Marmal-aid - a database for Infinium HumanMethylation450

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Novel DNA methylation profiles associated with key gene regulation and transcription pathways in blood and placenta of growth-restricted neonates

BB/H012494/1/ Biotechnology and Biological Sciences Research Counci

Correlation of an epigenetic mitotic clock with cancer risk.

BACKGROUND: Variation in cancer risk among somatic tissues has been attributed to variations in the underlying rate of stem cell division. For a given tissue type, variable cancer risk between individuals is thought to be influenced by extrinsic factors which modulate this rate of stem cell division. To date, no molecular mitotic clock has been developed to approximate the number of stem cell divisions in a tissue of an individual and which is correlated with cancer risk. RESULTS: Here, we integrate mathematical modeling with prior biological knowledge to construct a DNA methylation-based age-correlative model which approximates a mitotic clock in both normal and cancer tissue. By focusing on promoter CpG sites that localize to Polycomb group target genes that are unmethylated in 11 different fetal tissue types, we show that increases in DNA methylation at these sites defines a tick rate which correlates with the estimated rate of stem cell division in normal tissues. Using matched DNA methylation and RNA-seq data, we further show that it correlates with an expression-based mitotic index in cancer tissue. We demonstrate that this mitotic-like clock is universally accelerated in cancer, including pre-cancerous lesions, and that it is also accelerated in normal epithelial cells exposed to a major carcinogen. CONCLUSIONS: Unlike other epigenetic and mutational clocks or the telomere clock, the epigenetic clock proposed here provides a concrete example of a mitotic-like clock which is universally accelerated in cancer and precancerous lesions

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

Ageing-associated DNA methylation dynamics are a molecular readout of lifespan variation among mammalian species.

BACKGROUND: Mammalian species exhibit a wide range of lifespans. To date, a robust and dynamic molecular readout of these lifespan differences has not yet been identified. Recent studies have established the existence of ageing-associated differentially methylated positions (aDMPs) in human and mouse. These are CpG sites at which DNA methylation dynamics show significant correlations with age. We hypothesise that aDMPs are pan-mammalian and are a dynamic molecular readout of lifespan variation among different mammalian species. RESULTS: A large-scale integrated analysis of aDMPs in six different mammals reveals a strong negative relationship between rate of change of methylation levels at aDMPs and lifespan. This relationship also holds when comparing two different dog breeds with known differences in lifespans. In an ageing cohort of aneuploid mice carrying a complete copy of human chromosome 21, aDMPs accumulate far more rapidly than is seen in human tissues, revealing that DNA methylation at aDMP sites is largely shaped by the nuclear trans-environment and represents a robust molecular readout of the ageing cellular milieu. CONCLUSIONS: Overall, we define the first dynamic molecular readout of lifespan differences among mammalian species and propose that aDMPs will be an invaluable molecular tool for future evolutionary and mechanistic studies aimed at understanding the biological factors that determine lifespan in mammals

Early-life nutrition modulates the epigenetic state of specific rDNA genetic variants in mice.

A suboptimal early-life environment, due to poor nutrition or stress during pregnancy, can influence lifelong phenotypes in the progeny. Epigenetic factors are thought to be key mediators of these effects. We show that protein restriction in mice from conception until weaning induces a linear correlation between growth restriction and DNA methylation at ribosomal DNA (rDNA). This epigenetic response remains into adulthood and is restricted to rDNA copies associated with a specific genetic variant within the promoter. Related effects are also found in models of maternal high-fat or obesogenic diets. Our work identifies environmentally induced epigenetic dynamics that are dependent on underlying genetic variation and establishes rDNA as a genomic target of nutritional insults.This work was supported by the following grants and fellowships: Biotechnology and Biological Sciences Research Council, UK (BB/M012494/1) to V.K.R. and (BB/G00711/X/1) to V.K.R. and C.G.; and a Research Council UK Academic Fellowship to M.L.H. R.L. is supported by EU-FP7 BLUEPRINT. S.E.O. is supported by the British Heart Foundation (FS/12/64/30001) and the Medical Research Council (MC_UU_12012/4). This research used Queen Mary’s MidPlus computational facilities, supported by Queen Mary University of London Research-IT and funded by Engineering and Physical Sciences Research Council grant EP/K000128/1. We thank King’s College London FWB Genomics Centre and Barts and The London Genome Centre for performing high-throughput sequencing.This is the author accepted manuscript. The final version is available from the American Association for the Advancement of Science via http://dx.doi.org/10.1126/science.aaf704

The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations

Epidemiological research suggests that paternal obesity may increase the risk of fathering small for gestational age offspring. Studies in non-human mammals indicate that such associations could be mediated by DNA methylation changes in spermatozoa that influence offspring development in utero. Human obesity is associated with differential DNA methylation in peripheral blood. It is unclear, however, whether this differential DNA methylation is reflected in spermatozoa. We profiled genome-wide DNA methylation using the Illumina MethylationEPIC array in a cross-sectional study of matched human blood and sperm from lean (discovery n = 47; replication n = 21) and obese (n = 22) males to analyse tissue covariation of DNA methylation, and identify obesity-associated methylomic signatures. We found that DNA methylation signatures of human blood and spermatozoa are highly discordant, and methylation levels are correlated at only a minority of CpG sites (~1%). At the majority of these sites, DNA methylation appears to be influenced by genetic variation. Obesity-associated DNA methylation in blood was not generally reflected in spermatozoa, and obesity was not associated with altered covariation patterns or accelerated epigenetic ageing in the two tissues. However, one cross-tissue obesity-specific hypermethylated site (cg19357369; chr4:2429884; P = 8.95 × 10−8; 2% DNA methylation difference) was identified, warranting replication and further investigation. When compared to a wide range of human somatic tissue samples (n = 5,917), spermatozoa displayed differential DNA methylation across pathways enriched in transcriptional regulation. Overall, human sperm displays a unique DNA methylation profile that is highly discordant to, and practically uncorrelated with, that of matched peripheral blood. We observed that obesity was only nominally associated with differential DNA methylation in sperm, and therefore suggest that spermatozoal DNA methylation is an unlikely mediator of intergenerational effects of metabolic traits

Genetic variation at mouse and human ribosomal DNA influences associated epigenetic states

Background: Ribosomal DNA (rDNA) displays substantial inter-individual genetic variation in human and mouse. A systematic analysis of how this variation impacts epigenetic states and expression of the rDNA has thus far not been performed. Results: Using a combination of long- and short-read sequencing, we establish that 45S rDNA units in the C57BL/6J mouse strain exist as distinct genetic haplotypes that influence the epigenetic state and transcriptional output of any given unit. DNA methylation dynamics at these haplotypes are dichotomous and life-stage specific: at one haplotype, the DNA methylation state is sensitive to the in utero environment, but refractory to post-weaning influences, whereas other haplotypes entropically gain DNA methylation during aging only. On the other hand, individual rDNA units in human show limited evidence of genetic haplotypes, and hence little discernible correlation between genetic and epigenetic states. However, in both species, adjacent units show similar epigenetic profiles, and the overall epigenetic state at rDNA is strongly positively correlated with the total rDNA copy number. Analysis of different mouse inbred strains reveals that in some strains, such as 129S1/SvImJ, the rDNA copy number is only approximately 150 copies per diploid genome and DNA methylation levels are < 5%. Conclusions: Our work demonstrates that rDNA-associated genetic variation has a considerable influence on rDNA epigenetic state and consequently rRNA expression outcomes. In the future, it will be important to consider the impact of inter-individual rDNA (epi)genetic variation on mammalian phenotypes and diseases

Integrated Genetic and Epigenetic Analysis Identifies Haplotype-Specific Methylation in the FTO Type 2 Diabetes and Obesity Susceptibility Locus

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10−4, permutation p = 1.0×10−3). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10−7). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases

Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

BACKGROUND: Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease. METHODS: We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium(R) HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes. RESULTS: Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy. CONCLUSION: This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy