Strand-specific CpG hemimethylation, a novel epigenetic modification functional for genomic imprinting

Uncovering the roles of DNA hemi-methylation in transcriptional regulation using MspJI-assisted hemi-methylation sequencing

Hemi-methylated cytosine dyads widely occur on mammalian genomic DNA, and can be stably inherited across cell divisions, serving as potential epigenetic marks. Previous identification of hemi-methylation relied on harsh bisulfite treatment, leading to extensive DNA degradation and loss of methylation information. Here we introduce Mhemi-seq, a bisulfite-free strategy, to efficiently resolve methylation status of cytosine dyads into unmethylation, strand-specific hemi-methylation, or full-methylation. Mhemi-seq reproduces methylomes from bisulfite-based sequencing (BS-seq & hpBS-seq), including the asymmetric hemi-methylation enrichment flanking CTCF motifs. By avoiding base conversion, Mhemi-seq resolves allele-specific methylation and associated imprinted gene expression more efficiently than BS-seq. Furthermore, we reveal an inhibitory role of hemi-methylation in gene expression and transcription factor (TF)-DNA binding, and some displays a similar extent of inhibition as full-methylation. Finally, we uncover new hemi-methylation patterns within Alu retrotransposon elements. Collectively, Mhemi-seq can accelerate the identification of DNA hemi-methylation and facilitate its integration into the chromatin environment for future studies.

An ecologist's guide for studying DNA methylation variation in wild vertebrates

The field of molecular biology is advancing fast with new powerful technologies, sequencing methods and analysis software being developed constantly. Commonly used tools originally developed for research on humans and model species are now regularly used in ecological and evolutionary research. There is also a growing interest in the causes and consequences of epigenetic variation in natural populations. Studying ecological epigenetics is currently challenging, especially for vertebrate systems, because of the required technical expertise, complications with analyses and interpretation, and limitations in acquiring sufficiently high sample sizes. Importantly, neglecting the limitations of the experimental setup, technology and analyses may affect the reliability and reproducibility, and the extent to which unbiased conclusions can be drawn from these studies. Here, we provide a practical guide for researchers aiming to study DNA methylation variation in wild vertebrates. We review the technical aspects of epigenetic research, concentrating on DNA methylation using bisulfite sequencing, discuss the limitations and possible pitfalls, and how to overcome them through rigid and reproducible data analysis. This review provides a solid foundation for the proper design of epigenetic studies, a clear roadmap on the best practices for correct data analysis and a realistic view on the limitations for studying ecological epigenetics in vertebrates. This review will help researchers studying the ecological and evolutionary implications of epigenetic variation in wild populations.

A novel workflow for the qualitative analysis of DNA methylation data

•

A novel R package (EpiStatProfiler) for the qualitative analysis of DNA methylation data.

•

A novel workflow for the analysis of CG and non-CG epialleles starting from any type of bisulfite sequencing data.

•

EpiStatProfiler can perform strand-specific characterization of epialleles composition.

•

Important loci can be annotated along with their biological role and potential functions.

•

EpiStatProfiler has the ability to identify loci whose epiallelic profile is associated with disease pathogenesis.

DNA methylation is an epigenetic modification that plays a pivotal role in major biological mechanisms, such as gene regulation, genomic imprinting, and genome stability. Different combinations of methylated cytosines for a given DNA locus generate different epialleles and alterations of these latter have been associated with several pathological conditions. Existing computational methods and statistical tests relevant to DNA methylation analysis are mostly based on the comparison of average CpG sites methylation levels and they often neglect non-CG methylation. Here, we present EpiStatProfiler, an R package that allows the analysis of CpG and non-CpG based epialleles starting from bisulfite sequencing data through a collection of dedicated extraction functions and statistical tests. EpiStatProfiler is provided with a set of useful auxiliary features, such as customizable genomic ranges, strand-specific epialleles analysis, locus annotation and gene set enrichment analysis. We showcase the package functionalities on two public datasets by identifying putative relevant loci in mice harboring the Huntington’s disease-causing Htt gene mutation and in Ctcf +/− mice compared to their wild-type counterparts. To our knowledge, EpiStatProfiler is the first package providing functionalities dedicated to the analysis of epialleles composition derived from any kind of bisulfite sequencing experiment.

A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing

Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https://github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.

DNA methylation changes during long-term in vitro cell culture are caused by epigenetic drift

Culture expansion of primary cells evokes highly reproducible DNA methylation (DNAm) changes. We have identified CG dinucleotides (CpGs) that become continuously hyper- or hypomethylated during long-term culture of mesenchymal stem cells (MSCs) and other cell types. Bisulfite barcoded amplicon sequencing (BBA-seq) demonstrated that DNAm patterns of neighboring CpGs become more complex without evidence of continuous pattern development and without association to oligoclonal subpopulations. Circularized chromatin conformation capture (4C) revealed reproducible changes in nuclear organization between early and late passages, while there was no enriched interaction with other genomic regions that also harbor culture-associated DNAm changes. Chromatin immunoprecipitation of CTCF did not show significant differences during long-term culture of MSCs, however culture-associated hypermethylation was enriched at CTCF binding sites and hypomethylated CpGs were devoid of CTCF. Taken together, our results support the notion that DNAm changes during culture-expansion are not directly regulated by a targeted mechanism but rather resemble epigenetic drift.

Julia Franzen et al. investigate if changes in DNA methylation at specific genetic loci during cell culture expansion are due to a specific mechanism or gradual deregulation of an epigenetic state. Their results suggest that changes in CpG methylation are due to indirect epigenetic drift, rather than a consequence of targeting by DNA methyltransferases.

Statistical and bioinformatic analysis of hemimethylation patterns in non-small cell lung cancer

Background

DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns.

Methods

In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools.

Results

In this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. Several genes that are known to be associated with cancer are hemimethylated differently between the cancerous and normal samples. Furthermore, highly hemimethylated genes exhibit many different interactions with other genes that may be associated with cancer. Hemimethylation has diverse patterns and frequencies that are comparable between normal and tumorous cells. Therefore, hemimethylation may be related to both normal and tumor cell development.

Conclusions

Our research has identified CpG clusters and genes that are hemimethylated in normal and lung tumor samples. Due to the potential impact of hemimethylation on gene expression and cell function, these clusters and genes may be important to advance our understanding of the development and progression of non-small cell lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07990-7.

Methylation status of KLF4 and HS3ST2 genes as predictors of endometrial cancer and hyperplastic endometrial lesions

Endometrial carcinoma is one of the most common tumours in developed countries. In addition to the active role of genetic factors, epigenetic changes also have an important effect. The present study analysed the methylation status of kruppel like factor 4 (KLF4) and heparan sulfate‑glucosamine 3‑sulfotransferase 2 (HS3ST2) genes in three endometrial tissue types for carcinoma prediction. The sample comprised 91 women with histologically‑confirmed endometrial carcinoma (64.16±9.64 years old), 36 women with hyperplasia (53.39±9.64 years old) and 45 with no signs or symptoms of malignancy (48.53±11.11 years old). The CpG dinucleotide methylation levels were examined by quantitative pyrosequencing, and the discrimination accuracy of the model was calculated using the Random Forest classification algorithm of the area under the ROC curve (AUC). The mean values of KLF4 and HS3ST2 methylation indices were 23.83±11.39 and 8.52±2.57 in the control samples; 30.40±8.52 and 33.76±20.66 in hyperplasia and 34.72±10.79 and 34.49±18.39 in the cancerous tissues. Multinomial logistic regression indicated that the HS3ST2 CpG1 methylation status is a predictor of hyperplasia (P<0.05) and that the KLF4 CpG2 dinucleotide can predict carcinoma formation (P<0.001). The AUC value of 0.95 indicates high discrimination accuracy of the CpG nucleotides methylation status model between the controls and the two other diagnoses. The results of the present study establish the likelihood that aberrations in KLF4 and HS3ST2 gene methylation levels are important in the development of endometrial hyperplasia and carcinoma, with hyperplasia an intermediate step between healthy and tumour tissues.

Recent progress, methods and perspectives in forensic epigenetics

Forensic epigenetics, i.e., investigating epigenetics variation to resolve forensically relevant questions unanswerable with standard forensic DNA profiling has been gaining substantial ground over the last few years. Differential DNA methylation among tissues and individuals has been proposed as useful resource for three forensic applications i) determining the tissue type of a human biological trace, ii) estimating the age of an unknown trace donor, and iii) differentiating between monozygotic twins. Thus far, forensic epigenetic investigations have used a wide range of methods for CpG marker discovery, prediction modelling and targeted DNA methylation analysis, all coming with advantages and disadvantages when it comes to forensic trace analysis. In this review, we summarize the most recent literature on these three main topics of current forensic epigenetic investigations and discuss limitations and practical considerations in experimental design and data interpretation, such as technical and biological biases. Moreover, we provide future perspectives with regard to new research questions, new epigenetic markers and recent technological advances that - as we envision - will move the field towards forensic epigenomics in the near future.