DNA methylation profiles of human active and inactive X chromosomes.
TL;DR: This study provides a detailed analysis of the epigenetic profile of active and inactive X chromosomes, observing a global correlation between CGI methylation and the evolutionary age of X-chromosome strata, and that genes escaping XCI show increased methylation within gene bodies.
Abstract: X-chromosome inactivation (XCI) is a dosage compensation mechanism that silences the majority of genes on one X chromosome in each female cell. To characterize epigenetic changes that accompany this process, we measured DNA methylation levels in 45,X patients carrying a single active X chromosome (X(a)), and in normal females, who carry one X(a) and one inactive X (X(i)). Methylated DNA was immunoprecipitated and hybridized to high-density oligonucleotide arrays covering the X chromosome, generating epigenetic profiles of active and inactive X chromosomes. We observed that XCI is accompanied by changes in DNA methylation specifically at CpG islands (CGIs). While the majority of CGIs show increased methylation levels on the X(i), XCI actually results in significant reductions in methylation at 7% of CGIs. Both intra- and inter-genic CGIs undergo epigenetic modification, with the biggest increase in methylation occurring at the promoters of genes silenced by XCI. In contrast, genes escaping XCI generally have low levels of promoter methylation, while genes that show inter-individual variation in silencing show intermediate increases in methylation. Thus, promoter methylation and susceptibility to XCI are correlated. We also observed a global correlation between CGI methylation and the evolutionary age of X-chromosome strata, and that genes escaping XCI show increased methylation within gene bodies. We used our epigenetic map to predict 26 novel genes escaping XCI, and searched for parent-of-origin-specific methylation differences, but found no evidence to support imprinting on the human X chromosome. Our study provides a detailed analysis of the epigenetic profile of active and inactive X chromosomes.
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TL;DR: The results extend the knowledge of the unique role of DNA methylation in brain development and function, and offer a new framework for testing the role of the epigenome in healthy function and in pathological disruptions of neural circuits.
Abstract: DNA methylation is implicated in mammalian brain development and plasticity underlying learning and memory. We report the genome-wide composition, patterning, cell specificity, and dynamics of DNA methylation at single-base resolution in human and mouse frontal cortex throughout their lifespan. Widespread methylome reconfiguration occurs during fetal to young adult development, coincident with synaptogenesis. During this period, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. Moreover, we found an mCH signature that identifies genes escaping X-chromosome inactivation. Last, whole-genome single-base resolution 5-hydroxymethylcytosine (hmC) maps revealed that hmC marks fetal brain cell genomes at putative regulatory regions that are CG-demethylated and activated in the adult brain and that CG demethylation at these hmC-poised loci depends on Tet2 activity.
1,629 citations
TL;DR: Some of the challenges in studying epigenetic mediation of pathogenesis are discussed and some unique opportunities for exploring these phenomena are described.
Abstract: Changes in epigenetic marks such as DNA methylation and histone acetylation are associated with a broad range of disease traits, including cancer, asthma, metabolic disorders, and various reproductive conditions. It seems plausible that changes in epigenetic state may be induced by environmental exposures such as malnutrition, tobacco smoke, air pollutants, metals, organic chemicals, other sources of oxidative stress, and the microbiome, particularly if the exposure occurs during key periods of development. Thus, epigenetic changes could represent an important pathway by which environmental factors influence disease risks, both within individuals and across generations. We discuss some of the challenges in studying epigenetic mediation of pathogenesis and describe some unique opportunities for exploring these phenomena.
285 citations
Cites background from "DNA methylation profiles of human a..."
...The association between mono-allelic gene expression and DNA methylation has long been recognized, both in the context of X-inactivation in females (Boggs et al. 2002; Sharp et al. 2011) and in parent-of-origin determined genomic imprinting (Ferguson-Smith 2011), but now also in the mono-allelic expression of non-imprinted autosomal loci (Harris et al....
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...…mono-allelic gene expression and DNA methylation has long been recognized, both in the context of X-inactivation in females (Boggs et al. 2002; Sharp et al. 2011) and in parent-of-origin determined genomic imprinting (Ferguson-Smith 2011), but now also in the mono-allelic expression of…...
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TL;DR: DNMTs, demethylases, and associated partners are dynamically shaping the methylome and demonstrate great promise with regard to rejuvenation.
Abstract: DNA methylation is a major control program that modulates gene expression in a plethora of organisms. Gene silencing through methylation occurs through the activity of DNA methyltransferases, enzymes that transfer a methyl group from S-adenosyl-l-methionine to the carbon 5 position of cytosine. DNA methylation patterns are established by the de novo DNA methyltransferases (DNMTs) DNMT3A and DNMT3B and are subsequently maintained by DNMT1. Aging and age-related diseases include defined changes in 5-methylcytosine content and are generally characterized by genome-wide hypomethylation and promoter-specific hypermethylation. These changes in the epigenetic landscape represent potential disease biomarkers and are thought to contribute to age-related pathologies, such as cancer, osteoarthritis, and neurodegeneration. Some diseases, such as a hereditary form of sensory neuropathy accompanied by dementia, are directly caused by methylomic changes. Epigenetic modifications, however, are reversible and are therefore a prime target for therapeutic intervention. Numerous drugs that specifically target DNMTs are being tested in ongoing clinical trials for a variety of cancers, and data from finished trials demonstrate that some, such as 5-azacytidine, may even be superior to standard care. DNMTs, demethylases, and associated partners are dynamically shaping the methylome and demonstrate great promise with regard to rejuvenation.
282 citations
TL;DR: Refocused, epigenetics research aligns with the field of functional genomics to provide insights into environmental and genetic influences on phenotypic variation in humans.
Abstract: Epigenetic association studies have been carried out to test the hypothesis that environmental perturbations trigger cellular reprogramming, with downstream effects on cellular function and phenotypes. There have now been numerous studies of the potential molecular mediators of epigenetic changes by epigenome-wide association studies (EWAS). However, a challenge for the field is the interpretation of the results obtained. We describe a second-generation EWAS approach, which focuses on the possible cellular models of epigenetic perturbations, studied by rigorous analysis and interpretation of genomic data. Thus refocused, epigenetics research aligns with the field of functional genomics to provide insights into environmental and genetic influences on phenotypic variation in humans.
250 citations
TL;DR: Genes regulating oligodendrocyte survival, such as BCL2L2 and NDRG1, were hypermethylated and expressed at lower levels in multiple sclerosis–affected brains than in controls, while genes related to proteolytic processing were hypomethylated and expression at higher levels.
Abstract: Using the Illumina 450K array and a stringent statistical analysis with age and gender correction, we report genome-wide differences in DNA methylation between pathology-free regions derived from human multiple sclerosis-affected and control brains. Differences were subtle, but widespread and reproducible in an independent validation cohort. The transcriptional consequences of differential DNA methylation were further defined by genome-wide RNA-sequencing analysis and validated in two independent cohorts. Genes regulating oligodendrocyte survival, such as BCL2L2 and NDRG1, were hypermethylated and expressed at lower levels in multiple sclerosis-affected brains than in controls, while genes related to proteolytic processing (for example, LGMN, CTSZ) were hypomethylated and expressed at higher levels. These results were not due to differences in cellular composition between multiple sclerosis and controls. Thus, epigenomic changes in genes affecting oligodendrocyte susceptibility to damage are detected in pathology-free areas of multiple sclerosis-affected brains.
228 citations
References
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TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Abstract: SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
83,420 citations
"DNA methylation profiles of human a..." refers methods in this paper
...…across all samples 0.2 were removed from further analyses, and a moderated t-test (Smyth 2004) was conducted to identify probes that showed significantly different methylation between 45,XMAT and 45,XPATsamples using a 5% false discovery rate (FDR) correction (Benjamini and Hochberg 1995)....
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Harvard University1, Brigham and Women's Hospital2, University of Wisconsin-Madison3, University of California, Berkeley4, Technical University of Denmark5, Icahn School of Medicine at Mount Sinai6, Vienna University of Technology7, University of Erlangen-Nuremberg8, German Cancer Research Center9, University of Milan10, Johns Hopkins University11, University of Washington12, Scripps Research Institute13, Walter and Eliza Hall Institute of Medical Research14, University of Iowa15
TL;DR: Details of the aims and methods of Bioconductor, the collaborative creation of extensible software for computational biology and bioinformatics, and current challenges are described.
Abstract: The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.
12,142 citations
"DNA methylation profiles of human a..." refers methods in this paper
...All statistical analyses were performed using software from the Bioconductor project (Gentleman et al. 2004)....
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TL;DR: The hierarchical model of Lonnstedt and Speed (2002) is developed into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples and the moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom.
Abstract: The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model. The purpose of this paper is to develop the hierarchical model of Lonnstedt and Speed (2002) into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples. The model is reset in the context of general linear models with arbitrary coefficients and contrasts of interest. The approach applies equally well to both single channel and two color microarray experiments. Consistent, closed form estimators are derived for the hyperparameters in the model. The estimators proposed have robust behavior even for small numbers of arrays and allow for incomplete data arising from spot filtering or spot quality weights. The posterior odds statistic is reformulated in terms of a moderated t-statistic in which posterior residual standard deviations are used in place of ordinary standard deviations. The empirical Bayes approach is equivalent to shrinkage of the estimated sample variances towards a pooled estimate, resulting in far more stable inference when the number of arrays is small. The use of moderated t-statistics has the advantage over the posterior odds that the number of hyperparameters which need to estimated is reduced; in particular, knowledge of the non-null prior for the fold changes are not required. The moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom. The moderated t inferential approach extends to accommodate tests of composite null hypotheses through the use of moderated F-statistics. The performance of the methods is demonstrated in a simulation study. Results are presented for two publicly available data sets.
11,864 citations
"DNA methylation profiles of human a..." refers methods in this paper
...…distinctions between subgroups, probes with a standard deviation across all samples 0.2 were removed from further analyses, and a moderated t-test (Smyth 2004) was conducted to identify probes that showed significantly different methylation between 45,XMAT and 45,XPATsamples using a 5% false…...
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TL;DR: Three methods of performing normalization at the probe intensity level are presented: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure and the simplest and quickest complete data method is found to perform favorably.
Abstract: Motivation: When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations. Results: We present three methods of performing normalization at the probe intensity level. These methods are called complete data methods because they make use of data from all arrays in an experiment to form the normalizing relation. These algorithms are compared to two methods that make use of a baseline array: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure. Two publicly available datasets are used to carry out the comparisons. The simplest and quickest complete data method is found to perform favorably. Availabilty: Software implementing all three of the complete data normalization methods is available as part of the R package Affy, which is a part of the Bioconductor project http://www.bioconductor.org. Contact: bolstad@stat.berkeley.edu Supplementary information: Additional figures may be found at http://www.stat.berkeley.edu/∼bolstad/normalize/ index.html
8,324 citations
"DNA methylation profiles of human a..." refers methods in this paper
...We applied quantile normalization (Bolstad et al. 2003) to the raw data and filtered outlier probes to remove low-quality data points (Sharp et al. 2010)....
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Proceedings Article•
01 Jan 1994TL;DR: The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences.
Abstract: The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences Multiple motifs are found by fitting a mixture model to the data, probabilistically erasing the occurrences of the motif thus found, and repeating the process to find successive motifs The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input It returns a model of each motif and a threshold which together can be used as a Bayes-optimal classifier for searching for occurrences of the motif in other databases The algorithm estimates how many times each motif occurs in each sequence in the dataset and outputs an alignment of the occurrences of the motif The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset
4,978 citations
"DNA methylation profiles of human a..." refers methods in this paper
...For MEME analysis, all CGIs on the X chromosome were ranked based on their mean probe log2 ratio, and the top and bottom 5% tails of this distribution were tested for enriched motifs 5–20 bp in size....
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...Although MEME analysis at genes subject to XCI, with 50% of genes escaping XCI showing a difference in log2 0.39....
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...MEME (Bailey and Elkan1994) and DRIM (Eden et al. 2007) were used to search for sequence motifs enriched in CGIs that showed extreme gains or losses of methylation....
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