Genetics: profiling DNA methylation and beyond

DNA methylation of microRNA-365-1 induces apoptosis of hair follicle stem cells by targeting DAP3

Background

DNA methylation is a crucial epigenetic alteration involved in diverse biological processes and diseases. Nevertheless, the precise role of DNA methylation in chemotherapeutic drug-induced alopecia remains unclear. This study examined the role and novel processes of DNA methylation in regulating of chemotherapeutic drug-induced alopecia.

Methods

A mouse model of cyclophosphamide (CTX)-induced alopecia was established. Hematoxylin-eosin staining and immunohistochemical staining for the Ki67 proportion and a mitochondrial membrane potential assay (JC-1) were performed to assess the structural integrity and proliferative efficiency of the hair follicle stem cells (HFSCs). Immunofluorescence staining and real-time fluorescence quantitative PCR (RT-qPCR) were performed to determine the expression levels of key HFSC markers, namely Lgr5, CD49f, Sox9, CD200, and FZD10. Differential DNA methylation levels between the normal and CTX-induced model groups were determined through simple methylation sequencing and analyzed using bioinformatics tools. The expression levels of miR-365-1, apoptosis markers, and DAP3 were detected through RT-qPCR and western blotting. In parallel, primary mouse HFSCs were extracted and used as a cell model, which was constructed using 4-hydroperoxycyclophosphamide. The luciferase reporter gene assay was conducted to confirm miR-365-1 binding to DAP3. To measure the expression of relevant indicators, superoxide dismutase (SOD) and malondialdehyde (MDA) kits were used. Methylation-specific PCR (MS-PCR) was performed to determine DNA methylation levels. The regulatory relationship within HFSCs was confirmed through plasmid overexpression of miR-365-1 and DAP3.

Result

In the alopecia areata model, a substantial number of apoptotic cells were observed within the hair follicles on the mouse backs. Immunofluorescence staining revealed that the expression of HFSC markers significantly reduced in the CTX group. Both RT-qPCR and western blotting demonstrated a noteworthy difference in DNA methyltransferase expression. Simple methylation sequencing unveiled that DNA methylation substantially increased within the dorsal skin of the CTX group. Subsequent screening identified miR-365-1 as the most differentially expressed miRNA. miR-365-1 was predicted and confirmed to bind to the target gene DAP3. In the CTX group, SOD and ATP expression markedly reduced, whereas MDA levels were significantly elevated. Cellular investigations revealed 4-HC-induced cell cycle arrest and decreased expression of HFSC markers. MS-PCR indicated hypermethylation modification of miR-365-1 in the 4-HC-induced HFSCs. The luciferase reporter gene experiment confirmed the binding of miR-365-1 to the DAP3 promoter region. miR-365-1 overexpression dramatically reduced apoptotic protein expression in the HFSCs. However, this effect was slightly reversed after DAP3 overexpression in lentivirus.

Conclusion

This study explored the occurrence of miR-365-1 DNA methylation in chemotherapeutic drug-induced alopecia. The results unveiled that miR-365-1 reduces cell apoptosis by targeting DAP3 in HFSCs, thereby revealing the role of DNA methylation of the miR-365-1 promoter in chemotherapeutic drug-induced alopecia.

New tools for 'ZEBRA-FISHING'

Zebrafish has been established as a classical model for developmental studies, yet in the past years, with the explosion of novel technological methods, the use of zebrafish as a model has expanded. One of the prominent fields that took advantage of zebrafish as a model organism early on is hematopoiesis, the process of blood cell generation from hematopoietic stem and progenitor cells (HSPCs). In zebrafish, HSPCs are born early during development in the aorta-gonad-mesonephros region and then translocate to the caudal hematopoietic tissue, where they expand and finally take residence in the kidney marrow. This journey is tightly regulated at multiple levels from extracellular signals to chromatin. In order to delineate the mechanistic underpinnings of this process, next-generation sequencing techniques could be an important ally. Here, we describe genome-wide approaches that have been undertaken to delineate zebrafish hematopoiesis.

DNA methylation analysis in plants: review of computational tools and future perspectives

Genome-wide DNA methylation studies have quickly expanded due to advances in next-generation sequencing techniques along with a wealth of computational tools to analyze the data. Most of our knowledge about DNA methylation profiles, epigenetic heritability and the function of DNA methylation in plants derives from the model species Arabidopsis thaliana. There are increasingly many studies on DNA methylation in plants-uncovering methylation profiles and explaining variations in different plant tissues. Additionally, DNA methylation comparisons of different plant tissue types and dynamics during development processes are only slowly emerging but are crucial for understanding developmental and regulatory decisions. Translating this knowledge from plant model species to commercial crops could allow the establishment of new varieties with increased stress resilience and improved yield. In this review, we provide an overview of the most commonly applied bioinformatics tools for the analysis of DNA methylation data (particularly bisulfite sequencing data). The performances of a selection of the tools are analyzed for computational time and agreement in predicted methylated sites for A. thaliana, which has a smaller genome compared to the hexaploid bread wheat. The performance of the tools was benchmarked on five plant genomes. We give examples of applications of DNA methylation data analysis in crops (with a focus on cereals) and an outlook for future developments for DNA methylation status manipulations and data integration.

Detection and accurate false discovery rate control of differentially methylated regions from whole genome bisulfite sequencing

With recent advances in sequencing technology, it is now feasible to measure DNA methylation at tens of millions of sites across the entire genome. In most applications, biologists are interested in detecting differentially methylated regions, composed of multiple sites with differing methylation levels among populations. However, current computational approaches for detecting such regions do not provide accurate statistical inference. A major challenge in reporting uncertainty is that a genome-wide scan is involved in detecting these regions, which needs to be accounted for. A further challenge is that sample sizes are limited due to the costs associated with the technology. We have developed a new approach that overcomes these challenges and assesses uncertainty for differentially methylated regions in a rigorous manner. Region-level statistics are obtained by fitting a generalized least squares regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions. We develop an inferential approach, based on a pooled null distribution, that can be implemented even when as few as two samples per population are available. Here, we demonstrate the advantages of our method using both experimental data and Monte Carlo simulation. We find that the new method improves the specificity and sensitivity of lists of regions and accurately controls the false discovery rate.

Guide Positioning Sequencing identifies aberrant DNA methylation patterns that alter cell identity and tumor-immune surveillance networks

Aberrant DNA methylation is a distinguishing feature of cancer. Yet, how methylation affects immune surveillance and tumor metastasis remains ambiguous. We introduce a novel method, Guide Positioning Sequencing (GPS), for precisely detecting whole-genome DNA methylation with cytosine coverage as high as 96% and unbiased coverage of GC-rich and repetitive regions. Systematic comparisons of GPS with whole-genome bisulfite sequencing (WGBS) found that methylation difference between gene body and promoter is an effective predictor of gene expression with a correlation coefficient of 0.67 (GPS) versus 0.33 (WGBS). Moreover, Methylation Boundary Shift (MBS) in promoters or enhancers is capable of modulating expression of genes associated with immunity and tumor metabolism. Furthermore, aberrant DNA methylation results in tissue-specific enhancer switching, which is responsible for altering cell identity during liver cancer development. Altogether, we demonstrate that GPS is a powerful tool with improved accuracy and efficiency over WGBS in simultaneously detecting genome-wide DNA methylation and genomic variation. Using GPS, we show that aberrant DNA methylation is associated with altering cell identity and immune surveillance networks, which may contribute to tumorigenesis and metastasis.

High-throughput sequencing offers new insights into 5-hydroxymethylcytosine

Chemical modifications of DNA comprise epigenetic mechanisms that contribute to the maintenance of cellular activities and memory. Although the function of 5-methylcytosine (5-mC) has been extensively studied, little is known about the function(s) of relatively rarer and underappreciated cytosine modifications including 5-hydroxymethylcytosine (5-hmC). The discovery that ten-eleven translocation (Tet) proteins mediate conversion of 5-mC to 5-hmC, and other oxidation derivatives, sparked renewed interest to understand the biological role of 5-hmC. Studies examining total 5-hmC levels revealed the highly dynamic yet tissue-specific nature of this modification, implicating a role in epigenetic regulation and development. Intriguingly, 5-hmC levels are highest during early development and in the brain where abnormal patterns of 5-hmC have been observed in disease conditions. Thus, 5-hmC adds to the growing list of epigenetic modifications with potential utility in clinical applications and warrants further investigation. This review discusses the emerging functional roles of 5-hmC in normal and disease states, focusing primarily on insights provided by recent studies exploring the genome-wide distribution of this modification in mammals.