ARID1A regulates DNA repair through chromatin organization and its deficiency triggers DNA damage-mediated anti-tumor immune response

AT-rich interaction domain protein 1A (ARID1A), a SWI/SNF chromatin remodeling complex subunit, is frequently mutated across various cancer entities. Loss of ARID1A leads to DNA repair defects. Here, we show that ARID1A plays epigenetic roles to promote both DNA double-strand breaks (DSBs) repair pathways, non-homologous end-joining (NHEJ) and homologous recombination (HR). ARID1A is accumulated at DSBs after DNA damage and regulates chromatin loops formation by recruiting RAD21 and CTCF to DSBs. Simultaneously, ARID1A facilitates transcription silencing at DSBs in transcriptionally active chromatin by recruiting HDAC1 and RSF1 to control the distribution of activating histone marks, chromatin accessibility, and eviction of RNAPII. ARID1A depletion resulted in enhanced accumulation of micronuclei, activation of cGAS-STING pathway, and an increased expression of immunomodulatory cytokines upon ionizing radiation. Furthermore, low ARID1A expression in cancer patients receiving radiotherapy was associated with higher infiltration of several immune cells. The high mutation rate of ARID1A in various cancer types highlights its clinical relevance as a promising biomarker that correlates with the level of immune regulatory cytokines and estimates the levels of tumor-infiltrating immune cells, which can predict the response to the combination of radio- and immunotherapy.

Dnmt3a1 regulates hippocampus-dependent memory via the downstream target Nrp1

Epigenetic factors are well-established players in memory formation. Specifically, DNA methylation is necessary for the formation of long-term memory in multiple brain regions including the hippocampus. Despite the demonstrated role of DNA methyltransferases (Dnmts) in memory formation, it is unclear whether individual Dnmts have unique or redundant functions in long-term memory formation. Furthermore, the downstream processes controlled by Dnmts during memory consolidation have not been investigated. In this study, we demonstrated that Dnmt3a1, the predominant Dnmt in the adult brain, is required for long-term spatial object recognition and contextual fear memory. Using RNA sequencing, we identified an activity-regulated Dnmt3a1-dependent genomic program in which several genes were associated with functional and structural plasticity. Furthermore, we found that some of the identified genes are selectively dependent on Dnmt3a1, but not its isoform Dnmt3a2. Specifically, we identified Neuropilin 1 (Nrp1) as a downstream target of Dnmt3a1 and further demonstrated the involvement of Nrp1 in hippocampus-dependent memory formation. Importantly, we found that Dnmt3a1 regulates hippocampus-dependent memory via Nrp1. In contrast, Nrp1 overexpression did not rescue memory impairments triggered by reduced Dnmt3a2 levels. Taken together, our study uncovered a Dnmt3a-isoform-specific mechanism in memory formation, identified a novel regulator of memory, and further highlighted the complex and highly regulated functions of distinct epigenetic regulators in brain function.

Discovery of non-genomic drivers of YAP signaling modulating the cell plasticity in CRC tumor lines

In normal intestines, a fetal/regenerative/revival cell state can be induced upon inflammation. This plasticity in cell fate is also one of the current topics in human colorectal cancer (CRC). To dissect the underlying mechanisms, we generated human CRC organoids with naturally selected genetic mutation profiles and exposed them to two different conditions by modulating the extracellular matrix (ECM). Among tested mutation profiles, a fetal/regenerative/revival state was induced following YAP activation via a collagen type I-enriched microenvironment. Mechanistically, YAP transcription was promoted by activating AP-1 and TEAD-dependent transcription and suppressing intestinal lineage-determining transcription via mechanotransduction. The phenotypic conversion was also involved in chemoresistance, which could be potentially resolved by targeting the underlying YAP regulatory elements, a potential target of CRC treatment.

Aberrant MNX1 expression associated with t(7;12)(q36;p13) pediatric acute myeloid leukemia induces the disease through altering histone methylation

Certain subtypes of acute myeloid leukemia (AML) in children have inferior outcome, such as AML with translocation t(7;12)(q36;p13) leading to an MNX1::ETV6 fusion along with high expression of MNX1. We have identified the transforming event in this AML and possible ways of treatment. Retroviral expression of MNX1 was able to induce AML in mice, with similar gene expression and pathway enrichment to t(7;12) AML patient data. Importantly, this leukemia was only induced in immune incompetent mice using fetal but not adult hematopoietic stem and progenitor cells. The restriction in transforming capacity to cells from fetal liver is in alignment with t(7;12)(q36;p13) AML being mostly seen in infants. Expression of MNX1 led to increased histone 3 lysine 4 mono-, di- and trimethylation, reduction in H3K27me3, accompanied with changes in genome-wide chromatin accessibility and genome expression, likely mediated through MNX1 interaction with the methionine cycle and methyltransferases. MNX1 expression increased DNA damage, depletion of the Lin-/Sca1+/c-Kit+ population and skewing toward the myeloid lineage. These effects, together with leukemia development, were prevented by pre-treatment with the S-adenosylmethionine analog Sinefungin. In conclusion, we have shown the importance of MNX1 in development of AML with t(7;12), supporting a rationale for targeting MNX1 and downstream pathways.

Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients

To characterize the genomic landscape and leukemogenic pathways of older, newly diagnosed, non-intensively treated patients with AML and to study the clinical implications, comprehensive genetics analyses were performed including targeted DNA sequencing of 263 genes in 604 patients treated in a prospective Phase III clinical trial. Leukemic trajectories were delineated using oncogenetic tree modeling and hierarchical clustering, and prognostic groups were derived from multivariable Cox regression models. Clonal hematopoiesis-related genes (ASXL1, TET2, SRSF2, DNMT3A) were most frequently mutated. The oncogenetic modeling algorithm produced a tree with five branches with ASXL1, DDX41, DNMT3A, TET2, and TP53 emanating from the root suggesting leukemia-initiating events which gave rise to further subbranches with distinct subclones. Unsupervised clustering mirrored the genetic groups identified by the tree model. Multivariable analysis identified FLT3 internal tandem duplications (ITD), SRSF2, and TP53 mutations as poor prognostic factors, while DDX41 mutations exerted an exceptionally favorable effect. Subsequent backwards elimination based on the Akaike information criterion delineated three genetic risk groups: DDX41 mutations (favorable-risk), DDX41wildtype/FLT3-ITDneg/TP53wildtype (intermediate-risk), and FLT3-ITD or TP53 mutations (high-risk). Our data identified distinct trajectories of leukemia development in older AML patients and provide a basis for a clinically meaningful genetic outcome stratification for patients receiving less intensive therapies.

Heterogeneity in the gene regulatory landscape of leiomyosarcoma

Characterizing inter-tumor heterogeneity is crucial for selecting suitable cancer therapy, as the presence of diverse molecular subgroups of patients can be associated with disease outcome or response to treatment. While cancer subtypes are often characterized by differences in gene expression, the mechanisms driving these differences are generally unknown. We set out to model the regulatory mechanisms driving sarcoma heterogeneity based on patient-specific, genome-wide gene regulatory networks. We developed a new computational framework, PORCUPINE, which combines knowledge on biological pathways with permutation-based network analysis to identify pathways that exhibit significant regulatory heterogeneity across a patient population. We applied PORCUPINE to patient-specific leiomyosarcoma networks modeled on data from The Cancer Genome Atlas and validated our results in an independent dataset from the German Cancer Research Center. PORCUPINE identified 37 heterogeneously regulated pathways, including pathways representing potential targets for treatment of subgroups of leiomyosarcoma patients, such as FGFR and CTLA4 inhibitory signaling. We validated the detected regulatory heterogeneity through analysis of networks and chromatin states in leiomyosarcoma cell lines. We showed that the heterogeneity identified with PORCUPINE is not associated with methylation profiles or clinical features, thereby suggesting an independent mechanism of patient heterogeneity driven by the complex landscape of gene regulatory interactions.

The GAPDH redox switch safeguards reductive capacity and enables survival of stressed tumour cells

Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is known to contain an active-site cysteine residue undergoing oxidation in response to hydrogen peroxide, leading to rapid inactivation of the enzyme. Here we show that human and mouse cells expressing a GAPDH mutant lacking this redox switch retain catalytic activity but are unable to stimulate the oxidative pentose phosphate pathway and enhance their reductive capacity. Specifically, we find that anchorage-independent growth of cells and spheroids is limited by an elevation of endogenous peroxide levels and is largely dependent on a functional GAPDH redox switch. Likewise, tumour growth in vivo is limited by peroxide stress and suppressed when the GAPDH redox switch is disabled in tumour cells. The induction of additional intratumoural oxidative stress by chemo- or radiotherapy synergized with the deactivation of the GAPDH redox switch. Mice lacking the GAPDH redox switch exhibit altered fatty acid metabolism in kidney and heart, apparently in compensation for the lack of the redox switch. Together, our findings demonstrate the physiological and pathophysiological relevance of oxidative GAPDH inactivation in mammals.

TAL1 activation in T-Cell acute lymphoblastic leukemia: A novel oncogenic 3' neoenhancer

T-cell acute lymphocytic leukemia protein 1 (TAL1) is one of the most frequently deregulated oncogenes in T-cell acute lymphoblastic leukemia (T-ALL). Its deregulation can occur through diverse in cis-alterations, including SIL-TAL1 microdeletions, translocations with Tcell Receptor (TCR) loci and, more recently described upstream intergenic non-coding mutations. These mutations consist of recurrent focal microinsertions that create an oncogenic neo-enhancer accompanied with activating epigenetic marks. This observation laid the groundwork for an innovative paradigm, the activation of proto-oncogenes via genomic alterations of non-coding intergenic regions. However, for the majority of TAL1 expressing (TAL1+) T-ALLs, the deregulation mechanism remains "unresolved". We took advantage of H3K27ac and H3K4me3 ChIP-seq data of eight T-ALLs, including five TAL1+ cases and identified a putative novel oncogenic neo-enhancer downstream of TAL1 in an "unresolved" monoallelic TAL1+ case. A rare but recurrent somatic heterozygous microinsertion within this region creates a de novo binding site for MYB transcription factor (TF). Here, we demonstrate that this mutation leads to increased enhancer activity, gain of active epigenetic marks and TAL1 activation via recruitment of MYB. These results highlight the diversity of non-coding mutations that can drive oncogene activation.

Dynamic DNA methylation reveals novel cis-regulatory elements in mouse hematopoiesis

Differentiation of hematopoietic stem and progenitor cells to terminally differentiated immune cells is accompanied by large-scale remodeling of the DNA methylation landscape. Although significant insights into the molecular mechanisms of hematopoietic tissue regeneration were derived from mouse models, profiling of DNA methylation has been hampered by high cost or low resolution using available methods. The recent development of the Infinium Mouse Methylation BeadChip (MMBC) array facilitates methylation profiling of the mouse genome at a single CpG resolution at affordable cost. We extended the RnBeads package to provide a computational framework for the analysis of MMBC data. This framework was applied to a newly generated reference map of mouse hematopoiesis encompassing nine different cell types. Analysis of dynamically regulated CpG sites showed progressive and unidirectional DNA methylation changes from hematopoietic stem and progenitor cells to differentiated hematopoietic cells and allowed the identification of lineage- and cell type-specific DNA methylation programs. Comparison with previously published catalogs of cis-regulatory elements (CREs) revealed 12,856 novel putative CREs that were dynamically regulated by DNA methylation (mdCREs). These mdCREs were predominantly associated with patterns of cell type-specific DNA hypomethylation and could be identified as epigenetic control regions regulating the expression of key hematopoietic genes during differentiation. In summary, we established an analysis pipeline for MMBC data sets and provide a DNA methylation atlas of mouse hematopoiesis. This resource allowed us to identify novel putative CREs involved in hematopoiesis and will serve as a platform to study epigenetic regulation of normal and malignant hematopoiesis.

Global DNA Methylation Analysis of Cancer-Associated Fibroblasts Reveals Extensive Epigenetic Rewiring Linked with RUNX1 Upregulation in Breast Cancer Stroma

Cancer cells recruit and rewire normal fibroblasts in their microenvironment to become protumorigenic cancer-associated fibroblasts (CAF). These CAFs are genomically stable, yet their transcriptional programs are distinct from those of their normal counterparts. Transcriptional regulation plays a major role in this reprogramming, but the extent to which epigenetic modifications of DNA also contribute to the rewiring of CAF transcription is not clear. Here we address this question by dissecting the epigenetic landscape of breast CAFs. Applying tagmentation-based whole-genome bisulfite sequencing in a mouse model of breast cancer, we found that fibroblasts undergo massive DNA methylation changes as they transition into CAFs. Transcriptional and epigenetic analyses revealed RUNX1 as a potential mediator of this process and identified a RUNX1-dependent stromal gene signature. Coculture and mouse models showed that both RUNX1 and its stromal signature are induced as normal fibroblasts transition into CAFs. In breast cancer patients, RUNX1 was upregulated in CAFs, and expression of the RUNX1 signature was associated with poor disease outcome, highlighting the relevance of these findings to human disease. This work presents a comprehensive genome-wide map of DNA methylation in CAFs and reveals a previously unknown facet of the dynamic plasticity of the stroma.

SIGNIFICANCE

The first genome-wide map of DNA methylation in breast cancer-associated fibroblasts unravels a previously unknown facet of the dynamic plasticity of the stroma, with far-reaching therapeutic implications.

Genetic and methylation profiles distinguish benign, malignant and spitzoid melanocytic tumors

Accurate classification of melanocytic tumors is important for prognostic evaluation, treatment and follow-up protocols of patients. The majority of melanocytic proliferations can be classified solely based on clinical and pathological criteria, however in select cases a definitive diagnostic assessment remains challenging and additional diagnostic biomarkers would be advantageous. We analyzed melanomas, nevi, Spitz nevi and atypical spitzoid tumors using parallel sequencing (exons of 611 genes and 507 gene translocation analysis) and methylation arrays (850k Illumina EPIC). By combining detailed genetic and epigenetic analysis with reference-based and reference-free DNA methylome deconvolution we compared Spitz nevi to nevi and melanoma and assessed the potential for these methods in classifying challenging spitzoid tumors. Results were correlated with clinical and histologic features. Spitz nevi were found to cluster independently of nevi and melanoma and demonstrated a different mutation profile. Multiple copy number alterations and TERT promoter mutations were identified only in melanomas. Genome-wide methylation in Spitz nevi was comparable to benign nevi while the Leukocytes UnMethylation for Purity (LUMP) algorithm in Spitz nevi was comparable to melanoma. Histologically difficult to classify Spitz tumor cases were assessed which, based on methylation arrays, clustered between Spitz nevi and melanoma and in terms of genetic profile or copy number variations demonstrated worrisome features suggesting a malignant neoplasm. Comprehensive sequencing and methylation analysis verify Spitz nevi as an independent melanocytic entity distinct from both nevi and melanoma. Combined genetic and methylation assays can offer additional insights in diagnosing difficult to classify Spitzoid tumors.

Club cells employ regeneration mechanisms during lung tumorigenesis

The high plasticity of lung epithelial cells, has for many years, confounded the correct identification of the cell-of-origin of lung adenocarcinoma (LUAD), one of the deadliest malignancies worldwide. Here, we employ lineage-tracing mouse models to investigate the cell of origin of Eml4-Alk LUAD, and show that Club and Alveolar type 2 (AT2) cells give rise to tumours. We focus on Club cell originated tumours and find that Club cells experience an epigenetic switch by which they lose their lineage fidelity and gain an AT2-like phenotype after oncogenic transformation. Single-cell transcriptomic analyses identified two trajectories of Club cell evolution which are similar to the ones used during lung regeneration, suggesting that lung epithelial cells leverage on their plasticity and intrinsic regeneration mechanisms to give rise to a tumour. Together, this study highlights the role of Club cells in LUAD initiation, identifies the mechanism of Club cell lineage infidelity, confirms the presence of these features in human tumours, and unveils key mechanisms conferring LUAD heterogeneity.

Histone H3K27 demethylase KDM6A is an epigenetic gatekeeper of mTORC1 signalling in cancer

OBJECTIVE

Large-scale genome sequencing efforts of human tumours identified epigenetic modifiers as one of the most frequently mutated gene class in human cancer. However, how these mutations drive tumour development and tumour progression are largely unknown. Here, we investigated the function of the histone demethylase KDM6A in gastrointestinal cancers, such as liver cancer and pancreatic cancer.

DESIGN

Genetic alterations as well as expression analyses of KDM6A were performed in patients with liver cancer. Genetic mouse models of liver and pancreatic cancer coupled with Kdm6a-deficiency were investigated, transcriptomic and epigenetic profiling was performed, and in vivo and in vitro drug treatments were conducted.

RESULTS

KDM6A expression was lost in 30% of patients with liver cancer. Kdm6a deletion significantly accelerated tumour development in murine liver and pancreatic cancer models. Kdm6a-deficient tumours showed hyperactivation of mTORC1 signalling, whereas endogenous Kdm6a re-expression by inducible RNA-interference in established Kdm6a-deficient tumours diminished mTORC1 activity resulting in attenuated tumour progression. Genome-wide transcriptional and epigenetic profiling revealed direct binding of Kdm6a to crucial negative regulators of mTORC1, such as Deptor, and subsequent transcriptional activation by epigenetic remodelling. Moreover, in vitro and in vivo genetic epistasis experiments illustrated a crucial function of Deptor and mTORC1 in Kdm6a-dependent tumour suppression. Importantly, KDM6A expression in human tumours correlates with mTORC1 activity and KDM6A-deficient tumours exhibit increased sensitivity to mTORC1 inhibition.

CONCLUSION

KDM6A is an important tumour suppressor in gastrointestinal cancers and acts as an epigenetic toggle for mTORC1 signalling. Patients with KDM6A-deficient tumours could benefit of targeted therapy focusing on mTORC1 inhibition.

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

DNA methylation analysis by sequencing is becoming increasingly popular, yielding methylomes at single-base pair and single-molecule resolution. It has tremendous potential for cell-type heterogeneity analysis using intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, systematic evaluation has not been performed yet. Here, we thoroughly benchmark six previously published methods: Bayesian epiallele detection, DXM, PRISM, csmFinder+coMethy, ClubCpG and MethylPurify, together with two array-based methods, MeDeCom and Houseman, as a comparison group. Sequencing-based deconvolution methods consist of two main steps, informative region selection and cell-type composition estimation, thus each was individually assessed. With this elaborate evaluation, we aimed to establish which method achieves the highest performance in different scenarios of synthetic bulk samples. We found that cell-type deconvolution performance is influenced by different factors depending on the number of cell types within the mixture. Finally, we propose a best-practice deconvolution strategy for sequencing data and point out limitations that need to be handled. Array-based methods—both reference-based and reference-free—generally outperformed sequencing-based methods, despite the absence of read-level information. This implies that the current sequencing-based methods still struggle with correctly identifying cell-type-specific signals and eliminating confounding methylation patterns, which needs to be handled in future studies.

A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation

Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. These molecularly coordinated regions are named “variable chromatin modules” (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect a VCM-modulating noncoding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a large change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with subtle, long-range chromatin compaction and robust AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology.

Non-coding variants can regulate transcription factor binding and gene expression at variable chromatin modules. Here, the authors show that a germline variant induces transcription factor nucleation through chromatin compaction leading to AXIN2 up-regulation and is associated to better prognosis in chronic lymphocytic leukaemia.

ID3 promotes homologous recombination via non-transcriptional and transcriptional mechanisms and its loss confers sensitivity to PARP inhibition

The inhibitor of DNA-binding 3 (ID3) is a transcriptional regulator that limits interaction of basic helix-loop-helix transcription factors with their target DNA sequences. We previously reported that ID3 loss is associated with mutational signatures linked to DNA repair defects. Here we demonstrate that ID3 exhibits a dual role to promote DNA double-strand break (DSB) repair, particularly homologous recombination (HR). ID3 interacts with the MRN complex and RECQL helicase to activate DSB repair and it facilitates RAD51 loading and downstream steps of HR. In addition, ID3 promotes the expression of HR genes in response to ionizing radiation by regulating both chromatin accessibility and activity of the transcription factor E2F1. Consistently, analyses of TCGA cancer patient data demonstrate that low ID3 expression is associated with impaired HR. The loss of ID3 leads to sensitivity of tumor cells to PARP inhibition, offering new therapeutic opportunities in ID3-deficient tumors.

Epigenetic reprogramming of airway macrophages promotes polarization and inflammation in muco-obstructive lung disease

Lung diseases, such as cystic fibrosis and COPD, are characterized by mucus obstruction and chronic airway inflammation, but their mechanistic link remains poorly understood. Here, we focus on the function of the mucostatic airway microenvironment on epigenetic reprogramming of airway macrophages (AM) and resulting transcriptomic and phenotypical changes. Using a mouse model of muco-obstructive lung disease (Scnn1b-transgenic), we identify epigenetically controlled, differentially regulated pathways and transcription factors involved in inflammatory responses and macrophage polarization. Functionally, AMs from Scnn1b-transgenic mice have reduced efferocytosis and phagocytosis, and excessive inflammatory responses upon lipopolysaccharide challenge, mediated through enhanced Irf1 function and expression. Ex vivo stimulation of wild-type AMs with native mucus impairs efferocytosis and phagocytosis capacities. In addition, mucus induces gene expression changes, comparable with those observed in AMs from Scnn1b-transgenic mice. Our data show that mucostasis induces epigenetic reprogramming of AMs, leading to changes favoring tissue damage and disease progression. Targeting these altered AMs may support therapeutic approaches in patients with muco-obstructive lung diseases.

Epigenetic analysis of patients with T-ALL identifies poor outcomes and a hypomethylating agent-responsive subgroup

Adult "T cell" acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy that is associated with poor outcomes, requiring additional therapeutic options. The DNA methylation landscapes of adult T-ALL remain undercharacterized. Here, we systematically analyzed the DNA methylation profiles of normal thymic-sorted T cell subpopulations and 143 primary adult T-ALLs as part of the French GRAALL 2003-2005 trial. Our results indicated that T-ALL is epigenetically heterogeneous consisting of five subtypes (C₁-C₅), which were either associated with co-occurring DNA methyltransferase 3 alpha (DNMT3A)/isocitrate dehydrogenase [NADP(+)] 2 (IDH2) mutations (C₁), TAL bHLH transcription factor 1, erythroid differentiation factor (TAL1) deregulation (C₂), T cell leukemia homeobox 3 (TLX3) (C₃), TLX1/in cis-homeobox A9 (HOXA9) (C₄), or in trans-HOXA9 overexpression (C₅). Integrative analysis of DNA methylation and gene expression identified potential cluster-specific oncogenes and tumor suppressor genes. In addition to an aggressive hypomethylated subgroup (C₁), our data identified an unexpected subset of hypermethylated T-ALL (C₅) associated with poor outcome and primary therapeutic response. Using mouse xenografts, we demonstrated that hypermethylated T-ALL samples exhibited therapeutic responses to the DNA hypomethylating agent 5-azacytidine, which significantly (survival probability; P = 0.001 for C₃, 0.01 for C₄, and 0.0253 for C₅) delayed tumor progression. These findings suggest that epigenetic-based therapies may provide an alternative treatment option in hypermethylated T-ALL.

Activation-induced deaminase is critical for the establishment of DNA methylation patterns prior to the germinal center reaction

Activation-induced deaminase (AID) initiates antibody diversification in germinal center B cells by deaminating cytosines, leading to somatic hypermutation and class-switch recombination. Loss-of-function mutations in AID lead to hyper-IgM syndrome type 2 (HIGM2), a rare human primary antibody deficiency. AID-mediated deamination has been proposed as leading to active demethylation of 5-methycytosines in the DNA, although evidence both supports and casts doubt on such a role. In this study, using whole-genome bisulfite sequencing of HIGM2 B cells, we investigated direct AID involvement in active DNA demethylation. HIGM2 naïve and memory B cells both display widespread DNA methylation alterations, of which ∼25% are attributable to active DNA demethylation. For genes that undergo active demethylation that is impaired in HIGM2 individuals, our analysis indicates that AID is not directly involved. We demonstrate that the widespread alterations in the DNA methylation and expression profiles of HIGM2 naïve B cells result from premature overstimulation of the B-cell receptor prior to the germinal center reaction. Our data support a role for AID in B cell central tolerance in preventing the expansion of autoreactive cell clones, affecting the correct establishment of DNA methylation patterns.

Versatile workflow for cell type-resolved transcriptional and epigenetic profiles from cryopreserved human lung

Complexity of lung microenvironment and changes in cellular composition during disease make it exceptionally hard to understand molecular mechanisms driving development of chronic lung diseases. Although recent advances in cell type-resolved approaches hold great promise for studying complex diseases, their implementation relies on local access to fresh tissue, as traditional tissue storage methods do not allow viable cell isolation. To overcome these hurdles, we developed a versatile workflow that allows storage of lung tissue with high viability, permits thorough sample quality check before cell isolation, and befits sequencing-based profiling. We demonstrate that cryopreservation enables isolation of multiple cell types from both healthy and diseased lungs. Basal cells from cryopreserved airways retain their differentiation ability, indicating that cellular identity is not altered by cryopreservation. Importantly, using RNA sequencing and EPIC Array, we show that gene expression and DNA methylation signatures are preserved upon cryopreservation, emphasizing the suitability of our workflow for omics profiling of lung cells. Moreover, we obtained high-quality single-cell RNA-sequencing data of cells from cryopreserved human lungs, demonstrating that cryopreservation empowers single-cell approaches. Overall, thanks to its simplicity, our workflow is well suited for prospective tissue collection by academic collaborators and biobanks, opening worldwide access to viable human tissue.

Methrix: an R/bioconductor package for systematic aggregation and analysis of bisulfite sequencing data

MOTIVATION

Whole genome bisulfite sequencing (WGBS), measures DNA methylation at base pair resolution resulting in large bedGraph like coverage files. Current options for processing such files are hindered by discrepancies in file format specification, speed and memory requirements.

RESULTS

We developed methrix, an R package, which provides a toolset for systematic analysis of large datasets. Core functionality of the package includes a comprehensive bedGraph or similar tab-separated text file reader - which summarizes methylation calls based on annotated reference indices, infers and collapses strands, and handles uncovered reference CpG sites while facilitating a flexible input file format specification. Additional optimized functions for quality control filtering, sub-setting, and visualization allow user-friendly and effective processing of WGBS results. Easy integration with tools for differentially methylated region (DMR) calling and annotation further eases the analysis of genome-wide methylation data. Overall, methrix enriches established WGBS workflows by bringing together computational efficiency and versatile functionality.

AVAILABILITY AND IMPLEMENTATION

Methrix is implemented as an R package, made available under MIT license at https://github.com/CompEpigen/methrix and can be installed from the Bioconductor repository.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

AmpliconDesign - an interactive web server for the design of high-throughput targeted DNA methylation assays

Targeted analysis of DNA methylation patterns based on bisulfite-treated genomic DNA (BT-DNA) is considered as a gold-standard for epigenetic biomarker development. Existing software tools facilitate primer design, primer quality control or visualization of primer localization. However, high-throughput design of primers for BT-DNA amplification is hampered by limits in throughput and functionality of existing tools, requiring users to repeatedly perform specific tasks manually. Consequently, the design of PCR primers for BT-DNA remains a tedious and time-consuming process. To bridge this gap, we developed AmpliconDesign, a webserver providing a scalable and user-friendly platform for the design and analysis of targeted DNA methylation studies based on BT-DNA, e.g. deep amplicon bisulfite sequencing (ampBS-seq) or EpiTYPER MassArray. Core functionality of the web server includes high-throughput primer design and binding site validation based on in silico bisulfite-converted DNA sequences, prediction of fragmentation patterns for EpiTYPER MassArray, an interactive quality control as well as a streamlined analysis workflow for ampBS-seq.

Globally altered epigenetic landscape and delayed osteogenic differentiation in H3.3-G34W-mutant giant cell tumor of bone

The neoplastic stromal cells of giant cell tumor of bone (GCTB) carry a mutation in H3F3A, leading to a mutant histone variant, H3.3-G34W, as a sole recurrent genetic alteration. We show that in patient-derived stromal cells H3.3-G34W is incorporated into the chromatin and associates with massive epigenetic alterations on the DNA methylation, chromatin accessibility and histone modification level, that can be partially recapitulated in an orthogonal cell line system by the introduction of H3.3-G34W. These epigenetic alterations affect mainly heterochromatic and bivalent regions and provide possible explanations for the genomic instability, as well as the osteolytic phenotype of GCTB. The mutation occurs in differentiating mesenchymal stem cells and associates with an impaired osteogenic differentiation. We propose that the observed epigenetic alterations reflect distinct differentiation stages of H3.3 WT and H3.3 MUT stromal cells and add to H3.3-G34W-associated changes.

The histone variant mutation H3.3-G34W occurs in the majority of giant cell tumor of bone (GCTB). By profiling patient-derived GCTB tumor cells, the authors show that this mutation associates with epigenetic alterations in heterochromatic and bivalent regions that contribute to an impaired osteogenic differentiation and the osteolytic phenotype of GCTB.

Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz

DNA methylation profiling offers unique insights into human development and diseases. Often the analysis of complex tissues and cell mixtures is the only feasible option to study methylation changes across large patient cohorts. Since DNA methylomes are highly cell type specific, deconvolution methods can be used to recover cell type-specific information in the form of latent methylation components (LMCs) from such 'bulk' samples. Reference-free deconvolution methods retrieve these components without the need for DNA methylation profiles of purified cell types. Currently no integrated and guided procedure is available for data preparation and subsequent interpretation of deconvolution results. Here, we describe a three-stage protocol for reference-free deconvolution of DNA methylation data comprising: (i) data preprocessing, confounder adjustment using independent component analysis (ICA) and feature selection using DecompPipeline, (ii) deconvolution with multiple parameters using MeDeCom, RefFreeCellMix or EDec and (iii) guided biological inference and validation of deconvolution results with the R/Shiny graphical user interface FactorViz. Our protocol simplifies the analysis and guides the initial interpretation of DNA methylation data derived from complex samples. The harmonized approach is particularly useful to dissect and evaluate cell heterogeneity in complex systems such as tumors. We apply the protocol to lung cancer methylomes from The Cancer Genome Atlas (TCGA) and show that our approach identifies the proportions of stromal cells and tumor-infiltrating immune cells, as well as associations of the detected components with clinical parameters. The protocol takes slightly >3 d to complete and requires basic R skills.

Epigenomic technologies for precision oncology

Epigenetic patterns in a cell control the expression of genes and consequently determine the phenotype of a cell. Cancer cells possess altered epigenomes which include aberrant patterns of DNA methylation, histone tail modifications, nucleosome positioning and of the three-dimensional chromatin organization within a nucleus. These altered epigenetic patterns are potential useful biomarkers to detect cancer cells and to classify tumor types. In addition, the cancer epigenome dictates the response of a cancer cell to therapeutic intervention and, therefore its knowledge, will allow to predict response to different therapeutic approaches. Here we review the current state-of-the-art technologies that have been developed to decipher epigenetic patterns on the genomic level and discuss how these methods are potentially useful for precision oncology.

Methylome-based cell-of-origin modeling (Methyl-COOM) identifies aberrant expression of immune regulatory molecules in CLL

Background

In cancer, normal epigenetic patterns are disturbed and contribute to gene expression changes, disease onset, and progression. The cancer epigenome is composed of the epigenetic patterns present in the tumor-initiating cell at the time of transformation, and the tumor-specific epigenetic alterations that are acquired during tumor initiation and progression. The precise dissection of these two components of the tumor epigenome will facilitate a better understanding of the biological mechanisms underlying malignant transformation. Chronic lymphocytic leukemia (CLL) originates from differentiating B cells, which undergo extensive epigenetic programming. This poses the challenge to precisely determine the epigenomic ground state of the cell-of-origin in order to identify CLL-specific epigenetic aberrations.

Methods

We developed a linear regression model, methylome-based cell-of-origin modeling (Methyl-COOM), to map the cell-of-origin for individual CLL patients based on the continuum of epigenomic changes during normal B cell differentiation.

Results

Methyl-COOM accurately maps the cell-of-origin of CLL and identifies CLL-specific aberrant DNA methylation events that are not confounded by physiologic epigenetic B cell programming. Furthermore, Methyl-COOM unmasks abnormal action of transcription factors, altered super-enhancer activities, and aberrant transcript expression in CLL. Among the aberrantly regulated transcripts were many genes that have previously been implicated in T cell biology. Flow cytometry analysis of these markers confirmed their aberrant expression on malignant B cells at the protein level.

Conclusions

Methyl-COOM analysis of CLL identified disease-specific aberrant gene regulation. The aberrantly expressed genes identified in this study might play a role in immune-evasion in CLL and might serve as novel targets for immunotherapy approaches. In summary, we propose a novel framework for in silico modeling of reference DNA methylomes and for the identification of cancer-specific epigenetic changes, a concept that can be broadly applied to other human malignancies.

Electronic supplementary material

Supplementary information accompanies this paper at 10.1186/s13073-020-00724-7.

Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software

Background

Cell-type heterogeneity of tumors is a key factor in tumor progression and response to chemotherapy. Tumor cell-type heterogeneity, defined as the proportion of the various cell-types in a tumor, can be inferred from DNA methylation of surgical specimens. However, confounding factors known to associate with methylation values, such as age and sex, complicate accurate inference of cell-type proportions. While reference-free algorithms have been developed to infer cell-type proportions from DNA methylation, a comparative evaluation of the performance of these methods is still lacking.

Results

Here we use simulations to evaluate several computational pipelines based on the software packages MeDeCom, EDec, and RefFreeEWAS. We identify that accounting for confounders, feature selection, and the choice of the number of estimated cell types are critical steps for inferring cell-type proportions. We find that removal of methylation probes which are correlated with confounder variables reduces the error of inference by 30–35%, and that selection of cell-type informative probes has similar effect. We show that Cattell’s rule based on the scree plot is a powerful tool to determine the number of cell-types. Once the pre-processing steps are achieved, the three deconvolution methods provide comparable results. We observe that all the algorithms’ performance improves when inter-sample variation of cell-type proportions is large or when the number of available samples is large. We find that under specific circumstances the methods are sensitive to the initialization method, suggesting that averaging different solutions or optimizing initialization is an avenue for future research.

Conclusion

Based on the lessons learned, to facilitate pipeline validation and catalyze further pipeline improvement by the community, we develop a benchmark pipeline for inference of cell-type proportions and implement it in the R package medepir.

DNA methylation signatures of monozygotic twins clinically discordant for multiple sclerosis

Multiple sclerosis (MS) is an inflammatory, demyelinating disease of the central nervous system with a modest concordance rate in monozygotic twins, which strongly argues for involvement of epigenetic factors. We observe highly similar peripheral blood mononuclear cell-based methylomes in 45 MS-discordant monozygotic twins. Nevertheless, we identify seven MS-associated differentially methylated positions (DMPs) of which we validate two, including a region in the TMEM232 promoter and ZBTB16 enhancer. In CD4 + T cells we find an MS-associated differentially methylated region in FIRRE. Additionally, 45 regions show large methylation differences in individual pairs, but they do not clearly associate with MS. Furthermore, we present epigenetic biomarkers for current interferon-beta treatment, and extensive validation shows that the ZBTB16 DMP is a signature for prior glucocorticoid treatment. Taken together, this study represents an important reference for epigenomic MS studies, identifies new candidate epigenetic markers, and highlights treatment effects and genetic background as major confounders.

Monozygotic (MZ) twins are ideal to study the influence of non-genetic factors on complex phenotypes. Here, Souren et al. perform an EWAS in peripheral blood mononuclear cells from 45 MZ twins discordant for multiple sclerosis and identify disease and treatment-associated epigenetic markers.

Integrative Analysis Defines Distinct Prognostic Subgroups of Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer. It is defined by cholangiocytic differentiation and has poor prognosis. Recently, epigenetic processes have been shown to play an important role in cholangiocarcinogenesis. We performed an integrative analysis on 52 iCCAs using both genetic and epigenetic data with a specific focus on DNA methylation components. We found recurrent isocitrate dehydrogenase 1 (IDH1) and IDH2 (28%) gene mutations, recurrent arm-length copy number alterations (CNAs), and focal alterations such as deletion of 3p21 or amplification of 12q15, which affect BRCA1 Associated Protein 1, polybromo 1, and mouse double minute 2 homolog. DNA methylome analysis revealed excessive hypermethylation of iCCA, affecting primarily the bivalent genomic regions marked with both active and repressive histone modifications. Integrative clustering of genetic and epigenetic data identified four iCCA subgroups with prognostic relevance further designated as IDH, high (H), medium (M), and low (L) alteration groups. The IDH group consisted of all samples with IDH1 or IDH2 mutations and showed, together with the H group, a highly disrupted genome, characterized by frequent deletions of chromosome arms 3p and 6q. Both groups showed excessive hypermethylation with distinct patterns. The M group showed intermediate characteristics regarding both genetic and epigenetic marks, whereas the L group exhibited few methylation changes and mutations and a lack of CNAs. Methylation-based latent component analysis of cell-type composition identified differences among these four groups. Prognosis of the H and M groups was significantly worse than that of the L group. Conclusion: Using an integrative genomic and epigenomic analysis approach, we identified four major iCCA subgroups with widespread genomic and epigenomic differences and prognostic implications. Furthermore, our data suggest differences in the cell-of-origin of the iCCA subtypes.

RnBeads 2.0: comprehensive analysis of DNA methylation data

DNA methylation is a widely investigated epigenetic mark with important roles in development and disease. High-throughput assays enable genome-scale DNA methylation analysis in large numbers of samples. Here, we describe a new version of our RnBeads software - an R/Bioconductor package that implements start-to-finish analysis workflows for Infinium microarrays and various types of bisulfite sequencing. RnBeads 2.0 (https://rnbeads.org/) provides additional data types and analysis methods, new functionality for interpreting DNA methylation differences, improved usability with a novel graphical user interface, and better use of computational resources. We demonstrate RnBeads 2.0 in four re-runnable use cases focusing on cell differentiation and cancer.

Enhancer hijacking activates oncogenic transcription factor NR4A3 in acinic cell carcinomas of the salivary glands

The molecular pathogenesis of salivary gland acinic cell carcinoma (AciCC) is poorly understood. The secretory Ca-binding phosphoprotein (SCPP) gene cluster at 4q13 encodes structurally related phosphoproteins of which some are specifically expressed at high levels in the salivary glands and constitute major components of saliva. Here we report on recurrent rearrangements [t(4;9)(q13;q31)] in AciCC that translocate active enhancer regions from the SCPP gene cluster to the region upstream of Nuclear Receptor Subfamily 4 Group A Member 3 (NR4A3) at 9q31. We show that NR4A3 is specifically upregulated in AciCCs, and that active chromatin regions and gene expression signatures in AciCCs are highly correlated with the NR4A3 transcription factor binding motif. Overexpression of NR4A3 in mouse salivary gland cells increases expression of known NR4A3 target genes and has a stimulatory functional effect on cell proliferation. We conclude that NR4A3 is upregulated through enhancer hijacking and has important oncogenic functions in AciCC.

Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories

Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ≤55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.

From Basic Knowledge to Effective Therapies

In this issue of Cancer Cell, Ott et al. use integrative analysis of histone ChIP-seq and ATAC-seq to describe enhancer-based regulatory circuits in chronic lymphocytic leukemia. This work identified and validated transcription factor PAX5 as main driver of an oncogenic circuitry, which can be disrupted by BET bromodomain inhibition.

MeDeCom: discovery and quantification of latent components of heterogeneous methylomes

It is important for large-scale epigenomic studies to determine and explore the nature of hidden confounding variation, most importantly cell composition. We developed MeDeCom as a novel reference-free computational framework that allows the decomposition of complex DNA methylomes into latent methylation components and their proportions in each sample. MeDeCom is based on constrained non-negative matrix factorization with a new biologically motivated regularization function. It accurately recovers cell-type-specific latent methylation components and their proportions. MeDeCom is a new unsupervised tool for the exploratory study of the major sources of methylation variation, which should lead to a deeper understanding and better biological interpretation.

MeDeCom: discovery and quantification of latent components of heterogeneous methylomes

It is important for large-scale epigenomic studies to determine and explore the nature of hidden confounding variation, most importantly cell composition. We developed MeDeCom as a novel reference-free computational framework that allows the decomposition of complex DNA methylomes into latent methylation components and their proportions in each sample. MeDeCom is based on constrained non-negative matrix factorization with a new biologically motivated regularization function. It accurately recovers cell-type-specific latent methylation components and their proportions. MeDeCom is a new unsupervised tool for the exploratory study of the major sources of methylation variation, which should lead to a deeper understanding and better biological interpretation.

Mitochondrial DNA Variation and Heteroplasmy in Monozygotic Twins Clinically Discordant for Multiple Sclerosis

We examined the debated link between mitochondrial DNA (mtDNA) variation and multiple sclerosis (MS) using 49 monozygotic (MZ) twin pairs clinically discordant for MS, which enables to associate de novo mtDNA variants, skewed heteroplasmy, and mtDNA copy number with MS manifestation. Ultra-deep sequencing of blood-derived mtDNA revealed 25 heteroplasmic variants with potentially pathogenic features in 18 pairs. All variants were pair-specific and had low and/or similar heteroplasmy levels in both cotwins. In one pair, a confirmed pathogenic variant (m.11778G>A, heteroplasmy ∼50%) associated with Leber hereditary optic neuropathy was detected. Detailed diagnostic investigation revealed subclinical MS signs in the prior nondiseased cotwin. Moreover, neither mtDNA deletions nor copy-number variations were involved. Furthermore, the majority of heteroplasmic variants were shared among MZ twins and exhibited more similar heteroplasmy levels in the same tissue of MZ twins as compared with different tissues of the same individual. Heteroplasmy levels were also more similar within MZ twins compared with nonidentical siblings. Our analysis excludes mtDNA variation as a major driver of the discordant clinical manifestation of MS in MZ twins, and provides valuable insights into the occurrence and distribution of heteroplasmic variants within MZ twins and nonidentical siblings, and across different tissues.

Epigenome data release: a participant-centered approach to privacy protection

Large-scale epigenome mapping by the NIH Roadmap Epigenomics Project, the ENCODE Consortium and the International Human Epigenome Consortium (IHEC) produces genome-wide DNA methylation data at one base-pair resolution. We examine how such data can be made open-access while balancing appropriate interpretation and genomic privacy. We propose guidelines for data release that both reduce ambiguity in the interpretation of open-access data and limit immediate access to genetic variation data that are made available through controlled access.

AKSmooth: enhancing low-coverage bisulfite sequencing data via kernel-based smoothing

Whole-genome bisulfite sequencing (WGBS) is an approach of growing importance. It is the only approach that provides a comprehensive picture of the genome-wide DNA methylation profile. However, obtaining a sufficient amount of genome and read coverage typically requires high sequencing costs. Bioinformatics tools can reduce this cost burden by improving the quality of sequencing data. We have developed a statistical method Ajusted Local Kernel Smoother (AKSmooth) that can accurately and efficiently reconstruct the single CpG methylation estimate across the entire methylome using low-coverage bisulfite sequencing (Bi-Seq) data. We demonstrate the AKSmooth performance on the low-coverage (~ 4 ×) DNA methylation profiles of three human colon cancer samples and matched controls. Under the best set of parameters, AKSmooth-curated data showed high concordance with the gold standard high-coverage sample (Pearson 0.90), outperforming the popular analogous method. In addition, AKSmooth showed computational efficiency with runtime benchmark over 4.5 times better than the reference tool. To summarize, AKSmooth is a simple and efficient tool that can provide an accurate human colon methylome estimation profile from low-coverage WGBS data. The proposed method is implemented in R and is available at https://github.com/Junfang/AKSmooth.

Comprehensive analysis of DNA methylation data with RnBeads

RnBeads is a software tool for large-scale analysis and interpretation of DNA methylation data, providing a user-friendly analysis workflow that yields detailed hypertext reports (http://rnbeads.mpi-inf.mpg.de/). Supported assays include whole-genome bisulfite sequencing, reduced representation bisulfite sequencing, Infinium microarrays and any other protocol that produces high-resolution DNA methylation data. Notable applications of RnBeads include the analysis of epigenome-wide association studies and epigenetic biomarker discovery in cancer cohorts.

BiQ Analyzer HiMod: an interactive software tool for high-throughput locus-specific analysis of 5-methylcytosine and its oxidized derivatives

Recent data suggest important biological roles for oxidative modifications of methylated cytosines, specifically hydroxymethylation, formylation and carboxylation. Several assays are now available for profiling these DNA modifications genome-wide as well as in targeted, locus-specific settings. Here we present BiQ Analyzer HiMod, a user-friendly software tool for sequence alignment, quality control and initial analysis of locus-specific DNA modification data. The software supports four different assay types, and it leads the user from raw sequence reads to DNA modification statistics and publication-quality plots. BiQ Analyzer HiMod combines well-established graphical user interface of its predecessor tool, BiQ Analyzer HT, with new and extended analysis modes. BiQ Analyzer HiMod also includes updates of the analysis workspace, an intuitive interface, a custom vector graphics engine and support of additional input and output data formats. The tool is freely available as a stand-alone installation package from http://biq-analyzer-himod.bioinf.mpi-inf.mpg.de/.

Bi-PROF: bisulfite profiling of target regions using 454 GS FLX Titanium technology

The use of next generation sequencing has expanded our view on whole mammalian methylome patterns. In particular, it provides a genome-wide insight of local DNA methylation diversity at single nucleotide level and enables the examination of single chromosome sequence sections at a sufficient statistical power. We describe a bisulfite-based sequence profiling pipeline, Bi-PROF, which is based on the 454 GS-FLX Titanium technology that allows to obtain up to one million sequence stretches at single base pair resolution without laborious subcloning. To illustrate the performance of the experimental workflow connected to a bioinformatics program pipeline (BiQ Analyzer HT) we present a test analysis set of 68 different epigenetic marker regions (amplicons) in five individual patient-derived xenograft tissue samples of colorectal cancer and one healthy colon epithelium sample as a control. After the 454 GS-FLX Titanium run, sequence read processing and sample decoding, the obtained alignments are quality controlled and statistically evaluated. Comprehensive methylation pattern interpretation (profiling) assessed by analyzing 10 (2)-10 (4) sequence reads per amplicon allows an unprecedented deep view on pattern formation and methylation marker heterogeneity in tissues concerned by complex diseases like cancer.

Adult monozygotic twins discordant for intra-uterine growth have indistinguishable genome-wide DNA methylation profiles

Background

Low birth weight is associated with an increased adult metabolic disease risk. It is widely discussed that poor intra-uterine conditions could induce long-lasting epigenetic modifications, leading to systemic changes in regulation of metabolic genes. To address this, we acquire genome-wide DNA methylation profiles from saliva DNA in a unique cohort of 17 monozygotic monochorionic female twins very discordant for birth weight. We examine if adverse prenatal growth conditions experienced by the smaller co-twins lead to long-lasting DNA methylation changes.

Results

Overall, co-twins show very similar genome-wide DNA methylation profiles. Since observed differences are almost exclusively caused by variable cellular composition, an original marker-based adjustment strategy was developed to eliminate such variation at affected CpGs. Among adjusted and unchanged CpGs 3,153 are differentially methylated between the heavy and light co-twins at nominal significance, of which 45 show sensible absolute mean β-value differences. Deep bisulfite sequencing of eight such loci reveals that differences remain in the range of technical variation, arguing against a reproducible biological effect. Analysis of methylation in repetitive elements using methylation-dependent primer extension assays also indicates no significant intra-pair differences.

Conclusions

Severe intra-uterine growth differences observed within these monozygotic twins are not associated with long-lasting DNA methylation differences in cells composing saliva, detectable with up-to-date technologies. Additionally, our results indicate that uneven cell type composition can lead to spurious results and should be addressed in epigenomic studies.

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data.

Assisted reproductive technologies do not enhance the variability of DNA methylation imprints in human

BACKGROUND Assisted reproductive technologies (ART) such as in vitro fertilisation (IVF) and intracytoplasmic sperm injection (ICSI) are believed to destabilise genomic imprints. An increased frequency of Beckwith-Wiedemann syndrome in children born after ART has been reported. Other, mostly epidemiological, studies argue against this finding. OBJECTIVE To examine the effect of ART on the stability of DNA methylation imprints, DNA was extracted from maternal peripheral blood (MPB), umbilical cord blood (UCB) and amnion/chorion tissue (ACT) of 185 phenotypically normal children (77 ICSI, 35 IVF, and 73 spontaneous conceptions). Using bisulfite based technologies 10 differentially methylated regions (DMRs) were analysed, including KvDMR1, H19, SNRPN, MEST, GRB10, DLK1/MEG3 IG-DMR, GNAS NESP55, GNAS NESPas, GNAS XL-alpha-s and GNAS Exon1A. RESULTS Methylation indices (MI) do not reveal any significant differences at nine DMRs among the conception groups in neither MPB, UCB nor in ACT. The only slightly variable DMR was that of MEST. Here the mean MI was higher in UCB and MPB of IVF cases (mean MI+/-SD: 0.41+/-0.03 (UCB) and 0.40+/-0.03 (MPB)) compared to the ICSI (0.38+/-0.03, p=0.003 (UCB); 0.37+/-0.04, p=0.0007 (MPB)) or spontaneous cases (0.38+/-0.03, p=0.003 (UCB); 0.38+/-0.04, p=0.02 (MPB)). Weak but suggestive correlations between DMRs were, however, found between MPB, UCB and ACT. CONCLUSION This study supports the notion that children conceived by ART do not show a higher degree of imprint variability and hence do not have an a priori higher risk for imprinting disorders.