BackgroundGenetic influence on DNA methylation is potentially an important mechanism affecting individual differences in humans. We use next-generation sequencing to assay blood DNA methylation at approximately 4.5 million loci, each comprising 2.9 CpGs on average, in 697 normal subjects. Methylation measures at each locus are tested for association with approximately 4.5 million single nucleotide polymorphisms (SNPs) to exhaustively screen for methylation quantitative trait loci (meQTLs).ResultsUsing stringent false discovery rate control, 15 % of methylation sites show genetic influence. Most meQTLs are local, where the associated SNP and methylation site are in close genomic proximity. Distant meQTLs and those spanning different chromosomes are less common. Most local meQTLs encompass common SNPs that alter CpG sites (CpG-SNPs). Local meQTLs encompassing CpG-SNPs are enriched in regions of inactive chromatin in blood cells. In contrast, local meQTLs lacking CpG-SNPs are enriched in regions of active chromatin and transcription factor binding sites. Of 393 local meQTLs that overlap disease-associated regions from genome-wide studies, a high percentage encompass common CpG-SNPs. These meQTLs overlap active enhancers, differentiating them from CpG-SNP meQTLs in inactive chromatin.ConclusionsGenetic influence on the human blood methylome is common, involves several heterogeneous processes and is predominantly dependent on local sequence context at the meQTL site. Most meQTLs involve CpG-SNPs, while sequence-dependent effects on chromatin binding are also important in regions of active chromatin. An abundance of local meQTLs resulting from methylation of CpG-SNPs in inactive chromatin suggests that many meQTLs lack functional consequence. Integrating meQTL and Roadmap Epigenomics data could assist fine-mapping efforts.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0842-7) contains supplementary material, which is available to authorized users.

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The central importance of epigenetics to the aging process is increasingly being recognized. Here we perform a methylome-wide association study (MWAS) of aging in whole blood DNA from 718 individuals, aged 25 -92 years (mean 5 55). We sequenced the methyl-CpG-enriched genomic DNA fraction, averaging 67.3 million reads per subject, to obtain methylation measurements for the ∼27 million autosomal CpGs in the human genome. Following extensive quality control, we adaptively combined methylation measures for neighboring, highly-correlated CpGs into 4 344 016 CpG blocks with which we performed association testing. Eleven age-associated differentially methylated regions (DMRs) passed Bonferroni correction (P-value < 1.15 3 10 28 ). Top findings replicated in an independent sample set of 558 subjects using pyrosequencing of bisulfite-converted DNA (min P-value < 10 230 ). To examine biological themes, we selected 70 DMRs with false discovery rate of <0.1. Of these, 42 showed hypomethylation and 28 showed hypermethylation with age. Hypermethylated DMRs were more likely to overlap with CpG islands and shores. Hypomethylated DMRs were more likely to be in regions associated with polycomb/regulatory proteins (e.g. EZH2) or histone modifications H3K27ac, H3K4m1, H3K4m2, H3K4m3 and H3K9ac. Among genes implicated by the top DMRs were protocadherins, homeobox genes, MAPKs and ryanodine receptors. Several of our DMRs are at genes with potential relevance for age-related disease. This study successfully demonstrates the application of next-generation sequencing to MWAS, by interrogating a large proportion of the methylome and returning potentially novel age DMRs, in addition to replicating several loci implicated in previous studies using microarrays.

ISG activation is prominent in asthma, independent of viral transcripts, orthogonal to type 2 inflammation, and associated with distinct clinical features. ER stress is associated with both type 2 inflammation and ISG expression.

Aim We studied the use of methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq) as a cost-effective screening tool for methylome-wide association studies (MWAS). Materials & methods Because MBD-seq has not yet been applied on a large scale, we first developed and tested a pipeline for data processing using 1500 schizophrenia cases and controls plus 75 technical replicates with an average of 68 million reads per sample. This involved the use of technical replicates to optimize quality control for multi- and duplicate-reads, an in silico experiment to identify CpGs in loci with alignment problems, CpG coverage calculations based on multiparametric estimates of the fragment size distribution, a two-stage adaptive algorithm to combine data from correlated adjacent CpG sites, principal component analyses to control for confounders and new software tailored to handle the large data set. Results We replicated MWAS findings in independent samples using a different technology that provided single base resolution. In an MWAS of age-related methylation changes, one of our top findings was a previously reported robust association involving GRIA2. Our results also suggested that owing to the many confounding effects, a considerable challenge in MWAS is to identify those effects that are informative about disease processes. Conclusion This study showed the potential of MBD-seq as a cost-effective tool in large-scale disease studies.