Investigation of parent-of-origin effects induced by fenofibrate treatment on triglycerides levels

Background

Genome-wide association studies performed on triglycerides (TGs) have not accounted for epigenetic mechanisms that may partially explain trait heritability.

Results

Parent-of-origin (POO) effect association analyses using an agnostic approach or a candidate approach were performed for pretreatment TG levels, posttreatment TG levels, and pre- and posttreatment TG-level differences in the real GAW20 family data set. We detected 22 genetic variants with suggestive POO effects with at least 1 phenotype (P ≤ 10^− 5). We evaluated the association of these 22 significant genetic variants showing POO effects with close DNA methylation probes associated with TGs. A total of 18 DNA methylation probes located in the vicinity of the 22 SNPs were associated with at least 1 phenotype and 6 SNP-probe pairs were associated with DNA methylation probes at the nominal level of P < 0.05, among which 1 pair presented evidence of POO effect. Our analyses identified a paternal effect of SNP rs301621 on the difference between pre- and posttreatment TG levels (P = 1.2 × 10^− 5). This same SNP showed evidence for a maternal effect on methylation levels of a nearby probe (cg10206250; P = 0.01). Using a causal inference test we established that the observed POO effect of rs301621 was not mediated by DNA methylation at cg10206250.

Conclusions

We performed POO effect association analyses of SNPs with TGs, as well as association analyses of SNPs with DNA methylation probes. These analyses, which were followed by a causal inference test, established that the paternal effect at the SNP rs301621 is induced by treatment and is not mediated by methylation level at cg10206250.

     

Use of DNA methylation for cancer detection: promises and challenges

DNA methylation is an important and reversible epigenetic modification, which regulates genomic stability and cellular plasticity. Faithful DNA methylation is essential for mammalian development and health, and perturbation of methylation dynamics contributes to the development of disease, including cancer. The discovery and validation of the biological indicators (biomarkers) for human cancers are essential steps in the development of methods for accurate subtype classification and outcome prediction in clinic oncology. While genetics (SNP, LOH and mutation) and expression profiling (mRNA and protein) of biomarkers have been extensively assessed for cancer diagnosis and prognosis, the potential for using epigenetic fingerprints for early diagnosis and outcome prediction in clinic oncology propels the exploration of using DNA methylation as a biomarker for cancer prognosis. Both the promises and challenges to realizing the clinical utility of the DNA methylation in cancer management are discussed in this review.     

Future impact of integrated high-throughput methylome analyses on human health and disease

A spate of high-powered genome-wide association studies (GWAS) have recently identified numerous single-nucleotide polymor- phisms (SNPs) robustly linked with complex disease. Despite interrogating the majority of common human variation, these SNPs only account for a small proportion of the phenotypic variance, which suggests genetic factors are acting in concert with non-genetic factors. Although environmental measures are logical covariants for genotype-phenotype investigations, another non-genetic intermediary exists: epigenetics. Epigenetics is the analysis of somatically-acquired and, in some cases, transgenerationally inherited epigenetic modifications that regulate gene expression, and offers to bridge the gap between genetics and environment to understand phenotype. The most widely studied epigenetic mark is DNA methylation. Aberrant methylation at gene promoters is strongly implicated in disease etiology, most notably cancer. This review will highlight the importance of DNA methylation as an epigenetic regulator, outline techniques to character- ize the DNA methylome and present the idea of reverse phenotyping, where multiple layers of analysis are integrated at the individual level to create personalized digital phenotypes and, at a phenotype level, to identify novel molecular signatures of disease.     

Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells

Genetic variants have potential influence on DNA methylation and thereby regulate mRNA expression. This study aimed to comprehensively reveal the relationships among SNP, methylation and mRNA, and identify methylation‐mediated regulation patterns in human peripheral blood mononuclear cells (PBMCs). Based on in‐house multi‐omics datasets from 43 Chinese Han female subjects, genome‐wide association trios were constructed by simultaneously testing the following three association pairs: SNP‐methylation, methylation‐mRNA and SNP‐mRNA. Causal inference test (CIT) was used to identify methylation‐mediated genetic effects on mRNA. A total of 64,184 significant cis‐methylation quantitative trait loci (meQTLs) were identified (FDR < 0.05). Among the 745 constructed trios, 464 trios formed SNP‐methylation‐mRNA regulation chains (CIT). Network analysis (Cytoscape 3.3.0) constructed multiple complex regulation networks among SNP, methylation and mRNA (eg a total of 43 SNPs simultaneously connected to cg22517527 and further to PRMT2, DIP2A and YBEY). The regulation chains were supported by the evidence from 4DGenome database, relevant to immune or inflammatory related diseases/traits, and overlapped with previous eQTLs from dbGaP and GTEx. The results provide new insights into the regulation patterns among SNP, DNA methylation and mRNA expression, especially for the methylation‐mediated effects, and also increase our understanding of functional mechanisms underlying the established associations.     

LINE-1 and EPAS1 DNA methylation associations with high-altitude exposure

Recent discoveries indicate a genetic basis for high-altitude adaptation among human groups who have resided at high altitude for millennia, including Andeans, Tibetans, and Ethiopians. Yet, genetics alone does not explain the extent of variation in altitude-adaptive phenotypes. Current and past environments may also play a role, and one way to determine the effect of the environment is through the epigenome. To characterize if Andean adaptive responses to high altitude have an epigenetic component, we analyzed DNA methylation of the promoter region of EPAS1 and LINE-1 repetitive element among 572 Quechua individuals from high- (4,388 m) and low-altitude (0 m) in Peru. Participants recruited at high altitude had lower EPAS1 DNA methylation and higher LINE-1 methylation. Altitude of birth was associated with higher LINE-1 methylation, not with EPAS1 methylation. The number of years lived at high altitude was negatively associated with EPAS1 methylation and positively associated with LINE-1 methylation. We found four one-carbon metabolism SNPs (MTHFD1 rs2236225, TYMS rs502396, FOLH1 rs202676, GLDC rs10975681) that cumulatively explained 11.29% of the variation in average LINE-1 methylation. And identified an association between LINE-1 methylation and genome-wide SNP principal component 1 that distinguishes European from Indigenous American ancestry suggesting that European admixture decreases LINE-1 methylation. Our results indicate that both current and lifetime exposure to high-altitude hypoxia have an effect on EPAS1 and LINE-1 methylation among Andean Quechua, suggesting that epigenetic modifications may play a role in high-altitude adaptation.     

SNP mining porcine ESTs with MAVIANT, a novel tool for SNP evaluation and annotation

MOTIVATION: Single nucleotide polymorphisms (SNPs) analysis is an important means to study genetic variation. A fast and cost-efficient approach to identify large numbers of novel candidates is the SNP mining of large scale sequencing projects. The increasing availability of sequence trace data in public repositories makes it feasible to evaluate SNP predictions on the DNA chromatogram level. MAVIANT, a platform-independent Multipurpose Alignment VIewing and Annotation Tool, provides DNA chromatogram and alignment views and facilitates evaluation of predictions. In addition, it supports direct manual annotation, which is immediately accessible and can be easily shared with external collaborators. RESULTS: Large-scale SNP mining of polymorphisms bases on porcine EST sequences yielded more than 7900 candidate SNPs in coding regions (cSNPs), which were annotated relative to the human genome. Non-synonymous SNPs were analyzed for their potential effect on the protein structure/function using the PolyPhen and SIFT prediction programs. Predicted SNPs and annotations are stored in a web-based database. Using MAVIANT SNPs can visually be verified based on the DNA sequencing traces. A subset of candidate SNPs was selected for experimental validation by resequencing and genotyping. This study provides a web-based DNA chromatogram and contig browser that facilitates the evaluation and selection of candidate SNPs, which can be applied as genetic markers for genome wide genetic studies. AVAILABILITY: The stand-alone version of MAVIANT program for local use is freely available under GPL license terms at http://snp.agrsci.dk/maviant. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Prenatal famine and genetic variation are independently and additively associated with DNA methylation at regulatory loci within IGF2/H19

Both the early environment and genetic variation may affect DNA methylation, which is one of the major molecular marks of the epigenome. The combined effect of these factors on a well-defined locus has not been studied to date. We evaluated the association of periconceptional exposure to the Dutch Famine of 1944-45, as an example of an early environmental exposure, and single nucleotide polymorphisms covering the genetic variation (tagging SNPs) with DNA methylation at the imprinted IGF2/H19 region, a model for an epigenetically regulated genomic region. DNA methylation was measured at five differentially methylated regions (DMRs) that regulate the imprinted status of the IGF2/H19 region. Small but consistent differences in DNA methylation were observed comparing 60 individuals with periconceptional famine exposure with unexposed same-sex siblings at all IGF2 DMRs (P(BH)<0.05 after adjustment for multiple testing), but not at the H19 DMR. IGF2 DMR0 methylation was associated with IGF2 SNP rs2239681 (P(BH) = 0.027) and INS promoter methylation with INS SNPs, including rs689, which tags the INS VNTR, suggesting a mechanism for the reported effect of the VNTR on INS expression (P(BH) = 3.4 × 10(-3)). Prenatal famine and genetic variation showed similar associations with IGF2/H19 methylation and their contributions were additive. They were small in absolute terms (<3%), but on average 0.5 standard deviations relative to the variation in the population. Our analyses suggest that environmental and genetic factors could have independent and additive similarly sized effects on DNA methylation at the same regulatory site.     

Multi-Platform Whole-Genome Microarray Analyses Refine the Epigenetic Signature of Breast Cancer Metastasis with Gene Expression and Copy Number

Background

We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy) are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis.

Methodology/Principal Findings

We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model) using Affymetrix gene expression (U133), promoter (1.0R), and SNP/CNV (SNP 6.0) microarray platforms to correlate data from gene expression, epigenetic (DNA methylation), and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo) methylation with the loss (or gain) of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis.

Conclusions/Significance

Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.     

Hi-Meth：特定位点DNA甲基化高通量检测平台

胞嘧啶甲基化是DNA表观遗传修饰的主要类型之一,在维持正常细胞功能和调控基因表达中具有重要作用。重亚硫酸盐测序法(bisulfite sequencing PCR,BSP)是特异性位点DNA甲基化检测的通用方法,能明确目的片段中每一个CpG位点的甲基化状态,但此方法需要大量的单克隆测序,操作过程较繁琐、成本昂贵。因此,开发准确、高效、便捷的DNA甲基化检测技术对提升表观遗传研究效率具有重要意义。基于本课题组开发的高通量突变类型检测平台Hi-TOM (high-throughput tracking of mutations),我们进一步建立了特定位点DNA甲基化高通量检测平台Hi-Meth (high-throughput detection of DNA methylation)。DNA样品通过重亚硫酸盐处理之后,仅需一轮PCR扩增即可通过Hi-Meth平台获得特定位点DNA甲基化分析结果。利用Hi-Meth平台,对水稻不同基因启动子区域进行了DNA甲基化检测分析,并与基于BSP方法获得的结果进行了比较。结果表明,Hi-Meth策略与BSP策略检测结果基本一致。而且通过Hi-Meth平台可以更准确、便捷地获得特异性位点DNA甲基化分析结果。综上所述,Hi-Meth为特定DNA区域提供了重要的甲基化检测平台,对表观遗传研究具有重要意义。     

Epigenetic gene regulation by plant Jumonji group of histone demethylase

Histone methylation plays an important role in epigenetic regulation of gene expression. Reversible methylation/demethylation of several histone lysine residues is mediated by distinct histone methyltransferases and histone demethylases. Jumonji proteins have been characterized to be involved in histone demethylation. Plant Jumonji homologues are found to have important functions in epigenetic processes, gene expression and plant development and to play an essential role in interplay between histone modifications and DNA methylation. This article is part of a Special Issue entitled: Epigenetic Control of cellular and developmental processes in plants.     

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.

     

Genetic variation in DNMT3B and increased global DNA methylation is associated with suicide attempts in psychiatric patients

Recently, a significant epigenetic component in the pathology of suicide has been realized. Here we investigate candidate functional SNPs in epigenetic‐regulatory genes, DNMT1 and DNMT3B, for association with suicide attempt (SA) among patients with co‐existing psychiatric illness. In addition, global DNA methylation levels [5‐methyl cytosine (5‐mC%)] between SA and psychiatric controls were quantified using the Methylflash Methylated DNA Quantification Kit. DNA was obtained from blood of 79 suicide attempters and 80 non‐attempters, assessed for DSM‐IV Axis I disorders. Functional SNPs were selected for each gene (DNMT1; n = 7, DNMT3B; n = 10), and genotyped. A SNP (rs2424932) residing in the 3′ UTR of the DNMT3B gene was associated with SA compared with a non‐attempter control group (P = 0.001; Chi‐squared test, Bonferroni adjusted P value = 0.02). Moreover, haplotype analysis identified a DNMT3B haplotype which differed between cases and controls, however this association did not hold after Bonferroni correction (P = 0.01, Bonferroni adjusted P value = 0.56). Global methylation analysis showed that psychiatric patients with a history of SA had significantly higher levels of global DNA methylation compared with controls (P = 0.018, Student's t‐test). In conclusion, this is the first report investigating polymorphisms in DNMT genes and global DNA methylation quantification in SA risk. Preliminary findings suggest that allelic variability in DNMT3B may be relevant to the underlying diathesis for suicidal acts and our findings support the hypothesis that aberrant DNA methylation profiles may contribute to the biology of suicidal acts. Thus, analysis of global DNA hypermethylation in blood may represent a biomarker for increased SA risk in psychiatric patients.     

癌症相关的DNA甲基化连锁区域

DNA甲基化是重要的表观遗传标记之一,在转录调控中起直接作用。DNA甲基化的异常与癌症的发生发展密切相关。高通量测序使得在单碱基分辨率下检测全基因组的DNA甲基化水平成为可能。本文基于临近CpGs位点甲基化水平的相关性挖掘DNA甲基化连锁区域。结果发现DNA甲基化连锁区域的甲基化水平和模式在癌症中存在异常,而且显著富集到分化/发育相关的生物学功能。DNA甲基化连锁区域的挖掘有助于对具有生物学功能的表观遗传标记的进一步理解,有助于对癌症诊断的表观遗传标记的挖掘。     

HeteroMeth: A Database of Cell-to-cell Heterogeneity in DNA Methylation

DNA methylation is an important epigenetic mark that plays a vital role in gene expression and cell differentiation. The average DNA methylation level among a group of cells has been extensively documented. However, the cell-to-cell heterogeneity in DNA methylation, which reflects the differentiation of epigenetic status among cells, remains less investigated. Here we established a gold standard of the cell-to-cell heterogeneity in DNA methylation based on single-cell bisulfite sequencing (BS-seq) data. With that, we optimized a computational pipeline for estimating the heterogeneity in DNA methylation from bulk BS-seq data. We further built HeteroMeth, a database for searching, browsing, visualizing, and downloading the data for heterogeneity in DNA methylation for a total of 141 samples in humans, mice, Arabidopsis, and rice. Three genes are used as examples to illustrate the power of HeteroMeth in the identification of unique features in DNA methylation. The optimization of the computational strategy and the construction of the database in this study complement the recent experimental attempts on single-cell DNA methylomes and will facilitate the understanding of epigenetic mechanisms underlying cell differentiation and embryonic development. HeteroMeth is publicly available at http://qianlab.genetics.ac.cn/HeteroMeth.     

PGC7/Stella protects against DNA demethylation in early embryogenesis

DNA methylation is an important means of epigenetic gene regulation and must be carefully controlled as a prerequisite for normal early embryogenesis. Although global demethylation occurs soon after fertilization, it is not evenly distributed throughout the genome. Genomic imprinting and epigenetic asymmetry between parental genomes, that is, delayed demethylation of the maternal genome after fertilization, are clear examples of the functional importance of DNA methylation. Here, we show that PGC7/Stella, a maternal factor essential for early development, protects the DNA methylation state of several imprinted loci and epigenetic asymmetry. After determining that PGC7/Stella binds to Ran binding protein 5 (RanBP5; a nuclear transport shuttle protein), mutant versions of the two proteins were used to examine exactly when and where PGC7/Stella functions within the cell. It is likely that PGC7/Stella protects the maternal genome from demethylation only after localizing to the nucleus, where it maintains the methylation of several imprinted genes. These results demonstrate that PGC7/Stella is indispensable for the maintenance of methylation involved in epigenetic reprogramming after fertilization.     

植物表观遗传与DNA甲基化

表观遗传在植物生长发育过程中起着极其重要的作用。甲基化是基因组DNA的一种主要表观遗传修饰形式,是调节基因功能的重要手段。介绍了植物体中胞嘧啶甲基化现象,RNA指导的DNA甲基化的信号分子、作用机制,以及与RNA介导的基因沉默机制之间的区别和RNA对转座子的表观控制。