MeQA: a pipeline for MeDIP-seq data quality assessment and analysis

MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis

SUMMARY

Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) has emerged as a promising liquid biopsy technology to detect cancers and monitor treatments. While several bioinformatics tools for DNA methylation analysis have been adapted for cfMeDIP-seq data, an end-to-end pipeline and quality control framework specifically for this data type is still lacking. Here, we present the MEDIPIPE, which provides a one-stop solution for cfMeDIP-seq data quality control, methylation quantification, and sample aggregation. The major advantages of MEDIPIPE are: (i) ease of implementation and reproducibility with Snakemake containerized execution environments that will be automatically deployed via Conda; (ii) flexibility to handle different experimental settings with a single configuration file; and (iii) computationally efficiency for large-scale cfMeDIP-seq profiling data analysis and aggregation.

AVAILABILITY AND IMPLEMENTATION

This pipeline is an open-source software under the MIT license and it is freely available at https://github.com/pughlab/MEDIPIPE.

EpiMOLAS: an intuitive web-based framework for genome-wide DNA methylation analysis

BACKGROUND

DNA methylation is a crucial epigenomic mechanism in various biological processes. Using whole-genome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging.

RESULTS

To alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses.

CONCLUSION

To our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon. The Galaxy Docker image DocMethyl is available at https://hub.docker.com/r/lsbnb/docmethyl/. EpiMOLAS_web is publicly accessible at http://symbiosis.iis.sinica.edu.tw/epimolas/.

DNA methylation data by sequencing: experimental approaches and recommendations for tools and pipelines for data analysis

Sequencing technologies have changed not only our approaches to classical genetics, but also the field of epigenetics. Specific methods allow scientists to identify novel genome-wide epigenetic patterns of DNA methylation down to single-nucleotide resolution. DNA methylation is the most researched epigenetic mark involved in various processes in the human cell, including gene regulation and development of diseases, such as cancer. Increasing numbers of DNA methylation sequencing datasets from human genome are produced using various platforms-from methylated DNA precipitation to the whole genome bisulfite sequencing. Many of those datasets are fully accessible for repeated analyses. Sequencing experiments have become routine in laboratories around the world, while analysis of outcoming data is still a challenge among the majority of scientists, since in many cases it requires advanced computational skills. Even though various tools are being created and published, guidelines for their selection are often not clear, especially to non-bioinformaticians with limited experience in computational analyses. Separate tools are often used for individual steps in the analysis, and these can be challenging to manage and integrate. However, in some instances, tools are combined into pipelines that are capable to complete all the essential steps to achieve the result. In the case of DNA methylation sequencing analysis, the goal of such pipeline is to map sequencing reads, calculate methylation levels, and distinguish differentially methylated positions and/or regions. The objective of this review is to describe basic principles and steps in the analysis of DNA methylation sequencing data that in particular have been used for mammalian genomes, and more importantly to present and discuss the most pronounced computational pipelines that can be used to analyze such data. We aim to provide a good starting point for scientists with limited experience in computational analyses of DNA methylation and hydroxymethylation data, and recommend a few tools that are powerful, but still easy enough to use for their own data analysis.

DNA methylation studies of depression with onset in the peripartum: A critical systematic review

OBJECTIVE

Major depression with peripartum onset (MDP) has been associated with multiple adverse offspring health outcomes. The biological mechanisms underlying this relationship remain unclear, but DNA methylation (DNAm) represents a plausible mechanism for mediating MDP exposures and changes in offspring development, behavior, and health. Advances in DNAm research necessitate reevaluating the MDP-DNAm literature to determine how well past studies conform with current best practices.

METHOD

Five databases were searched to identify studies of prenatal-onset MDP and DNAm. Quality scores were assigned to each article independently by two raters using a novel scale specific for MDP-DNAm research.

RESULTS

Nineteen studies met inclusion criteria. Quality scores ranged from 10 to 17 out of 24 points (M = 12.8; SD = 1.9), with higher scores indicating increased study rigor. Poor covariate reporting was the most significant contributor to lower scores.

CONCLUSION

No longitudinal MDP-DNAm studies exist. Earlier MDP-DNAm studies should be interpreted with caution, and future research must commit to sharing methodology and data to facilitate cross-study comparisons and maximize dataset utility.

Considerations for Design and Analysis of DNA Methylation Studies

The number of epigenetic studies is exponentially increasing. There is anticipation that DNA methylation may close gaps in our understanding of disease etiology, and how certain risk factors affect health and disease, but also that it has potential as a biomarker for disease. Human DNA methylation studies require careful considerations for design and analysis including population and tissue selection, population stratification, cell heterogeneity, confounding, temporality, sample size, appropriate statistical analysis, and validation of results. In this chapter, we discuss relevant aspects for the design of DNA methylation studies and delineate essential steps for their analysis. Specifically, we summarize methods used to extricate biologic signals from technical noise, and statistical approaches to capture meaningful variability based on the research hypothesis.

Epigenetic regulation of mitochondrial function in neurodegenerative disease: New insights from advances in genomic technologies

The field of mitochondrial epigenetics has received increased attention in recent years and changes in mitochondrial DNA (mtDNA) methylation has been implicated in a number of diseases, including neurodegenerative diseases such as amyotrophic lateral sclerosis. However, current publications have been limited by the use of global or targeted methods of measuring DNA methylation. In this review, we discuss current findings in mitochondrial epigenetics as well as its potential role as a regulator of mitochondria within the brain. Finally, we summarize the current technologies best suited to capturing mtDNA methylation, and how a move towards whole epigenome sequencing of mtDNA may help to advance our current understanding of the field.

New technologies for DNA analysis--a review of the READNA Project

The REvolutionary Approaches and Devices for Nucleic Acid analysis (READNA) project received funding from the European Commission for 41/2 years. The objectives of the project revolved around technological developments in nucleic acid analysis. The project partners have discovered, created and developed a huge body of insights into nucleic acid analysis, ranging from improvements and implementation of current technologies to the most promising sequencing technologies that constitute a 3(rd) and 4(th) generation of sequencing methods with nanopores and in situ sequencing, respectively.

CpG island hypermethylation as a biomarker for the early detection of lung cancer

Lung cancer is the most frequent cause of cancer-related deaths and causes over one million deaths worldwide each year. Despite significant strides in the diagnosis and treatment of lung cancer, the prognosis is extremely poor, with the overall 5-year survival rates still remaining around 15 %. This is largely due to occult metastatic dissemination, which appears in approximately two-thirds of patients at the time of detection. Thus, the development of efficient diagnostic methods to enable the early detection of cancer for these patients is clearly imperative.One promising approach is the identification of lung cancer-specific biomarkers at an early stage. The de novo methylation of CpG islands within the promoters of tumor suppressor genes is one of the most frequently acquired epigenetic changes during the pathogenesis of lung cancer and usually associated with transcriptional downregulation of a gene. The analysis of DNA methylation patterns in sputum, bronchial fluid, plasma, or serum could become a powerful tool for the accurate and early diagnosis of lung cancer with unparalleled specificity and sensitivity.

Involvement of microRNA-24 and DNA methylation in resistance of nasopharyngeal carcinoma to ionizing radiation

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating in the epithelium. Radiotherapy is the standard therapy, but tumor resistance to this treatment reduces the 5-year patient survival rate dramatically. Studies are urgently needed to elucidate the mechanism of NPC radioresistance. Epigenetics--particularly microRNAs (miRNA) and DNA methylation--plays an important role in carcinogenesis and oncotherapy. We used qRT-PCR analysis and identified an miRNA signature from differentially expressed miRNAs. Our objectives were to identify the role of miR24 in NPC tumorigenesis and radioresistance and to identify the mechanisms by which miR24 is regulated. We found that miR24 inhibited NPC cell growth, promoted cell apoptosis, and suppressed the growth of NPC xenografts. We showed that miR24 was significantly downregulated in recurrent NPC tissues. When combined with irradiation, miR24 acted as a radiosensitizer in NPC cells. One of the miR24 precursors was embedded in a CpG island. Aberrant DNA methylation was involved in NPC response to radiotherapy, which linked inactivation of miR24 through hypermethylation of its precursor promoter with NPC radioresistance. Treating NPC cells with the DNA-hypomethylating agent 5-aza-2'-deoxycytidine compensated for the reduced miR24 expression. Together, our findings showed that miR24 was negatively regulated by hypermethylation of its precursor promoter in NPC radioresistance. Our findings defined a central role for miR24 as a tumor-suppressive miRNA in NPC and suggested its use in novel strategies for treatment of this cancer.

Developmental ORIgins of Healthy and Unhealthy AgeiNg: the role of maternal obesity--introduction to DORIAN

Europe has the highest proportion of elderly people in the world. Cardiovascular disease, type 2 diabetes, sarcopenia and cognitive decline frequently coexist in the same aged individual, sharing common early risk factors and being mutually reinforcing. Among conditions which may contribute to establish early risk factors, this review focuses on maternal obesity, since the epidemic of obesity involves an ever growing number of women of reproductive age and children, calling for appropriate studies to understand the consequences of maternal obesity on the offspring's health and for developing effective measures and policies to improve people's health before their conception and birth. Though the current knowledge suggests that the long-term impact of maternal obesity on the offspring's health may be substantial, the outcomes of maternal obesity over the lifespan have not been quantified, and the molecular changes induced by maternal obesity remain poorly characterized. We hypothesize that maternal insulin resistance and reduced placental glucocorticoid catabolism, leading to oxidative stress, may damage the DNA, either in its structure (telomere shortening) or in its function (via epigenetic changes), resulting in altered gene expression/repair, disease during life, and pathological ageing. This review illustrates the background to the EU-FP7-HEALTH-DORIAN project.

Functional DNA methylation differences between tissues, cell types, and across individuals discovered using the M&M algorithm

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.

A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip(®) for methylome profiling

DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.

Analysing and interpreting DNA methylation data

DNA methylation is an epigenetic mark that has suspected regulatory roles in a broad range of biological processes and diseases. The technology is now available for studying DNA methylation genome-wide, at a high resolution and in a large number of samples. This Review discusses relevant concepts, computational methods and software tools for analysing and interpreting DNA methylation data. It focuses not only on the bioinformatic challenges of large epigenome-mapping projects and epigenome-wide association studies but also highlights software tools that make genome-wide DNA methylation mapping more accessible for laboratories with limited bioinformatics experience.

Resources for methylome analysis suitable for gene knockout studies of potential epigenome modifiers

Background

Methylated DNA immunoprecipitation (MeDIP) is a popular enrichment based method and can be combined with sequencing (termed MeDIP-seq) to interrogate the methylation status of cytosines across entire genomes. However, quality control and analysis of MeDIP-seq data have remained to be a challenge.

Results

We report genome-wide DNA methylation profiles of wild type (wt) and mutant mouse cells, comprising 3 biological replicates of Thymine DNA glycosylase (Tdg) knockout (KO) embryonic stem cells (ESCs), in vitro differentiated neural precursor cells (NPCs) and embryonic fibroblasts (MEFs). The resulting 18 methylomes were analysed with MeDUSA (Methylated DNA Utility for Sequence Analysis), a novel MeDIP-seq computational analysis pipeline for the identification of differentially methylated regions (DMRs). The observed increase of hypermethylation in MEF promoter-associated CpG islands supports a previously proposed role for Tdg in the protection of regulatory regions from epigenetic silencing. Further analysis of genes and regions associated with the DMRs by gene ontology, pathway, and ChIP analyses revealed further insights into Tdg function, including an association of TDG with low-methylated distal regulatory regions.

Conclusions

We demonstrate that MeDUSA is able to detect both large-scale changes between cells from different stages of differentiation and also small but significant changes between the methylomes of cells that only differ in the KO of a single gene. These changes were validated utilising publicly available datasets and confirm TDG's function in the protection of regulatory regions from epigenetic silencing.