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Changes in DNA methylation at specific CpG sites have been used to build predictive models to estimate animal age, predominantly in mammals. Little testing for this effect has been conducted in other vertebrate groups, such as bony fish, the largest vertebrate class. The development of most age-predictive models has relied on a genome-wide sequencing method to obtain a DNA methylation level, which makes it costly to deploy as an assay to estimate age in many samples. Here, we have generated a reduced representation bisulfite sequencing data set of caudal fin tissue from a model fish species, zebrafish ( Danio rerio ), aged from 11.9-60.1 weeks. We identified changes in methylation at specific CpG sites that correlated strongly with increasing age. Using an optimised unique set of 26 CpG sites we developed a multiplex PCR assay that predicts age with an average median absolute error rate of 3.2 weeks in zebrafish between 10.9-78.1 weeks of age. We also demonstrate the use of multiplex PCR as an efficient quantitative approach to measure DNA methylation for the use of age estimation. This study highlights the potential further use of DNA methylation as an age estimation method in non-mammalian vertebrate species.

Background: DNA methylation is a well-studied epigenetic mark that is frequently altered in diseases such as cancer, where specific changes are known to reflect the type and severity of the disease. Therefore, there is a growing interest in assessing the clinical utility of DNA methylation as a biomarker for diagnosing disease and guiding treatment. The development of an accurate loci-specific methylation assay, suitable for use on low-input clinical material, is crucial for advancing DNA methylation biomarkers into a clinical setting. A targeted multiplex bisulphite PCR sequencing approach meets these needs by allowing multiple DNA methylated regions to be interrogated simultaneously in one experiment on limited clinical material., Results: Here, we provide an updated protocol and recommendations for multiplex bisulphite PCR sequencing (MBPS) assays for target DNA methylation analysis. We describe additional steps to improve performance and reliability: (1) pre-sequencing PCR optimisation which includes assessing the optimal PCR cycling temperature and primer concentration and (2) post-sequencing PCR optimisation to achieve uniform coverage of each amplicon. We use a gradient of methylated controls to demonstrate how PCR bias can be assessed and corrected. Methylated controls also allow assessment of the sensitivity of methylation detection for each amplicon. Here, we show that the MBPS assay can amplify as little as 0.625 ng starting DNA and can detect methylation differences of 1% with a sequencing coverage of 1000 reads. Furthermore, the multiplex bisulphite PCR assay can comprehensively interrogate multiple regions on 1-5 ng of formalin-fixed paraffin-embedded DNA or circulating cell-free DNA., Conclusions: The MBPS assay is a valuable approach for assessing methylated DNA regions in clinical samples with limited material. The optimisation and additional quality control steps described here improve the performance and reliability of this method, advancing it towards potential clinical applications in biomarker studies.

Epigenetic reprogramming in cancer genomes creates a distinct methylation landscape encompassing clustered methylation at regulatory regions separated by large intergenic tracks of hypomethylated regions. This methylation landscape that we referred to as Methylscape is displayed by most cancer types, thus may serve as a universal cancer biomarker. To-date most research has focused on the biological consequences of DNA Methylscape changes whereas its impact on DNA physicochemical properties remains unexplored. Herein, we examine the effect of levels and genomic distribution of methylcytosines on the physicochemical properties of DNA to detect the Methylscape biomarker. We find that DNA polymeric behaviour is strongly affected by differential patterning of methylcytosine, leading to fundamental differences in DNA solvation and DNA-gold affinity between cancerous and normal genomes. We exploit these Methylscape differences to develop simple, highly sensitive and selective electrochemical or colorimetric one-step assays for the detection of cancer. These assays are quick, i.e., analysis time ≤10 minutes, and require minimal sample preparation and small DNA input.

We report a new multiplexed strategy for the electrochemical detection of regional DNA methylation across multiple regions. Using the sequence dependent affinity of bisulfite treated DNA towards gold surfaces, the method integrates the high sensitivity of a micro-fabricated multiplex device comprising a microarray of gold electrodes, with the powerful multiplexing capability of multiplex-PCR. The synergy of this combination enables the monitoring of the methylation changes across several genomic regions simultaneously from as low as 500 pg μl -1 of DNA with no sequencing requirement.

Multiplex bisulfite-PCR sequencing is a convenient and scalable method for the quantitative determination of the methylation state of target DNA regions. A challenge of this application is the presence of CpGs in the same region where primers are being placed. A common solution to the presence of CpGs within a primer-binding region is to substitute a base degeneracy at the cytosine position. However, the efficacy of different substitutions and the extent to which bias towards methylated or unmethylated templates may occur has never been evaluated in bisulfite multiplex sequencing applications. In response, we examined the performance of four different primer substitutions at the cytosine position of CpG's contained within the PCR primers. In this study, deoxyinosine-, 5-nitroindole-, mixed-base primers and primers with an abasic site were evaluated across a series of methylated controls. Primers that contained mixed- or deoxyinosine- base modifications performed most robustly. Mixed-base primers were further selected to determine the conditions that induce bias towards methylated templates. This identified an optimized set of conditions where the methylated state of bisulfite DNA templates can be accurately assessed using mixed-base primers, and expands the scope of bisulfite resequencing assays when working with challenging templates.

Background: DNA methylation at a gene promoter region has the potential to regulate gene transcription. Patterns of methylation over multiple CpG sites in a region are often complex and cell type specific, with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). True representation of methylation patterns can only be fully characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount and complexity of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns., Results: We have developed a new analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. Methpat was used to analyse multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Methpat was able to represent the clonal diversity of epialleles analysed at specific gene promoter regions. We also used Methpat to describe epiallelic DNA methylation within the mitochondrial genome., Conclusions: Methpat can summarise and visualise epiallelic DNA methylation results from targeted amplicon, massively parallel sequencing of bisulfite converted DNA in a compact and interpretable format. Unlike currently available tools, Methpat can visualise the diversity of epiallelic DNA methylation patterns in a sample.

Background: DNA methylation is a complex epigenetic marker that can be analyzed using a wide variety of methods. Interpretation and visualization of DNA methylation data can mask complexity in terms of methylation status at each CpG site, cellular heterogeneity of samples and allelic DNA methylation patterns within a given DNA strand. Bisulfite sequencing is considered the gold standard, but visualization of massively parallel sequencing results remains a significant challenge., Findings: We created a program called Methpat that facilitates visualization and interpretation of bisulfite sequencing data generated by massively parallel sequencing. To demonstrate this, we performed multiplex PCR that targeted 48 regions of interest across 86 human samples. The regions selected included known gene promoters associated with cancer, repetitive elements, known imprinted regions and mitochondrial genomic sequences. We interrogated a range of samples including human cell lines, primary tumours and primary tissue samples. Methpat generates two forms of output: a tab-delimited text file for each sample that summarizes DNA methylation patterns and their read counts for each amplicon, and a HTML file that summarizes this data visually. Methpat can be used with publicly available whole genome bisulfite sequencing and reduced representation bisulfite sequencing datasets with sufficient read depths., Conclusions: Using Methpat, complex DNA methylation data derived from massively parallel sequencing can be summarized and visualized for biological interpretation. By accounting for allelic DNA methylation states and their abundance in a sample, Methpat can unmask the complexity of DNA methylation and yield further biological insight in existing datasets.

Expression of oestrogen receptor (ESR1) determines whether a breast cancer patient receives endocrine therapy, but does not guarantee patient response. The molecular factors that define endocrine response in ESR1-positive breast cancer patients remain poorly understood. Here we characterize the DNA methylome of endocrine sensitivity and demonstrate the potential impact of differential DNA methylation on endocrine response in breast cancer. We show that DNA hypermethylation occurs predominantly at oestrogen-responsive enhancers and is associated with reduced ESR1 binding and decreased gene expression of key regulators of ESR1 activity, thus providing a novel mechanism by which endocrine response is abated in ESR1-positive breast cancers. Conversely, we delineate that ESR1-responsive enhancer hypomethylation is critical in transition from normal mammary epithelial cells to endocrine-responsive ESR1-positive cancer. Cumulatively, these novel insights highlight the potential of ESR1-responsive enhancer methylation to both predict ESR1-positive disease and stratify ESR1-positive breast cancer patients as responders to endocrine therapy.