DNA methylation and hypoxia to underlie tumor immunotolerance.

[Identification of nucleosome positioning using support vector machine method based on comprehensive DNA sequence feature]

In this article, based on z-curve theory and position weight matrix (PWM), a model for nucleosome sequences was constructed. Nucleosome sequence dataset was transformed into three-dimensional coordinates, PWM of the nucleosome sequences was calculated and the similarity score was obtained. After integrating them, a nucleosome feature model based on the comprehensive DNA sequences was obtained and named CSeqFM. We calculated the Euclidean distance between nucleosome sequence candidates or linker sequences and CSeqFM model as the feature dataset, and put the feature datasets into the support vector machine (SVM) for training and testing by ten-fold cross-validation. The results showed that the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of identifying nucleosome positioning for S. cerevisiae were 97.1%, 96.9%, 94.2% and 0.89, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.980 1. Compared with another z-curve method, it was found that our method had better identifying effect and each evaluation performance showed better superiority. CSeqFM method was applied to identify nucleosome positioning for other three species, including C. elegans, H. sapiens and D. melanogaster. The results showed that AUCs of the three species were all higher than 0.90, and CSeqFM method also showed better stability and effectiveness compared with iNuc-STNC and iNuc-PseKNC methods, which is further demonstrated that CSeqFM method has strong reliability and good identification performance.

The DNA methylation landscape in cancer

As one of the most abundant and well-studied epigenetic modifications, DNA methylation plays an essential role in normal development and cellular biology. Global alterations to the DNA methylation landscape contribute to alterations in the transcriptome and deregulation of cellular pathways. Indeed, improved methods to study DNA methylation patterning and dynamics at base pair resolution and across individual DNA molecules on a genome-wide scale has highlighted the scope of change to the DNA methylation landscape in disease states, particularly during tumorigenesis. More recently has been the development of DNA hydroxymethylation profiling techniques, which allows differentiation between 5mC and 5hmC profiles and provides further insights into DNA methylation dynamics and remodeling in tumorigenesis. In this review, we describe the distribution of DNA methylation and DNA hydroxymethylation in different genomic contexts, first in normal cells, and how this is altered in cancer. Finally, we discuss DNA methylation profiling technologies and the most recent advances in single-cell methods, bisulfite-free approaches and ultra-long read sequencing techniques.

Unique and assay specific features of NOMe-, ATAC- and DNase I-seq data

Chromatin accessibility maps are important for the functional interpretation of the genome. Here, we systematically analysed assay specific differences between DNase I-seq, ATAC-seq and NOMe-seq in a side by side experimental and bioinformatic setup. We observe that most prominent nucleosome depleted regions (NDRs, e.g. in promoters) are roboustly called by all three or at least two assays. However, we also find a high proportion of assay specific NDRs that are often ‘called’ by only one of the assays. We show evidence that these assay specific NDRs are indeed genuine open chromatin sites and contribute important information for accurate gene expression prediction. While technically ATAC-seq and DNase I-seq provide a superb high NDR calling rate for relatively low sequencing costs in comparison to NOMe-seq, NOMe-seq singles out for its genome-wide coverage allowing to not only detect NDRs but also endogenous DNA methylation and as we show here genome wide segmentation into heterochromatic B domains and local phasing of nucleosomes outside of NDRs. In summary, our comparisons strongly suggest to consider assay specific differences for the experimental design and for generalized and comparative functional interpretations.

Long non-coding RNA MANCR is a target of BET bromodomain protein BRD4 and plays a critical role in cellular migration and invasion abilities of prostate cancer

Androgen receptor (AR)-negative castration-resistant prostate cancer (CRPC) is highly aggressive and is resistant to most of the current therapies. Bromodomain and extra terminal domain (BET) protein BRD4 binds to super-enhancers (SEs) that drive high expression of oncogenes in many cancers. A BET inhibitor, JQ1, has been found to suppress the malignant phenotypes of prostate cancer cells, however, the target genes of JQ1 remain largely unknown. Here we show that SE-associated genes specific for AR-negative CRPC PC3 cells include genes involved in migration and invasion, and that JQ1 impairs migration and invasion of PC3 cells. We identified a long non-coding RNA, MANCR, which was markedly down-regulated by JQ1, and found that BRD4 binds to the MANCR locus. MANCR knockdown led to a significant decrease in migration and invasion of PC3 cells. Furthermore, RNA sequencing analysis revealed that expression of the genes involved in migration and invasion was altered by MANCR knockdown. In summary, our data demonstrate that MANCR plays a critical role in migration and invasion of PC3 cells.

Chromatyping: Reconstructing Nucleosome Profiles from NOMe Sequencing Data

Measuring nucleosome positioning in cells is crucial for the analysis of epigenetic gene regulation. Reconstruction of nucleosome profiles of individual cells or subpopulations of cells remains challenging because most genome-wide assays measure nucleosome positioning and DNA accessibility for thousands of cells using bulk sequencing. In this study we use characteristics of the NOMe (nucleosome occupancy and methylation)-sequencing assay to derive a new approach, called ChromaClique, for deconvolution of different nucleosome profiles (chromatypes) from cell subpopulations of one NOMe-seq measurement. ChromaClique uses a maximal clique enumeration algorithm on a newly defined NOMe read graph that is able to group reads according to their nucleosome profiles. We show that the edge probabilities of that graph can be efficiently computed using hidden Markov models. We demonstrate using simulated data that ChromaClique is more accurate than a related method and scales favorably, allowing genome-wide analyses of chromatypes in cell subpopulations.

Constitutively bound CTCF sites maintain 3D chromatin architecture and long-range epigenetically regulated domains

The architectural protein CTCF is a mediator of chromatin conformation, but how CTCF binding to DNA is orchestrated to maintain long-range gene expression is poorly understood. Here we perform RNAi knockdown to reduce CTCF levels and reveal a shared subset of CTCF-bound sites are robustly resistant to protein depletion. The ‘persistent’ CTCF sites are enriched at domain boundaries and chromatin loops constitutive to all cell types. CRISPR-Cas9 deletion of 2 persistent CTCF sites at the boundary between a long-range epigenetically active (LREA) and silenced (LRES) region, within the Kallikrein (KLK) locus, results in concordant activation of all 8 KLK genes within the LRES region. CTCF genome-wide depletion results in alteration in Topologically Associating Domain (TAD) structure, including the merging of TADs, whereas TAD boundaries are not altered where persistent sites are maintained. We propose that the subset of essential CTCF sites are involved in cell-type constitutive, higher order chromatin architecture.

The architectural protein CTCF is a mediator of chromatin conformation, but how CTCF binding to DNA is regulated remains poorly understood. Here the authors find that there is a shared subset of CTCF-bound sites resistant to protein depletion in different cell lines, which are enriched at domain boundaries and chromatin loops constitutive to all cell types.

DNA hypomethylation promotes invasion and metastasis of gastric cancer cells by regulating the binding of SP1 to the CDCA3 promoter

BACKGROUND

Cell division cycle associated protein-3 (CDCA3) has been reported frequently upregulated in various cancers. It has been progressively realized that changed DNA methylations occur in diverse carcinomas. However, the concrete involvement of CDCA3 and DNA methylation in gastric cancer (GC) still needs to be further elucidated.

METHODS

In this study, quantitative reverse-transcription polymerase chain reaction (PCR) was utilized to determine the relative expressions of CDCA3 in GC and normal tissue samples. The methylation condition of CDCA3 was determined by bisulfite-sequencing PCR (BSP) and methylation-specific PCR (MSP). A chromatin immunoprecipitation (ChIP) assay and luciferase activity assay was used for the interaction between transcription factors and promoters and binding site determination, respectively. The effects of knockdown or overexpression of specificity protein 1 (SP1) or CDCA3 on GC cells in vitro were further assessed via wound healing assay, colony formation assay, and matrigel invasion assay.

RESULTS

In comparison to paired normal tissues, CDCA3 expressions were significantly increased in the GC tissues. The CDCA3 expression was regulated by DNA methylation, with the CpG island hypomethylation responsible for CDCA3 upregulation of GC. ChIP assays verified that the activity of SP1 binding to the CDCA3 promoter was dramatically increased. When the CDCA3 expression was downregulated in MKN45 cells by knockdown SP1, the proliferation ability, healing ability, and invasive ability were significantly suppressed.

CONCLUSION

The process by which SP1 bound to the nearest promoter region was expedited in GC cells, by which DNA was hypomethylated and CDCA3 expression was promoted. The effect on cell proliferation and invasion by CDCA3 was under the regulation of SP1 and also affected by hypomethylation of DNA.

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

ELF5 modulates the estrogen receptor cistrome in breast cancer

Acquired resistance to endocrine therapy is responsible for half of the therapeutic failures in the treatment of breast cancer. Recent findings have implicated increased expression of the ETS transcription factor ELF5 as a potential modulator of estrogen action and driver of endocrine resistance, and here we provide the first insight into the mechanisms by which ELF5 modulates estrogen sensitivity. Using chromatin immunoprecipitation sequencing we found that ELF5 binding overlapped with FOXA1 and ER at super enhancers, enhancers and promoters, and when elevated, caused FOXA1 and ER to bind to new regions of the genome, in a pattern that replicated the alterations to the ER/FOXA1 cistrome caused by the acquisition of resistance to endocrine therapy. RNA sequencing demonstrated that these changes altered estrogen-driven patterns of gene expression, the expression of ER transcription-complex members, and 6 genes known to be involved in driving the acquisition of endocrine resistance. Using rapid immunoprecipitation mass spectrometry of endogenous proteins, and proximity ligation assays, we found that ELF5 interacted physically with members of the ER transcription complex, such as DNA-PKcs. We found 2 cases of endocrine-resistant brain metastases where ELF5 levels were greatly increased and ELF5 patterns of gene expression were enriched, compared to the matched primary tumour. Thus ELF5 alters ER-driven gene expression by modulating the ER/FOXA1 cistrome, by interacting with it, and by modulating the expression of members of the ER transcriptional complex, providing multiple mechanisms by which ELF5 can drive endocrine resistance.

HMMRATAC: a Hidden Markov ModeleR for ATAC-seq

ATAC-seq has been widely adopted to identify accessible chromatin regions across the genome. However, current data analysis still utilizes approaches initially designed for ChIP-seq or DNase-seq, without considering the transposase digested DNA fragments that contain additional nucleosome positioning information. We present the first dedicated ATAC-seq analysis tool, a semi-supervised machine learning approach named HMMRATAC. HMMRATAC splits a single ATAC-seq dataset into nucleosome-free and nucleosome-enriched signals, learns the unique chromatin structure around accessible regions, and then predicts accessible regions across the entire genome. We show that HMMRATAC outperforms the popular peak-calling algorithms on published human ATAC-seq datasets. We find that single-end sequenced or size-selected ATAC-seq datasets result in a loss of sensitivity compared to paired-end datasets without size-selection.

Tales from topographic oceans: topologically associated domains and cancer

The 3D organization of the genome within the cell nucleus has come into sharp focus over the last decade. This has largely arisen because of the application of genomic approaches that have revealed numerous levels of genomic and chromatin interactions, including topologically associated domains (TADs). The current review examines how these domains were identified, are organized, how their boundaries arise and are regulated, and how genes within TADs are coordinately regulated. There are many examples of the disruption to TAD structure in cancer and the altered regulation, structure and function of TADs are discussed in the context of hormone responsive cancers, including breast, prostate and ovarian cancer. Finally, some aspects of the statistical insight and computational skills required to interrogate TAD organization are considered and future directions discussed.

Modifications of H3K4 methylation levels are associated with DNA hypermethylation in acute myeloid leukemia

The 'instructive model' of aberrant DNA methylation in human tumors is based on the observation that CpG islands prone to hypermethylation in cancers are embedded in chromatin enriched in H3K27me3 in human embryonic stem cells (hESC). Recent studies also link methylation of CpG islands to the methylation status of H3K4, where H3K4me3 is inversely correlated with DNA methylation. To provide insight into these conflicting findings, we generated DNA methylation profiles for acute myeloid leukemia samples from patients and leukemic cell lines and integrated them with publicly available ChIp-seq data, containing H3K4me3 and H3K27me3 CpG island occupation in hESC, or hematopoietic stem or progenitor cells (hHSC/MPP). Hypermethylated CpG islands in AML samples displayed H3K27me3 enrichments in hESC and hHSC/MPP; however, ChIp analysis of specific hypermethylated CpG islands revealed a significant reduction in H3K4me3 signal with a concomitant increase in H3K4me0 levels as opposed to a nonsignificant increase in H3K27me3 marks. The integration of AML DNA methylation profiles with the ChIp-seq data in hESC and hHSC/MPP also led to the identification of Iroquois homeobox 2 (IRX2) as a previously unknown factor promoting differentiation of leukemic cells. Our results indicate that in contrast to the 'instructive model', H3K4me3 levels are strongly associated with DNA methylation patterns in AML and have a role in the regulation of critical genes, such as the putative tumor suppressor IRX2.

Early-life DNA methylation profiles are indicative of age-related transcriptome changes

Background

Alterations to cellular and molecular programs with brain aging result in cognitive impairment and susceptibility to neurodegenerative disease. Changes in DNA methylation patterns, an epigenetic modification required for various CNS functions are observed with brain aging and can be prevented by anti-aging interventions, but the relationship of altered methylation to gene expression is poorly understood.

Results

Paired analysis of the hippocampal methylome and transcriptome with aging of male and female mice demonstrates that age-related differences in methylation and gene expression are anti-correlated within gene bodies and enhancers. Altered promoter methylation with aging was found to be generally un-related to altered gene expression. A more striking relationship was found between methylation levels at young age and differential gene expression with aging. Highly methylated gene bodies and promoters in early life were associated with age-related increases in gene expression even in the absence of significant methylation changes with aging. As well, low levels of methylation in early life were correlated to decreased expression with aging. This relationship was also observed in genes altered in two mouse Alzheimer’s models.

Conclusion

DNA methylation patterns established in youth, in combination with other epigenetic marks, were able to accurately predict changes in transcript trajectories with aging. These findings are consistent with the developmental origins of disease hypothesis and indicate that epigenetic variability in early life may explain differences in aging trajectories and age-related disease.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.

ZCMM: A Novel Method Using Z-Curve Theory- Based and Position Weight Matrix for Predicting Nucleosome Positioning

Nucleosomes are the basic units of eukaryotes. The accurate positioning of nucleosomes plays a significant role in understanding many biological processes such as transcriptional regulation mechanisms and DNA replication and repair. Here, we describe the development of a novel method, termed ZCMM, based on Z-curve theory and position weight matrix (PWM). The ZCMM was trained and tested using the nucleosomal and linker sequences determined by support vector machine (SVM) in Saccharomyces cerevisiae (S. cerevisiae), and experimental results showed that the sensitivity (Sn), specificity (Sp), accuracy (Acc), and Matthews correlation coefficient (MCC) values for ZCMM were 91.40%, 96.56%, 96.75%, and 0.88, respectively, and the average area under the receiver operating characteristic curve (AUC) value was 0.972. A ZCMM predictor was developed to predict nucleosome positioning in Homo sapiens (H. sapiens), Caenorhabditis elegans (C. elegans), and Drosophila melanogaster (D. melanogaster) genomes, and the accuracy (Acc) values were 77.72%, 85.34%, and 93.62%, respectively. The maximum AUC values of the four species were 0.982, 0.861, 0.912 and 0.911, respectively. Another independent dataset for S. cerevisiae was used to predict nucleosome positioning. Compared with the results of Wu's method, it was found that the Sn, Sp, Acc, and MCC of ZCMM results for S. cerevisiae were all higher, reaching 96.72%, 96.54%, 94.10%, and 0.88. Compared with the Guo's method 'iNuc-PseKNC', the results of ZCMM for D. melanogaster were better. Meanwhile, the ZCMM was compared with some experimental data in vitro and in vivo for S. cerevisiae, and the results showed that the nucleosomes predicted by ZCMM were highly consistent with those confirmed by these experiments. Therefore, it was further confirmed that the ZCMM method has good accuracy and reliability in predicting nucleosome positioning.

DNA Methylation of Enhancer Elements in Myeloid Neoplasms: Think Outside the Promoters?

Gene regulation through DNA methylation is a well described phenomenon that has a prominent role in physiological and pathological cell-states. This epigenetic modification is usually grouped in regions denominated CpG islands, which frequently co-localize with gene promoters, silencing the transcription of those genes. Recent genome-wide DNA methylation studies have challenged this paradigm, demonstrating that DNA methylation of regulatory regions outside promoters is able to influence cell-type specific gene expression programs under physiologic or pathologic conditions. Coupling genome-wide DNA methylation assays with histone mark annotation has allowed for the identification of specific epigenomic changes that affect enhancer regulatory regions, revealing an additional layer of complexity to the epigenetic regulation of gene expression. In this review, we summarize the novel evidence for the molecular and biological regulation of DNA methylation in enhancer regions and the dynamism of these changes contributing to the fine-tuning of gene expression. We also analyze the contribution of enhancer DNA methylation on the expression of relevant genes in acute myeloid leukemia and chronic myeloproliferative neoplasms. The characterization of the aberrant enhancer DNA methylation provides not only a novel pathogenic mechanism for different tumors but also highlights novel potential therapeutic targets for myeloid derived neoplasms.

Epigenetic Regulation and Risk Factors During the Development of Human Gametes and Early Embryos

Drastic epigenetic reprogramming occurs during human gametogenesis and early embryo development. Advances in low-input and single-cell epigenetic techniques have provided powerful tools to dissect the genome-wide dynamics of different epigenetic molecular layers in these processes. In this review, we focus mainly on the most recent progress in understanding the dynamics of DNA methylation, chromatin accessibility, and histone modifications in human gametogenesis and early embryo development. Deficiencies in remodeling of the epigenomes can cause severe developmental defects, infertility, and long-term health issues in offspring. Aspects of the external environment, including assisted reproductive technology procedures, parental diets, and unhealthy parental habits, may disturb the epigenetic reprogramming processes and lead to an aberrant epigenome in the offspring. Here, we review the current knowledge of the potential risk factors of aberrant epigenomes in humans.

The Polycomb Repressor Complex 1 Drives Double-Negative Prostate Cancer Metastasis by Coordinating Stemness and Immune Suppression

The mechanisms that enable immune evasion at metastatic sites are poorly understood. We show that the Polycomb Repressor Complex 1 (PRC1) drives colonization of the bones and visceral organs in double-negative prostate cancer (DNPC). In vivo genetic screening identifies CCL2 as the top prometastatic gene induced by PRC1. CCL2 governs self-renewal and induces the recruitment of M2-like tumor-associated macrophages and regulatory T cells, thus coordinating metastasis initiation with immune suppression and neoangiogenesis. A catalytic inhibitor of PRC1 cooperates with immune checkpoint therapy to reverse these processes and suppress metastasis in genetically engineered mouse transplantation models of DNPC. These results reveal that PRC1 coordinates stemness with immune evasion and neoangiogenesis and point to the potential clinical utility of targeting PRC1 in DNPC.

DNA G-Quadruplexes (G4s) Modulate Epigenetic (Re)Programming and Chromatin Remodeling: Transient Genomic G4s Assist in the Establishment and Maintenance of Epigenetic Marks, While Persistent G4s May Erase Epigenetic Marks

Here, the emerging data on DNA G-quadruplexes (G4s) as epigenetic modulators are reviewed and integrated. This concept has appeared and evolved substantially in recent years. First, persistent G4s (e.g., those stabilized by exogenous ligands) were linked to the loss of the histone code. More recently, transient G4s (i.e., those formed upon replication or transcription and unfolded rapidly by helicases) were implicated in CpG island methylation maintenance and de novo CpG methylation control. The most recent data indicate that there are direct interactions between G4s and chromatin remodeling factors. Finally, multiple findings support the indirect participation of G4s in chromatin reshaping via interactions with remodeling-related transcription factors (TFs) or damage responders. Here, the links between the above processes are analyzed; also, how further elucidation of these processes may stimulate the progress of epigenetic therapy is discussed, and the remaining open questions are highlighted.

Single-Nucleotide Polymorphisms Sequencing Identifies Candidate Functional Variants at Prostate Cancer Risk Loci

Genome-wide association studies have identified over 150 risk loci that increase prostate cancer risk. However, few causal variants and their regulatory mechanisms have been characterized. In this study, we utilized our previously developed single-nucleotide polymorphisms sequencing (SNPs-seq) technology to test allele-dependent protein binding at 903 SNP sites covering 28 genomic regions. All selected SNPs have shown significant cis-association with at least one nearby gene. After preparing nuclear extract using LNCaP cell line, we first mixed the extract with dsDNA oligo pool for protein–DNA binding incubation. We then performed sequencing analysis on protein-bound oligos. SNPs-seq analysis showed protein-binding differences (>1.5-fold) between reference and variant alleles in 380 (42%) of 903 SNPs with androgen treatment and 403 (45%) of 903 SNPs without treatment. From these significant SNPs, we performed a database search and further narrowed down to 74 promising SNPs. To validate this initial finding, we performed electrophoretic mobility shift assay in two SNPs (rs12246440 and rs7077275) at CTBP2 locus and one SNP (rs113082846) at NCOA4 locus. This analysis showed that all three SNPs demonstrated allele-dependent protein-binding differences that were consistent with the SNPs-seq. Finally, clinical association analysis of the two candidate genes showed that CTBP2 was upregulated, while NCOA4 was downregulated in prostate cancer (p < 0.02). Lower expression of CTBP2 was associated with poor recurrence-free survival in prostate cancer. Utilizing our experimental data along with bioinformatic tools provides a strategy for identifying candidate functional elements at prostate cancer susceptibility loci to help guide subsequent laboratory studies.

Enrichment analysis with EpiAnnotator

Motivation

Deciphering relevant biological insights from epigenomic data can be a challenging task. One commonly used approach is to perform enrichment analysis. However, finding, downloading and using the publicly available functional annotations require time, programming skills and IT infrastructure. Here we describe the online tool EpiAnnotator for performing enrichment analyses on epigenomic data in a fast and user-friendly way.

Results

EpiAnnotator is an R Package accompanied by a web interface. It contains regularly updated annotations from 4 public databases: Blueprint, RoadMap, GENCODE and the UCSC Genome Browser. Annotations are hosted locally or in a server environment and automatically updated by scripts of our own design. Thousands of tracks are available, reflecting data on a variety of tissues, cell types and cell lines from the human and mouse genomes. Users need to upload sets of selected and background regions. Results are displayed in customizable and easily interpretable figures.

Availability and implementation

The R package and Shiny app are open source and available under the GPL v3 license. EpiAnnotator’s web interface is accessible at http://computational-epigenomics.com/en/epiannotator.

NOMePlot: analysis of DNA methylation and nucleosome occupancy at the single molecule

Recent technical advances highlight that to understand mammalian development and human disease we need to consider transcriptional and epigenetic cell-to-cell differences within cell populations. This is particularly important in key areas of biomedicine like stem cell differentiation and intratumor heterogeneity. The recently developed nucleosome occupancy and methylome (NOMe) assay facilitates the simultaneous study of DNA methylation and nucleosome positioning on the same DNA strand. NOMe-treated DNA can be sequenced by sanger (NOMe-PCR) or high throughput approaches (NOMe-seq). NOMe-PCR provides information for a single locus at the single molecule while NOMe-seq delivers genome-wide data that is usually interrogated to obtain population-averaged measures. Here, we have developed a bioinformatic tool that allow us to easily obtain locus-specific information at the single molecule using genome-wide NOMe-seq datasets obtained from bulk populations. We have used NOMePlot to study mouse embryonic stem cells and found that polycomb-repressed bivalent gene promoters coexist in two different epigenetic states, as defined by the nucleosome binding pattern detected around their transcriptional start site.

Hierarchical cooperation of transcription factors from integration analysis of DNA sequences, ChIP-Seq and ChIA-PET data

Background

Chromosomal architecture, which is constituted by chromatin loops, plays an important role in cellular functions. Gene expression and cell identity can be regulated by the chromatin loop, which is formed by proximal or distal enhancers and promoters in linear DNA (1D). Enhancers and promoters are fundamental non-coding elements enriched with transcription factors (TFs) to form chromatin loops. However, the specific cooperation of TFs involved in forming chromatin loops is not fully understood.

Results

Here, we proposed a method for investigating the cooperation of TFs in four cell lines by the integrative analysis of DNA sequences, ChIP-Seq and ChIA-PET data. Results demonstrate that the interaction of enhancers and promoters is a hierarchical and dynamic complex process with cooperative interactions of different TFs synergistically regulating gene expression and chromatin structure. The TF cooperation involved in maintaining and regulating the chromatin loop of cells can be regulated by epigenetic factors, such as other TFs and DNA methylation.

Conclusions

Such cooperation among TFs provides the potential features that can affect chromatin’s 3D architecture in cells. The regulation of chromatin 3D organization and gene expression is a complex process associated with the hierarchical and dynamic prosperities of TFs.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5535-2) contains supplementary material, which is available to authorized users.