DNA methylation profiling of the human major histocompatibility complex: A pilot study for the Human Epigenome Project

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine-guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data

Exploring genome wide bisulfite sequencing for DNA methylation analysis in livestock: a technical assessment

peer-reviewedRecent advances made in “omics” technologies are contributing to a revolution in livestock selection and breeding practices. Epigenetic mechanisms, including DNA methylation are important determinants for the control of gene expression in mammals. DNA methylation research will help our understanding of how environmental factors contribute to phenotypic variation of complex production and health traits. High-throughput sequencing is a vital tool for the comprehensive analysis of DNA methylation, and bisulfite-based strategies coupled with DNA sequencing allows for quantitative, site-specific methylation analysis at the genome level or genome wide. Reduced representation bisulfite sequencing (RRBS) and more recently whole genome bisulfite sequencing (WGBS) have proven to be effective techniques for studying DNA methylation in both humans and mice. Here we report the development of RRBS and WGBS for use in sheep, the first application of this technology in livestock species. Important technical issues associated with these methodologies including fragment size selection and sequence depth are examined and discussed.AgResearch AR&C grant for funding and Teagasc for providing a short-term overseas training awar

Detection of suspicious interactions of spiking covariates in methylation data

BACKGROUND: In methylation analyses like epigenome-wide association studies, a high amount of biomarkers is tested for an association between the measured continuous outcome and different covariates. In the case of a continuous covariate like smoking pack years (SPY), a measure of lifetime exposure to tobacco toxins, a spike at zero can occur. Hence, all non-smokers are generating a peak at zero, while the smoking patients are distributed over the other SPY values. Additionally, the spike might also occur on the right side of the covariate distribution, if a category "heavy smoker" is designed. Here, we will focus on methylation data with a spike at the left or the right of the distribution of a continuous covariate. After the methylation data is generated, analysis is usually performed by preprocessing, quality control, and determination of differentially methylated sites, often performed in pipeline fashion. Hence, the data is processed in a string of methods, which are available in one software package. The pipelines can distinguish between categorical covariates, i.e. for group comparisons or continuous covariates, i.e. for linear regression. The differential methylation analysis is often done internally by a linear regression without checking its inherent assumptions. A spike in the continuous covariate is ignored and can cause biased results. RESULTS: We have reanalysed five data sets, four freely available from ArrayExpress, including methylation data and smoking habits reported by smoking pack years. Therefore, we generated an algorithm to check for the occurrences of suspicious interactions between the values associated with the spike position and the non-spike positions of the covariate. Our algorithm helps to decide if a suspicious interaction can be found and further investigations should be carried out. This is mostly important, because the information on the differentially methylated sites will be used for post-hoc analyses like pathway analyses. CONCLUSIONS: We help to check for the validation of the linear regression assumptions in a methylation analysis pipeline. These assumptions should also be considered for machine learning approaches. In addition, we are able to detect outliers in the continuous covariate. Therefore, more statistical robust results should be produced in methylation analysis using our algorithm as a preprocessing step

Plant-RRBS, a bisulfite and next-generation sequencing-based methylome profiling method enriching for coverage of cytosine positions

Background: Cytosine methylation in plant genomes is important for the regulation of gene transcription and transposon activity. Genome-wide methylomes are studied upon mutation of the DNA methyltransferases, adaptation to environmental stresses or during development. However, from basic biology to breeding programs, there is a need to monitor multiple samples to determine transgenerational methylation inheritance or differential cytosine methylation. Methylome data obtained by sodium hydrogen sulfite (bisulfite)-conversion and next-generation sequencing (NGS) provide genome- wide information on cytosine methylation. However, a profiling method that detects cytosine methylation state dispersed over the genome would allow high-throughput analysis of multiple plant samples with distinct epigenetic signatures. We use specific restriction endonucleases to enrich for cytosine coverage in a bisulfite and NGS-based profiling method, which was compared to whole-genome bisulfite sequencing of the same plant material. Methods: We established an effective methylome profiling method in plants, termed plant-reduced representation bisulfite sequencing (plant-RRBS), using optimized double restriction endonuclease digestion, fragment end repair, adapter ligation, followed by bisulfite conversion, PCR amplification and NGS. We report a performant laboratory protocol and a straightforward bioinformatics data analysis pipeline for plant-RRBS, applicable for any reference-sequenced plant species. Results: As a proof of concept, methylome profiling was performed using an Oryza sativa ssp. indica pure breeding line and a derived epigenetically altered line (epiline). Plant-RRBS detects methylation levels at tens of millions of cytosine positions deduced from bisulfite conversion in multiple samples. To evaluate the method, the coverage of cytosine positions, the intra-line similarity and the differential cytosine methylation levels between the pure breeding line and the epiline were determined. Plant-RRBS reproducibly covers commonly up to one fourth of the cytosine positions in the rice genome when using MspI-DpnII within a group of five biological replicates of a line. The method predominantly detects cytosine methylation in putative promoter regions and not-annotated regions in rice. Conclusions: Plant-RRBS offers high-throughput and broad, genome- dispersed methylation detection by effective read number generation obtained from reproducibly covered genome fractions using optimized endonuclease combinations, facilitating comparative analyses of multi-sample studies for cytosine methylation and transgenerational stability in experimental material and plant breeding populations

Examination of Methylation Sites for Forensic Age Determination from Semen

Methylation Sensitive High-Resolution Melt (MS-HRM) is based on quantitating the melt curve from an experimental sample against a standard of known methylation levels. Whereas most applications of age prediction using methylation markers are based upon pyrosequencing or SNaPshot technologies, these analysis methods are both cost and instrumentation prohibitive. This study sought to use to the varied methylation status of the ELOVL2 and FHL2 alleles, both having known correlation with age (Hamano et. al.), in a labor and time efficient manner to develop an age prediction model. A non-linear regression and standard curve was compiled from the methylation status in a sample (n=7) of extracted semen samples and compared to chronological age. The methylation status of ELVOL2 and FHL2 from each sample was obtained, with the conclusion that no correlation in methylation percentage and biological age existed for this sample of individuals aged 20-33. The principal objective of this study, to expand the application of MS-HRM age prediction from blood to other body fluids, will need further testing using larger sample sizes and broader age ranges prior to application in forensic casework.https://scholarscompass.vcu.edu/uresposters/1281/thumbnail.jp

Methyl-CpG-binding domain sequencing reveals a prognostic methylation signature in neuroblastoma

Accurate assessment of neuroblastoma outcome prediction remains challenging. Therefore, this study aims at establishing novel prognostic tumor DNA methylation biomarkers. In total, 396 low- and high-risk primary tumors were analyzed, of which 87 were profiled using methyl-CpG-binding domain (MBD) sequencing for differential methylation analysis between prognostic patient groups. Subsequently, methylation-specific PCR (MSP) assays were developed for 78 top-ranking differentially methylated regions and tested on two independent cohorts of 132 and 177 samples, respectively. Further, a new statistical framework was used to identify a robust set of MSP assays of which the methylation score (i.e. the percentage of methylated assays) allows accurate outcome prediction. Survival analyses were performed on the individual target level, as well as on the combined multimarker signature. As a result of the differential DNA methylation assessment by MBD sequencing, 58 of the 78 MSP assays were designed in regions previously unexplored in neuroblastoma, and 36 are located in non-promoter or non-coding regions. In total, 5 individual MSP assays (located in CCDC177, NXPH1, lnc-MRPL3-2, lnc-TREX1-1 and one on a region from chromosome 8 with no further annotation) predict event-free survival and 4 additional assays (located in SPRED3, TNFAIP2, NPM2 and CYYR1) also predict overall survival. Furthermore, a robust 58-marker methylation signature predicting overall and event-free survival was established. In conclusion, this study encompasses the largest DNA methylation biomarker study in neuroblastoma so far. We identified and independently validated several novel prognostic biomarkers, as well as a prognostic 58-marker methylation signature

Possible role of GADD45γ methylation in diffuse large B-cell Lymphoma: Does it affect the progression and tissue involvement?

Objective: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma among adults and is characterized by heterogeneous clinical, immunophenotypic, and genetic features. Different mechanisms deregulating cell cycle and apoptosis play a role in the pathogenesis of DLBCL. Growth arrest DNA damage-inducible 45 (GADD45γ) is an important gene family involved in these mechanisms. The aims of this study are to determine the frequency of GADD45γ methylation, to evaluate the correlation between GADD45γ methylation and protein expression, and to investigate the relation between methylation status and clinicopathologic parameters in DLBCL tissues and reactive lymphoid node tissues from patients with reactive lymphoid hyperplasia. Materials and Methods: Thirty-six tissue samples of DLBCL and 40 nonmalignant reactive lymphoid node tissues were analyzed in this study. Methylation-sensitive high-resolution melting analysis was used for the determination of GADD45γ methylation status. The GADD45γ protein expression was determined by immunohistochemistry. Results: GADD45γ methylation was frequent (50.0%) in DLBCL. It was also significantly higher in advanced-stage tumors compared with early-stage (p=0.041). In contrast, unmethylated GADD45γ was associated with nodal involvement as the primary anatomical site (p=0.040). Conclusion: The results of this study show that, in contrast to solid tumors, the frequency of GADD45γ methylation is higher and this epigenetic alteration of GADD45γ may be associated with progression in DLBCL. In addition, nodal involvement is more likely to be present in patients with unmethylated GADD45γ. © 2015 Turkish Society of Hematology. All rights reserved

In utero tobacco smoke exposure, DNA methylation, and asthma in Latino children.

BackgroundMaternal smoking during pregnancy is a risk factor for chronic disease later in life and has been associated with variability of DNA methylation at specific cytosine-phosphate-guanine (CpG) loci. We assessed the role of DNA methylation as a potential mediator of adverse effects of in utero tobacco smoke exposures on asthma outcomes in Latino children from the US mainland and Puerto Rico.MethodsRelationships between self-reported exposure and DNA methylation at CpG loci previously reported to be associated with maternal smoking were assessed in a subsample consisting of 572 children aged 8-21 years (310 cases with asthma, 262 healthy controls), sampled from a larger asthma case-control study. Subsequently, we assessed associations between top loci and asthma-related outcomes, followed by mediation analysis for loci for which associations with outcomes were observed.ResultsSelf-reported maternal smoking was associated with a -1.5% (95% confidence interval (CI) = -2.4%, -0.6%) lower methylation at CpG locus cg05575921 on the AHRR gene; a 1% increase in DNA methylation at the same locus resulted in an odds ratio (OR) of 0.90 (95% CI = 0.83, 0.96) for the odds of asthma. The OR for the indirect effect of maternal smoking on asthma mediated through methylation at the cg05575921 locus was 1.18 (95% CI = 1.07, 1.68), compared to the OR for the total effect of exposure in the parent study of 1.48 (95% CI = 1.03, 2.11).ConclusionsOur findings suggest potential mediation by DNA methylation in the association between maternal smoking during pregnancy and asthma status