De novo quantitative bisulfite sequencing using the pyrosequencing technology

Current protocols for DNA methylation analysis are either labor intensive or limited to the measurement of only one or two CpG positions. Pyrosequencing is a real-time sequencing technology that can overcome these limitations and be used as an epigenotype-mapping tool. Initial experiments demonstrated reliable quantification of the degree of DNA methylation when 2-6 CpGs were analyzed. We sought to improve the sequencing protocol so as to analyze as many CpGs as possible in a single sequencing run. By using an improved enzyme mix and adding single-stranded DNA-binding protein to the reaction, we obtained reproducible results for as many as 10 successive CpGs in a single sequencing reaction spanning up to 75 nucleotides. A minimum amount of 10 ng of bisulfite-treated DNA is necessary to obtain good reproducibility and avoid preferential amplification. We applied the assay to the analysis of DNA methylation patterns in four CpG islands in the vicinity of IGF2 and H19 genes. This allowed accurate and quantitative de novo sequencing of the methylation state of each CpG, showing reproducible variations of methylation state in contiguous CpGs, and proved to be a useful adjunct to current technologies.     

Corruption of the Intra-Gene DNA Methylation Architecture Is a Hallmark of Cancer

Epigenetic processes - including DNA methylation - are increasingly seen as having a fundamental role in chronic diseases like cancer. It is well known that methylation levels at particular genes or loci differ between normal and diseased tissue. Here we investigate whether the intra-gene methylation architecture is corrupted in cancer and whether the variability of levels of methylation of individual CpGs within a defined gene is able to discriminate cancerous from normal tissue, and is associated with heterogeneous tumour phenotype, as defined by gene expression. We analysed 270985 CpGs annotated to 18272 genes, in 3284 cancerous and 681 normal samples, corresponding to 14 different cancer types. In doing so, we found novel differences in intra-gene methylation pattern across phenotypes, particularly in those genes which are crucial for stem cell biology; our measures of intra-gene methylation architecture are a better determinant of phenotype than measures based on mean methylation level alone (K-S test in all 14 diseases tested). These per-gene methylation measures also represent a considerable reduction in complexity, compared to conventional per-CpG beta-values. Our findings strongly support the view that intra-gene methylation architecture has great clinical potential for the development of DNA-based cancer biomarkers.     

DNA Methylation: Bisulphite Modification and Analysis

Epigenetics describes the heritable changes in gene function that occur independently to the DNA sequence. The molecular basis of epigenetic gene regulation is complex, but essentially involves modifications to the DNA itself or the proteins with which DNA associates. The predominant epigenetic modification of DNA in mammalian genomes is methylation of cytosine nucleotides (5-MeC). DNA methylation provides instruction to gene expression machinery as to where and when the gene should be expressed. The primary target sequence for DNA methylation in mammals is 5''-CpG-3'' dinucleotides (Figure 1). CpG dinucleotides are not uniformly distributed throughout the genome, but are concentrated in regions of repetitive genomic sequences and CpG "islands" commonly associated with gene promoters (Figure 1). DNA methylation patterns are established early in development, modulated during tissue specific differentiation and disrupted in many disease states including cancer. To understand the biological role of DNA methylation and its role in human disease, precise, efficient and reproducible methods are required to detect and quantify individual 5-MeCs.This protocol for bisulphite conversion is the "gold standard" for DNA methylation analysis and facilitates identification and quantification of DNA methylation at single nucleotide resolution. The chemistry of cytosine deamination by sodium bisulphite involves three steps (Figure 2). (1) Sulphonation: The addition of bisulphite to the 5-6 double bond of cytosine (2) Hydrolic Deamination: hydrolytic deamination of the resulting cytosine-bisulphite derivative to give a uracil-bisulphite derivative (3) Alkali Desulphonation: Removal of the sulphonate group by an alkali treatment, to give uracil. Bisulphite preferentially deaminates cytosine to uracil in single stranded DNA, whereas 5-MeC, is refractory to bisulphite-mediated deamination. Upon PCR amplification, uracil is amplified as thymine while 5-MeC residues remain as cytosines, allowing methylated CpGs to be distinguished from unmethylated CpGs by presence of a cytosine "C" versus thymine "T" residue during sequencing.DNA modification by bisulphite conversion is a well-established protocol that can be exploited for many methods of DNA methylation analysis. Since the detection of 5-MeC by bisulphite conversion was first demonstrated by Frommer et al.¹ and Clark et al.², methods based around bisulphite conversion of genomic DNA account for the majority of new data on DNA methylation. Different methods of post PCR analysis may be utilized, depending on the degree of specificity and resolution of methylation required. Cloning and sequencing is still the most readily available method that can give single nucleotide resolution for methylation across the DNA molecule.     

GeMes,Clusters of DNA Methylation under Genetic Control,Can Inform Genetic and Epigenetic Analysis of Disease

Epigenetic marks such as DNA methylation have generated great interest in the study of human disease. However, studies of DNA methylation have not established population-epigenetics principles to guide design, efficient statistics, or interpretation. Here, we show that the clustering of correlated DNA methylation at CpGs was similar to that of linkage-disequilibrium (LD) correlation in genetic SNP variation but for much shorter distances. Some clustering of methylated CpGs appeared to be genetically driven. Further, a set of correlated methylated CpGs related to a single SNP-based LD block was not always physically contiguous—segments of uncorrelated methylation as long as 300 kb could be interspersed in the cluster. Thus, we denoted these sets of correlated CpGs as GeMes, defined as potentially noncontiguous methylation clusters under the control of one or more methylation quantitative trait loci. This type of correlated methylation structure has implications for both biological functions of DNA methylation and for the design, analysis, and interpretation of epigenome-wide association studies.     

The dynamics and prognostic potential of DNA methylation changes at stem cell gene loci in women's cancer

Aberrant DNA methylation is an important cancer hallmark, yet the dynamics of DNA methylation changes in human carcinogenesis remain largely unexplored. Moreover, the role of DNA methylation for prediction of clinical outcome is still uncertain and confined to specific cancers. Here we perform the most comprehensive study of DNA methylation changes throughout human carcinogenesis, analysing 27,578 CpGs in each of 1,475 samples, ranging from normal cells in advance of non-invasive neoplastic transformation to non-invasive and invasive cancers and metastatic tissue. We demonstrate that hypermethylation at stem cell PolyComb Group Target genes (PCGTs) occurs in cytologically normal cells three years in advance of the first morphological neoplastic changes, while hypomethylation occurs preferentially at CpGs which are heavily Methylated in Embryonic Stem Cells (MESCs) and increases significantly with cancer invasion in both the epithelial and stromal tumour compartments. In contrast to PCGT hypermethylation, MESC hypomethylation progresses significantly from primary to metastatic cancer and defines a poor prognostic signature in four different gynaecological cancers. Finally, we associate expression of TET enzymes, which are involved in active DNA demethylation, to MESC hypomethylation in cancer. These findings have major implications for cancer and embryonic stem cell biology and establish the importance of systemic DNA hypomethylation for predicting prognosis in a wide range of different cancers.     

Different measures of “genome-wide” DNA methylation exhibit unique properties in placental and somatic tissues

DNA methylation of CpGs located in two types of repetitive elements—LINE1 (L1) and Alu—is used to assess “global” changes in DNA methylation in studies of human disease and environmental exposure. L1 and Alu contribute close to 30% of all base pairs in the human genome and transposition of repetitive elements is repressed through DNA methylation. Few studies have investigated whether repetitive element DNA methylation is associated with DNA methylation at other genomic regions, or the biological and technical factors that influence potential associations. Here, we assess L1 and Alu DNA methylation by Pyrosequencing of consensus sequences and using subsets of probes included in the Illumina Infinium HumanMethylation27 BeadChip array. We show that evolutionary age and assay method affect the assessment of repetitive element DNA methylation. Additionally, we compare Pyrosequencing results for repetitive elements to average DNA methylation of CpG islands, as assessed by array probes classified into strong, weak and non-islands. We demonstrate that each of these dispersed sequences exhibits different patterns of tissue-specific DNA methylation. Correlation of DNA methylation suggests an association between L1 and weak CpG island DNA methylation in some of the tissues examined. We caution, however, that L1, Alu and CpG island DNA methylation are distinct measures of dispersed DNA methylation and one should not be used in lieu of another. Analysis of DNA methylation data is complex and assays may be influenced by environment and pathology in different or complementary ways.     

Different measures of “genome-wide” DNA methylation exhibit unique properties in placental and somatic tissues

DNA methylation of CpGs located in two types of repetitive elements—LINE1 (L1) and Alu—is used to assess “global” changes in DNA methylation in studies of human disease and environmental exposure. L1 and Alu contribute close to 30% of all base pairs in the human genome and transposition of repetitive elements is repressed through DNA methylation. Few studies have investigated whether repetitive element DNA methylation is associated with DNA methylation at other genomic regions, or the biological and technical factors that influence potential associations. Here, we assess L1 and Alu DNA methylation by Pyrosequencing of consensus sequences and using subsets of probes included in the Illumina Infinium HumanMethylation27 BeadChip array. We show that evolutionary age and assay method affect the assessment of repetitive element DNA methylation. Additionally, we compare Pyrosequencing results for repetitive elements to average DNA methylation of CpG islands, as assessed by array probes classified into strong, weak and non-islands. We demonstrate that each of these dispersed sequences exhibits different patterns of tissue-specific DNA methylation. Correlation of DNA methylation suggests an association between L1 and weak CpG island DNA methylation in some of the tissues examined. We caution, however, that L1, Alu and CpG island DNA methylation are distinct measures of dispersed DNA methylation and one should not be used in lieu of another. Analysis of DNA methylation data is complex and assays may be influenced by environment and pathology in different or complementary ways.     

Genome-Wide DNA Methylation Analysis of Systemic Lupus Erythematosus Reveals Persistent Hypomethylation of Interferon Genes and Compositional Changes to CD4+ T-cell Populations

Systemic lupus erythematosus (SLE) is an autoimmune disease with known genetic, epigenetic, and environmental risk factors. To assess the role of DNA methylation in SLE, we collected CD4+ T-cells, CD19+ B-cells, and CD14+ monocytes from 49 SLE patients and 58 controls, and performed genome-wide DNA methylation analysis with Illumina Methylation450 microarrays. We identified 166 CpGs in B-cells, 97 CpGs in monocytes, and 1,033 CpGs in T-cells with highly significant changes in DNA methylation levels (p<1×10⁻⁸) among SLE patients. Common to all three cell-types were widespread and severe hypomethylation events near genes involved in interferon signaling (type I). These interferon-related changes were apparent in patients collected during active and quiescent stages of the disease, suggesting that epigenetically-mediated hypersensitivity to interferon persists beyond acute stages of the disease and is independent of circulating interferon levels. This interferon hypersensitivity was apparent in memory, naïve and regulatory T-cells, suggesting that this epigenetic state in lupus patients is established in progenitor cell populations. We also identified a widespread, but lower amplitude shift in methylation in CD4+ T-cells (>16,000 CpGs at FDR<1%) near genes involved in cell division and MAPK signaling. These cell type-specific effects are consistent with disease-specific changes in the composition of the CD4+ population and suggest that shifts in the proportion of CD4+ subtypes can be monitored at CpGs with subtype-specific DNA methylation patterns.     

Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B-lymphocyte populations

Changes to the DNA methylome have been described in patients with rheumatoid arthritis (RA). In previous work, we reported genome-wide methylation differences in T-lymphocyte and B-lymphocyte populations from healthy individuals. Now, using HumanMethylation450 BeadChips to interrogate genome-wide DNA methylation, we have determined disease-associated methylation changes in blood-derived T- and B-lymphocyte populations from 12 female patients with seropositive established RA, relative to 12 matched healthy individuals. Array data were analyzed using NIMBL software and bisulfite pyrosequencing was used to validate array candidates. Genome-wide DNA methylation, determined by analysis of LINE-1 sequences, revealed higher methylation in B-lymphocytes compared with T-lymphocytes (P ≤ 0.01), which is consistent with our findings in healthy individuals. Moreover, loci-specific methylation differences that distinguished T-lymphocytes from B-lymphocytes in healthy individuals were also apparent in RA patients. However, disease-associated methylation differences were also identified in RA. In these cases, we identified 509 and 252 CpGs in RA-derived T- and B-lymphocytes, respectively, that showed significant changes in methylation compared with their cognate healthy counterparts. Moreover, this included a restricted set of 32 CpGs in T-lymphocytes and 20 CpGs in B-lymphocytes (representing 15 and 10 genes, respectively, and including two, MGMT and CCS, that were common to both cell types) that displayed more substantial changes in methylation. These changes, apparent as hyper- or hypo-methylation, were independently confirmed by pyrosequencing analysis. Validation by pyrosequencing also revealed additional sites in some candidate genes that also displayed altered methylation in RA. In this first study of genome-wide DNA methylation in individual T- and B-lymphocyte populations in RA patients, we report disease-associated methylation changes that are distinct to each cell type and which support a role for discrete epigenetic regulation in this disease.     

Semen samples showing an increased rate of spermatozoa with imprinting errors have a negligible effect in the outcome of assisted reproduction techniques

The topic of imprinting defects present in the sperm of infertile patients has been addressed by several reports in the last few years. However, whether methylation abnormalities at one or few CpGs within an imprinted locus are pathological is a matter of debate. Moreover, whether imprinting anomalies in sperm could interfere with fertility treatment outcomes is still unknown. In this report we analyze the sperm DNA methylation profile of H19-ICR, KvDMR, SNRPN-ICR, IG-DMR and MEG3-DMR by pyrosequencing in 107 infertile men series and a control population of 30 proven fertile males. DNA methylation was statistically evaluated from two points of view: first, the methylation of each CpG was analyzed in the control population and the mean, standard deviation and range were determined and compared with infertile population data; second, in order to define altered methylation patterns for each region, a hierarchical cluster analysis was performed by which individuals were grouped in different clusters according to the degree of similarity of their methylation pattern. Two pieces of data supported the results obtained in the multi-variate analysis: the classification of the vast majority of control individuals in clusters with normal methylation patterns and the significant differences in methylation levels found between individuals within the normal and abnormal clusters. Individuals included in normal and abnormal methylation clusters were compared according to seminal parameters as well as to the outcome of assisted reproduction.     

Collaboration between CpG sites is needed for stable somatic inheritance of DNA methylation states

Inheritance of 5-methyl cytosine modification of CpG (CG/CG) DNA sequences is needed to maintain early developmental decisions in vertebrates. The standard inheritance model treats CpGs as independent, with methylated CpGs maintained by efficient methylation of hemimethylated CpGs produced after DNA replication, and unmethylated CpGs maintained by an absence of de novo methylation. By stochastic simulations of CpG islands over multiple cell cycles and systematic sampling of reaction parameters, we show that the standard model is inconsistent with many experimental observations. In contrast, dynamic collaboration between CpGs can provide strong error-tolerant somatic inheritance of both hypermethylated and hypomethylated states of a cluster of CpGs, reproducing observed stable bimodal methylation patterns. Known recruitment of methylating enzymes by methylated CpGs could provide the necessary collaboration, but we predict that recruitment of demethylating enzymes by unmethylated CpGs strengthens inheritance and allows CpG islands to remain hypomethylated within a sea of hypermethylation.     

Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B-lymphocyte populations

Changes to the DNA methylome have been described in patients with rheumatoid arthritis (RA). In previous work, we reported genome-wide methylation differences in T-lymphocyte and B-lymphocyte populations from healthy individuals. Now, using HumanMethylation450 BeadChips to interrogate genome-wide DNA methylation, we have determined disease-associated methylation changes in blood-derived T- and B-lymphocyte populations from 12 female patients with seropositive established RA, relative to 12 matched healthy individuals. Array data were analyzed using NIMBL software and bisulfite pyrosequencing was used to validate array candidates. Genome-wide DNA methylation, determined by analysis of LINE-1 sequences, revealed higher methylation in B-lymphocytes compared with T-lymphocytes (P ≤ 0.01), which is consistent with our findings in healthy individuals. Moreover, loci-specific methylation differences that distinguished T-lymphocytes from B-lymphocytes in healthy individuals were also apparent in RA patients. However, disease-associated methylation differences were also identified in RA. In these cases, we identified 509 and 252 CpGs in RA-derived T- and B-lymphocytes, respectively, that showed significant changes in methylation compared with their cognate healthy counterparts. Moreover, this included a restricted set of 32 CpGs in T-lymphocytes and 20 CpGs in B-lymphocytes (representing 15 and 10 genes, respectively, and including two, MGMT and CCS, that were common to both cell types) that displayed more substantial changes in methylation. These changes, apparent as hyper- or hypo-methylation, were independently confirmed by pyrosequencing analysis. Validation by pyrosequencing also revealed additional sites in some candidate genes that also displayed altered methylation in RA. In this first study of genome-wide DNA methylation in individual T- and B-lymphocyte populations in RA patients, we report disease-associated methylation changes that are distinct to each cell type and which support a role for discrete epigenetic regulation in this disease.     

Semen samples showing an increased rate of spermatozoa with imprinting errors have a negligible effect in the outcome of assisted reproduction techniques

The topic of imprinting defects present in the sperm of infertile patients has been addressed by several reports in the last few years. However, whether methylation abnormalities at one or few CpGs within an imprinted locus are pathological is a matter of debate. Moreover, whether imprinting anomalies in sperm could interfere with fertility treatment outcomes is still unknown. In this report we analyze the sperm DNA methylation profile of H19-ICR, KvDMR, SNRPN-ICR, IG-DMR and MEG3-DMR by pyrosequencing in 107 infertile men series and a control population of 30 proven fertile males. DNA methylation was statistically evaluated from two points of view: first, the methylation of each CpG was analyzed in the control population and the mean, standard deviation and range were determined and compared with infertile population data; second, in order to define altered methylation patterns for each region, a hierarchical cluster analysis was performed by which individuals were grouped in different clusters according to the degree of similarity of their methylation pattern. Two pieces of data supported the results obtained in the multi-variate analysis: the classification of the vast majority of control individuals in clusters with normal methylation patterns and the significant differences in methylation levels found between individuals within the normal and abnormal clusters. Individuals included in normal and abnormal methylation clusters were compared according to seminal parameters as well as to the outcome of assisted reproduction.     

Bio-CAP: a versatile and highly sensitive technique to purify and characterise regions of non-methylated DNA

Across vertebrate genomes methylation of cytosine residues within the context of CpG dinucleotides is a pervasive epigenetic mark that can impact gene expression and has been implicated in various developmental and disease-associated processes. Several biochemical approaches exist to profile DNA methylation, but recently an alternative approach based on profiling non-methylated CpGs was developed. This technique, called CxxC affinity purification (CAP), uses a ZF-CxxC (CxxC) domain to specifically capture DNA containing clusters of non-methylated CpGs. Here we describe a new CAP approach, called biotinylated CAP (Bio-CAP), which eliminates the requirement for specialized equipment while dramatically improving and simplifying the CxxC-based DNA affinity purification. Importantly, this approach isolates non-methylated DNA in a manner that is directly proportional to the density of non-methylated CpGs, and discriminates non-methylated CpGs from both methylated and hydroxymethylated CpGs. Unlike conventional CAP, Bio-CAP can be applied to nanogram quantities of genomic DNA and in a magnetic format is amenable to efficient parallel processing of samples. Furthermore, Bio-CAP can be applied to genome-wide profiling of non-methylated DNA with relatively small amounts of input material. Therefore, Bio-CAP is a simple and streamlined approach for characterizing regions of the non-methylated DNA, whether at specific target regions or genome wide.     

Global Analysis of DNA Methylation Variation in Adipose Tissue from Twins Reveals Links to Disease-Associated Variants in Distal Regulatory Elements

Epigenetic modifications such as DNA methylation play a key role in gene regulation and disease susceptibility. However, little is known about the genome-wide frequency, localization, and function of methylation variation and how it is regulated by genetic and environmental factors. We utilized the Multiple Tissue Human Expression Resource (MuTHER) and generated Illumina 450K adipose methylome data from 648 twins. We found that individual CpGs had low variance and that variability was suppressed in promoters. We noted that DNA methylation variation was highly heritable (h²_median = 0.34) and that shared environmental effects correlated with metabolic phenotype-associated CpGs. Analysis of methylation quantitative-trait loci (metQTL) revealed that 28% of CpGs were associated with nearby SNPs, and when overlapping them with adipose expression quantitative-trait loci (eQTL) from the same individuals, we found that 6% of the loci played a role in regulating both gene expression and DNA methylation. These associations were bidirectional, but there were pronounced negative associations for promoter CpGs. Integration of metQTL with adipose reference epigenomes and disease associations revealed significant enrichment of metQTL overlapping metabolic-trait or disease loci in enhancers (the strongest effects were for high-density lipoprotein cholesterol and body mass index [BMI]). We followed up with the BMI SNP rs713586, a cg01884057 metQTL that overlaps an enhancer upstream of ADCY3, and used bisulphite sequencing to refine this region. Our results showed widespread population invariability yet sequence dependence on adipose DNA methylation but that incorporating maps of regulatory elements aid in linking CpG variation to gene regulation and disease risk in a tissue-dependent manner.     

Constitutively methylated CpG dinucleotides as mutation hot spots in the retinoblastoma gene (RB1).

A wide spectrum of mutations, ranging from point mutations to large deletions, have been described in the retinoblastoma gene (RB1). Mutations have been found throughout the gene; however, these genetic alterations do not appear to be homogeneously distributed. In particular, a significant proportion of disease-causing mutations results in the premature termination of protein synthesis, and the majority of these mutations occur as C-->T transitions at CpG dinucleotides (CpGs). Such recurrent CpG mutations, including those found in RB1, are likely the result of the deamination of 5-methylcytosine within these CpGs. In the present study, we used the sodiumbisulfite conversion method to detect cytosine methylation in representative exons of RB1. We analyzed DNA from a variety of tissues and specifically targeted CGA codons in RB1, where recurrent premature termination mutations have been reported. We found that DNA methylation within RB1 exons 8, 14, 25, and 27 appeared to be restricted to CpGs, including six CGA codons. Other codons containing methylated cytosines have not been reported to be mutated. Therefore, disease-causing mutations at CpGs in RB1 appear to be determined by several factors, including the constitutive presence of DNA methylation at cytosines within CpGs, the specific codon within which the methylated cytosine is located, and the particular region of the gene within which that codon resides.