DNA Methylation Heterogeneity Research Articles

Genetic Alterations, DNA Methylation, Alloantibodies and Phenotypic Heterogeneity in Type III von Willebrand Disease.

Type III von Willebrand disease is present in the Punjab province of Pakistan along with other inherited bleeding disorders like hemophilia. Cousin marriages are very common in Pakistan so genetic studies help to establish protocols for screening, especially at the antenatal level. Factors behind the phenotypic variation of the severity of bleeding in type III vWD are largely unknown. The study was conducted to determine Mutations/genetic alterations in type III von Willebrand disease and also to determine the association of different mutations, methylation status, ITGA2B/B3 mutations and alloimmunization with the severity of type III vWD. After informed consent and detailed history of the patients, routine tests and DNA extraction from blood, mutational analysis was performed by Next Generation Sequencing on Ion Torrent PGM. DNA methylation status was also checked with the help of PCR. In our cohort, 55 cases were detected with pathogenic mutations. A total of 27 different mutations were identified in 55 solved cases; 16 (59.2%) were novel. The mean bleeding score in truncating mutations and essential splice site mutations was relatively higher than weak and strong missense mutations. The mean bleeding score showed insignificant variation for different DNA methylation statuses of the VWF gene at the cg23551979 CpG site. Mutations in exons 7,10, 25, 28, 31, 43, and intron 41 splice site account for 75% of the mutations.

ScTEM-seq: Single-cell analysis of transposable element methylation to link global epigenetic heterogeneity with transcriptional programs

Global changes in DNA methylation are observed in development and disease, and single-cell analyses are highlighting the heterogeneous regulation of these processes. However, technical challenges associated with single-cell analysis of DNA methylation limit these studies. We present single-cell transposable element methylation sequencing (scTEM-seq) for cost-effective estimation of average DNA methylation levels. By targeting high-copy SINE Alu elements, we achieve amplicon bisulphite sequencing with thousands of loci covered in each scTEM-seq library. Parallel transcriptome analysis is also performed to link global DNA methylation estimates with gene expression. We apply scTEM-seq to KG1a acute myeloid leukaemia (AML) cells, and primary AML cells. Our method reveals global DNA methylation heterogeneity induced by decitabine treatment of KG1a cells associated with altered expression of immune process genes. We also compare global DNA methylation estimates to expression of transposable elements and find a predominance of negative correlations. Finally, we observe co-ordinated upregulation of many transposable elements in a sub-set of decitabine treated cells. By linking global DNA methylation heterogeneity with transcription, scTEM-seq will refine our understanding of epigenetic regulation in cancer and beyond.

Analysis at the single-cell level indicates an important role of heterogeneous global DNA methylation status on the progression of lung adenocarcinoma

Aberrant DNA modifications affect the tumorigenesis and progression of lung cancer. However, the global methylation status of tumor cells and the heterogeneous methylation status of cells within the same tumor need further study. We used publicly available single-cell RNAseq data to investigate the impact and diversity of global methylation status on lung adenocarcinoma. Clustering cells into subgroups and cell differentiation pseudotime analysis, based on expression profile, demonstrated that the global methylation status was crucial to lung adenocarcinoma function and progression. Hypermethylated tumor cells had increased activity related to the hypoxia response. Hyper- and hypomethylated cells indicated upregulation in pathways involving focal adhesion and cell junctions. Pseudotime analysis showed that cell clusters with unique methylation activities were located at the ends of the putative trajectories, suggesting that DNA methylation and demethylation activities were essential to tumor cell progression. Expression of SPP1 was associated with the global methylation status of tumor cells and with patient prognosis. Our study identified the importance and diversity of global DNA methylation status by analysis at the single-cell level. Our findings provide new information about the global DNA methylation status of tumor cells and suggest new approaches for precision medical treatments for lung adenocarcinoma.

CUT&Tag-BS for simultaneous profiling of histone modification and DNA methylation with high efficiency and low cost

SummaryIt remains a challenge to decipher the complex relationship between DNA methylation, histone modification, and the underlying DNA sequence with limited input material. Here, we developed an efficient, low-input, and low-cost method for the simultaneous profiling of genomic localization of histone modification and methylation status of the underlying DNA at single-base resolution from the same cells in a single experiment by integrating cleavage under targets and tagmentation (CUT&Tag) with tagmentation-based bisulfite sequencing (CUT&Tag-BS). We demonstrated the validity of our method using representative histone modifications of euchromatin and constitutive and facultative heterochromatin (H3K4me1, H3K9me3, and H3K27me3, respectively). Similar histone modification enrichment patterns were observed in CUT&Tag-BS compared with non-bisulfite-treated control, and H3K4me1-marked regions were found to mostly be CpG poor, lack methylation concordance, and exhibit prevalent DNA methylation heterogeneity among mouse embryonic stem cells (mESCs). We anticipate that CUT&Tag-BS will be widely applied to directly address the genomic relationship between DNA methylation and histone modification, especially in low-input scenarios with precious biological samples.

The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability

BackgroundCancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective.MethodsHere, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients.ResultsWe show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability.ConclusionsWe propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.

DNA Methylation and Intra-Clonal Heterogeneity: The Chronic Myeloid Leukemia Model.

Simple SummaryIn Chronic Myeloid Leukemia (CML), intra-clonal heterogeneity is a major factor in the response to tyrosine kinase inhibitors and in leukemia stem cell persistence. This intra-clonal heterogeneity could be partially explained by epigenetic abnormalities. This review focuses on DNA methylation abnormalities in CML and its potential implications for the development of new biomarkers of the treatment response and new therapy opportunities. DNA methylation abnormalities are considered an important event in the CML progression phase. Moreover, in recent years, DNA methylation abnormalities have also been characterized at CML diagnosis (in the chronic phase), with specific alterations in the immature cells of the tumor clone. Lastly, the review discusses the importance of these finding for understanding the disease emergence, for developing new therapeutic strategies, and for a personalized management of CML.Chronic Myeloid Leukemia (CML) is a model to investigate the impact of tumor intra-clonal heterogeneity in personalized medicine. Indeed, tyrosine kinase inhibitors (TKIs) target the BCR-ABL fusion protein, which is considered the major CML driver. TKI use has highlighted the existence of intra-clonal heterogeneity, as indicated by the persistence of a minority subclone for several years despite the presence of the target fusion protein in all cells. Epigenetic modifications could partly explain this heterogeneity. This review summarizes the results of DNA methylation studies in CML. Next-generation sequencing technologies allowed for moving from single-gene to genome-wide analyses showing that methylation abnormalities are much more widespread in CML cells. These data showed that global hypomethylation is associated with hypermethylation of specific sites already at diagnosis in the early phase of CML. The BCR-ABL-independence of some methylation profile alterations and the recent demonstration of the initial intra-clonal DNA methylation heterogeneity suggests that some DNA methylation alterations may be biomarkers of TKI sensitivity/resistance and of disease progression risk. These results also open perspectives for understanding the epigenetic/genetic background of CML predisposition and for developing new therapeutic strategies.

Integrative Epigenomics Reveals Novel Chronic Lymphocytic Leukemia-Specific Chromatin States Associated with Epigenetic and Transcriptional Heterogeneity

Chronic lymphocytic leukemia (CLL) evolves through progression and relapse. Intra-leukemic epigenetic heterogeneity in DNA methylation (DNAme) has been shown to co-operate with genetic heterogeneity in increasing CLL's evolutionary capacity. However, DNAme constitutes only one layer of epigenetic information. To comprehensively study the epigenetic landscape of CLL and its intra-leukemic heterogeneity, we complemented bisulfite sequencing with RNA-seq and a ChIP-seq compendium of histone modification maps (H3K4me3, H3K27ac, H3K27me3, H3K9me3, H3K36me3) in a cohort of 17 primary CLL and 5 normal B cell samples.Analysis of H3K4me3 and H3K27ac distribution revealed that CLL is associated with greater enhancer activation than normal B cells, with enhanced NFAT, FOXP1, NFkB, and BACH2 activity, as well as downregulated TP53 activity. 1,013 super-enhancers were differentially regulated in CLL compared with normal B cells, with preferential association for genes critical for lymphocyte proliferation and differentiation (including BCL2, TCF/LEF, and EP400) (Figure A).Next, we hypothesized that intra-leukemic admixtures of epigenetic states and stochastic epigenetic changes during CLL evolution, may lead to reduced co-ordination between any two layers of epigenetic or transcriptional information. To assess this, we drew on a fundamental metric in information theory - mutual information (MI) - which measures how much can be learned from one variable about another. Normal B cells exhibited highly coordinated transcriptional regulation, resulting in higher pairwise MI compared with CLL samples. For example, we observed a 13% decrease in DNAme-RNAseq MI in CLL relative to normal B cells, suggesting that stochastic changes and intra-leukemic heterogeneity decreases the MI of these two variables when measured at the population level (Figure B).To extend the evaluation of epigenetic co-ordination beyond mutual information of two variables, we modeled the combinatorial patterns of histone modifications, DNAme, and gene expression using a Dirichlet Process Mixture (DPM), which allows learning de novo the number of combinatorial states. DPM analysis revealed that while in normal B cells the combinatorial chromatin states were generally associated with a uniform transcriptional output, in CLL many of these states were associated with variable expression level. For example, transcription start sites (TSSs) with H3K27me3hi/H3K4me3low/H3K27aclow, that in normal B cells were associated with uniform gene silencing, were 3 times more likely to be associated with gene expression in CLL (P < 0.0001, Figure C).To validate the greater combinatorial epigenetic complexity in CLL, we applied an orthogonal method by training a multivariate Hidden Markov Model (HMM) in CLL and normal B cells. We identified convergence at 12 states(Figure D). HHM distinguished between CLL and normal B cells, with ~20,000 segments assigned to discrepant states between CLL and normal cells, enriched for TP53 regulated genes. Consistent with greater combinatorial complexity, we observed higher within-state variation in CLL, with active TSSs, transcribed regions, and poised TSSs exhibiting the largest fold-change increase in within-state variability (2.7, 2.5, and 1.4, respectively).Interestingly, HMM also revealed a CLL specific state (P < 0.0001) marked by intermediate H3K27ac and H3K27me3, which are typically exclusive. This state was >2-fold more common in CLL than normal B cells. CLL cells harbored ~1.6M segments of this novel state often located at non-first introns and LTRs and distal regulatory elements. Interestingly, these segments, repressed by Polycomb in normal B cells, were also more likely to be reactivated in CLL (OR: 1.98; CI: 1.39-2.82; P < 0.0001), putatively enabling higher MYC activity by motif enrichment analysis (Figure D-inset).Thus, CLL's epigenetic landscape is marked by decreased co-ordination between different layers of the epigenome. Our data suggest that ongoing diversification of the CLL cell population leads to an admixture of cells with diverging epigenetic identities, resulting in incomplete gene silencing by the Polycomb complex, and unexpected co-occurrence of, typically mutually exclusive, activating and repressing histone modifications. [Display omitted] DisclosuresLandau:Pharmacyclics: Membership on an entity's Board of Directors or advisory committees.

ScMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution

High-throughput single-cell measurements of DNA methylomes can quantify methylation heterogeneity and uncover its role in gene regulation. However, technical limitations and sparse coverage can preclude this task. scMET is a hierarchical Bayesian model which overcomes sparsity, sharing information across cells and genomic features to robustly quantify genuine biological heterogeneity. scMET can identify highly variable features that drive epigenetic heterogeneity, and perform differential methylation and variability analyses. We illustrate how scMET facilitates the characterization of epigenetically distinct cell populations and how it enables the formulation of novel hypotheses on the epigenetic regulation of gene expression. scMET is available at https://github.com/andreaskapou/scMET.

Intratumor heterogeneity of breast cancer detected by epialleles shows association with hypoxic microenvironment.

Rationale: In breast cancer, high intratumor DNA methylation heterogeneity can lead to drug-resistant, metastasis and poor prognosis of tumors, which increases the complexity of cancer diagnosis and treatment. However, most studies are limited to average DNA methylation level of individual CpGs and ignore heterogeneous DNA methylation patterns of cell subpopulations within the tumor. Thus, quantifying the variability in DNA methylation pattern in sequencing reads is valuable for understanding intratumor heterogeneity.Methods: We performed Reduced Representation Bisulfite Sequencing and RNA sequencing for tumor core and tumor periphery regions within one breast tumor. By developing a method named “epialleJS” based on Jensen-Shannon divergence, we detected the differential epialleles between tumor core and tumor periphery (CPDEs). We then explored the correlation between intratumor methylation heterogeneity and hypoxic microenvironment in TCGA breast cancer cohort.Results: More than 70% of CPDEs had higher epipolymorphism in tumor core than tumor periphery, and these CPDEs had lower methylation in tumor core. The CPDEs with lower methylation in tumor core may associate with hypoxic tumor microenvironment. Moreover, we identified a signature of five hypoxia-related DNA methylation markers which can predict the prognosis of breast cancer patients, including a CpG site cg15190451 in gene SLC16A5. Furthermore, immunohistochemical analysis confirmed that the expression of SLC16A5 was associated with clinicopathological characteristics and survival of breast cancer patients.Conclusions: The analysis of intratumor DNA methylation heterogeneity based on epialleles reveals that disordered methylation patterns in tumor core are associated with hypoxic microenvironment, which provides a framework for understanding biological heterogeneous behavior and guidance for developing effective treatment schemes for breast cancer patients.

CUT&amp;amp;Tag-BS: An Efficient and Low-Cost Method for Simultaneous Profiling of Histone Modification and DNA Methylation

SummaryIt remains a challenge to decipher the complex relationship between DNA methylation, histone modification, and the underlying DNA sequence with limited input material. Here, we developed an efficient, low-input, and low-cost method for simultaneous profiling of genomic localization of histone modification and methylation status of the underlying DNA at single-base resolution from the same cells in a single experiment by integrating CUTT it further reveals that H3K4me1-marked regions are mostly CpG-poor, lack methylation concordance, and exhibit prevalent DNA methylation heterogeneity among the cells. We anticipate that CUT&Tag-BS will be widely applied to directly address the genomic relationship between DNA methylation and histone modification, especially in low-input scenarios with precious biological samples.

A DNA methylation state transition model reveals the programmed epigenetic heterogeneity in human pre-implantation embryos

BackgroundDuring mammalian early embryogenesis, expression and epigenetic heterogeneity emerge before the first cell fate determination, but the programs causing such determinate heterogeneity are largely unexplored.ResultsHere, we present MethylTransition, a novel DNA methylation state transition model, for characterizing methylation changes during one or a few cell cycles at single-cell resolution. MethylTransition involves the creation of a transition matrix comprising three parameters that represent the probabilities of DNA methylation-modifying activities in order to link the methylation states before and after a cell cycle. We apply MethylTransition to single-cell DNA methylome data from human pre-implantation embryogenesis and elucidate that the DNA methylation heterogeneity that emerges at promoters during this process is largely an intrinsic output of a program with unique probabilities of DNA methylation-modifying activities. Moreover, we experimentally validate the effect of the initial DNA methylation on expression heterogeneity in pre-implantation mouse embryos.ConclusionsOur study reveals the programmed DNA methylation heterogeneity during human pre-implantation embryogenesis through a novel mathematical model and provides valuable clues for identifying the driving factors of the first cell fate determination during this process.

1228P Integrated analysis of gene expression and chromosomal aberrations to determine the global patterns of DNA methylation heterogeneity in the TRACERx lung study

1228P Integrated analysis of gene expression and chromosomal aberrations to determine the global patterns of DNA methylation heterogeneity in the TRACERx lung study

DNA Methylation Heterogeneity Induced by Collaborations Between Enhancers.

During mammalian embryo development, reprogramming of DNA methylation plays important roles in the erasure of parental epigenetic memory and the establishment of naive pluripotent cells. Multiple enzymes that regulate the processes of methylation and demethylation work together to shape the pattern of genome-scale DNA methylation and guide the process of cell differentiation. Recent availability of methylome information from single-cell whole genome bisulfite sequencing (scBS-seq) provides an opportunity to study DNA methylation dynamics in the whole genome in individual cells, which reveal the heterogeneous methylation distributions of enhancers in embryo stem cells. In this study, we developed a computational model of enhancer methylation inheritance to study the dynamics of genome-scale DNA methylation reprogramming during exit from pluripotency. The model enables us to track genome-scale DNA methylation reprogramming at single-cell level during the embryo development process and reproduce the DNA methylation heterogeneity reported by scBS-seq. Model simulations show that DNA methylation heterogeneity is an intrinsic property driven by cell division along the development process, and the collaboration between neighboring enhancers is required for heterogeneous methylation. Our study suggests that the mechanism of genome-scale oscillation might not be necessary for the DNA methylation heterogeneity during exit from pluripotency.

Stochastic modeling reveals kinetic heterogeneity in post-replication DNA methylation.

DNA methylation is a heritable epigenetic modification that plays an essential role in mammalian development. Genomic methylation patterns are dynamically maintained, with DNA methyltransferases mediating inheritance of methyl marks onto nascent DNA over cycles of replication. A recently developed experimental technique employing immunoprecipitation of bromodeoxyuridine labeled nascent DNA followed by bisulfite sequencing (Repli-BS) measures post-replication temporal evolution of cytosine methylation, thus enabling genome-wide monitoring of methylation maintenance. In this work, we combine statistical analysis and stochastic mathematical modeling to analyze Repli-BS data from human embryonic stem cells. We estimate site-specific kinetic rate constants for the restoration of methyl marks on >10 million uniquely mapped cytosines within the CpG (cytosine-phosphate-guanine) dinucleotide context across the genome using Maximum Likelihood Estimation. We find that post-replication remethylation rate constants span approximately two orders of magnitude, with half-lives of per-site recovery of steady-state methylation levels ranging from shorter than ten minutes to five hours and longer. Furthermore, we find that kinetic constants of maintenance methylation are correlated among neighboring CpG sites. Stochastic mathematical modeling provides insight to the biological mechanisms underlying the inference results, suggesting that enzyme processivity and/or collaboration can produce the observed kinetic correlations. Our combined statistical/mathematical modeling approach expands the utility of genomic datasets and disentangles heterogeneity in methylation patterns arising from replication-associated temporal dynamics versus stable cell-to-cell differences.

MP18-14 CHARACTERISING DNA METHYLATION PATTERNS IN TISSUE AND CIRCULATING TUMOUR DNA TO ENABLE DIFFERENTIATION OF SMALL RENAL MASSES

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology II (MP18)1 Apr 2020MP18-14 CHARACTERISING DNA METHYLATION PATTERNS IN TISSUE AND CIRCULATING TUMOUR DNA TO ENABLE DIFFERENTIATION OF SMALL RENAL MASSES Sabrina Rossi*, Sara Pita, Anne Babbage, Gahee Park, Radoslaw Lach, Christopher Smith, Kevin Brennan, Tom Mitchell, Anne Warren, Olivier Gevaert, Charlie Massie, Grant Stewart, and DIAMOND Biobank Study Group Sabrina Rossi*Sabrina Rossi* More articles by this author , Sara PitaSara Pita More articles by this author , Anne BabbageAnne Babbage More articles by this author , Gahee ParkGahee Park More articles by this author , Radoslaw LachRadoslaw Lach More articles by this author , Christopher SmithChristopher Smith More articles by this author , Kevin BrennanKevin Brennan More articles by this author , Tom MitchellTom Mitchell More articles by this author , Anne WarrenAnne Warren More articles by this author , Olivier GevaertOlivier Gevaert More articles by this author , Charlie MassieCharlie Massie More articles by this author , Grant StewartGrant Stewart More articles by this author , and DIAMOND Biobank Study GroupDIAMOND Biobank Study Group More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000843.014AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Small renal masses (SRM) represent a diagnostic challenge. Indeed, ∼20% of SRM removed at surgery are found to be benign post-operatively. Renal biopsy may be non-diagnostic due to small tumour size, challenging anatomy or tumour heterogeneity. Circulating tumour DNA (ctDNA) analysis of DNA methylation in plasma or urine may overcome sampling bias associated with genetic intratumoral heterogeneity and offer a non-invasive method to derive a diagnosis. To test whether epigenetic markers differentiate pathological subtypes of renal masses we aim to (a) analyse multi-region samples from patients with renal tumours to map the landscape of DNA methylation heterogeneity and (b) evaluate methylation markers in triplicates of tissue, plasma and urine. METHODS: We recruited a cohort of patients across the RCC disease spectrum, from small renal masses to metastatic disease, including different pathological subtypes. Ethical approval was obtained (DIAMOND biobank; REC ID 03/018). Multi-region kidney tumour samples were collected from the nephrectomy specimen, including adjacent normal tissue, as well as urine and plasma samples from the same patients. Methylation analysis was performed in tissue using the Illumina EPIC Methyl Capture library preparation kit, with post capture bisulfite conversion. RESULTS: Tumour and normal samples were collected from 75 individuals with clear cell (N=35), chromophobe (N=10), papillary (N=20) RCC and oncocytoma (N=10). Additionally, we sequenced 142 multi-region samples from a subset of 26 patients and performed epigenetic phylogenetic analyses. We identified sets of differentially methylated cytosines at base-pair resolution in tumour tissue that (a) classify pathological subtypes of RCC and oncocytomas and (b) represent early ‘stem’ markers for ctDNA analysis. We present a summary of epigenetic clonal evolution and identify markers for high-sensitivity targeted analysis of DNA methylation in liquid samples. CONCLUSIONS: We evaluate DNA methylation in a large cohort of patients with pathological subtypes of renal tumours. This may represent a promising target for non-invasive liquid biopsy to differentiate benign from malignant small renal masses. Source of Funding: SHR is funded by a Cancer Research UK PhD Fellowship. © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e240-e241 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Sabrina Rossi* More articles by this author Sara Pita More articles by this author Anne Babbage More articles by this author Gahee Park More articles by this author Radoslaw Lach More articles by this author Christopher Smith More articles by this author Kevin Brennan More articles by this author Tom Mitchell More articles by this author Anne Warren More articles by this author Olivier Gevaert More articles by this author Charlie Massie More articles by this author Grant Stewart More articles by this author DIAMOND Biobank Study Group More articles by this author Expand All Advertisement PDF downloadLoading ...

CLL intraclonal fractions exhibit established and recently acquired patterns of DNA methylation

AbstractIntraclonal subpopulations of circulating chronic lymphocytic leukemia (CLL) cells with different proliferative histories and reciprocal surface expression of CXCR4 and CD5 have been observed in the peripheral blood of CLL patients and named proliferative (PF), intermediate (IF), and resting (RF) cellular fractions. Here, we found that these intraclonal circulating fractions share persistent DNA methylation signatures largely associated with the mutation status of the immunoglobulin heavy chain locus (IGHV) and their origins from distinct stages of differentiation of antigen-experienced B cells. Increased leukemic birth rate, however, showed a very limited impact on DNA methylation of circulating CLL fractions independent of IGHV mutation status. Additionally, DNA methylation heterogeneity increased as leukemic cells advanced from PF to RF in the peripheral blood. This frequently co-occurred with heterochromatin hypomethylation and hypermethylation of Polycomb-repressed regions in the PF, suggesting accumulation of longevity-associated epigenetic features in recently born cells. On the other hand, transcriptional differences between paired intraclonal fractions confirmed their proliferative experience and further supported a linear advancement from PF to RF in the peripheral blood. Several of these differentially expressed genes showed unique associations with clinical outcome not evident in the bulk clone, supporting the pathological and therapeutic relevance of studying intraclonal CLL fractions. We conclude that independent methylation and transcriptional landscapes reflect both preexisting cell-of-origin fingerprints and more recently acquired hallmarks associated with the life cycle of circulating CLL cells.

Quantitative comparison of within-sample heterogeneity scores for DNA methylation data.

DNA methylation is an epigenetic mark with important regulatory roles in cellular identity and can be quantified at base resolution using bisulfite sequencing. Most studies are limited to the average DNA methylation levels of individual CpGs and thus neglect heterogeneity within the profiled cell populations. To assess this within-sample heterogeneity (WSH) several window-based scores that quantify variability in DNA methylation in sequencing reads have been proposed. We performed the first systematic comparison of four published WSH scores based on simulated and publicly available datasets. Moreover, we propose two new scores and provide guidelines for selecting appropriate scores to address cell-type heterogeneity, cellular contamination and allele-specific methylation. Most of the measures were sensitive in detecting DNA methylation heterogeneity in these scenarios, while we detected differences in susceptibility to technical bias. Using recently published DNA methylation profiles of Ewing sarcoma samples, we show that DNA methylation heterogeneity provides information complementary to the DNA methylation level. WSH scores are powerful tools for estimating variance in DNA methylation patterns and have the potential for detecting novel disease-associated genomic loci not captured by established statistics. We provide an R-package implementing the WSH scores for integration into analysis workflows.

Inter- and intratumor DNA methylation heterogeneity associated with lymph node metastasis and prognosis of esophageal squamous cell carcinoma.

Background: Esophageal squamous cell carcinoma (ESCC), one of the leading causes of cancer mortality worldwide, is a heterogeneous cancer with diverse clinical manifestations. However, little is known about the epigenetic heterogeneity and its clinical relevance for this prevalent cancer.Methods: We generated 7.56 Tb single-base resolution whole-genome bisulfite sequencing data for 84 ESCC and paired paraneoplastic tissues. The analysis identified inter- and intratumor DNA methylation (DNAm) heterogeneity, epigenome-wide DNAm alterations together with the functional regulators involved in the hyper- or hypomethylated regions, and their association with clinical features. We then validated the correlation between the methylation level of specific regions and clinical outcomes of 96 ESCC patients in an independent cohort.Results: ESCC manifested substantial inter- and intratumor DNAm heterogeneity. The high intratumor DNAm heterogeneity was associated with lymph node metastasis and worse overall survival. Interestingly, hypermethylated regions in ESCC were enriched in promoters of numerous transcription factors, and demethylated noncoding regions related to RXR transcription factor binding appeared to contribute to the development of ESCC. Furthermore, we identified numerous DNAm alterations associated with carcinogenesis and lymph node metastasis of ESCC. We also validated three novel prognostic markers for ESCC, including one each in the promoter of CLK1, the 3' untranslated region of ZEB2, and the intergenic locus surrounded by several lncRNAs.Conclusions: This study presents the first population-level resource for dissecting base-resolution DNAm variation in ESCC and provides novel insights into the ESCC pathogenesis and progression, which might facilitate diagnosis and prognosis for this prevalent malignancy.

The diverse roles of DNA methylation in mammalian development and disease.

DNA methylation is of paramount importance for mammalian embryonic development. DNA methylation has numerous functions: it is implicated in the repression of transposons and genes, but is also associated with actively transcribed gene bodies and, in some cases, with gene activation per se. In recent years, sensitive technologies have been developed that allow the interrogation of DNA methylation patterns from a small number of cells. The use of these technologies has greatly improved our knowledge of DNA methylation dynamics and heterogeneity in embryos and in specific tissues. Combined with genetic analyses, it is increasingly apparent that regulation of DNA methylation erasure and (re-)establishment varies considerably between different developmental stages. In this Review, we discuss the mechanisms and functions of DNA methylation and demethylation in both mice and humans at CpG-rich promoters, gene bodies and transposable elements. We highlight the dynamic erasure and re-establishment of DNA methylation in embryonic, germline and somatic cell development. Finally, we provide insights into DNA methylation gained from studying genetic diseases.

Corrupted coordination of epigenetic modifications leads to diverging chromatin states and transcriptional heterogeneity in CLL

Cancer evolution is fueled by epigenetic as well as genetic diversity. In chronic lymphocytic leukemia (CLL), intra-tumoral DNA methylation (DNAme) heterogeneity empowers evolution. Here, to comprehensively study the epigenetic dimension of cancer evolution, we integrate DNAme analysis with histone modification mapping and single cell analyses of RNA expression and DNAme in 22 primary CLL and 13 healthy donor B lymphocyte samples. Our data reveal corrupted coherence across different layers of the CLL epigenome. This manifests in decreased mutual information across epigenetic modifications and gene expression attributed to cell-to-cell heterogeneity. Disrupted epigenetic-transcriptional coordination in CLL is also reflected in the dysregulation of the transcriptional output as a function of the combinatorial chromatin states, including incomplete Polycomb-mediated gene silencing. Notably, we observe unexpected co-mapping of typically mutually exclusive activating and repressing histone modifications, suggestive of intra-tumoral epigenetic diversity. Thus, CLL epigenetic diversification leads to decreased coordination across layers of epigenetic information, likely reflecting an admixture of cells with diverging cellular identities.