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Understanding the impact of DNA methylation within different disease contexts often requires accurate assessment of these modifications in a genome-wide fashion. Frequently, patient-derived tissues stored in long-term hospital tissue banks have been preserved using formalin-fixation paraffin-embedding (FFPE). While these samples can comprise valuable resources for studying disease, the fixation process ultimately compromises the DNA's integrity and leads to degradation. Degraded DNA can complicate CpG methylome profiling using traditional techniques, particularly when performing methylation-sensitive restriction enzyme sequencing (MRE-seq), yielding high backgrounds and resulting in lowered library complexity. Here, we describe Capture MRE-seq, a new MRE-seq protocol tailored to preserving unmethylated CpG information when using samples with highly degraded DNA. The results using Capture MRE-seq correlate well (0.92) with traditional MRE-seq calls when profiling non-degraded samples, and can recover unmethylated regions in highly degraded samples when traditional MRE-seq fails, which we validate using bisulfite sequencing-based data (WGBS) as well as methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq)., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In the analysis of next-generation sequencing technology, massive discrete data are generated from short read counts with varying biological coverage. Conducting conditional hypothesis testing such as Fisher's Exact Test at every genomic region of interest thus leads to a heterogeneous multiple discrete testing problem. However, most existing multiple testing procedures for controlling the false discovery rate (FDR) assume that test statistics are continuous and become conservative for discrete tests. To overcome the conservativeness, in this article, we propose a novel multiple testing procedure for better FDR control on heterogeneous discrete tests. Our procedure makes decisions based on the marginal critical function (MCF) of randomized tests, which enables achieving a powerful and non-randomized multiple testing procedure. We provide upper bounds of the positive FDR (pFDR) and the positive false non-discovery rate (pFNR) corresponding to our procedure. We also prove that the set of detections made by our method contains every detection made by a naive application of the widely-used q-value method. We further demonstrate the improvement of our method over other existing multiple testing procedures by simulations and a real example of differentially methylated region (DMR) detection using whole-genome bisulfite sequencing (WGBS) data., (© 2019 Wiley Periodicals, Inc.)

Transposable elements (TEs) are an abundant and rich genetic resource of regulatory sequences 1-3 . Cryptic regulatory elements within TEs can be epigenetically reactivated in cancer to influence oncogenesis in a process termed onco-exaptation 4 . However, the prevalence and impact of TE onco-exaptation events across cancer types are poorly characterized. Here, we analyzed 7,769 tumors and 625 normal datasets from 15 cancer types, identifying 129 TE cryptic promoter-activation events involving 106 oncogenes across 3,864 tumors. Furthermore, we interrogated the AluJb-LIN28B candidate: the genetic deletion of the TE eliminated oncogene expression, while dynamic DNA methylation modulated promoter activity, illustrating the necessity and sufficiency of a TE for oncogene activation. Collectively, our results characterize the global profile of TE onco-exaptation and highlight this prevalent phenomenon as an important mechanism for promiscuous oncogene activation and ultimately tumorigenesis.

The studies proposed here were undertaken to test the hypothesis that, under specific circumstances (e.g., a strong enough inflammatory stimulus), genes that are repressed at the maternal-fetal interface via DNA methylation might be de-methylated, allowing either a maternal immune response to the semi-allogenic fetus or the onset of early labor. Chorionic trophoblasts (CT) were isolated from fetal membranes, followed by incubation with medium from LPS-activated PBMC or resting PBMC medium for 2 h. RNA and DNA were isolated from the cells for RNA-seq and DNA methylation studies. Two hrs after being exposed to conditioned medium from LPS-activated PBMC, CT showed differential expression of 114 genes, all but 2 of which showed higher expression in the stimulated cells than is the unstimulated cells. We also identified 318 differentially methylated regions (DMRs) that associated with 306 genes (155 protein coding genes) in the two groups, but the observed methylation changes had negligible impact on the observed transcriptional changes in CT. CT display complex patterns of transcription in response to inflammation. DNA methylation does not appear to be an important regulator of the observed transcriptional changes., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Understanding the role of DNA methylation often requires accurate assessment and comparison of these modifications in a genome-wide fashion. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA CpG methylomes. These include whole genome bisulfite sequencing (WGBS), Reduced-Representation Bisulfite-Sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. An investigator needs a method that is flexible with the quantity of input DNA, provides the appropriate balance among genomic CpG coverage, resolution, quantitative accuracy, and cost, and comes with robust bioinformatics software for analyzing the data. In this chapter, we describe four protocols that combine state-of-the-art experimental strategies with state-of-the-art computational algorithms to achieve this goal. We first introduce two experimental methods that are complementary to each other. MeDIP-seq, or methylation-dependent immunoprecipitation followed by sequencing, uses an anti-methylcytidine antibody to enrich for methylated DNA fragments, and uses massively parallel sequencing to reveal identity of enriched DNA. MRE-seq, or methylation-sensitive restriction enzyme digestion followed by sequencing, relies on a collection of restriction enzymes that recognize CpG containing sequence motifs, but only cut when the CpG is unmethylated. Digested DNA fragments enrich for unmethylated CpGs at their ends, and these CpGs are revealed by massively parallel sequencing. The two computational methods both implement advanced statistical algorithms that integrate MeDIP-seq and MRE-seq data. M&M is a statistical framework to detect differentially methylated regions between two samples. methylCRF is a machine learning framework that predicts CpG methylation levels at single CpG resolution, thus raising the resolution and coverage of MeDIP-seq and MRE-seq to a comparable level of WGBS, but only incurring a cost of less than 5% of WGBS. Together these methods form an effective, robust, and affordable platform for the investigation of genome-wide DNA methylation.

Directed reprogramming of human fibroblasts into fully differentiated neurons requires massive changes in epigenetic and transcriptional states. Induction of a chromatin environment permissive for acquiring neuronal subtype identity is therefore a major barrier to fate conversion. Here we show that the brain-enriched miRNAs miR-9/9 ∗ and miR-124 (miR-9/9 ∗ -124) trigger reconfiguration of chromatin accessibility, DNA methylation, and mRNA expression to induce a default neuronal state. miR-9/9 ∗ -124-induced neurons (miNs) are functionally excitable and uncommitted toward specific subtypes but possess open chromatin at neuronal subtype-specific loci, suggesting that such identity can be imparted by additional lineage-specific transcription factors. Consistently, we show that ISL1 and LHX3 selectively drive conversion to a highly homogeneous population of human spinal cord motor neurons. This study shows that modular synergism between miRNAs and neuronal subtype-specific transcription factors can drive lineage-specific neuronal reprogramming, providing a general platform for high-efficiency generation of distinct subtypes of human neurons., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Uterine carcinosarcoma (UCS) is a form of endometrial cancer simultaneously exhibiting carcinomatous and sarcomatous elements, but the underlying molecular and epigenetic basis of this disease is poorly understood. We generated complete DNA methylomes for both the carcinomatous and the sarcomatous components of three UCS samples separated by laser capture microdissection and compared DNA methylomes of UCS with those of normal endometrium as well as methylomes derived from endometrioid carcinoma, serous endometrial carcinoma, and endometrial stromal sarcoma. We identified epigenetic lesions specific to carcinosarcoma and specific to its two components. Hallmarks of DNA methylation abnormalities in UCS included global hypomethylation, especially in repetitive elements, and hypermethylation of tumor suppressor gene promoters. Among these, aberrant DNA methylation of MIR200 genes is a key feature of UCS. The carcinoma component of UCS was characterized by hypermethylation of promoters of EMILIN1, NEFM, and CLEC14A, genes that are associated with tumor vascularization. In contrast, DNA methylation changes of PKP3, FAM83F, and TCP11 were more characteristic of the sarcoma components. Our findings highlight the epigenetic signatures that distinguish the two components of UCS, providing a valuable resource for investigation of this disease., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Many studies have mapped DNA methylation changes associated with embryogenesis, cell differentiation, and cancer at a genome-wide scale. Our understanding of genome-wide DNA methylation changes in a developmental or disease-related context has been steadily growing. However, the investigation of which CpGs are variably methylated in different normal cell or tissue types is still limited. Here, we present an in-depth analysis of 54 single-CpG-resolution DNA methylomes of normal human cell types by integrating high-throughput sequencing-based methylation data. We found that the ratio of methylated to unmethylated CpGs is relatively constant regardless of cell type. However, which CpGs made up the unmethylated complement was cell-type specific. We categorized the 26,000,000 human autosomal CpGs based on their methylation levels across multiple cell types to identify variably methylated CpGs and found that 22.6% exhibited variable DNA methylation. These variably methylated CpGs formed 660,000 variably methylated regions (VMRs), encompassing 11% of the genome. By integrating a multitude of genomic data, we found that VMRs enrich for histone modifications indicative of enhancers, suggesting their role as regulatory elements marking cell type specificity. VMRs enriched for transcription factor binding sites in a tissue-dependent manner. Importantly, they enriched for GWAS variants, suggesting that VMRs could potentially be implicated in disease and complex traits. Taken together, our results highlight the link between CpG methylation variation, genetic variation, and disease risk for many human cell types., (Copyright © 2016 Gu et al.)

Thyroid hormone binds to nuclear receptors and regulates gene transcription. Here we report that in mice, at around the first day of life, there is a transient surge in hepatocyte type 2 deiodinase (D2) that activates the prohormone thyroxine to the active hormone triiodothyronine, modifying the expression of ∼165 genes involved in broad aspects of hepatocyte function, including lipid metabolism. Hepatocyte-specific D2 inactivation (ALB-D2KO) is followed by a delay in neonatal expression of key lipid-related genes and a persistent reduction in peroxisome proliferator-activated receptor-γ expression. Notably, the absence of a neonatal D2 peak significantly modifies the baseline and long-term hepatic transcriptional response to a high-fat diet (HFD). Overall, changes in the expression of approximately 400 genes represent the HFD response in control animals toward the synthesis of fatty acids and triglycerides, whereas in ALB-D2KO animals, the response is limited to a very different set of only approximately 200 genes associated with reverse cholesterol transport and lipase activity. A whole genome methylation profile coupled to multiple analytical platforms indicate that 10-20% of these differences can be related to the presence of differentially methylated local regions mapped to sites of active/suppressed chromatin, thus qualifying as epigenetic modifications occurring as a result of neonatal D2 inactivation. The resulting phenotype of the adult ALB-D2KO mouse is dramatic, with greatly reduced susceptibility to diet-induced steatosis, hypertriglyceridemia, and obesity.

DNA CpG methylation is a widespread epigenetic mark in high eukaryotes including mammals. DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and control of gene expression. Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to measure DNA methylation in a genome-wide fashion, making it possible to comprehensively investigate the role of DNA methylation. Several methods have been developed, such as Whole Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), and enrichment-based methods including Methylation Dependent ImmunoPrecipitation followed by sequencing (MeDIP-seq), methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq), methyltransferase-directed Transfer of Activated Groups followed by sequencing (mTAG), and Methylation-sensitive Restriction Enzyme digestion followed by sequencing (MRE-seq). These methods differ by their genomic CpG coverage, resolution, quantitative accuracy, cost, and software for analyzing the data. Among these, WGBS is considered the gold standard. However, it is still a cost-prohibitive technology for a typical laboratory due to the required sequencing depth. We found that by integrating two enrichment-based methods that are complementary in nature (i.e., MeDIP-seq and MRE-seq), we can significantly increase the efficiency of whole DNA methylome profiling. By using two recently developed computational algorithms (i.e., M&M and methylCRF), the combination of MeDIP-seq and MRE-seq produces genome-wide CpG methylation measurement at high coverage and high resolution, and robust predictions of differentially methylated regions. Thus, the combination of the two enrichment-based methods provides a cost-effective alternative to WGBS. In this article we describe both the experimental protocols for performing MeDIP-seq and MRE-seq, and the computational protocols for running M&M and methylCRF., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Summary: We present methylC track, an efficient mechanism for visualizing single-base resolution DNA methylation data on a genome browser. The methylC track dynamically integrates the level of methylation, the position and context of the methylated cytosine (i.e. CG, CHG and CHH), strand and confidence level (e.g. read coverage depth in the case of whole-genome bisulfite sequencing data). Investigators can access and integrate these information visually at specific locus or at the genome-wide level on the WashU EpiGenome Browser in the context of other rich epigenomic datasets., Availability and Implementation: The methylC track is part of the WashU EpiGenome Browser, which is open source and freely available at http://epigenomegateway.wustl.edu/browser/. The most up-to-date instructions and tools for preparing methylC track are available at http://epigenomegateway.wustl.edu/+/cmtk., Contact: twang@genetics.wustl.edu, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Aberrant DNA hypomethylation may play an important role in the growth rate of glioblastoma (GBM), but the functional impact on transcription remains poorly understood. We assayed the GBM methylome with MeDIP-seq and MRE-seq, adjusting for copy number differences, in a small set of non-glioma CpG island methylator phenotype (non-G-CIMP) primary tumors. Recurrent hypomethylated loci were enriched within a region of chromosome 5p15 that is specified as a cancer amplicon and also encompasses TERT, encoding telomerase reverse transcriptase, which plays a critical role in tumorigenesis. Overall, 76 gene body promoters were recurrently hypomethylated, including TERT and the oncogenes GLI3 and TP73. Recurring hypomethylation also affected previously unannotated alternative promoters, and luciferase reporter assays for three of four of these promoters confirmed strong promoter activity in GBM cells. Histone H3 lysine 4 trimethylation (H3K4me3) ChIP-seq on tissue from the GBMs uncovered peaks that coincide precisely with tumor-specific decrease of DNA methylation at 200 loci, 133 of which are in gene bodies. Detailed investigation of TP73 and TERT gene body hypomethylation demonstrated increased expression of corresponding alternate transcripts, which in TP73 encodes a truncated p73 protein with oncogenic function and in TERT encodes a putative reverse transcriptase-null protein. Our findings suggest that recurring gene body promoter hypomethylation events, along with histone H3K4 trimethylation, alter the transcriptional landscape of GBM through the activation of a limited number of normally silenced promoters within gene bodies, in at least one case leading to expression of an oncogenic protein.

DNA methylation plays key roles in diverse biological processes such as X chromosome inactivation, transposable element repression, genomic imprinting, and tissue-specific gene expression. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA methylomes. This includes one of the most widely applied technologies for measuring DNA methylation: methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq), coupled with a complementary method, methylation-sensitive restriction enzyme sequencing (MRE-seq). A computational approach that integrates data from these two different but complementary assays and predicts methylation differences between samples has been unavailable. Here, we present a novel integrative statistical framework M&M (for integration of MeDIP-seq and MRE-seq) that dynamically scales, normalizes, and combines MeDIP-seq and MRE-seq data to detect differentially methylated regions. Using sample-matched whole-genome bisulfite sequencing (WGBS) as a gold standard, we demonstrate superior accuracy and reproducibility of M&M compared to existing analytical methods for MeDIP-seq data alone. M&M leverages the complementary nature of MeDIP-seq and MRE-seq data to allow rapid comparative analysis between whole methylomes at a fraction of the cost of WGBS. Comprehensive analysis of nineteen human DNA methylomes with M&M reveals distinct DNA methylation patterns among different tissue types, cell types, and individuals, potentially underscoring divergent epigenetic regulation at different scales of phenotypic diversity. We find that differential DNA methylation at enhancer elements, with concurrent changes in histone modifications and transcription factor binding, is common at the cell, tissue, and individual levels, whereas promoter methylation is more prominent in reinforcing fundamental tissue identities.

Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to map complete DNA methylomes. These include whole-genome bisulfite sequencing (WGBS, MethylC-seq, or BS-seq), reduced-representation bisulfite sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. These methods yield largely comparable results but differ significantly in extent of genomic CpG coverage, resolution, quantitative accuracy, and cost, at least while using current algorithms to interrogate the data. None of these existing methods provides single-CpG resolution, comprehensive genome-wide coverage, and cost feasibility for a typical laboratory. We introduce methylCRF, a novel conditional random fields-based algorithm that integrates methylated DNA immunoprecipitation (MeDIP-seq) and methylation-sensitive restriction enzyme (MRE-seq) sequencing data to predict DNA methylation levels at single-CpG resolution. Our method is a combined computational and experimental strategy to produce DNA methylomes of all 28 million CpGs in the human genome for a fraction (<10%) of the cost of whole-genome bisulfite sequencing methods. methylCRF was benchmarked for accuracy against Infinium arrays, RRBS, WGBS sequencing, and locus-specific bisulfite sequencing performed on the same human embryonic stem cell line. methylCRF transformation of MeDIP-seq/MRE-seq was equivalent to a biological replicate of WGBS in quantification, coverage, and resolution. We used conventional bisulfite conversion, PCR, cloning, and sequencing to validate loci where our predictions do not agree with whole-genome bisulfite data, and in 11 out of 12 cases, methylCRF predictions of methylation level agree better with validated results than does whole-genome bisulfite sequencing. Therefore, methylCRF transformation of MeDIP-seq/MRE-seq data provides an accurate, inexpensive, and widely accessible strategy to create full DNA methylomes.

The density of epilithic algae and concentration of chlorophyll a, Shannon-Wiener index and primary productivity were chosen to study the river continuum characteristics of Xiangxi River. The results showed that in general, the algal density, chlorophyll a concentration and Shannon-Wiener index tended to be increased with increasing stream order, but this trend was not very evident in the first three orders and even reversed. The primary productivity was also higher in the higher than that in the lower stream orders, and reached the maximum in the fourth order, then decreased slightly. The ratio of gross primary productivity to community respiration was the highest in the first stream orders, which means autochthonous productivity was dominant in the river. The results did not absolutely tally with the RCC forecast, therefore, we can conclude that Xiangxi River had been undergone anthropogenic influence.

Cluster analysis and principal component analysis were used to analyze the physical and chemical characteristics of water samples collected from 19 sampling sites along Xiangxi River. The result of cluster analysis showed that Xiangxi River could be divided into three reaches, which belonged to different sub-basins. The principle component analysis on each reach showed that the main information of water quality was different from each other. In the upper reach, the main information of river water quality was hardness and total alkalinity; in the middle reach, the main information was dissolved phosphorus, total phosphorus and Cl-, in the lower reach, the main information was pH, NO2(-)-N, total nitrogen and COD. Furthermore, considering the geographical and environmental backgrounds of the Xiangxi River basin, the reason that caused the different distribution pattern of water quality in Xiangxi River was discussed. Hence, a simple approach to analyze the spatial distribution of water quality was provided.