Age‐ and quality‐dependent DNA methylation correlate with melanin‐based coloration in a wild bird

Secondary sexual trait expression can be influenced by fixed individual factors (such as genetic quality) as well as by dynamic factors (such as age and environmentally induced gene expression) that may be associated with variation in condition or quality. In particular, melanin‐based traits are known to relate to condition and there is a well‐characterized genetic pathway underpinning their expression. However, the mechanisms linking variable trait expression to genetic quality remain unclear. One plausible mechanism is that genetic quality could influence trait expression via differential methylation and differential gene expression. We therefore conducted a pilot study examining DNA methylation at a candidate gene (agouti‐related neuropeptide: AgRP) in the black grouse Lyrurus tetrix. We specifically tested whether CpG methylation covaries with age and multilocus heterozygosity (a proxy of genetic quality) and from there whether the expression of a melanin‐based ornament (ultraviolet‐blue chroma) correlates with DNA methylation. Consistent with expectations, we found clear evidence for age‐ and heterozygosity‐specific patterns of DNA methylation, with two CpG sites showing the greatest DNA methylation in highly heterozygous males at their peak age of reproduction. Furthermore, DNA methylation at three CpG sites was significantly positively correlated with ultraviolet‐blue chroma. Ours is the first study to our knowledge to document age‐ and quality‐dependent variation in DNA methylation and to show that dynamic sexual trait expression across the lifespan of an organism is associated with patterns of DNA methylation. Although we cannot demonstrate causality, our work provides empirical support for a mechanism that could potentially link key individual factors to variation in sexual trait expression in a wild vertebrate.     

Methyl CpG Binding Domain Ultra‐Sequencing: a novel method for identifying inter‐individual and cell‐type‐specific variation in DNA methylation

Experience‐dependent changes in DNA methylation can exert profound effects on neuronal function and behaviour. A single learning event can induce a variety of DNA modifications within the neuronal genome, some of which may be common to all individuals experiencing the event, whereas others may occur in a subset of individuals. Variations in experience‐induced DNA methylation may subsequently confer increased vulnerability or resilience to the development of neuropsychiatric disorders. However, the detection of experience‐dependent changes in DNA methylation in the brain has been hindered by the interrogation of heterogeneous cell populations, regional differences in epigenetic states and the use of pooled tissue obtained from multiple individuals. Methyl CpG Binding Domain Ultra‐Sequencing (MBD Ultra‐Seq) overcomes current limitations on genome‐wide epigenetic profiling by incorporating fluorescence‐activated cell sorting and sample‐specific barcoding to examine cell‐type‐specific CpG methylation in discrete brain regions of individuals. We demonstrate the value of this method by characterizing differences in 5‐methylcytosine (5mC) in neurons and non‐neurons of the ventromedial prefrontal cortex of individual adult C57BL/6 mice, using as little as 50 ng of genomic DNA per sample. We find that the neuronal methylome is characterized by greater CpG methylation as well as the enrichment of 5mC within intergenic loci. In conclusion, MBD Ultra‐Seq is a robust method for detecting DNA methylation in neurons derived from discrete brain regions of individual animals. This protocol will facilitate the detection of experience‐dependent changes in DNA methylation in a variety of behavioural paradigms and help identify aberrant experience‐induced DNA methylation that may underlie risk and resiliency to neuropsychiatric disease.     

A two-CpG-based prognostic signature for oral squamous cell carcinoma overall survival

Oral squamous cell carcinoma (OSCC) represents one of the most common head and neck cancer that with dire prognosis due partly to the lack of reliable prognostic biomarker. Here, we aimed to develop a CpG site–based prognostic signature through which we could accurately predict overall survival (OS) of patients with OSCC. We obtained OSCC-related DNA methylation and gene expression data sets from the public accessible Gene Expression Omnibus. Correlations between methylation level of CpG sites and OS of patients with OSCC were assessed by univariate Cox regression analysis followed by robust likelihood-based survival analysis on those CpG sites with permutation P < 0.05 for further screening the optimal CpG sites for OSCC OS prediction based on the risk score formula that composed of the methylation level of optimal CpG sites weighted by their regression coefficients. Besides, differential expression genes (DEGs) and differential methylation genes (DMGs) in OSCC samples compared with normal samples were obtained and shared genes were considered as vital genes in OSCC tumorgenesis and progression. As a result, two CpG sites including cg17892178 and cg17378966 that located in NID2 and IDO1, respectively, were identified as the optimal prognostic signatures for OSCC OS. In addition, 12 overlapping genes between DEGs and DMGs that closely associated with inflammation or blood and tissue development–related biological processes were obtained. In conclusions, this study should provide valuable signatures for OSCC diagnosis and treatment.     

Dynamic methylation pattern of the methyltransferase1o (Dnmt1o) 5′‐flanking region during mouse oogenesis and spermatogenesis

DNA methyltransferase1o (Dnmt1o), which is specific to oocyte and preimplantation embryo, plays a role in maintaining DNA methylation in mammalian cells. Here, we investigated the methylation status of CpGs sites in the Dnmt1o 5′‐flanking region in germ cells at different stages of oogenesis or spermatogenesis. The methylation levels of the CpG sites at the 5′‐flanking regions were hypermethylated in growing oocytes of all follicular stages, while the oocytes in meiotic metaphase II (MII) were demethylated. The methylation pattern within the CpGs sites in the 5′‐flanking region, however, was dramatically changed during spermatogenesis. We observed that there was significant non‐CpG methylation both in MII oocytes and spermatocytes. Although a low methylation level in non‐CpG sites was observed in primary and secondary oocytes, the CpA site of position 25 and CpT site of position 29 within the no‐CpG region in the 5′‐flanking region of Dnmt1o was highly methylated in MII oocytes. During spermatogenesis, the low degree of methylation at CpG sites in spermatocytes increased to a higher degree in sperm, while the high ratio of methylation in non‐CpG sites in spermatocytes decreased. Together, germ cells showed inverted methylation patterns between CpG and non‐CpG sites in the Dnmt1o 5′‐upstream region, and the methylation pattern during oogenesis did not drastically change, remaining generally hypomethylated at the MII stage. Mol. Reprod. Dev. 80: 212–222, 2013. © 2013 Wiley Periodicals, Inc.     

Age estimation in a long‐lived seabird (Ardenna tenuirostris) using DNA methylation‐based biomarkers

Age structure is a fundamental aspect of animal population biology. Age is strongly related to individual physiological condition, reproductive potential and mortality rate. Currently, there are no robust molecular methods for age estimation in birds. Instead, individuals must be ringed as chicks to establish known‐age populations, which is a labour‐intensive and expensive process. The estimation of chronological age using DNA methylation (DNAm) is emerging as a robust approach in mammals including humans, mice and some non‐model species. Here, we quantified DNAm in whole blood samples from a total of 71 known‐age Short‐tailed shearwaters (Ardenna tenuirostris) using digital restriction enzyme analysis of methylation (DREAM). The DREAM method measures DNAm levels at thousands of CpG dinucleotides throughout the genome. We identified seven CpG sites with DNAm levels that correlated with age. A model based on these relationships estimated age with a mean difference of 2.8 years to known age, based on validation estimates from models created by repeated sampling of training and validation data subsets. Longitudinal observation of individuals re‐sampled over 1 or 2 years generally showed an increase in estimated age (6/7 cases). For the first time, we have shown that epigenetic changes with age can be detected in a wild bird. This approach should be of broad interest to researchers studying age biomarkers in non‐model species and will allow identification of markers that can be assessed using targeted techniques for accurate age estimation in large population studies.     

Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Illumina’s Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677–0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.     

A novel imprinted transgene located near a repetitive element that exhibits allelic imbalance in DNA methylation during early development

A mouse line carrying a lacZ transgene driven by the human EEF1A1/EF1alpha promoter was established. Although the promoter is known to show ubiquitous activity, only paternal transgene alleles were expressed, resulting in a transgene imprinting. At mid‐gestation, the promoter sequence was differentially methylated, hypomethylated for paternal and hypermethylated for maternal alleles. In germline, the promoter was a typical differentially methylated region. After fertilization, however, both alleles were hypermethylated. Thus, the differential methylation of the promoter required for transgene imprinting was re‐established during later embryonic development independently of the germline differential methylation. Furthermore, also a retroelement promoter closely‐flanking imprinted transgene and its wild type counterpart displayed similar differential methylation during early development. The retroelement promoter was methylated differentially also in germline, but in an opposite pattern to the embryonic differential methylation. These results suggest that there might be an unknown epigenetic regulation inducing transgene imprinting independently of DNA methylation in the transgene insertion site. Then, besides CpG dinucleotides, non‐CpG cytosines of the retroelement promoter were highly methylated especially in the transgene‐active mid‐gestational embryos, suggesting that an unusual epigenetic regulation might protect the active transgene against de novo methylation occurring generally in mid‐gestational embryo.     

DNA methylation in imprinted genes IGF2 and GNASXL is associated with prenatal maternal stress

Epigenetic regulation of imprinted genes during embryonic development is influenced by the prenatal environment. Our aim was to examine the effect of maternal emotional stress and cortisol levels during pregnancy on methylation of imprinted genes, insulin‐like growth factor 2 (IGF2) and guanine nucleotide‐binding protein, alpha stimulating extra‐large (GNASXL), using umbilical cord blood DNA. Maternal depressed mood (Edinburgh Depression Scale; EDS), pregnancy‐related anxiety questionnaire (PRAQ) and cortisol day profiles were assessed throughout pregnancy. At birth, a cord blood sample (n = 80) was taken to study DNA methylation of IGF2 DMR0 (differentially methylated region), IGF2 anti‐sense (IGF2AS) and GNASXL using Sequenom Epi TYPER. Linear mixed models were used to examine the relationship between DNA methylation and maternal stress, while correcting for confounders. We also studied the association of DNA methylation with the child ponderal index at birth. We found a cytosine–guanine dinucleotide (CpG)‐specific association of PRAQ subscales with IGF2 DMR0 (CpG5, P < 0.0001) and GNASXL (CpG11, P = 0.0003), while IGF2AS was associated with maternal EDS scores (CpG33, P = 0.0003) and cortisol levels (CpG33, P = 0.0006; CpG37‐38, P = 0.0005). However, there was no association of methylation with ponderal index at birth. In conclusion, maternal stress during pregnancy, as defined by cortisol measurements, EDS and PRAQ scores, is associated with DNA methylation of imprinted genes IGF2 and GNASXL. Our results provide further evidence that prenatal adversity can influence imprinted gene methylation, although future studies are needed to unravel the exact mechanisms.     

An epigenome-wide association meta-analysis of prenatal maternal stress in neonates: A model approach for replication

Prenatal maternal stress exposure has been associated with neonatal differential DNA methylation. However, the available evidence in humans is largely based on candidate gene methylation studies, where only a few CpG sites were evaluated. The aim of this study was to examine the association between prenatal exposure to maternal stress and offspring genome-wide cord blood methylation using different methods. First, we conducted a meta-analysis and follow-up pathway analyses. Second, we used novel region discovery methods [i.e., differentially methylated regions (DMRs) analyses]. To this end, we used data from two independent population-based studies, the Generation R Study (n = 912) and the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 828), to (i) measure genome-wide DNA methylation in cord blood and (ii) extract a prenatal maternal stress composite. The meta-analysis (n_total = 1,740) revealed no epigenome-wide (meta P <1.00e-07) associations of prenatal maternal stress exposure with neonatal differential DNA methylation. Follow-up analyses of the top hits derived from our epigenome-wide meta-analysis (meta P <1.00e-04) indicated an over-representation of the methyltransferase activity pathway. We identified no Bonferroni-corrected (P <1.00e-06) DMRs associated with prenatal maternal stress exposure. Combining data from two independent population-based samples in an epigenome-wide meta-analysis, the current study indicates that there are no large effects of prenatal maternal stress exposure on neonatal DNA methylation. Such replication efforts are essential in the search for robust associations, whether derived from candidate gene methylation or epigenome-wide studies.     

DNA methylation in neonates born to women receiving psychiatric care

Prenatal exposure both to maternal psychiatric illness and psychiatric medication has been linked with adverse child outcomes that affect physiological, emotional and psychiatric development. Studies suggest that epigenetic mechanisms, such as DNA methylation, may facilitate these effects. In this report, we explore the association between maternal psychiatric illness and treatment during pregnancy and neonatal DNA methylation patterns in a prospectively-characterized clinical cohort of 201 dyads. Associations between the percent of umbilical cord blood DNA methylated at 27,578 CpG sites and maternal psychiatric diagnosis, symptoms and antidepressant use were evaluated by fitting a separate linear mixed effects model for each CpG site. There were no significant changes in neonatal DNA methylation attributable to maternal psychiatric diagnosis or depressive symptoms during pregnancy. Exposure to an antidepressant medication was associated with differential methylation of CpG sites in TNFRSF21 and CHRNA2 (false discovery rate < 0.05), but the average difference in methylation for both CpG sites was less than 3% between each group. The results were not specific to type of antidepressant or duration of the exposure. This study suggests that there are no large effects of maternal psychiatric illness, depressive symptoms or prenatal exposure to antidepressants on neonatal DNA methylation. Delineation of the influence of maternal psychiatric illness and pharmacological exposures on the developing fetuses has critical implications for clinical care during pregnancy.     

Array-based profiling of reference-independent methylation status (aPRIMES) identifies frequent promoter methylation and consecutive downregulation of ZIC2 in pediatric medulloblastoma

Existing microarray-based approaches for screening of DNA methylation are hampered by a number of shortcomings, such as the introduction of bias by DNA copy-number imbalances in the test genome and negligence of tissue-specific methylation patterns. We developed a method designated array-based profiling of reference-independent methylation status (aPRIMES) that allows the detection of direct methylation status rather than relative methylation. Array-PRIMES is based on the differential restriction and competitive hybridization of methylated and unmethylated DNA by methylation-specific and methylation-sensitive restriction enzymes, respectively. We demonstrate the accuracy of aPRIMES in detecting the methylation status of CpG islands for different states of methylation. Application of aPRIMES to the DNA from desmoplastic medulloblastomas of monozygotic twins showed strikingly similar methylation profiles. Additional analysis of 18 sporadic medulloblastomas revealed an overall correlation between highly methylated tumors and poor clinical outcome and identified ZIC2 as a frequently methylated gene in pediatric medulloblastoma.     

Methylation-specific MLPA (MS-MLPA): simultaneous detection of CpG methylation and copy number changes of up to 40 sequences

Copy number changes and CpG methylation of various genes are hallmarks of tumor development but are not yet widely used in diagnostic settings. The recently developed multiplex ligation-dependent probe amplification (MLPA) method has increased the possibilities for multiplex detection of gene copy number aberrations in a routine laboratory. Here we describe a novel robust method: the methylation-specific MLPA (MS-MLPA) that can detect changes in both CpG methylation as well as copy number of up to 40 chromosomal sequences in a simple reaction. In MS-MLPA, the ligation of MLPA probe oligonucleotides is combined with digestion of the genomic DNA–probe hybrid complexes with methylation-sensitive endonucleases. Digestion of the genomic DNA–probe complex, rather than double-stranded genomic DNA, allowed the use of DNA derived from the formalin treated paraffin-embedded tissue samples, enabling retrospective studies. To validate this novel method, we used MS-MLPA to detect aberrant methylation in DNA samples of patients with Prader–Willy syndrome, Angelman syndrome or acute myeloid leukemia.     

Bayesian Modeling of ChIP‐chip Data Through a High‐Order Ising Model

Summary ChIP‐chip experiments are procedures that combine chromatin immunoprecipitation (ChIP) and DNA microarray (chip) technology to study a variety of biological problems, including protein–DNA interaction, histone modification, and DNA methylation. The most important feature of ChIP‐chip data is that the intensity measurements of probes are spatially correlated because the DNA fragments are hybridized to neighboring probes in the experiments. We propose a simple, but powerful Bayesian hierarchical approach to ChIP‐chip data through an Ising model with high‐order interactions. The proposed method naturally takes into account the intrinsic spatial structure of the data and can be used to analyze data from multiple platforms with different genomic resolutions. The model parameters are estimated using the Gibbs sampler. The proposed method is illustrated using two publicly available data sets from Affymetrix and Agilent platforms, and compared with three alternative Bayesian methods, namely, Bayesian hierarchical model, hierarchical gamma mixture model, and Tilemap hidden Markov model. The numerical results indicate that the proposed method performs as well as the other three methods for the data from Affymetrix tiling arrays, but significantly outperforms the other three methods for the data from Agilent promoter arrays. In addition, we find that the proposed method has better operating characteristics in terms of sensitivities and false discovery rates under various scenarios.