Allele-specific DNA methylation (ASM) is well studied in imprinted domains, but this type of epigenetic asymmetry is actually found more commonly at non-imprinted loci, where the ASM is dictated not by parent-of-origin but instead by the local haplotype. We identified loci with strong ASM in human tissues from methylation-sensitive SNP array data. Two index regions (bisulfite PCR amplicons), one between the C3orf27 and RPN1 genes in chromosome band 3q21 and the other near the VTRNA2-1 vault RNA in band 5q31, proved to be new examples of imprinted DMRs (maternal alleles methylated) while a third, between STEAP3 and C2orf76 in chromosome band 2q14, showed non-imprinted haplotype-dependent ASM. Using long-read bisulfite sequencing (bis-seq) in 8 human tissues we found that in all 3 domains the ASM is restricted to single differentially methylated regions (DMRs), each less than 2kb. The ASM in the C3orf27-RPN1 intergenic region was placenta-specific and associated with allele-specific expression of a long non-coding RNA. Strikingly, the discrete DMRs in all 3 regions overlap with binding sites for the insulator protein CTCF, which we found selectively bound to the unmethylated allele of the STEAP3-C2orf76 DMR. Methylation mapping in two additional genes with non-imprinted haplotype-dependent ASM, ELK3 and CYP2A7, showed that the CYP2A7 DMR also overlaps a CTCF site. Thus, two features of imprinted domains, highly localized DMRs and allele-specific insulator occupancy by CTCF, can also be found in chromosomal domains with non-imprinted ASM. Arguing for biological importance, our analysis of published whole genome bis-seq data from hES cells revealed multiple genome-wide association study (GWAS) peaks near CTCF binding sites with ASM.
Allele-specific DNA methylation (ASM) is a central mechanism of gene regulation in humans, which can influence inter-individual differences in physical and mental traits and disease susceptibility. ASM is mediated either by parental imprinting, in which the repressed copy (allele) of the gene is determined by which type of parent (mother or father) transmitted it or, for a larger number of genes, by the local DNA sequence, independent of which parent transmitted it. Chromosomal regions with imprinted ASM have been well studied, and certain mechanistic principles, including the role of discrete differentially methylated regions (DMRs) and involvement of the insulator protein CTCF, have emerged. However, the molecular mechanisms underlying non-imprinted sequence-dependent ASM are not yet understood. Here we describe our detailed mapping of ASM across 5 gene regions, including two novel examples of imprinted ASM and three gene regions with non-imprinted, sequence-dependent ASM. Our data uncover shared molecular features – small discrete DMRs, and the binding of CTCF to these DMRs, in examples of both types of ASM. Combining ASM mapping with genetic association data suggests that sequence-dependent ASM at CTCF binding sites influences diverse human traits.
Genome-wide dynamic changes in DNA methylation are indispensable for germline development and genomic imprinting in mammals. Here, we report single-base resolution DNA methylome and transcriptome maps of mouse germ cells, generated using whole-genome shotgun bisulfite sequencing and cDNA sequencing (mRNA-seq). Oocyte genomes showed a significant positive correlation between mRNA transcript levels and methylation of the transcribed region. Sperm genomes had nearly complete coverage of methylation, except in the CpG-rich regions, and showed a significant negative correlation between gene expression and promoter methylation. Thus, these methylome maps revealed that oocytes and sperms are widely different in the extent and distribution of DNA methylation. Furthermore, a comparison of oocyte and sperm methylomes identified more than 1,600 CpG islands differentially methylated in oocytes and sperm (germline differentially methylated regions, gDMRs), in addition to the known imprinting control regions (ICRs). About half of these differentially methylated DNA sequences appear to be at least partially resistant to the global DNA demethylation that occurs during preimplantation development. In the absence of Dnmt3L, neither methylation of most oocyte-methylated gDMRs nor intragenic methylation was observed. There was also genome-wide hypomethylation, and partial methylation at particular retrotransposons, while maintaining global gene expression, in oocytes. Along with the identification of the many Dnmt3L-dependent gDMRs at intragenic regions, the present results suggest that oocyte methylation can be divided into 2 types: Dnmt3L-dependent methylation, which is required for maternal methylation imprinting, and Dnmt3L-independent methylation, which might be essential for endogenous retroviral DNA silencing. The present data provide entirely new perspectives on the evaluation of epigenetic markers in germline cells.
In mammals, germ-cell–specific methylation patterns and genomic imprints are established throughout large-scale de novo DNA methylation in oogenesis and spermatogenesis. These steps are required for normal germline differentiation and embryonic development; however, current DNA methylation analyses only provide us a partial picture of germ cell methylome. To the best of our knowledge, this is the first study to generate comprehensive maps of DNA methylomes and transcriptomes at single base resolution for mouse germ cells. These methylome maps revealed genome-wide opposing DNA methylation patterns and differential correlation between methylation and gene expression levels in oocyte and sperm genomes. In addition, our results indicate the presence of 2 types of methylation patterns in the oocytes: (i) methylation across the transcribed regions, which might be required for the establishment of maternal methylation imprints and normal embryogenesis, and (ii) retroviral methylation, which might be essential for silencing of retrotransposons and normal oogenesis. We believe that an extension of this work would lead to a better understanding of the epigenetic reprogramming in germline cells and of the role for gene regulations.
Peripheral blood monocytes (PBMs) play multiple and critical roles in the immune response, and abnormalities in PBMs have been linked to a variety of human disorders. However, the DNA methylation landscape in PBMs is largely unknown. In this study, we characterized epigenome-wide DNA methylation profiles in purified PBMs.
Materials & methods
PBMs were isolated from freshly collected peripheral blood from 18 unrelated healthy postmenopausal Caucasian females. Epigenome-wide DNA methylation profiles (the methylome) were characterized by using methylated DNA immunoprecipitation combined with high-throughput sequencing.
Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (~58%) found to be unmethylated; whereas protein coding regions were largely (~84%) methylated. Although CpG-rich and -poor promoters showed distinct methylation patterns, interestingly, a negative correlation between promoter methylation levels and gene transcription levels was consistently observed across promoters with high to low CpG densities. Importantly, we observed substantial interindividual variation in DNA methylation across the individual PBM methylomes and the pattern of this interindividual variation varied between different genomic features, with highly variable regions enriched for repetitive DNA elements. Furthermore, we observed a modest but significant excess (p < 2.2 × 10−16) of genes showing a negative correlation between interindividual promoter methylation and transcription levels. These significant genes were enriched in biological processes that are closely related to PBM functions, suggesting that alteration in DNA methylation is likely to be an important mechanism contributing to the interindividual variation in PBM function, and PBM-related phenotypic and disease-susceptibility variation in humans.
This study represents a comprehensive analysis of the human PBM methylome and its interindividual variation. Our data provide a valuable resource for future epigenomic and multiomic studies, exploring biological and disease-related regulatory mechanisms in PBMs.
DNA methylation; interindividual variation; peripheral blood monocyte
Genetic polymorphisms can shape the global landscape of DNA methylation, by either changing substrates for DNA methyltransferases or altering the DNA binding affinity of cis-regulatory proteins. The interactions between CpG methylation and genetic polymorphisms have been previously investigated by methylation quantitative trait loci (mQTL) and allele-specific methylation (ASM) analysis. However, it remains unclear whether these approaches can effectively and comprehensively identify all genetic variants that contribute to the inter-individual variation of DNA methylation levels. Here we used three independent approaches to systematically investigate the influence of genetic polymorphisms on variability in DNA methylation by characterizing the methylation state of 96 whole blood samples in 52 parent-child trios from 22 nuclear pedigrees. We performed targeted bisulfite sequencing with padlock probes to quantify the absolute DNA methylation levels at a set of 411,800 CpG sites in the human genome. With mid-parent offspring analysis (MPO), we identified 10,593 CpG sites that exhibited heritable methylation patterns, among which 70.1% were SNPs directly present in methylated CpG dinucleotides. We determined the mQTL analysis identified 49.9% of heritable CpG sites for which regulation occurred in a distal cis-regulatory manner, and that ASM analysis was only able to identify 5%. Finally, we identified hundreds of clusters in the human genome for which the degree of variation of CpG methylation, as opposed to whether or not CpG sites were methylated, was associated with genetic polymorphisms, supporting a recent hypothesis on the genetic influence of phenotypic plasticity. These results show that cis-regulatory SNPs identified by mQTL do not comprise the full extent of heritable CpG methylation, and that ASM appears overall unreliable. Overall, the extent of genome-methylome interactions is well beyond what is detectible with the commonly used mQTL and ASM approaches, and is likely to include effects on plasticity.
Cancer cells undergo massive alterations to their DNA methylation patterns that result in aberrant gene expression and malignant phenotypes. However, the mechanisms that underlie methylome changes are not well understood nor is the genomic distribution of DNA methylation changes well characterized.
Here, we performed methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq) to obtain whole-genome DNA methylation profiles for eight human breast cancer cell (BCC) lines and for normal human mammary epithelial cells (HMEC). The MeDIP-seq analysis generated non-biased DNA methylation maps by covering almost the entire genome with sufficient depth and resolution. The most prominent feature of the BCC lines compared to HMEC was a massively reduced methylation level particularly in CpG-poor regions. While hypomethylation did not appear to be associated with particular genomic features, hypermethylation preferentially occurred at CpG-rich gene-related regions independently of the distance from transcription start sites. We also investigated methylome alterations during epithelial-to-mesenchymal transition (EMT) in MCF7 cells. EMT induction was associated with specific alterations to the methylation patterns of gene-related CpG-rich regions, although overall methylation levels were not significantly altered. Moreover, approximately 40% of the epithelial cell-specific methylation patterns in gene-related regions were altered to those typical of mesenchymal cells, suggesting a cell-type specific regulation of DNA methylation.
This study provides the most comprehensive analysis to date of the methylome of human mammary cell lines and has produced novel insights into the mechanisms of methylome alteration during tumorigenesis and the interdependence between DNA methylome alterations and morphological changes.
DNA methylation is globally reprogrammed during mammalian preimplantation development, which is critical for normal development. Recent reduced representation bisulfite sequencing (RRBS) studies suggest that the methylome dynamics are essentially conserved between human and mouse early embryos. RRBS is known to cover 5–10% of all genomic CpGs, favoring those contained within CpG-rich regions. To obtain an unbiased and more complete representation of the methylome during early human development, we performed whole genome bisulfite sequencing of human gametes and blastocysts that covered>70% of all genomic CpGs. We found that the maternal genome was demethylated to a much lesser extent in human blastocysts than in mouse blastocysts, which could contribute to an increased number of imprinted differentially methylated regions in the human genome. Global demethylation of the paternal genome was confirmed, but SINE-VNTR-Alu elements and some other tandem repeat-containing regions were found to be specifically protected from this global demethylation. Furthermore, centromeric satellite repeats were hypermethylated in human oocytes but not in mouse oocytes, which might be explained by differential expression of de novo DNA methyltransferases. These data highlight both conserved and species-specific regulation of DNA methylation during early mammalian development. Our work provides further information critical for understanding the epigenetic processes underlying differentiation and pluripotency during early human development.
DNA methylation reprogramming after fertilization is critical for normal mammalian development. Early embryos are sensitive to environmental stresses and a number of reports have pointed out the increased risk of DNA methylation errors associated with assisted reproduction technologies. Therefore, it is very important to understand normal DNA methylation patterns during early human development. Recent reduced representation bisulfite sequencing studies reported partial methylomes of human gametes and early embryos. To provide a more comprehensive view of DNA methylation dynamics during early human development, we report on whole genome bisulfite sequencing of human gametes and blastocysts. We show that the paternal genome is globally demethylated in blastocysts whereas the maternal genome is demethylated to a much lesser extent. We also reveal unique regulation of imprinted differentially methylated regions, gene bodies and repeat sequences during early human development. Our high-resolution methylome maps are essential to understand epigenetic reprogramming by human oocytes and will aid in the preimplantation epigenetic diagnosis of human embryos.
Genes subject to genomic imprinting are mono-allelically expressed in a parent-of-origin dependent manner. Each imprinted locus has at least one differentially methylated region (DMR) which has allele specific DNA methylation and contributes to imprinted gene expression. Once DMRs are established, they are potentially able to withstand normal genome reprogramming events that occur during cell differentiation and germ-line DMRs are stably maintained throughout development. These DMRs, in addition to being either maternally or paternally methylated, have differences in whether methylation was acquired in the germ-line or post fertilization and are present in a variety of genomic locations with different Cytosine-phosphate guanine (CpG) densities and CTCF binding capacities. We therefore examined the stability of maintenance of DNA methylation imprints and determined the normal baseline DNA methylation levels in several adult tissues for all imprinted genes. In order to do this, we first developed and validated 50 highly specific, quantitative DNA methylation pyrosequencing assays for the known DMRs associated with human imprinted genes.
Remarkable stability of the DNA methylation imprint was observed in all germ-line DMRs and paternally methylated somatic DMRs (which maintained average methylation levels of between 35% - 65% in all somatic tissues, independent of gene expression). Maternally methylated somatic DMRs were found to have more variation with tissue specific methylation patterns. Most DMRs, however, showed some intra-individual variability for DNA methylation levels in peripheral blood, suggesting that more than one DMR needs to be examined in order to get an overall impression of the epigenetic stability in a tissue. The plasticity of DNA methylation at imprinted genes was examined in a panel of normal and cancer cell lines. All cell lines showed changes in DNA methylation, especially at the paternal germ-line and the somatic DMRs.
Our validated pyrosequencing methylation assays can be widely used as a tool to investigate DNA methylation levels of imprinted genes in clinical samples. This first comprehensive analysis of normal methylation levels in adult somatic tissues at human imprinted regions confirm that, despite intra-individual variability and tissue specific expression, imprinted genes faithfully maintain their DNA methylation in healthy adult tissue. DNA methylation levels of a selection of imprinted genes are, therefore, a valuable indicator for epigenetic stability.
The haploid human genome contains approximately 29 million CpGs that exist in a methylated, hydroxymethylated or unmethylated state, collectively referred to as the DNA methylome. The methylation status of cytosines in CpGs and occasionally in non-CpG cytosines influences protein–DNA interactions, gene expression, and chromatin structure and stability. The degree of DNA methylation at particular loci may be heritable transgenerationally and may be altered by environmental exposures and diet, potentially contributing to the development of human diseases. For the vast majority of normal and disease methylomes however, less than 1% of the CpGs have been assessed, revealing the formative stage of methylation mapping techniques. Thus, there is significant discovery potential in new genome-scale platforms applied to methylome mapping, particularly oligonucleotide arrays and the transformative technology of next-generation sequencing. Here, we outline the currently used methylation detection reagents and their application to microarray and sequencing platforms. A comparison of the emerging methods is presented, highlighting their degrees of technical complexity, methylome coverage and precision in resolving methylation. Because there are hundreds of unique methylomes to map within one individual and interindividual variation is likely to be significant, international coordination is essential to standardize methylome platforms and to create a full repository of methylome maps from tissues and unique cell types.
DNA methylation; MeDIP; methylation-sensitive restriction enzyme; microarray; MRE; next-generation sequencing; reduced representation bisulfite sequencing; RRBS
Across the genome, outside of a small number of known imprinted genes and regions subject to X-inactivation in females, DNA methylation at CpG dinucleotides is often assumed to be complementary across both alleles in a diploid cell. However, recent findings suggest the reality is more complex, with the discovery that allele-specific methylation (ASM) is a common feature across the human genome. A key observation is that the majority of ASM is associated with genetic variation in cis, although a noticeable proportion is also non-cis in nature and mediated, for example, by parental origin. ASM appears to be both quantitative, characterized by subtle skewing of DNA methylation between alleles, and heterogeneous, varying across tissues and between individuals. These findings have important implications for complex disease genetics; while cis-mediated ASM provides a functional consequence for non-coding genetic variation, heterogeneous and quantitative ASM complicates the identification of disease-associated loci. We propose that non-cis ASM could contribute toward the “missing heritability” of complex diseases, rendering certain loci hemizygous and masking the direct association between genotype and phenotype. We suggest that the interpretation of results from genome-wide association studies can be improved by the incorporation of epi-allelic information and that in order to fully understand the extent and consequence of ASM in the human genome, a comprehensive sequencing-based analysis of allelic methylation patterns across tissues and individuals is required.
DNA methylation; allelespecific methylation; allele-specific expression; tissue-specific methylation; epigenetics; imprinting; genome-wide association study (GWAS); genetics; complex disease; missing heritability
With recent development in sequencing technology, a large number of genome-wide DNA methylation studies have generated massive amounts of bisulfite sequencing data. The analysis of DNA methylation patterns helps researchers understand epigenetic regulatory mechanisms. Highly variable methylation patterns reflect stochastic fluctuations in DNA methylation, whereas well-structured methylation patterns imply deterministic methylation events. Among these methylation patterns, bipolar patterns are important as they may originate from allele-specific methylation (ASM) or cell-specific methylation (CSM).
Utilizing nonparametric Bayesian clustering followed by hypothesis testing, we have developed a novel statistical approach to identify bipolar methylated genomic regions in bisulfite sequencing data. Simulation studies demonstrate that the proposed method achieves good performance in terms of specificity and sensitivity. We used the method to analyze data from mouse brain and human blood methylomes. The bipolar methylated segments detected are found highly consistent with the differentially methylated regions identified by using purified cell subsets.
Bipolar DNA methylation often indicates epigenetic heterogeneity caused by ASM or CSM. With allele-specific events filtered out or appropriately taken into account, our proposed approach sheds light on the identification of cell-specific genes/pathways under strong epigenetic control in a heterogeneous cell population.
Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0439-2) contains supplementary material, which is available to authorized users.
DNA methylation; Epigenetics; Nonparametric Bayesian
Epigenetic modifications play important roles in plant and animal development. DNA methylation impacts the transposable element (TE) silencing, gene imprinting and expression regulation.
Through a genome-wide analysis, DNA methylation peaks were characterized and mapped in maize embryo and endosperm genome, respectively. Distinct methylation level was observed across maize embryo and endosperm. The maize embryo genome contained more DNA methylation than endosperm. Totally, 985,478 CG islands (CGIs) were identified and most of them were unmethylated. More CGI shores were methylated than CGIs in maize suggested that DNA methylation level was not positively correlated with CpG density. The promoter sequence and transcriptional termination region (TTR) were more methylated than the gene body (intron and exon) region based on peak number and methylated depth. Result showed that 99% TEs were methylated in maize embryo, but a large portion of them (34.8%) were not methylated in endosperm. Maize embryo and endosperm exhibit distinct pattern/level of methylation. The most differentially methylated region between embryo and endosperm are CGI shores. Our results indicated that DNA methylation is associated with both gene silencing and gene activation in maize. Many genes involved in embryogenesis and seed development were found differentially methylated in embryo and endosperm. We found 41.5% imprinting genes were similarly methylated and 58.5% imprinting genes were differentially methylated between embryo and endosperm. Methylation level was associated with allelic silencing of only a small number of imprinting genes. The expression of maize DEMETER-like (DME-like) gene and MBD101 gene (MBD4 homolog) were higher in endosperm than in embryo. These two genes may be associated with distinct methylation levels across maize embryo and endosperm.
Through MeDIP-seq we systematically analyzed the methylomes of maize embryo and endosperm and results indicated that the global methylation status of embryo was more than that of the endosperm. Differences could be observed at the total number of methylation peaks, DMRs and specific methylated genes which were tightly associated with development of embryo and endosperm. Our results also revealed that many DNA methylation regions didn’t affect transcription of the corresponding genes.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-014-1204-7) contains supplementary material, which is available to authorized users.
DNA methylation; Maize; Embryo; Endosperm; Transposable element; Imprinting gene; MeDIP-seq
Common human diseases are caused by the complex interplay of genetic susceptibility as well as environmental factors. Due to the environment’s influence on the epigenome, and therefore genome function, as well as conversely the genome’s facilitative effect on the epigenome, analysis of this level of regulation may increase our knowledge of disease pathogenesis.
In order to identify human-specific epigenetic influences, we have performed a novel genome-wide DNA methylation analysis comparing human, chimpanzee and rhesus macaque.
We have identified that the immunological Leukotriene B4 receptor (LTB4R, BLT1 receptor) is the most epigenetically divergent human gene in peripheral blood in comparison with other primates. This difference is due to the co-ordinated active state of human-specific hypomethylation in the promoter and human-specific increased gene body methylation. This gene is significant in innate immunity and the LTB4/LTB4R pathway is involved in the pathogenesis of the spectrum of human inflammatory diseases. This finding was confirmed by additional neutrophil-only DNA methylome and lymphoblastoid H3K4me3 chromatin comparative data. Additionally we show through functional analysis that this receptor has increased expression and a higher response to the LTB4 ligand in human versus rhesus macaque peripheral blood mononuclear cells. Genome-wide we also find human species-specific differentially methylated regions (human s-DMRs) are more prevalent in CpG island shores than within the islands themselves, and within the latter are associated with the CTCF motif.
This result further emphasises the exclusive nature of the human immunological system, its divergent adaptation even from very closely related primates, and the power of comparative epigenomics to identify and understand human uniqueness.
Although prostate cancer (PCa) is the second leading cause of cancer death among men worldwide, not all men diagnosed with PCa will die from the disease. A critical challenge, therefore, is to distinguish indolent PCa from more advanced forms to guide appropriate treatment decisions. We used Enhanced Reduced Representation Bisulfite Sequencing, a genome-wide high-coverage single-base resolution DNA methylation method to profile seven localized PCa samples, seven matched benign prostate tissues, and six aggressive castration-resistant prostate cancer (CRPC) samples. We integrated these data with RNA-seq and whole-genome DNA-seq data to comprehensively characterize the PCa methylome, detect changes associated with disease progression, and identify novel candidate prognostic biomarkers. Our analyses revealed the correlation of cytosine guanine dinucleotide island (CGI)-specific hypermethylation with disease severity and association of certain breakpoints (deletion, tandem duplications, and interchromosomal translocations) with DNA methylation. Furthermore, integrative analysis of methylation and single-nucleotide polymorphisms (SNPs) uncovered widespread allele-specific methylation (ASM) for the first time in PCa. We found that most DNA methylation changes occurred in the context of ASM, suggesting that variations in tumor epigenetic landscape of individuals are partly mediated by genetic differences, which may affect PCa disease progression. We further selected a panel of 13 CGIs demonstrating increased DNA methylation with disease progression and validated this panel in an independent cohort of 20 benign prostate tissues, 16 PCa, and 8 aggressive CRPCs. These results warrant clinical evaluation in larger cohorts to help distinguish indolent PCa from advanced disease.
Using genome-wide methylation profiles in honey bee queen and worker brains to understand how contrasting organismal outputs are generated from the same genotype.
In honey bees (Apis mellifera) the behaviorally and reproductively distinct queen and worker female castes derive from the same genome as a result of differential intake of royal jelly and are implemented in concert with DNA methylation. To determine if these very different diet-controlled phenotypes correlate with unique brain methylomes, we conducted a study to determine the methyl cytosine (mC) distribution in the brains of queens and workers at single-base-pair resolution using shotgun bisulfite sequencing technology. The whole-genome sequencing was validated by deep 454 sequencing of selected amplicons representing eight methylated genes. We found that nearly all mCs are located in CpG dinucleotides in the exons of 5,854 genes showing greater sequence conservation than non-methylated genes. Over 550 genes show significant methylation differences between queens and workers, revealing the intricate dynamics of methylation patterns. The distinctiveness of the differentially methylated genes is underscored by their intermediate CpG densities relative to drastically CpG-depleted methylated genes and to CpG-richer non-methylated genes. We find a strong correlation between methylation patterns and splicing sites including those that have the potential to generate alternative exons. We validate our genome-wide analyses by a detailed examination of two transcript variants encoded by one of the differentially methylated genes. The link between methylation and splicing is further supported by the differential methylation of genes belonging to the histone gene family. We propose that modulation of alternative splicing is one mechanism by which DNA methylation could be linked to gene regulation in the honey bee. Our study describes a level of molecular diversity previously unknown in honey bees that might be important for generating phenotypic flexibility not only during development but also in the adult post-mitotic brain.
The queen honey bee and her worker sisters do not seem to have much in common. Workers are active and intelligent, skillfully navigating the outside world in search of food for the colony. They never reproduce; that task is left entirely to the much larger and longer-lived queen, who is permanently ensconced within the colony and uses a powerful chemical influence to exert control. Remarkably, these two female castes are generated from identical genomes. The key to each female's developmental destiny is her diet as a larva: future queens are raised on royal jelly. This specialized diet is thought to affect a particular chemical modification, methylation, of the bee's DNA, causing the same genome to be deployed differently. To document differences in this epigenomic setting and hypothesize about its effects on behavior, we performed high-resolution bisulphite sequencing of whole genomes from the brains of queen and worker honey bees. In contrast to the heavily methylated human genome, we found that only a small and specific fraction of the honey bee genome is methylated. Most methylation occurred within conserved genes that provide critical cellular functions. Over 550 genes showed significant methylation differences between the queen and the worker, which may contribute to the profound divergence in behavior. How DNA methylation works on these genes remains unclear, but it may change their accessibility to the cellular machinery that controls their expression. We found a tantalizing clue to a mechanism in the clustering of methylation within parts of genes where splicing occurs, suggesting that methylation could control which of several versions of a gene is expressed. Our study provides the first documentation of extensive molecular differences that may allow honey bees to generate different phenotypes from the same genome.
Sequencing-based DNA methylation profiling methods are comprehensive and, as accuracy and affordability improve, will increasingly supplant microarrays for genome-scale analyses. Here, four sequencing-based methodologies were applied to biological replicates of human embryonic stem cells to compare their CpG coverage genome-wide and in transposons, resolution, cost, concordance and its relationship with CpG density and genomic context. The two bisulfite methods reached concordance of 82% for CpG methylation levels and 99% for non-CpG cytosine methylation levels. Using binary methylation calls, two enrichment methods were 99% concordant, while regions assessed by all four methods were 97% concordant. To achieve comprehensive methylome coverage while reducing cost, an approach integrating two complementary methods was examined. The integrative methylome profile along with histone methylation, RNA, and SNP profiles derived from the sequence reads allowed genome-wide assessment of allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.
DNA methylation; Sequencing; Bisulfite
There is increasing evidence that interindividual epigenetic variation is an etiological factor in common human diseases. Such epigenetic variation could be genetic or non-genetic in origin, and epigenome-wide association studies (EWASs) are underway for a wide variety of diseases/phenotypes. However, performing an EWAS is associated with a range of issues not typically encountered in genome-wide association studies (GWASs), such as the tissue to be analyzed. In many EWASs, it is not possible to analyze the target tissue in large numbers of live humans, and consequently surrogate tissues are employed, most commonly blood. But there is as yet no evidence demonstrating that blood is more informative than buccal cells, the other easily accessible tissue. To assess the potential of buccal cells for use in EWASs, we performed a comprehensive analysis of a buccal cell methylome using whole-genome bisulfite sequencing. Strikingly, a buccal vs. blood comparison reveals > 6X as many hypomethylated regions in buccal. These tissue-specific differentially methylated regions (tDMRs) are strongly enriched for DNaseI hotspots. Almost 75% of these tDMRs are not captured by commonly used DNA methylome profiling platforms such as Reduced Representational Bisulfite Sequencing and the Illumina Infinium HumanMethylation450 BeadChip, and they also display distinct genomic properties. Buccal hypo-tDMRs show a statistically significant enrichment near SNPs associated to disease identified through GWASs. Finally, we find that, compared with blood, buccal hypo-tDMRs show significantly greater overlap with hypomethylated regions in other tissues. We propose that for non-blood based diseases/phenotypes, buccal will be a more informative tissue for EWASs.
BS-seq; buccal; complex disease; epigenome wide association study; human
Epigenetics can be loosely defined as the study of cellular “traits” that influence biological phenotype in a fashion that is not dependent on the underlying primary DNA sequence. One setting in which epigenetics is likely to have a profound influence on biological phenotype is during intrauterine development. In this context there is a defined and critical window during which balanced homeostasis is essential for normal fetal growth and development. We have carried out a detailed structural and functional analysis of the placental epigenome at its maternal interface. Specifically, we performed genome wide analysis of DNA methylation in samples of chorionic villus (CVS) and maternal blood cells (MBC) using both commercially available and custom designed microarrays. We then compared these data with genome wide transcription data for the same tissues. In addition to the discovery that CVS genomes are significantly more hypomethylated than their MBC counterparts, we identified numerous tissue-specific differentially methylated regions (T-DMRs). We further discovered that these T-DMRs are clustered spatially along the genome and are enriched for genes with tissue-specific biological functions. We identified unique patterns of DNA methylation associated with distinct genomic structures such as gene bodies, promoters and CpG islands and identified both direct and inverse relationships between DNA methylation levels and gene expression levels in gene bodies and promoters respectively. Furthermore, we found that these relationships were significantly associated with CpG content. We conclude that the early gestational placental DNA methylome is highly organized and is significantly and globally associated with transcription. These data provide a unique insight into the structural and regulatory characteristics of the placental epigenome at its maternal interface and will drive future analyses of the role of placental dysfunction in gestational disease.
DNA methylation undergoes dynamic changes during mouse development and plays crucial roles in embryogenesis, cell-lineage determination and genomic imprinting. Bisulfite sequencing enables profiling of mouse developmental methylomes on an unprecedented scale; however, integrating and mining these data are challenges for experimental biologists. Therefore, we developed DevMouse, which focuses on the efficient storage of DNA methylomes in temporal order and quantitative analysis of methylation dynamics during mouse development. The latest release of DevMouse incorporates 32 normalized and temporally ordered methylomes across 15 developmental stages and related genome information. A flexible query engine is developed for acquisition of methylation profiles for genes, microRNAs, long non-coding RNAs and genomic intervals of interest across selected developmental stages. To facilitate in-depth mining of these profiles, DevMouse offers online analysis tools for the quantification of methylation variation, identification of differentially methylated genes, hierarchical clustering, gene function annotation and enrichment. Moreover, a configurable MethyBrowser is provided to view the base-resolution methylomes under a genomic context. In brief, DevMouse hosts comprehensive mouse developmental methylome data and provides online tools to explore the relationships of DNA methylation and development.
Database URL: http://www.devmouse.org/
Genomic DNA methylation profiles exhibit substantial variation within the human population, with important functional implications for gene regulation. So far little is known about the characteristics and determinants of DNA methylation variation among healthy individuals. We performed bioinformatic analysis of high-resolution methylation profiles from multiple individuals, uncovering complex patterns of inter-individual variation that are strongly correlated with the local DNA sequence. CpG-rich regions exhibit low and relatively similar levels of DNA methylation in all individuals, but the sequential order of the (few) methylated among the (many) unmethylated CpGs differs randomly across individuals. In contrast, CpG-poor regions exhibit substantially elevated levels of inter-individual variation, but also significant conservation of specific DNA methylation patterns between unrelated individuals. This observation has important implications for experimental analysis of DNA methylation, e.g. in the context of epigenome projects. First, DNA methylation mapping at single-CpG resolution is expected to uncover informative DNA methylation patterns for the CpG-poor bulk of the human genome. Second, for CpG-rich regions it will be sufficient to measure average methylation levels rather than assaying every single CpG. We substantiate these conclusions by an in silico benchmarking study of six widely used methods for DNA methylation mapping. Based on our findings, we propose a cost-optimized two-track strategy for mammalian methylome projects.
Human papillomavirus-positive (HPV+) head and neck squamous cell carcinoma (HNSCC) represents a distinct clinical and epidemiological condition compared with HPV-negative (HPV-) HNSCC. To test the possible involvement of epigenetic modulation by HPV in HNSCC, we conducted a genome-wide DNA-methylation analysis.
Using laser-capture microdissection of 42 formalin-fixed paraffin wax-embedded (FFPE) HNSCCs, we generated DNA-methylation profiles of 18 HPV+ and 14 HPV- samples, using Infinium 450 k BeadArray technology. Methylation data were validated in two sets of independent HPV+/HPV- HNSCC samples (fresh-frozen samples and cell lines) using two independent methods (Infinium 450 k and whole-genome methylated DNA immunoprecipitation sequencing (MeDIP-seq)). For the functional analysis, an HPV- HNSCC cell line was transduced with lentiviral constructs containing the two HPV oncogenes (E6 and E7), and effects on methylation were assayed using the Infinium 450 k technology.
Results and discussion
Unsupervised clustering over the methylation variable positions (MVPs) with greatest variation showed that samples segregated in accordance with HPV status, but also that HPV+ tumors are heterogeneous. MVPs were significantly enriched at transcriptional start sites, leading to the identification of a candidate CpG island methylator phenotype in a sub-group of the HPV+ tumors. Supervised analysis identified a strong preponderance (87%) of MVPs towards hypermethylation in HPV+ HNSCC. Meta-analysis of our HNSCC and publicly available methylation data in cervical and lung cancers confirmed the observed DNA-methylation signature to be HPV-specific and tissue-independent. Grouping of MVPs into functionally more significant differentially methylated regions identified 43 hypermethylated promoter DMRs, including for three cadherins of the Polycomb group target genes. Integration with independent expression data showed strong negative correlation, especially for the cadherin gene-family members. Combinatorial ectopic expression of the two HPV oncogenes (E6 and E7) in an HPV- HNSCC cell line partially phenocopied the hypermethylation signature seen in HPV+ HNSCC tumors, and established E6 as the main viral effector gene.
Our data establish that archival FFPE tissue is very suitable for this type of methylome analysis, and suggest that HPV modulates the HNSCC epigenome through hypermethylation of Polycomb repressive complex 2 target genes such as cadherins, which are implicated in tumor progression and metastasis.
Genomic imprinting is an important epigenetic process involved in regulating placental and foetal growth. Imprinted genes are typically associated with differentially methylated regions (DMRs) whereby one of the two alleles is DNA methylated depending on the parent of origin. Identifying imprinted DMRs in humans is complicated by species- and tissue-specific differences in imprinting status and the presence of multiple regulatory regions associated with a particular gene, only some of which may be imprinted. In this study, we have taken advantage of the unbalanced parental genomic constitutions in triploidies to further characterize human DMRs associated with known imprinted genes and identify novel imprinted DMRs.
By comparing the promoter methylation status of over 14,000 genes in human placentas from ten diandries (extra paternal haploid set) and ten digynies (extra maternal haploid set) and using 6 complete hydatidiform moles (paternal origin) and ten chromosomally normal placentas for comparison, we identified 62 genes with apparently imprinted DMRs (false discovery rate <0.1%). Of these 62 genes, 11 have been reported previously as DMRs that act as imprinting control regions, and the observed parental methylation patterns were concordant with those previously reported. We demonstrated that novel imprinted genes, such as FAM50B, as well as novel imprinted DMRs associated with known imprinted genes (for example, CDKN1C and RASGRF1) can be identified by using this approach. Furthermore, we have demonstrated how comparison of DNA methylation for known imprinted genes (for example, GNAS and CDKN1C) between placentas of different gestations and other somatic tissues (brain, kidney, muscle and blood) provides a detailed analysis of specific CpG sites associated with tissue-specific imprinting and gestational age-specific methylation.
DNA methylation profiling of triploidies in different tissues and developmental ages can be a powerful and effective way to map and characterize imprinted regions in the genome.
DNA methylation is crucial for gene regulation and maintenance of genomic stability. Rat has been a key model system in understanding mammalian systemic physiology, however detailed rat methylome remains uncharacterized till date. Here, we present the first high resolution methylome of rat liver generated using Methylated DNA immunoprecipitation and high throughput sequencing (MeDIP-Seq) approach. We observed that within the DNA/RNA repeat elements, simple repeats harbor the highest degree of methylation. Promoter hypomethylation and exon hypermethylation were common features in both RefSeq genes and expressed genes (as evaluated by proteomic approach). We also found that although CpG islands were generally hypomethylated, about 6% of them were methylated and a large proportion (37%) of methylated islands fell within the exons. Notably, we obeserved significant differences in methylation of terminal exons (UTRs); methylation being more pronounced in coding/partially coding exons compared to the non-coding exons. Further, events like alternate exon splicing (cassette exon) and intron retentions were marked by DNA methylation and these regions are retained in the final transcript. Thus, we suggest that DNA methylation could play a crucial role in marking coding regions thereby regulating alternative splicing. Apart from generating the first high resolution methylome map of rat liver tissue, the present study provides several critical insights into methylome organization and extends our understanding of interplay between epigenome, gene expression and genome stability.
DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.
Motivations: High-throughput sequencing has made it possible to sequence DNA methylation of a whole genome at the single-base resolution. A sample, however, may contain a number of distinct methylation patterns. For instance, cells of different types and in different developmental stages may have different methylation patterns. Alleles may be differentially methylated, which may partially explain that the large portions of epigenomes from single cell types are partially methylated, and may have major effects on transcriptional output. Approaches relying on DNA sequence polymorphism to identify individual patterns from a mixture of heterogeneous epigenomes are insufficient as methylcytosines occur at a much higher density than SNPs.
Results: We have developed a mixture model-based approach for resolving distinct epigenomes from a heterogeneous sample. In particular, the model is applied to the detection of allele-specific methylation (ASM). The methods are tested on a synthetic methylome and applied to an Arabidopsis single root cell methylome.
DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters.
Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework.
CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/.