Genome-wide DNA methylation map of human neutrophils reveals widespread inter-individual epigenetic variation

Human Brain Aging is Associated with Dysregulation of Cell-Type Epigenetic Identity

Significant links between aging and DNA methylation are emerging from recent studies. On the one hand, DNA methylation undergoes changes with age, a process termed as epigenetic drift. On the other hand, DNA methylation serves as a readily accessible and accurate biomarker for aging. A key missing piece of information, however, is the molecular mechanisms underlying these processes, and how they are related, if any. Addressing the limitations of previous research due to the limited number of investigated CpGs and the heterogeneous nature of tissue samples, here we have examined DNA methylation of over 20 million CpGs across a broad age span in neurons and non-neuronal cells, primarily oligodendrocytes. We show that aging is a primary predictor of DNA methylation variation, surpassing the influence of factors such as sex and schizophrenia diagnosis, among others. On the genome-wide scale, epigenetic drift manifests as significant yet subtle trends that are influenced by the methylation level of individual CpGs. We reveal that CpGs that are highly differentiated between cell types are especially prone to age-associated DNA methylation alterations, leading to the divergence of epigenetic cell type identities as individuals age. On the other hand, CpGs that are included in commonly used epigenetic clocks tend to be those sites that are not highly cell type differentiated. Therefore, dysregulation of epigenetic cell-type identities and current DNA epigenetic clocks represent distinct features of age-associated DNA methylation alterations.

Neural-net-based cell deconvolution from DNA methylation reveals tumor microenvironment associated with cancer prognosis

DNA methylation is a pivotal epigenetic modification that defines cellular identity. While cell deconvolution utilizing this information is considered useful for clinical practice, current methods for deconvolution are limited in their accuracy and resolution. In this study, we collected DNA methylation data from 945 human samples derived from various tissues and tumor-infiltrating immune cells and trained a neural network model with them. The model, termed MEnet, predicted abundance of cell population together with the detailed immune cell status from bulk DNA methylation data, and showed consistency to those of flow cytometry and histochemistry. MEnet was superior to the existing methods in the accuracy, speed, and detectable cell diversity, and could be applicable for peripheral blood, tumors, cell-free DNA, and formalin-fixed paraffin-embedded sections. Furthermore, by applying MEnet to 72 intrahepatic cholangiocarcinoma samples, we identified immune cell profiles associated with cancer prognosis. We believe that cell deconvolution by MEnet has the potential for use in clinical settings.

Colorectal cancer with low SLC35A3 is associated with immune infiltrates and poor prognosis

The expression level of SLC35A3 is associated with the prognosis of many cancers, but its role in colorectal cancer (CRC) is unclear. The purpose of our study was to elucidate the role of SLC35A3 in CRC. The expression levels of SLC35A3 in CRC were evaluated through tumor immune resource assessment (TIMER), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), Human Protein Atlas (HPA), qRT-PCR, and immunohistochemical evaluation. TCGA, GEO, and ICGC databases were used to analyze the diagnostic and prognostic value of SLC35A3 in CRC. A overall survival (OS) model was constructed and validated based on the expression level of SLC35A3 and multivariable analysis results. The cBioPortal tool was used to analyze SLC35A3 mutation in CRC. The UALCAN tool was used to analyze the promoter methylation level of SLC35A3 in colorectal cancer. In addition, the role of SLC35A3 in CRC was determined through GO analysis, KEGG analysis, gene set enrichment analysis (GSEA), immune infiltration analysis, and immune checkpoint correlation analysis. In vitro experiments validated the function of SLC35A3 in colorectal cancer cells. Compared with adjacent normal tissues and colonic epithelial cells, the expression of SLC35A3 was decreased in CRC tissues and CRC cell lines. Low expression of SLC35A3 was associated with N stage, pathological stage, and lymphatic infiltration, and it was unfavorable for OS, disease-specific survival (DSS), recurrence-free survival (RFS), and post-progression survival (PPS). According to the Receiver Operating Characteristic (ROC) analysis, SLC35A3 is a potential important diagnostic biomarker for CRC patients. The nomograph based on the expression level of SLC35A3 showed a better predictive model for OS than single prognostic factors and TNM staging. SLC35A3 has multiple types of mutations in CRC, and its promoter methylation level is significantly decreased. GO and KEGG analysis indicated that SLC35A3 may be involved in transmembrane transport protein activity, cell communication, and interaction with neurotransmitter receptors. GSEA revealed that SLC35A3 may be involved in energy metabolism, DNA repair, and cancer pathways. In addition, SLC35A3 was closely related to immune cell infiltration and immune checkpoint expression. Immunohistochemistry confirmed the positive correlation between SLC35A3 and helper T cell infiltration. In vitro experiments showed that overexpression of SLC35A3 inhibited the proliferation and invasion capability of colorectal cancer cells and promoted apoptosis. The results of this study indicate that decreased expression of SLC35A3 is closely associated with poor prognosis and immune cell infiltration in colorectal cancer, and it can serve as a promising independent prognostic biomarker and potential therapeutic target.

Protocol for generating high-quality genome-scale DNA methylation sequencing data from human cancer biospecimens

Aberrant DNA methylation is a universal feature of cancer. Here, we present a protocol for generating high-quality genome-scale DNA methylation sequencing data from a variety of human cancer biospecimens including immortalized cell lines, fresh-frozen surgical resections, and formalin-fixed paraffin-embedded tissues. We describe steps for DNA extraction considerations, reduced representation bisulfite sequencing, data processing and quality control, and downstream data analysis and integration. This protocol is also applicable for other human diseases and methylome profiling in other organisms. For complete details on the use and execution of this protocol, please refer to Rodger et al. (2023).1.

Application of deep learning in cancer epigenetics through DNA methylation analysis

DNA methylation is a fundamental epigenetic modification involved in various biological processes and diseases. Analysis of DNA methylation data at a genome-wide and high-throughput level can provide insights into diseases influenced by epigenetics, such as cancer. Recent technological advances have led to the development of high-throughput approaches, such as genome-scale profiling, that allow for computational analysis of epigenetics. Deep learning (DL) methods are essential in facilitating computational studies in epigenetics for DNA methylation analysis. In this systematic review, we assessed the various applications of DL applied to DNA methylation data or multi-omics data to discover cancer biomarkers, perform classification, imputation and survival analysis. The review first introduces state-of-the-art DL architectures and highlights their usefulness in addressing challenges related to cancer epigenetics. Finally, the review discusses potential limitations and future research directions in this field.

Sweetener System Intervention Shifted Neutrophils from Homeostasis to Priming

BACKGROUND

Non-nutritive sweeteners (NNS) are part of personalized nutrition strategies supporting healthy glycemic control. In contrast, the consumption of non-nutritive sweeteners has been related to person-specific and microbiome-dependent glycemic impairments. Reports on the effects of NNS on our highly individual cellular immune system are sparse. The recent identification of taste receptor expression in a variety of immune cells, however, suggested their immune-modulatory relevance.

METHODS

We studied the influence of a beverage-typical NNS system on the transcriptional profiling of sweetener-cognate taste receptors, selected cytokines and their receptors, and on Ca²⁺ signaling in isolated blood neutrophils. We determined plasma concentrations of saccharin, acesulfame-K, and cyclamate by HPLC-MS/MS, upon ingestion of a soft drink-typical sweetener surrogate. In an open-labeled, randomized intervention study, we determined pre- versus post-intervention transcript levels by RT-qPCR of sweetener-cognate taste receptors and immune factors.

RESULTS

Here we show that the consumption of a food-typical sweetener system modulated the gene expression of cognate taste receptors and induced the transcriptional regulation signatures of early homeostasis- and late receptor/signaling- and inflammation-related genes in blood neutrophils, shifting their transcriptional profile from homeostasis to priming. Notably, sweeteners at postprandial plasma concentrations facilitated fMLF (N-formyl-Met-Leu-Phe)-induced Ca²⁺ signaling.

CONCLUSIONS

Our results support the notion of sweeteners priming neutrophils to higher alertness towards their adequate stimuli.

Inter-Individual Variation in DNA Methylation Patterns across Two Tissues and Leukocytes in Mature Brahman Cattle

Quantifying the natural inter-individual variation in DNA methylation patterns is important for identifying its contribution to phenotypic variation, but also for understanding how the environment affects variability, and for incorporation into statistical analyses. The inter-individual variation in DNA methylation patterns in female cattle and the effect that a prenatal stressor has on such variability have yet to be quantified. Thus, the objective of this study was to utilize methylation data from mature Brahman females to quantify the inter-individual variation in DNA methylation. Pregnant Brahman cows were transported for 2 h durations at days 60 ± 5; 80 ± 5; 100 ± 5; 120 ± 5; and 140 ± 5 of gestation. A non-transport group was maintained as a control. Leukocytes, amygdala, and anterior pituitary glands were harvested from eight cows born from the non-transport group (Control) and six from the transport group (PNS) at 5 years of age. The DNA harvested from the anterior pituitary contained the greatest variability in DNA methylation of cytosine-phosphate-guanine (mCpG) sites from both the PNS and Control groups, and the amygdala had the least. Numerous variable mCpG sites were associated with retrotransposable elements and highly repetitive regions of the genome. Some of the genomic features that had high variation in DNA methylation are involved in immune responses, signaling, responses to stimuli, and metabolic processes. The small overlap of highly variable CpG sites and features between tissues and leukocytes supports the role of variable DNA methylation in regulating tissue-specific gene expression. Many of the CpG sites that exhibited high variability in DNA methylation were common between the PNS and Control groups within a tissue, but there was little overlap in genomic features with high variability. The interaction between the prenatal environment and the genome could be responsible for the differences in location of the variable DNA methylation.

DNA Methylation Alterations in Fractionally Irradiated Rats and Breast Cancer Patients Receiving Radiotherapy

Radiation-Induced CardioVascular Disease (RICVD) is an important concern in thoracic radiotherapy with complex underlying pathophysiology. Recently, we proposed DNA methylation as a possible mechanism contributing to RICVD. The current study investigates DNA methylation in heart-irradiated rats and radiotherapy-treated breast cancer (BC) patients. Rats received fractionated whole heart X-irradiation (0, 0.92, 6.9 and 27.6 Gy total doses) and blood was collected after 1.5, 3, 7 and 12 months. Global and gene-specific methylation of the samples were evaluated; and gene expression of selected differentially methylated regions (DMRs) was validated in rat and BC patient blood. In rats receiving an absorbed dose of 27.6 Gy, DNA methylation alterations were detected up to 7 months with differential expression of cardiac-relevant DMRs. Of those, SLMAP showed increased expression at 1.5 months, which correlated with hypomethylation. Furthermore, E2F6 inversely correlated with a decreased global longitudinal strain. In BC patients, E2F6 and SLMAP exhibited differential expression directly and 6 months after radiotherapy, respectively. This study describes a systemic radiation fingerprint at the DNA methylation level, elucidating a possible association of DNA methylation to RICVD pathophysiology, to be validated in future mechanistic studies.

Predicting Immunotherapy Outcomes in Older Patients with Solid Tumors Using the LIPI Score

Immunotherapy with immune checkpoint blockers (ICB) represents a valid therapeutic option in older patients for several solid cancer types. However, most of the data concerning efficacy and adverse events of ICB available are derived from younger and fitter patients. Reliable biomarkers are needed to better select the population that will benefit from ICB especially in older patients who may be at a higher risk of developing immune-related adverse events (irAEs) with a greater impact on their quality of life. The Lung Immune Prognostic Index (LIPI) is a score that combines pretreatment dNLR (neutrophils/[leukocytes − neutrophils]) and lactate dehydrogenase (LDH) and is correlated with outcomes in patients treated with ICB in non-small-cell lung cancer. We aimed to assess the impact of LIPI in ICB outcomes in a dedicated cohort of older patients. The primary objective was to study the prognostic role of LIPI score in patients aged 70 years or above in a real-life population treated with anti-programmed death-(ligand)1 (anti PD-(L)1). dNLR and LDH were collected in a prospective cohort of patients aged 70 years or above treated with PD-(L)1 inhibitors with metastatic disease between June 2014 and October 2017 at Gustave Roussy. LIPI categorizes the population into three different prognostic groups: good (dNLR ≤ 3 and LDH ≤ ULN—upper normal limit), intermediate (dNLR > 3 or LDH > ULN), and poor (dNLR > 3 and LDH > ULN). Anti PD-(L)1 benefit was analyzed according to overall survival (OS), progression free survival (PFS), and overall response rate (ORR) using RECIST v1.1. criteria. In the 191 older patients treated, most of them (95%) were ICB-naïve, and 160 (84%) had an ECOG performance status of 0−1 with a median age at ICB treatment of 77 (range, 70−93). The most common tumor types were melanoma (66%) and non-small-cell lung cancer (15%). The median follow-up duration was 18.8 months (95% CI 14.7−24.2). LIPI classified the population into three different groups: 38 (23%) patients had a good LIPI score, 84 (51%) had an intermediate LIPI score, and 43 (26%) had a poor LIPI score. The median OS was 20.7 months [95% CI, 12.6−not reached] compared to 11.2 months [95% CI, 8.41−22.2] and 4.7 months [95% CI, 2.2−11.3] in patients with a good, intermediate, and poor LIPI score, respectively (p = 0.0003). The median PFS was 9.2 months [95% CI, 6.2−18.1] in the good LIPI group, 7.2 months [95% CI, 5.4−13] in the intermediate LIPI group, and 3.9 months [95% CI, 2.3−8.2] in the poor LIPI group (p = 0.09). The rate of early death (OS < 3 months) was 37% in the poor LIPI group compared to 5% in the good LIPI group (<0.001). Poor LIPI score was associated with a poorer outcome in older patients treated with anti PD-(L)1. LIPI is a simple and accessible worldwide tool that can serve as a prognostic factor and can be useful for stratification benefit from ICB.

Comparison of Neutrophil Function in Granulocyte Concentrates From Prednisone- and G-CSF-Treated Donors: Effect of Stimulant, Leukapheresis and Storage

Transfusion of granulocyte concentrates (GC) is an alternative therapy for neutropenic patients with life-threatening infections. While neutrophils are the main source of antimicrobial activity, only neutrophil numbers are used to certify GCs. The objective of this study was thus to functionally characterize neutrophils in GCs prepared by leukapheresis from G-CSF-stimulated donors and compare to the less characterized prednisone GCs. GCs prepared from healthy donors stimulated with prednisone and then G-CSF after a 6-month washout period were analyzed prior to and after leukapheresis, and after storage. Leukocyte composition, neutrophil viability, calcium mobilization, chemotaxis, phagocytosis, reactive oxygen species, cytokine production and metabolites were determined. G-CSF GCs contained significantly more neutrophils than prednisone GCs of which 40% were immature. In comparison to non-stimulated healthy donor neutrophils, prednisone GC neutrophils exhibited enhanced phagocytosis and G-CSF GC neutrophils showed decreased chemotaxis but increased IL-8 production. Leukapheresis altered prednisone GC neutrophil responses. Storage had a significant, negative impact on G-CSF GC neutrophils compared to prednisone GC neutrophils. G-CSF and prednisone GC neutrophils thus differ in maturity and function, and G-CSF GC neutrophils are more sensitive to storage. Functional testing of GC neutrophils and better storage conditions would improve the quality of this blood product.

Editing of DNA Methylation Patterns Using CRISPR-Based Tools

DNA methylation is an epigenetic modification with an established role in both normal cellular function and mammalian disease. Despite well-characterized associations between aberrant DNA methylation changes and gene expression, evidence for a causal relationship in this context has been difficult to obtain. Early techniques for interrogating the role of DNA methylation in the regulation of gene transcription lack specificity and, where more specific techniques such and ZNFs and TALEs have been developed, they are limited by their extensive cost and labor requirements. However, the recent advent of CRISPR-based technologies has revolutionized our potential for site-specific epigenomic editing. Here, we provide a detailed protocol for the design, construction, and utilization of a transient, CRISPR-based DNA methylation-editing system in mammalian cells.

Genetic and in utero environmental contributions to DNA methylation variation in placenta

Genetic and prenatal environmental factors shape fetal development and cardiometabolic health in later life. A key target of genetic and prenatal environmental factors is the epigenome of the placenta, an organ that is implicated in fetal growth and diseases in later life. This study had two aims: (1) to identify and functionally characterize placental variably methylated regions (VMRs), which are regions in the epigenome with high inter-individual methylation variability; and (2) to investigate the contributions of fetal genetic loci and 12 prenatal environmental factors (maternal cardiometabolic-,psychosocial-, demographic- and obstetric-related) on methylation at each VMR. Akaike's information criterion was used to select the best model out of four models [prenatal environment only, genotype only, additive effect of genotype and prenatal environment (G + E), and their interaction effect (G × E)]. We identified 5850 VMRs in placenta. Methylation at 70% of VMRs was best explained by G × E, followed by genotype only (17.7%), and G + E (12.3%). Prenatal environment alone best explained only 0.03% of VMRs. We observed that 95.4% of G × E models and 93.9% of G + E models included maternal age, parity, delivery mode, maternal depression or gestational weight gain. VMR methylation sites and their regulatory genetic variants were enriched (P < 0.05) for genomic regions that have known links with regulatory functions and complex traits. This study provided a genome-wide catalog of VMRs in placenta and highlighted that variation in placental DNA methylation at loci with regulatory and trait relevance is best elucidated by integrating genetic and prenatal environmental factors, and rarely by environmental factors alone.

The Mouse Papillomavirus Epigenetic Signature Is Characterised by DNA Hypermethylation after Lesion Regression

Papillomaviruses (PVs) are double-stranded DNA tumour viruses that can infect cutaneous and mucosal epidermis. Human papillomavirus (HPV) types have been linked to the causality of cutaneous squamous cell carcinoma (cSCC); however, HPV DNA is not always detected in the resultant tumour. DNA methylation is an epigenetic change that can contribute to carcinogenesis. We hypothesise that the DNA methylation pattern in cells is altered following PV infection. We tested if DNA methylation was altered by PV infection in the mouse papillomavirus (MmuPV1) model. Immunosuppressed mice were infected with MmuPV1 on cutaneous tail skin. Immunosuppression was withdrawn for some mice, causing lesions to spontaneously regress. Reduced representation bisulphite sequencing was carried out on DNA from the actively infected lesions, visibly regressed lesions, and mock-infected control mice. DNA methylation libraries were generated and analysed for differentially methylated regions throughout the genome. The presence of MmuPV1 sequences was also assessed. We identified 834 predominantly differentially hypermethylated fragments in regressed lesions, and no methylation differences in actively infected lesions. The promoter regions of genes associated with tumorigenicity, including the tumour suppressor protein DAPK1 and mismatch repair proteins MSH6 and PAPD7, were hypermethylated. Viral DNA was detected in active lesions and in some lesions that had regressed. This is the first description of the genome-wide DNA methylation landscape for active and regressed MmuPV1 lesions. We propose that the DNA hypermethylation in the regressed lesions that we report here may increase the susceptibility of cells to ultraviolet-induced cSCC.

Increasing Age Affected Polymorphonuclear Neutrophils in Prognosis of Mycoplasma pneumoniae Pneumonia

Purpose

It is well known that age is related to the incidence of Mycoplasma pneumoniae pneumonia (MPP), and how age and other factors contribute to MPP remains unclear. In this study, we investigate how age affects the prognosis of MPP.

Patients and Methods

A total number of 1875 hospitalized children with pneumonia were enrolled in this study, including 52 children with refractory M. pneumoniae pneumonia (RMPP) and 298 children with non-RMPP. We used multiple logistic regression analysis to further identify the risk factors of RMPP, and found that age and polymorphonuclear neutrophils (PMNs) count were the key independent risk factors for the occurrence of RMPP. In order to improve specificity, 4.5 years old was taken as the cut-off value. Then, according to the cut-off value of age, 76 participants were recruited and divided into four groups: <4.5y MPP group, ≥4.5y MPP group, <4.5y health control (<4.5yHC) and ≥4.5y HC group. We explored the diverse functions of primary PMNs from children of different ages with MPP at cellular level. Besides, we studied the relationship between lung injury and PMNs in mice model with MPP of different ages.

Results

We found that the age and PMNs count of RMPP group were significantly higher than those of the non-RMPP group. Importantly, there is a linear correlation between the age of patients with RMPP and the percentage of PMNs. Further analysis showed that elderly patients infected with M. pneumoniae had more active PMNs function. Meanwhile, proteomics showed that children with M. pneumoniae infection in different age groups have differences in PMNs apoptosis, nicotinamide adenine dinucleotide phosphate, mitochondrial function and oxidative stress. Finally, we found that age is also involved in the pathogenesis of mouse model with MPP.

Conclusion

We speculate that age may contribute to the development of RMPP.

Hydroxycarbamide effects on DNA methylation and gene expression in myeloproliferative neoplasms

Hydroxycarbamide (HC, hydroxyurea) is a cytoreductive drug inducing cell cycle blockade. However, emerging evidence suggests that HC plays a role in the modulation of transcription through the activity of transcription factors and DNA methylation. Examining the global mechanism of action of HC in the context of myeloproliferative neoplasms (MPNs), for which HC is the first-line treatment, will provide a better understanding of its molecular effects. To explore the effects of HC genome-wide, transcriptomic analyses were performed on two clinically relevant cell types at different stages of differentiation treated with HC in a murine MPN model. This study was replicated in MPN patients by profiling genome-wide gene expression and DNA methylation using patient blood samples collected longitudinally, before and following HC exposure. The effects of HC on the transcriptome were not only associated with cell cycle interruption but also with hematopoietic functions. Moreover, a group of genes were restored to normal expression levels in murine hematopoietic stem cells (HSCs) following drug treatment, including the master regulator of hematopoiesis, RUNX1. In humans, HC significantly modifies DNA methylation levels in HSCs at several distal regulatory regions, which we show to be associated with SPI1 binding sites and at the SPI1 locus itself. We have identified novel targets of HC that include pivotal transcription factors involved in hematopoiesis, and for the first time we report abnormal methylation patterns in MPN patients at the master regulator gene SPI1 and its distal binding sites, which HC is able to restore to normal levels.

Profiling chromatin accessibility responses in human neutrophils with sensitive pathogen detection

ATAC-seq reveals unique neutrophil chromatin architecture changes in response to different stimuli before transcriptional activation, possibly regulating downstream gene expression.

Sepsis, sequela of bloodstream infections and dysregulated host responses, is a leading cause of death globally. Neutrophils tightly regulate responses to pathogens to prevent organ damage. Profiling early host epigenetic responses in neutrophils may aid in disease recognition. We performed assay for transposase-accessible chromatin (ATAC)-seq of human neutrophils challenged with six toll-like receptor ligands and two organisms; and RNA-seq after Escherichia coli exposure for 1 and 4 h along with ATAC-seq. ATAC-seq of neutrophils facilitates detection of pathogen DNA. In addition, despite similarities in genomic distribution of differential chromatin changes across challenges, only a fraction overlaps between the challenges. Ligands depict shared signatures, but majority are unique in position, function, and challenge. Epigenomic changes are plastic, only ∼120 are shared by E. coli challenges over time, resulting in varied differential genes and associated processes. We identify three classes of gene regulation, chromatin access changes in the promoter; changes in the promoter and distal enhancers; and controlling expression through changes solely in distal enhancers. These and transcription factor footprinting reveal timely and challenge specific mechanisms of transcriptional regulation in neutrophils.

Exploring hTERT promoter methylation in cutaneous T-cell lymphomas

Cutaneous T‐cell lymphomas (CTCLs) are telomerase‐positive tumors expressing hTERT, although neither gene rearrangement/amplification nor promoter hotspot mutations could explain the hTERT re‐expression. As the hTERT promoter is rich in CpG, we investigated the contribution of epigenetic mechanisms in its re‐expression. We analyzed hTERT promoter methylation status in CTCL cells compared with healthy cells. Gene‐specific methylation analyses revealed a common methylation pattern exclusively in tumor cells. This methylation pattern encompassed a hypermethylated distal region from −650 to −150 bp and a hypomethylated proximal region from −150 to +150 bp. Interestingly, the hypermethylated region matches with the recently named TERT hypermethylated oncogenic region (THOR). THOR has been associated with telomerase reactivation in many cancers, but it has so far not been reported in cutaneous lymphomas. Additionally, we assessed the effect of THOR on two histone deacetylase inhibitors (HDACi), romidepsin and vorinostat, both approved for CTCL treatment and a DNA methyltransferase inhibitor (DNMTi) 5‐azacytidine, unapproved for CTCL. Contrary to our expectations, the findings reported herein revealed that THOR methylation is relatively stable under these epigenetic drugs' pressure, whereas these drugs reduced the hTERT gene expression.

Tet Proteins Regulate Neutrophil Granulation in Zebrafish through Demethylation of socs3b mRNA

Tet proteins (Tet1/2/3) convert 5-methylcytosine (5mC) to 5-hydroxy-methylcytosine (5hmC), initiating the process of active demethylation to regulate gene expression. Demethylation has been investigated primarily in the context of DNA, but recently Tet enzymes have also been shown to mediate demethylation of 5mC in RNA as an additional level of epitranscriptomic regulation. We analyzed compound tet2/3 mutant zebrafish and discovered a role for Tet enzymes in the maturation of primitive and definitive neutrophils during granulation. Transcript profiling showed dysregulation of cytokine signaling in tet mutant neutrophils, including upregulation of socs3b. We show that Tet normally demethylates socs3b mRNA during granulation, thereby destabilizing the transcript, leading to its downregulation. Failure of this process leads to accumulation of socs3b mRNA and repression of cytokine signaling at this crucial step of neutrophil maturation. This study provides further evidence for Tets as epitranscriptomic regulatory enzymes and implicates Tet2/3 in regulation of neutrophil maturation.

Role of environmentally induced epigenetic transgenerational inheritance in evolutionary biology: Unified Evolution Theory

The current evolutionary biology theory primarily involves genetic alterations and random DNA sequence mutations to generate the phenotypic variation required for Darwinian natural selection to act. This neo-Darwinian evolution is termed the Modern Evolution Synthesis and has been the primary paradigm for nearly 100 years. Although environmental factors have a role in neo-Darwinian natural selection, Modern Evolution Synthesis does not consider environment to impact the basic molecular processes involved in evolution. An Extended Evolutionary Synthesis has recently developed that extends the modern synthesis to consider non-genetic processes. Over the past few decades, environmental epigenetics research has been demonstrated to regulate genetic processes and directly generate phenotypic variation independent of genetic sequence alterations. Therefore, the environment can on a molecular level through non-genetic (i.e. epigenetic) mechanisms directly influence phenotypic variation, genetic variation, inheritance and adaptation. This direct action of the environment to alter phenotype that is heritable is a neo-Lamarckian concept that can facilitate neo-Darwinian (i.e. Modern Synthesis) evolution. The integration of genetics, epigenetics, Darwinian theory, Lamarckian concepts, environment, and epigenetic inheritance provides a paradigm shift in evolution theory. The role of environmental-induced epigenetic transgenerational inheritance in evolution is presented to describe a more unified theory of evolutionary biology.

Neutrophil Modulation in Alpha-1 Antitrypsin Deficiency

Neutrophils have been implicated in the pathogenesis of alpha-1 antitrypsin deficiency (AATD) since the first descriptions of the disease. Neutrophil proteinases can cause all lung manifestations of AATD, from small airways destruction, to emphysema, to chronic bronchitis and airflow obstruction. Initially, it was proposed that neutrophil functions were normal in AATD, responding in an initially physiological manner to a high burden of pulmonary inflammation. More recent studies have shed new light on this, describing changes in neutrophil responses (a modulation of usual cellular functions) in the presence of inflammation or infection which might enhance tissue damage while impeding bacterial clearance, providing some evidence to support there being an AATD neutrophil phenotype. Many facets of neutrophil function in AATD can be explained by the loss of alpha-1 antitrypsin (AAT) in diverse biological processes. If this were the only reason for altered neutrophil functions, one would predict similar disease presentation across affected people. However, this is not the case. Despite similar (low) levels of AAT, lung disease is extremely variable in AATD, with some patients suffering a significant burden of lung disease and some much less, irrespective of smoking habits and, in some cases, despite augmentation therapy. This review will explore how complex neutrophil responses are and how they are altered with age, inflammation and AATD. Further, it will discuss the need to understand more completely which aspects of AATD-associated disease are driven by neutrophils and how patients more susceptible to neutrophil dysfunction could be identified to potentially stratify treatment approaches.

deconvSeq: deconvolution of cell mixture distribution in sequencing data

MOTIVATION

Although single-cell sequencing is becoming more widely available, many tissue samples such as intracranial aneurysms are both fibrous and minute, and therefore not easily dissociated into single cells. To account for the cell type heterogeneity in such tissues therefore requires a computational method. We present a computational deconvolution method, deconvSeq, for sequencing data (RNA and bisulfite) obtained from bulk tissue. This method can also be applied to single-cell RNA sequencing data.

RESULTS

DeconvSeq utilizes a generalized linear model to model effects of tissue type on feature quantification, which is specific to the data structure of the sequencing type used. Estimated model coefficients can then be used to predict the cell type mixture within a tissue. Predicted cell type mixtures were validated against actual cell counts in whole blood samples. Using this method, we obtained a mean correlation of 0.998 (95% CI 0.995-0.999) from the RNA sequencing data of 35 whole blood samples and 0.95 (95% CI 0.91-0.98) from the reduced representation bisulfite sequencing data from 35 whole blood samples. Using symmetric balances to obtain the correlation between compositional parts, we found that the lowest correlation occurred for monocytes for both RNA and bisulfite sequencing. Comparison with other methods of decomposition such as deconRNAseq, CIBERSORT, MuSiC and EpiDISH showed that deconvSeq is able to achieve good prediction using mean correlation with far fewer genes or CpG sites in the signature set.

AVAILABILITY AND IMPLEMENTATION

Software implementing deconvSeq is available at https://github.com/rosedu1/deconvSeq.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Promoter DNA Hypermethylation and Paradoxical Gene Activation

DNA methylation is a stable epigenetic modification that contributes to the spatiotemporal regulation of gene expression. The manner in which DNA methylation contributes to transcriptional control is dependent on the biological context, including physiological state and the properties of the DNA itself. Classically, dense promoter DNA methylation is associated with transcriptional repression. However, growing evidence suggests that this association may not always hold true, and promoter hypermethylation now also appears to be associated with high transcriptional activity. Furthermore, in a selection of contexts, increasing levels of promoter methylation correlate directly with increased gene expression. These findings postulate a context-dependent model whereby epigenetic contributions to transcriptional regulation occur in a more complex and dynamic manner. We present current evidence documenting promoter hypermethylation and high levels of gene expression, offer insights into the possible mechanisms by which this occurs, and discuss the potential implications for both research and clinical applications.

Genome-wide methylation and transcriptome of blood neutrophils reveal the roles of DNA methylation in affecting transcription of protein-coding genes and miRNAs in E. coli-infected mastitis cows

Background

Neutrophils are the first effectors of inflammatory response triggered by mastitis infection, and are important defense cells against pathogenic Escherichia coli (E. coli). DNA methylation, as a critical epigenetic mechanism for regulating gene function, is involved in bovine mastitis.

Results

In this study, we sequenced the blood neutrophils of healthy and E. coli-infected mastitic half-sib cows for the overall DNA methylation levels using transcriptome sequencing and reduced representation bisulfite sequencing. The methylation levels in the mastitis cows (MCs) were decreased compared with healthy cows (HCs). A total of 494 differentially methylated regions were identified, among which 61 were up-methylated and 433 were down-methylated (MCs vs. HCs). The expression levels of 1094 differentially expressed genes were up-regulated, and 245 genes were down-regulated. Twenty-nine genes were found in methylation and transcription data, among which seven genes’ promoter methylation levels were negatively correlated with expression levels, and 11 genes were differentially methylated in the exon regions. The bisulfite sequencing PCR and quantitative real-time PCR validation results demonstrated that the promoter methylation of CITED2 and SLC40A1 genes affected differential expression. The methylation of LGR4 exon 5 regulated its own alternative splicing. The promoter methylation of bta-miR-15a has an indirect effect on the expression of its target gene CD163. The CITED2, SLC40A1, and LGR4 genes can be used as candidates for E. coli-induced mastitis resistance.

Conclusions

This study explored the roles of DNA methylation in affecting transcription of protein-coding genes and miRNAs in E. coli-induced mastitis, thereby helping explain the function of DNA methylation in the pathogenesis of mastitis and provided new target genes and epigenetic markers for mastitis resistance breeding in dairy cattle.

Heterogeneity of neutrophils

Structured models of ontogenic, phenotypic and functional diversity have been instrumental for a renewed understanding of the biology of immune cells, such as macrophages and lymphoid cells. However, there are no established models that can be used to define the diversity of neutrophils, the most abundant myeloid cells. This lack of an established model is largely due to the uniquely short lives of neutrophils, a consequence of their inability to divide once terminally differentiated, which has been perceived as a roadblock to functional diversity. This perception is rapidly evolving as multiple phenotypic and functional variants of neutrophils have been found, both in homeostatic and disease conditions. In this Opinion article, we present an overview of neutrophil heterogeneity and discuss possible mechanisms of diversification, including genomic regulation. We suggest that neutrophil heterogeneity is an important feature of immune pathophysiology, such that co-option of the mechanisms of diversification by cancer or other disorders contributes to disease progression.

Influence of pre-pregnancy body mass index (p-BMI) and gestational weight gain (GWG) on DNA methylation and protein expression of obesogenic genes in umbilical vein

Understanding the regulatory mechanisms that affect obesogenic genes expression in newborns is essential for early prevention efforts, but they remain unclear. Our study aimed to explore whether the maternal p-BMI and GWG were associated with regulatory single-locus DNA methylation in selected obesogenic genes. For this purpose, DNA methylation was assayed by Methylation-Sensitive High Resolution Melting (MS-HRM) technique and Sanger allele-bisulfite sequencing in fifty samples of umbilical vein to evaluate glucosamine-6-phosphate deaminase 2 (GNPDA2), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC1α), and leptin receptor (LEPR) genes. Correlations between DNA methylation levels and indicators of maternal nutritional status were carried out. Western blotting was used to evaluate protein expression in extracts of the same samples. Results indicated that GNPDA2 and PGC1α genes have the same level of DNA methylation in all samples; however, a differential DNA methylation of LEPR gene promoter was found, correlating it with GWG and this correlation is unaffected by maternal age or unhealthy habits. Furthermore, leptin receptor (Lep-Rb) was upregulated in samples that showed the lowest levels of DNA methylation. This study highlights the association between poor GWG and adjustments on obesogenic genes expression in newborn tissues with potential consequences for development of obesity in the future.

Analyses of inter-individual variations of sperm DNA methylation and their potential implications in cattle

Background

DNA methylation has been shown to be involved in many biological processes, including X chromosome inactivation in females, paternal genomic imprinting, and others.

Results

Based on the correlation patterns of methylation levels of neighboring CpG sites among 28 sperm whole genome bisulfite sequencing (WGBS) data (486 × coverage), we obtained 31,272 methylation haplotype blocks (MHBs). Among them, we defined conserved methylated regions (CMRs), variably methylated regions (VMRs) and highly variably methylated regions (HVMRs) among individuals, and showed that HVMRs might play roles in transcriptional regulation and function in complex traits variation and adaptive evolution by integrating evidence from traditional and molecular quantitative trait loci (QTL), and selection signatures. Using a weighted correlation network analysis (WGCNA), we also detected a co-regulated module of HVMRs that was significantly associated with reproduction traits, and enriched for glycosyltransferase genes, which play critical roles in spermatogenesis and fertilization. Additionally, we identified 46 VMRs significantly associated with reproduction traits, nine of which were regulated by cis-SNPs, implying the possible intrinsic relationships among genomic variations, DNA methylation, and phenotypes. These significant VMRs were co-localized (± 10 kb) with genes related to sperm motility and reproduction, including ZFP36L1, CRISP2 and HGF. We provided further evidence that rs109326022 within a predominant QTL on BTA18 might influence the reproduction traits through regulating the methylation level of nearby genes JOSD2 and ASPDH in sperm.

Conclusion

In summary, our results demonstrated associations of sperm DNA methylation with reproduction traits, highlighting the potential of epigenomic information in genomic improvement programs for cattle.

Neutrophil phenotypes in chronic lung disease

Introduction: Neutrophils are the most abundant inflammatory cells in the lungs of patients with chronic lung diseases, especially COPD, yet despite this, patients often experience repeated chest infections. Neutrophil function may be altered in disease, but the reasons are unclear. In chronic disease, sequential pro-inflammatory and pro-repair responses appear distorted. As understanding of neutrophil heterogeneity has expanded, it is suggested that different neutrophil phenotypes may impact on health and disease. Areas covered: In this review, the definition of cellular phenotype, the implication of neutrophil surface markers and functions in chronic lung disease and the complex influences of external, local and genetic factors on these changes are discussed. Literature was accessed up to the 19 July 2019 using: PubMed, US National Library of Medicine National Institutes of Health and the National Centre for Biotechnology Information. Expert opinion: As more is learned about neutrophils, the further we step from the classical view of neutrophils being unrefined killing machines to highly complex and finely tuned cells. Future therapeutics may aim to normalize neutrophil function, but to achieve this, knowledge of phenotypes in humans and how these relate to observed pathology and disease processes is required.

Characterisation of DNA methylation changes in EBF3 and TBC1D16 associated with tumour progression and metastasis in multiple cancer types

Background

Characteristic DNA methylation differences have been identified between primary and metastatic melanomas at EBF3 and/or TBC1D16 gene loci. To further evaluate whether these epigenetic changes may act more generally as drivers of tumour onset and metastasis, we have investigated DNA methylation changes involving EBF3 and TBC1D16 in additional publicly available data of multiple different tumour types.

Results

Promoter hypermethylation and gene body hypomethylation of EBF3 were observed in a number of metastatic tumour types, when compared to normal or primary tumour tissues, as well as in tumour vs normal tissues and in a colorectal primary/metastasis pair, although not all tumour samples or primary/metastasis cancer pairs exhibited altered patterns of EBF3 methylation. In addition, hypomethylation of TBC1D16 was observed in multiple tumours, including a breast cancer primary/metastasis pair, and to a lesser degree in melanoma, although again not all tumours or cancer primary/metastasis pairs exhibited altered patterns of methylation.

Conclusions

These findings suggest characteristic DNA methylation changes in EBF3 and TBC1D16 are relatively common tumour-associated epigenetic events in multiple tumour types, which is consistent with a potential role as more general drivers of tumour progression.

Inferring and modeling inheritance of differentially methylated changes across multiple generations

High-throughput methylation sequencing enables genome-wide detection of differentially methylated sites (DMS) or regions (DMR). Increasing evidence suggests that treatment-induced DMS can be transmitted across generations, but the analysis of induced methylation changes across multiple generations is complicated by the lack of sound statistical methods to evaluate significance levels. Due to software design, DMS detection was usually made on each generation separately, thus disregarding stochastic effects expected when a large number of DMS is detected in each generation. Here, we present a novel method based on Monte Carlo sampling, methylInheritance, to evaluate that the number of conserved DMS between several generations is associated to an effect inherited from a treatment and not randomness. Moreover, we developed an inheritance simulation package, methInheritSim, to demonstrate the performance of the methylInheritance method and to evaluate the power of different experimental designs. Finally, we applied methylInheritance to a DNA methylation dataset obtained from early-life persistent organic pollutants (POPs) exposed Sprague-Dawley female rats and their descendants through a paternal transmission. The results show that metylInheritance can efficiently identify treatment-induced inherited methylation changes. Specifically, we identified two intergenerationally conserved DMS at transcription start site (TSS); one of those persisted transgenerationally. Three transgenerationally conserved DMR were found at intra or integenic regions.

Understanding the role of neutrophils in chronic inflammatory airway disease

Airway neutrophilia is a common feature of many chronic inflammatory lung diseases and is associated with disease progression, often regardless of the initiating cause. Neutrophils and their products are thought to be key mediators of the inflammatory changes in the airways of patients with chronic obstructive pulmonary disease (COPD) and have been shown to cause many of the pathological features associated with disease, including emphysema and mucus hypersecretion. Patients with COPD also have high rates of bacterial colonisation and recurrent infective exacerbations, suggesting that neutrophil host defence mechanisms are impaired, a concept supported by studies showing alterations to neutrophil migration, degranulation and reactive oxygen species production in cells isolated from patients with COPD. Although the role of neutrophils is best described in COPD, many of the pathological features of this disease are not unique to COPD and also feature in other chronic inflammatory airway diseases, including asthma, cystic fibrosis, alpha-1 anti-trypsin deficiency, and bronchiectasis. There is increasing evidence for immune cell dysfunction contributing to inflammation in many of these diseases, focusing interest on the neutrophil as a key driver of pulmonary inflammation and a potential therapeutic target than spans diseases. This review discusses the evidence for neutrophilic involvement in COPD and also considers their roles in alpha-1 anti-trypsin deficiency, bronchiectasis, asthma, and cystic fibrosis. We provide an in-depth assessment of the role of the neutrophil in each of these conditions, exploring recent advances in understanding, and finally discussing the possibility of common mechanisms across diseases.

Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data

High-throughput bisulfite methylation sequencing such as reduced representation bisulfite sequencing (RRBS), Agilent SureSelect Human Methyl-Seq (Methyl-seq) or whole-genome bisulfite sequencing is commonly used for base resolution methylome research. These data are represented either by the ratio of methylated cytosine versus total coverage at a CpG site or numbers of methylated and unmethylated cytosines. Multiple statistical methods can be used to detect differentially methylated CpGs (DMCs) between conditions, and these methods are often the base for the next step of differentially methylated region identification. The ratio data have a flexibility of fitting to many linear models, but the raw count data take consideration of coverage information. There is an array of options in each datatype for DMC detection; however, it is not clear which is an optimal statistical method. In this study, we systematically evaluated four statistic methods on methylation ratio data and four methods on count-based data and compared their performances with regard to type I error control, sensitivity and specificity of DMC detection and computational resource demands using real RRBS data along with simulation. Our results show that the ratio-based tests are generally more conservative (less sensitive) than the count-based tests. However, some count-based methods have high false-positive rates and should be avoided. The beta-binomial model gives a good balance between sensitivity and specificity and is preferred method. Selection of methods in different settings, signal versus noise and sample size estimation are also discussed.

Genome-wide miRNA methylome analysis in oral cancer: possible biomarkers associated with patient survival

AIM

The methylome associated with miRNA loci was investigated in oral cancer to explore tobacco specific methylation and potential biomarkers for patient survival.

METHODS

Methylome data was generated from 16 pairs of cancer-normal tissues by reduced representation bisulfite sequencing method. Differentially methylated regions were identified using the DMAP pipeline. In silico validation and Kaplan-Meier survival analyses were performed on The Cancer Genome Atlas data based on our miRNA methylome data.

RESULTS

A total of 4310 unique differentially methylated regions, mapping to 144 miRNA loci, were identified. Three distinct groups of miRNAs were differentially methylated in cancer tissues from smokers, chewers and mixed habitués. Hypermethylation of miR-503, miR-200a/b, miR-320b and miR-489 was associated with worse 5-year survival.

CONCLUSION

Differential methylation patterns in miRNA loci are associated with poor survival underscoring their potential as predictive and prognostic biomarkers in oral cancer.

A Guide for Designing and Analyzing RNA-Seq Data

The identity of a cell or an organism is at least in part defined by its gene expression and therefore analyzing gene expression remains one of the most frequently performed experimental techniques in molecular biology. The development of the RNA-Sequencing (RNA-Seq) method allows an unprecedented opportunity to analyze expression of protein-coding, noncoding RNA and also de novo transcript assembly of a new species or organism. However, the planning and design of RNA-Seq experiments has important implications for addressing the desired biological question and maximizing the value of the data obtained. In addition, RNA-Seq generates a huge volume of data and accurate analysis of this data involves several different steps and choices of tools. This can be challenging and overwhelming, especially for bench scientists. In this chapter, we describe an entire workflow for performing RNA-Seq experiments. We describe critical aspects of wet lab experiments such as RNA isolation, library preparation and the initial design of an experiment. Further, we provide a step-by-step description of the bioinformatics workflow for different steps involved in RNA-Seq data analysis. This includes power calculations, setting up a computational environment, acquisition and processing of publicly available data if desired, quality control measures, preprocessing steps for the raw data, differential expression analysis, and data visualization. We particularly mention important considerations for each step to provide a guide for designing and analyzing RNA-Seq data.

Cellular Uptake of the Atypical Antipsychotic Clozapine Is a Carrier-Mediated Process

The weak base antipsychotic clozapine is the most effective medication for treating refractory schizophrenia. The brain-to-plasma concentration of unbound clozapine is greater than unity, indicating transporter-mediated uptake, which has been insufficiently studied. This is important, because it could have a significant impact on clozapine's efficacy, drug-drug interaction, and safety profile. A major limitation of clozapine's use is the risk of clozapine-induced agranulocytosis/granulocytopenia (CIAG), which is a rare but severe hematological adverse drug reaction. We first studied the uptake of clozapine into human brain endothelial cells (hCMEC/D3). Clozapine uptake into cells was consistent with a carrier-mediated process, which was time-dependent and saturable ( V_max = 3299 pmol/million cells/min, K_m = 35.9 μM). The chemical inhibitors lamotrigine, quetiapine, olanzapine, prazosin, verapamil, indatraline, and chlorpromazine reduced the uptake of clozapine by up to 95%. This could in part explain the in vivo interactions observed in rodents or humans for these compounds. An extensive set of studies utilizing transporter-overexpressing cell lines and siRNA-mediated transporter knockdown in hCMEC/D3 cells showed that clozapine was not a substrate of OCT1 (SLC22A1), OCT3 (SLC22A3), OCTN1 (SLC22A4), OCTN2 (SLC22A5), ENT1 (SLC29A1), ENT2 (SLC29A2), and ENT4/PMAT (SLC29A4). In a recent genome-wide analysis, the hepatic uptake transporters SLCO1B1 (OATP1B1) and SLCO1B3 (OATP1B3) were identified as additional candidate transporters. We therefore also investigated clozapine transport into OATP1B-transfected cells and found that clozapine was neither a substrate nor an inhibitor of OATP1B1 and OATP1B3. In summary, we have identified a carrier-mediated process for clozapine uptake into brain, which may be partly responsible for clozapine's high unbound accumulation in the brain and its drug-drug interaction profile. Cellular clozapine uptake is independent from currently known drug transporters, and thus, molecular identification of the clozapine transporter will help to understand clozapine's efficacy and safety profile.

DNA methylation of hepatic iron sensing genes and the regulation of hepcidin expression

Production of the iron regulatory peptide hepcidin is tightly controlled by a network of proteins in hepatocytes that sense levels of iron in the circulation (as diferric-transferrin) and in tissues (in ferritin). Human studies show high variability in the normal range of serum hepcidin levels. We have postulated that this may, in part, be related to inter-individual variability in the expression of genes in the iron sensing pathway, potentially governed by epigenetic factors. Here, we have investigated whether genes encoding hepatic iron sensing proteins and hepcidin are regulated by DNA methylation. Experiments were performed on two human hepatoma cell lines, HepG2 cells and Huh7 cells. Basal expression of TFR2 and HAMP was significantly lower in Huh7 cells compared with HepG2 cells. Analysis of bisulphite-converted DNA from Huh7 cells revealed partial methylation of TFR2 (alpha transcript), which could result in gene silencing. Demethylation using 5-aza-2’-deoxycitidine (AZA) increased TFR2 mRNA expression in Huh7. PCR analysis of bisulphite-converted HAMP promoter DNA, using methylation-specific primers, revealed no differences between cell lines. However, HAMP mRNA expression in Huh7 was increased by AZA treatment, suggesting that methylation of one or more iron sensing genes may indirectly influence HAMP expression. Our study provides evidence that DNA methylation might control expression of HAMP and other hepatic iron sensing genes, and indicates that epigenetic influences on iron homeostasis warrant further investigation.

The Methylome of Vertebrate Sex Chromosomes

DNA methylation is a key epigenetic modification in vertebrate genomes known to be involved in the regulation of gene expression, X chromosome inactivation, genomic imprinting, chromatin structure, and control of transposable elements. DNA methylation is common to all eukaryote genomes, but we still lack a complete understanding of the variation in DNA methylation patterns on sex chromosomes and between the sexes in diverse species. To better understand sex chromosome DNA methylation patterns between different amniote vertebrates, we review literature that has analyzed the genome-wide distribution of DNA methylation in mammals and birds. In each system, we focus on DNA methylation patterns on the autosomes versus the sex chromosomes.

DNA Methylation variability among individuals is related to CpGs cluster density and evolutionary signatures

BACKGROUND

In recent years, epigenetics has gained a central role in the understanding of the process of natural selection. It is now clear how environmental impacts on the methylome could promote methylation variability with direct effects on disease etiology as well as phenotypic and genotypic variations in evolutionary processes. To identify possible factors influencing inter-individual methylation variability, we studied methylation values standard deviation of 166 healthy individuals searching for possible associations with genomic features and evolutionary signatures.

RESULTS

We analyzed methylation variability values in relation to CpG cluster density and we found a strong association between them (p-value < 2.2 × 10- 16). Furthermore, we found that genes related to CpGs with high methylation variability values were enriched for immunological pathways; instead, those associated with low ones were enriched for pathways related to basic cellular functions. Finally, we found an association between methylation variability values and signals of both ancient (p-value < 2.2 × 10- 16) and recent selective pressure (p-value < 1 × 10- 4).

CONCLUSION

Our results indicate the presence of an intricate interplay between genetics, epigenetic code and evolutionary constraints in humans.

iMETHYL: an integrative database of human DNA methylation, gene expression, and genomic variation

We launched an integrative multi-omics database, iMETHYL (http://imethyl.iwate-megabank.org). iMETHYL provides whole-DNA methylation (~24 million autosomal CpG sites), whole-genome (~9 million single-nucleotide variants), and whole-transcriptome (>14 000 genes) data for CD4⁺ T-lymphocytes, monocytes, and neutrophils collected from approximately 100 subjects. These data were obtained from whole-genome bisulfite sequencing, whole-genome sequencing, and whole-transcriptome sequencing, making iMETHYL a comprehensive database.

The epigenetic alterations of endogenous retroelements in aging

Endogenous retroelements, transposons that mobilize through RNA intermediates, include some of the most abundant repetitive sequences of the human genome, such as Alu and LINE-1 sequences, and human endogenous retroviruses. Recent discoveries demonstrate that these mobile genetic elements not only act as intragenomic parasites, but also exert regulatory roles in living cells. The risk of genomic instability represented by endogenous retroelements is normally counteracted by a series of epigenetic control mechanisms which include, among the most important, CpG DNA methylation. Indeed, most of the genomic CpG sites subjected to DNA methylation in the nuclear DNA are carried by these repetitive elements. As other parts of the genome, endogenous retroelements and other transposable elements are subjected to deep epigenetic alterations during aging, repeatedly observed in the context of organismal and cellular senescence, in human and other species. This review summarizes the current status of knowledge about the epigenetic alterations occurring in this large, non-genic portion of the genome in aging and age-related conditions, with a focus on the causes and the possible functional consequences of these alterations.

Thyroid State Regulates Gene Expression in Human Whole Blood

CONTEXT

Despite the well-recognized clinical features resulting from insufficient or excessive thyroid hormone (TH) levels in humans, it is largely unknown which genes are regulated by TH in human tissues.

OBJECTIVE

To study the effect of TH on human gene expression profiles in whole blood, mainly consisting of T3 receptor (TR) α-expressing cells.

METHODS

We performed next-generation RNA sequencing on whole blood samples from eight athyroid patients (four females) on and after 4 weeks off levothyroxine replacement. Gene expression changes were analyzed through paired differential expression analysis and confirmed in a validation cohort. Weighted gene coexpression network analysis (WGCNA) was applied to identify thyroid state-related networks.

RESULTS

We detected 486 differentially expressed genes (fold-change >1.5; multiple testing corrected P value < 0.05), of which 76% were positively and 24% were negatively regulated. Gene ontology (GO) enrichment analysis revealed that three biological processes were significantly overrepresented, of which the process translational elongation showed the highest fold enrichment (7.3-fold, P = 1.8 × 10-6). WGCNA analysis independently identified various gene clusters that correlated with thyroid state. Further GO analysis suggested that thyroid state affects platelet function.

CONCLUSIONS

Changes in thyroid state regulate numerous genes in human whole blood, predominantly TRα-expressing leukocytes. In addition, TH may regulate gene transcripts in platelets.

A streamlined method for analysing genome-wide DNA methylation patterns from low amounts of FFPE DNA

Background

Formalin fixed paraffin embedded (FFPE) tumor samples are a major source of DNA from patients in cancer research. However, FFPE is a challenging material to work with due to macromolecular fragmentation and nucleic acid crosslinking. FFPE tissue particularly possesses challenges for methylation analysis and for preparing sequencing-based libraries relying on bisulfite conversion. Successful bisulfite conversion is a key requirement for sequencing-based methylation analysis.

Methods

Here we describe a complete and streamlined workflow for preparing next generation sequencing libraries for methylation analysis from FFPE tissues. This includes, counting cells from FFPE blocks and extracting DNA from FFPE slides, testing bisulfite conversion efficiency with a polymerase chain reaction (PCR) based test, preparing reduced representation bisulfite sequencing libraries and massively parallel sequencing.

Results

The main features and advantages of this protocol are:

An optimized method for extracting good quality DNA from FFPE tissues.

An efficient bisulfite conversion and next generation sequencing library preparation protocol that uses 50 ng DNA from FFPE tissue.

Incorporation of a PCR-based test to assess bisulfite conversion efficiency prior to sequencing.

Conclusions

We provide a complete workflow and an integrated protocol for performing DNA methylation analysis at the genome-scale and we believe this will facilitate clinical epigenetic research that involves the use of FFPE tissue.

Electronic supplementary material

The online version of this article (10.1186/s12920-017-0290-1) contains supplementary material, which is available to authorized users.

Comparative assessment of DNA methylation patterns between reduced representation bisulfite sequencing and Sequenom EpiTyper methylation analysis

AIM

Validation of sequencing-based DNA methylation data is an important step for meaningful translation of findings. However, there has been limited assessment of different platforms to validate methylation data from next generation sequencing.

METHODS

We performed a comparative methylation analysis between the genome-wide platform of reduced representation bisulfite sequencing with a targeted, Sequenom EpiTyper platform (four genes were analyzed in 15 cell lines covering 52 CpG sites).

RESULTS

We show that the accuracy of validation substantially improves if results from multiple and adjacent CpG sites are combined rather than at single CpG sites. We demonstrate increased read number improves accuracy of reduced representation bisulfite sequencing results. Further, by using series of replicates, we document variation in samples analyzed by Sequenom EpiTyper, indicating the importance of including replicates to increase precision.

CONCLUSION

The results reveal potential sources of bias and provide a guideline for refining study design for DNA methylation analysis.

Genome-wide methylation sequencing of paired primary and metastatic cell lines identifies common DNA methylation changes and a role for EBF3 as a candidate epigenetic driver of melanoma metastasis

Epigenetic alterations are increasingly implicated in metastasis, whereas very few genetic mutations have been identified as authentic drivers of cancer metastasis. Yet, to date, few studies have identified metastasis-related epigenetic drivers, in part because a framework for identifying driver epigenetic changes in metastasis has not been established. Using reduced representation bisulfite sequencing (RRBS), we mapped genome-wide DNA methylation patterns in three cutaneous primary and metastatic melanoma cell line pairs to identify metastasis-related epigenetic drivers. Globally, metastatic melanoma cell lines were hypomethylated compared to the matched primary melanoma cell lines. Using whole genome RRBS we identified 75 shared (10 hyper- and 65 hypomethylated) differentially methylated fragments (DMFs), which were associated with 68 genes showing significant methylation differences. One gene, Early B Cell Factor 3 (EBF3), exhibited promoter hypermethylation in metastatic cell lines, and was validated with bisulfite sequencing and in two publicly available independent melanoma cohorts (n = 40 and 458 melanomas, respectively). We found that hypermethylation of the EBF3 promoter was associated with increased EBF3 mRNA levels in metastatic melanomas and subsequent inhibition of DNA methylation reduced EBF3 expression. RNAi-mediated knockdown of EBF3 mRNA levels decreased proliferation, migration and invasion in primary and metastatic melanoma cell lines. Overall, we have identified numerous epigenetic changes characterising metastatic melanoma cell lines, including EBF3-induced aggressive phenotypic behaviour with elevated EBF3 expression in metastatic melanoma, suggesting that EBF3 promoter hypermethylation may be a candidate epigenetic driver of metastasis.

The epigenomic basis of common diseases

A report of the 6th Epigenomics of Common Diseases Conference held at the Wellcome Genome Campus in Hinxton, Cambridge, UK, on 1-4 November 2016.

Tools and Strategies for Analysis of Genome-Wide and Gene-Specific DNA Methylation Patterns

DNA methylation is a stable epigenetic mechanism that has important roles in the normal function of a cell and therefore also in disease etiology. Accurate measurements of normal and altered DNA methylation patterns are important to understand its role in regulating gene expression and cell phenotype. Remarkable progress has been made over the last decade in developing methodologies to investigate DNA methylation. The availability of next-generation sequencing has enabled the profiling of methylation marks at an unprecedented scale. Several methods that were previously used to profile locus-specific methylation have now been upgraded to a genome-wide scale using high-throughput sequencing or array platforms. However, because there are so many techniques available, researchers are faced with the challenge of assessing the potential merits or limitations of each technique and selecting the appropriate method for their analysis. In this review we discuss the strengths and weaknesses of genome-wide and gene-specific analysis tools for interrogating DNA methylation. We particularly focus on the design and analysis strategies involved. This review will provide a guideline for selecting the appropriate methods and tools for large-scale and locus-specific DNA methylation analysis.

Generating Multiple Base-Resolution DNA Methylomes Using Reduced Representation Bisulfite Sequencing

Reduced representation bisulfite sequencing (RRBS) is an effective technique for profiling genome-wide DNA methylation patterns in eukaryotes. RRBS couples size selection, bisulfite conversion, and second-generation sequencing to enrich for CpG-dense regions of the genome. The progressive improvement of second-generation sequencing technologies and reduction in cost provided an opportunity to examine the DNA methylation patterns of multiple genomes. Here, we describe a protocol for sequencing multiple RRBS libraries in a single sequencing reaction to generate base-resolution methylomes. Furthermore, we provide a brief guideline for base-calling and data analysis of multiplexed RRBS libraries. These strategies will be useful to perform large-scale, genome-wide DNA methylation analysis.

The Universal 3D3 Antibody of Human PODXL Is Pluripotent Cytotoxic, and Identifies a Residual Population After Extended Differentiation of Pluripotent Stem Cells

Podocalyxin-like protein (PODXL) is a member of CD34 family proteins. It is the protein that carries many post-translational epitopes responsible for various pluripotent surface markers including TRA-1-60, TRA-1-81, GCTM2, GP200, and mAb84. However, PODXL has not attracted the attention of stem cell biologists. Here, we report several features of PODXL mRNA and protein in pluripotent stem cells. Similar to the modification-dependent pluripotent epitopes, PODXL transcripts and carrier protein are also features of pluripotency. PODXL is highly expressed in early human embryos from oocytes up to four-cell stages. During reprogramming of human cells to pluripotency, in contrast to TRA-1-60 and TRA-1-81, PODXL is activated by KLF4 at a very early time of reprogramming. Although TRA-1-60 and TRA-1-81 are completely lost upon differentiation, a residual PODXL(+) population exists even after extended differentiation and they were identified by the universal human PODXL epitope 3D3. Unlike TRA-1-60 and TRA-1-81 epitopes that are unique to primate pluripotent stem cells (PSCs), PODXL carrier protein can be used as a murine surface marker. Most importantly, antibody to 3D3 epitope causes massive necrosis and apoptosis of human PSCs (hPSCs). We suggest that 3D3 antibody could be employed to eliminate the tumorigenic pluripotent cells in hPSC-derived cells for cell transplantation.

DNA methylation detection at single base resolution using targeted next generation bisulfite sequencing and cross validation using capillary sequencing

With a purpose of accurate and simultaneous determination of DNA methylation from multiple loci in multiple samples, here, we are demonstrating a method to aid rapid DNA methylation detection of genomic sequences. Using genomic DNA of peripheral blood from 14 healthy individuals, DNA methylation in 465 CpG sites from 12 loci of genes (ADAM22, ATF2, BCR, CD83, CREBBP, IL12B, IL17RA, MAP2K2, RBM38, TGFBR2, TGFBR3, and WNT5A) was analysed by targeted next generation bisulfite sequencing. Analysed region for three genes, BCR, IL17RA and RBM38 showed an absolute mean DNA methylation of 25.6%, 89.2% and 38.9% respectively. Other nine gene loci were unmethylated and exhibited <10% absolute mean DNA methylation. Two genes, IL17RA and RBM38 were technically validated using direct capillary sequencing and results were comparable with positive correlation (P=0.0088 & P<0.0001 respectively) in the CpG sites for DNA methylation. All CpG sites analysed from RBM38 genes locus displayed 95% limits of agreement for DNA methylation measurements from the two methods. The present approach provides a fast and reliable DNA methylation quantitative data at single base resolution with good coverage of the CpG sites under analysis in multiple loci and samples simultaneously. Use of targeted next generation bisulfite sequencing may provide an opportunity to explore genes in the discovery panel for biomarker identification and facilitate functional validation.

Aberrant Epigenetic Regulation in the Pathogenesis of Systemic Lupus Erythematosus and Its Implication in Precision Medicine

Great progress has been made in the last decades in understanding the complex immune dysregulation in systemic lupus erythematosus (SLE), yet the efforts to pursue an effective treatment of SLE proved to be futile. The pathoetiology of SLE involves extremely complicated and multifactorial interaction among various genetic and epigenetic factors. Multiple gene loci predispose to disease susceptibility, and the interaction with epigenetic modifications mediated through sex, hormones, and the hypothalamo-pituitary-adrenal axis complicates susceptibility and manifestations of this disease. Finally, certain environmental and psychological factors probably trigger the disease via epigenetic mechanisms. In this review, we summarize and discuss recent epigenetic studies of SLE and suggest a personalized approach to the dissection of disease onset and therapy or precision medicine. We speculate that in the future, precision medicine based on epigenetic and genetic information could help guide more effective targeted therapeutic intervention.