MethCP: Differentially Methylated Region Detection with Change Point Models

DNA methylation and gene expression profiling reveal potential association of retinol metabolism related genes with hepatocellular carcinoma development

Background

Aberrant DNA methylation patterns play a critical role in the development of hepatocellular carcinoma (HCC). However, the molecular mechanisms associated with these aberrantly methylated genes remain unclear. This study aimed to comprehensively investigate the methylation-driven gene expression alterations in HCC using a multi-omics dataset.

Methods

Whole genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) techniques were used to assess the methylation and gene expression profiles of HCC tissues (HCCs) and normal adjacent tissues (NATs). The candidate genes' potential function was further investigated using single-cell RNA sequencing (scRNA seq) data.

Results

We observed widespread hypomethylation in HCCs compared to NATs. Methylation levels in distinct genomic regions exhibited significant differences between HCCs and NATs. We identified 247,632 differentially methylated regions (DMRs) and 4,926 differentially expressed genes (DEGs) between HCCs and NATs. Integrated analysis of DNA methylation and RNA-seq data identified 987 methylation-driven candidate genes, with 970 showing upregulation and 17 showing downregulation. Four genes involved in the retinol metabolic pathway, namely ADH1A, CYP2A6, CYP2C8, and CYP2C19, were identified as hyper-downregulated genes. Their expression levels could stratify HCCs into three subgroups with distinct survival outcomes, immune cell infiltration, and tumor microenvironments. Validation of these findings in an independent dataset yielded similar outcomes, confirming the high concordance and potential prognostic value of these genes. ScRNA seq data revealed the low expression of these genes in immune cells, emphasizing their role in promoting malignant cell proliferation and migration. In conclusion, this study provides insights into the molecular characteristics of HCC, revealing the involvement of retinol metabolism-related genes in the development and progression of HCC. These findings have implications for HCC diagnosis, prognosis prediction, and the development of therapeutic targets.

The fungicide pyraclostrobin affects gene expression by altering the DNA methylation pattern in Magnaporthe oryzae

Introduction

Rice blast disease caused by Magnaporthe oryzae has long been the main cause of rice (Oryza sativa L.) yield reduction worldwide. The quinone external inhibitor pyraclostrobin is widely used as a fungicide to effectively control the spread of pathogenic fungi, including M. oryzae. However, M. oryzae can develop resistance through multiple levels of mutation, such as target protein cytb mutation G143A/S, leading to a decrease in the effectiveness of the biocide after a period of application. Therefore, uncovering the possible mutational mechanisms from multiple perspectives will further provide feasible targets for drug development.

Methods

In this work, we determined the gene expression changes in M. oryzae in response to pyraclostrobin stress and their relationship with DNA methylation by transcriptome and methylome.

Results

The results showed that under pyraclostrobin treatment, endoplasmic reticulum (ER)-associated and ubiquitin-mediated proteolysis were enhanced, suggesting that more aberrant proteins may be generated that need to be cleared. DNA replication and repair processes were inhibited. Glutathione metabolism was enhanced, while lipid metabolism was impaired. The number of alternative splicing events increased. These changes may be related to the elevated methylation levels of cytosine and adenine in gene bodies. Both hypermethylation and hypomethylation of differentially methylated genes (DMGs) mainly occurred in exons and promoters. Some DMGs and differentially expressed genes (DEGs) were annotated to the same pathways by GO and KEGG, including protein processing in the ER, ubiquitin-mediated proteolysis, RNA transport and glutathione metabolism, suggesting that pyraclostrobin may affect gene expression by altering the methylation patterns of cytosine and adenine.

Discussion

Our results revealed that 5mC and 6mA in the gene body are associated with gene expression and contribute to adversity adaptation in M. oryzae. This enriched the understanding for potential mechanism of quinone inhibitor resistance, which will facilitate the development of feasible strategies for maintaining the high efficacy of this kind of fungicide.

pycoMeth: a toolbox for differential methylation testing from Nanopore methylation calls

We present pycoMeth, a toolbox to store, manage and analyze DNA methylation calls from long-read sequencing data obtained using the Oxford Nanopore Technologies sequencing platform. Building on a novel, rapid-access, read-level and reference-anchored methylation storage format MetH5, we propose efficient algorithms for haplotype aware, multi-sample consensus segmentation and differential methylation testing. We show that MetH5 is more efficient than existing solutions for storing Oxford Nanopore Technologies methylation calls, and carry out benchmarking for pycoMeth segmentation and differential methylation testing, demonstrating increased performance and sensitivity compared to existing solutions designed for short-read methylation data.

ramr: an R/Bioconductor package for detection of rare aberrantly methylated regions

MOTIVATION

With recent advances in the field of epigenetics, the focus is widening from large and frequent disease- or phenotype-related methylation signatures to rare alterations transmitted mitotically or transgenerationally (constitutional epimutations). Merging evidence indicate that such constitutional alterations, albeit occurring at a low mosaic level, may confer risk of disease later in life. Given their inherently low incidence rate and mosaic nature, there is a need for bioinformatic tools specifically designed to analyze such events.

RESULTS

We have developed a method (ramr) to identify aberrantly methylated DNA regions (AMRs). ramr can be applied to methylation data obtained by array or next-generation sequencing techniques to discover AMRs being associated with elevated risk of cancer as well as other diseases. We assessed accuracy and performance metrics of ramr and confirmed its applicability for analysis of large public datasets. Using ramr we identified aberrantly methylated regions that are known or may potentially be associated with development of colorectal cancer and provided functional annotation of AMRs that arise at early developmental stages.

AVAILABILITY AND IMPLEMENTATION

The R package is freely available at https://github.com/BBCG/ramr and https://bioconductor.org/packages/ramr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.