A statistical method for excluding non-variable CpG sites in high-throughput DNA methylation profiling

Background  

High-throughput DNA methylation arrays are likely to accelerate the pace of methylation biomarker discovery for a wide variety of diseases. A potential problem with a standard set of probes measuring the methylation status of CpG sites across the whole genome is that many sites may not show inter-individual methylation variation among the biosamples for the disease outcome being studied. Inclusion of these so-called "non-variable sites" will increase the risk of false discoveries and reduce statistical power to detect biologically relevant methylation markers.     

Methylation levels at selected CpG sites in the factor VIII and FGFR3 genes, in mature female and male germ cells: implications for male-driven evolution.

Transitional mutations at CpG dinucleotides account for approximately a third of all point mutations. These mutations probably arise through spontaneous deamination of 5-methylcytosine. Studies of CpG mutation rates in disease-linked genes, such as factor VIII and FGFR3, have indicated that they more frequently originate in male than in female germ cells. It has been speculated that these sex-biased mutation rates might be a consequence of sex-specific methylation differences between the female and the male germ lines. Using the bisulfite-based genomic-sequencing method, we investigated the methylation status of the human factor VIII and FGFR3 genes in mature male and female germ cells. With the exception of a single CpG, both genes were found to be equally and highly methylated in oocytes and spermatocytes. Whereas these observations strongly support the notion that DNA methylation is the major determining factor for recurrent CpG germ-line mutations in patients with hemophilia and achondroplasia, the higher mutation rate in the male germ line is apparently not a simple reflection of sex-specific methylation differences.     

Non-Steroidal Anti-Inflammatory Drug Use and Genomic DNA Methylation in Blood

Background

Non-steroidal anti-inflammatory drug (NSAID) use is associated with decreased risk of some cancers. NSAID use modulates the epigenetic profile of normal colonic epithelium and may reduce risk of colon cancer through this pathway; however, the effect of NSAID use on the DNA methylation profile of other tissues including whole blood has not yet been examined.

Findings

Using the Sister Study cohort, we examined the association between NSAID usage and whole genome methylation patterns in blood DNA. Blood DNA methylation status across 27,589 CpG sites was evaluated for 871 women using the Illumina Infinium HumanMethylation27 Beadchip, and in a non-overlapping replication sample of 187 women at 485,512 CpG sites using the Infinium HumanMethylation450 Beadchip. We identified a number of CpG sites that were differentially methylated in regular, long-term users of NSAIDs in the discovery group, but none of these sites were statistically significant in our replication group.

Conclusions

We found no replicable methylation differences in blood related to NSAID usage. If NSAID use does effect blood DNA methylation patterns, differences are likely small.     

Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia

Background

Although aberrant DNA methylation has been observed previously in acute lymphoblastic leukemia (ALL), the patterns of differential methylation have not been comprehensively determined in all subtypes of ALL on a genome-wide scale. The relationship between DNA methylation, cytogenetic background, drug resistance and relapse in ALL is poorly understood.

Results

We surveyed the DNA methylation levels of 435,941 CpG sites in samples from 764 children at diagnosis of ALL and from 27 children at relapse. This survey uncovered four characteristic methylation signatures. First, compared with control blood cells, the methylomes of ALL cells shared 9,406 predominantly hypermethylated CpG sites, independent of cytogenetic background. Second, each cytogenetic subtype of ALL displayed a unique set of hyper- and hypomethylated CpG sites. The CpG sites that constituted these two signatures differed in their functional genomic enrichment to regions with marks of active or repressed chromatin. Third, we identified subtype-specific differential methylation in promoter and enhancer regions that were strongly correlated with gene expression. Fourth, a set of 6,612 CpG sites was predominantly hypermethylated in ALL cells at relapse, compared with matched samples at diagnosis. Analysis of relapse-free survival identified CpG sites with subtype-specific differential methylation that divided the patients into different risk groups, depending on their methylation status.

Conclusions

Our results suggest an important biological role for DNA methylation in the differences between ALL subtypes and in their clinical outcome after treatment.     

Meta-analysis of human methylation data for evidence of sex-specific autosomal patterns

Background

Several individual studies have suggested that autosomal CpG methylation differs by sex both in terms of individual CpG sites and global autosomal CpG methylation. However, these findings have been inconsistent and plagued by spurious associations due to the cross reactivity of CpG probes on commercial microarrays. We collectively analysed 76 published studies (n = 6,795) for sex-associated differences in both autosomal and sex chromosome CpG sites.

Results

Overall autosomal methylation profiles varied substantially by study, and we encountered substantial batch effects. We accounted for these by conducting random effects meta-analysis for individual autosomal CpG methylation associations. After excluding non-specific probes, we found 184 autosomal CpG sites differentially methylated by sex after correction for multiple testing. In line with previous studies, average beta differences were small. Many of the most significantly associated CpG probes were new. Of note was differential CpG methylation in the promoters of genes thought to be involved in spermatogenesis and male fertility, such as SLC9A2, SPESP1, CRISP2, and NUPL1. Pathway analysis revealed overrepresentation of genes differentially methylated by sex in several broad Gene Ontology biological processes, including RNA splicing and DNA repair.

Conclusions

This study represents a comprehensive analysis of sex-specific methylation patterns. We demonstrate the existence of sex-specific methylation profiles and report a large number of novel DNA methylation differences in autosomal CpG sites between sexes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-981) contains supplementary material, which is available to authorized users.     

Improved reduced representation bisulfite sequencing for epigenomic profiling of clinical samples

Background

DNA methylation plays crucial roles in epigenetic gene regulation in normal development and disease pathogenesis. Efficient and accurate quantification of DNA methylation at single base resolution can greatly advance the knowledge of disease mechanisms and be used to identify potential biomarkers. We developed an improved pipeline based on reduced representation bisulfite sequencing (RRBS) for cost-effective genome-wide quantification of DNA methylation at single base resolution. A selection of two restriction enzymes (Taq^αI and MspI) enables a more unbiased coverage of genomic regions of different CpG densities. We further developed a highly automated software package to analyze bisulfite sequencing results from the Solexa GAIIx system.

Results

With two sequencing lanes, we were able to quantify ~1.8 million individual CpG sites at a minimum sequencing depth of 10. Overall, about 76.7% of CpG islands, 54.9% of CpG island shores and 52.2% of core promoters in the human genome were covered with at least 3 CpG sites per region.

Conclusions

With this new pipeline, it is now possible to perform whole-genome DNA methylation analysis at single base resolution for a large number of samples for understanding how DNA methylation and its changes are involved in development, differentiation, and disease pathogenesis.     

Evaluation of microarray-based DNA methylation measurement using technical replicates: the Atherosclerosis Risk In Communities (ARIC) Study

Background

DNA methylation is a widely studied epigenetic phenomenon; alterations in methylation patterns influence human phenotypes and risk of disease. As part of the Atherosclerosis Risk in Communities (ARIC) study, the Illumina Infinium HumanMethylation450 (HM450) BeadChip was used to measure DNA methylation in peripheral blood obtained from ~3000 African American study participants. Over 480,000 cytosine-guanine (CpG) dinucleotide sites were surveyed on the HM450 BeadChip. To evaluate the impact of technical variation, 265 technical replicates from 130 participants were included in the study.

Results

For each CpG site, we calculated the intraclass correlation coefficient (ICC) to compare variation of methylation levels within- and between-replicate pairs, ranging between 0 and 1. We modeled the distribution of ICC as a mixture of censored or truncated normal and normal distributions using an EM algorithm. The CpG sites were clustered into low- and high-reliability groups, according to the calculated posterior probabilities. We also demonstrated the performance of this clustering when applied to a study of association between methylation levels and smoking status of individuals. For the CpG sites showing genome-wide significant association with smoking status, most (~96%) were seen from sites in the high reliability cluster.

Conclusions

We suggest that CpG sites with low ICC may be excluded from subsequent association analyses, or extra caution needs to be taken for associations at such sites.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-312) contains supplementary material, which is available to authorized users.     

Incorporating methylation genome information improves prediction accuracy for drug treatment responses

Background

An accumulation of evidence has revealed the important role of epigenetic factors in explaining the etiopathogenesis of human diseases. Several empirical studies have successfully incorporated methylation data into models for disease prediction. However, it is still a challenge to integrate different types of omics data into prediction models, and the contribution of methylation information to prediction remains to be fully clarified.

Results

A stratified drug-response prediction model was built based on an artificial neural network to predict the change in the circulating triglyceride level after fenofibrate intervention. Associated single-nucleotide polymorphisms (SNPs), methylation of selected cytosine-phosphate-guanine (CpG) sites, age, sex, and smoking status, were included as predictors. The model with selected SNPs achieved a mean 5-fold cross-validation prediction error rate of 43.65%. After adding methylation information into the model, the error rate dropped to 41.92%. The combination of significant SNPs, CpG sites, age, sex, and smoking status, achieved the lowest prediction error rate of 41.54%.

Conclusions

Compared to using SNP data only, adding methylation data in prediction models slightly improved the error rate; further prediction error reduction is achieved by a combination of genome, methylation genome, and environmental factors.

     

Strong and weak male mutation bias at different sites in the primate genomes: insights from the human-chimpanzee comparison

Male mutation bias is a higher mutation rate in males than in females thought to result from the greater number of germ line cell divisions in males. If errors in DNA replication cause most mutations, then the magnitude of male mutation bias, measured as the male-to-female mutation rate ratio (alpha), should reflect the relative excess of male versus female germ line cell divisions. Evolutionary rates averaged among all sites in a sequence and compared between mammalian sex chromosomes were shown to be indeed higher in males than in females. However, it is presently unknown whether individual classes of substitutions exhibit such bias. To address this issue, we investigated male mutation bias separately at non-CpG and CpG sites using human-chimpanzee whole-genome alignments. We observed strong male mutation bias at non-CpG sites: alpha in the X-autosome comparison was approximately 6-7, which was similar to the male-to-female ratio in the number of germ line cell divisions. In contrast, mutations at CpG sites exhibited weak male mutation bias: alpha in the X-autosome comparison was only approximately 2-3. This is consistent with the methylation-induced and replication-independent mechanism of CpG transitions, which constitute the majority of mutations at CpG sites. Interestingly, our study also indicated weak male mutation bias for transversions at CpG sites, implying a spontaneous mechanism largely not associated with replication. Male mutation bias was equally strong at CpG and non-CpG sites located within unmethylated "CpG islands," suggesting the replication-dependent origin of these mutations. Thus, we found that the strength of male mutation bias is nonuniform in the primate genomes. Importantly, we discovered that male mutation bias depends on the proportion of CpG sites in the loci compared. This might explain the differences in the magnitude of primate male mutation bias observed among studies.     

Epigenetic reprogramming in the porcine germ line

Background  

Epigenetic reprogramming is critical for genome regulation during germ line development. Genome-wide demethylation in mouse primordial germ cells (PGC) is a unique reprogramming event essential for erasing epigenetic memory and preventing the transmission of epimutations to the next generation. In addition to DNA demethylation, PGC are subject to a major reprogramming of histone marks, and many of these changes are concurrent with a cell cycle arrest in the G2 phase. There is limited information on how well conserved these events are in mammals. Here we report on the dynamic reprogramming of DNA methylation at CpGs of imprinted loci and DNA repeats, and the global changes in H3K27me3 and H3K9me2 in the developing germ line of the domestic pig.     

BISMA - Fast and accurate bisulfite sequencing data analysis of individual clones from unique and repetitive sequences

Background  

Bisulfite sequencing is a popular method to analyze DNA methylation patterns at high resolution. A region of interest is targeted by PCR and about 20-50 subcloned DNA molecules are usually analyzed, to determine the methylation status at single CpG sites and molecule resolution.     

Association of ATRX with pericentric heterochromatin and the Y chromosome of neonatal mouse spermatogonia

Background  

Establishment of chromosomal cytosine methylation and histone methylation patterns are critical epigenetic modifications required for heterochromatin formation in the mammalian genome. However, the nature of the primary signal(s) targeting DNA methylation at specific genomic regions is not clear. Notably, whether histone methylation and/or chromatin remodeling proteins play a role in the establishment of DNA methylation during gametogenesis is not known. The chromosomes of mouse neonatal spermatogonia display a unique pattern of 5-methyl cytosine staining whereby centromeric heterochromatin is hypo-methylated whereas chromatids are strongly methylated. Thus, in order to gain some insight into the relationship between global DNA and histone methylation in the germ line we have used neonatal spermatogonia as a model to determine whether these unique chromosomal DNA methylation patterns are also reflected by concomitant changes in histone methylation.     

Orthology between genomes of Brachypodium, wheat and rice

Background

Differential expression of perforin (PRF1), a gene with a pivotal role in immune surveillance, can be attributed to differential methylation of CpG sites in its promoter region. A reproducible method for quantitative and CpG site-specific determination of perforin methylation is required for molecular epidemiologic studies of chronic diseases with immune dysfunction.

Findings

We developed a pyrosequencing based method to quantify site-specific methylation levels in 32 out of 34 CpG sites in the PRF1 promoter, and also compared methylation pattern in DNAs extracted from whole blood drawn into PAXgene blood DNA tubes (whole blood DNA) or DNA extracted from peripheral blood mononuclear cells (PBMC DNA) from the same normal subjects. Sodium bisulfite treatment of DNA and touchdown PCR were highly reproducible (coefficient of variation 1.63 to 2.18%) to preserve methylation information. Application of optimized pyrosequencing protocol to whole blood DNA revealed that methylation level varied along the promoter in normal subjects with extremely high methylation (mean 86%; range 82–92%) in the distal enhancer region (CpG sites 1–10), a variable methylation (range 49%–83%) in the methylation sensitive region (CpG sites 11–17), and a progressively declining methylation level (range 12%–80%) in the proximal promoter region (CpG sites 18–32) of PRF1. This pattern of methylation remained the same between whole blood and PBMC DNAs, but the absolute values of methylation in 30 out of 32 CpG sites differed significantly, with higher values for all CpG sites in the whole blood DNA.

Conclusion

This reproducible, site-specific and quantitative method for methylation determination of PRF1 based on pyrosequencing without cloning is well suited for large-scale molecular epidemiologic studies of diseases with immune dysfunction. PBMC DNA may be better suited than whole blood DNA for examining methylation levels in genes associated with immune function.     

DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines

Background  

DNA methylation is an essential epigenetic mechanism involved in gene regulation and disease, but little is known about the mechanisms underlying inter-individual variation in methylation profiles. Here we measured methylation levels at 22,290 CpG dinucleotides in lymphoblastoid cell lines from 77 HapMap Yoruba individuals, for which genome-wide gene expression and genotype data were also available.     

BSMAP: whole genome bisulfite sequence MAPping program

Background  

Bisulfite sequencing is a powerful technique to study DNA cytosine methylation. Bisulfite treatment followed by PCR amplification specifically converts unmethylated cytosines to thymine. Coupled with next generation sequencing technology, it is able to detect the methylation status of every cytosine in the genome. However, mapping high-throughput bisulfite reads to the reference genome remains a great challenge due to the increased searching space, reduced complexity of bisulfite sequence, asymmetric cytosine to thymine alignments, and multiple CpG heterogeneous methylation.     

Optical mapping discerns genome wide DNA methylation profiles

Background  

Methylation of CpG dinucleotides is a fundamental mechanism of epigenetic regulation in eukaryotic genomes. Development of methods for rapid genome wide methylation profiling will greatly facilitate both hypothesis and discovery driven research in the field of epigenetics. In this regard, a single molecule approach to methylation profiling offers several unique advantages that include elimination of chemical DNA modification steps and PCR amplification.     

Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing

Background

Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis.

Objective

Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results.

Methods

We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively.

Results

We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites.

Conclusion

The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing.