Modeling complex patterns of differential DNA methylation that associate with gene expression changes.
Ontology highlight
ABSTRACT:
SUBMITTER: Schlosberg CE
PROVIDER: S-EPMC5435975 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Methylation of the CpG-rich region (CpG island) overlapping a gene's promoter is a generally accepted mechanism for silencing expression. While recent technological advances have enabled measurement of DNA methylation and expression changes genome-wide, only modest correlations between differential methylation at gene promoters and expression have been found. We hypothesize that stronger associations are not observed because existing analysis methods oversimplify their representation of the data and do not capture the diversity of existing methylation patterns. Recently, other patterns such as CpG island shore methylation and long partially hypomethylated domains have also been linked with gene silencing. Here, we detail a new approach for discovering differential methylation patterns associated with expression change using genome-wide high-resolution methylation data: we represent differential methylation as an interpolated curve, or signature, and then identify groups of genes with similarly shaped signatures and corresponding expression changes. Our technique uncovers a diverse set of patterns that are conserved across embryonic stem cell and cancer data sets. Overall, we find strong associations between these methylation patterns and expression. We further show that an extension of our method also outperforms other approaches by generating a longer list of genes with higher quality associations between differential methylation and expression.
| S-EPMC3737560 | biostudies-literature
Project description:Mitochondrial DNA copy number is strictly regulated during development as naive cells differentiate into mature cells to ensure that specific cell types have sufficient copies of mitochondrial DNA to perform their specialised functions. Mitochondrial DNA haplotypes are defined as specific regions of mitochondrial DNA that cluster with other mitochondrial sequences to show the phylogenetic origins of maternal lineages. Mitochondrial DNA haplotypes are associated with a range of phenotypes and disease. To understand how mitochondrial DNA haplotypes induce these characteristics, we used four embryonic stem cell lines that have the same set of chromosomes but possess different mitochondrial DNA haplotypes. We show that mitochondrial DNA haplotypes influence changes in chromosomal gene expression and affinity for nuclear-encoded mitochondrial DNA replication factors to modulate mitochondrial DNA copy number, two events that act synchronously during differentiation. Global DNA methylation analysis showed that each haplotype induces distinct DNA methylation patterns, which, when modulated by DNA demethylation agents, resulted in skewed gene expression patterns that highlight the effectiveness of the new DNA methylation patterns established by each haplotype. The haplotypes differentially regulate α-ketoglutarate, a metabolite from the TCA cycle that modulates the TET family of proteins, which catalyse the transition from 5-methylcytosine, indicative of DNA methylation, to 5-hydroxymethylcytosine, indicative of DNA demethylation. Our outcomes show that mitochondrial DNA haplotypes differentially modulate chromosomal gene expression patterns of naive and differentiating cells by establishing mitochondrial DNA haplotype-specific DNA methylation patterns.
| S-EPMC5592988 | biostudies-literature
Project description: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.Association analyses of methylation levels with more than three million common single nucleotide polymorphisms (SNPs) identified 180 CpG-sites in 173 genes that were associated with nearby SNPs (putatively in cis, usually within 5 kb) at a false discovery rate of 10%. The most intriguing trans signal was obtained for SNP rs10876043 in the disco-interacting protein 2 homolog B gene (DIP2B, previously postulated to play a role in DNA methylation), that had a genome-wide significant association with the first principal component of patterns of methylation; however, we found only modest signal of trans-acting associations overall. As expected, we found significant negative correlations between promoter methylation and gene expression levels measured by RNA-sequencing across genes. Finally, there was a significant overlap of SNPs that were associated with both methylation and gene expression levels.Our results demonstrate a strong genetic component to inter-individual variation in DNA methylation profiles. Furthermore, there was an enrichment of SNPs that affect both methylation and gene expression, providing evidence for shared mechanisms in a fraction of genes.
| S-EPMC3091299 | biostudies-literature
Project description:Risk for adverse neonatal outcome increases with declining gestational age (GA), and changes in DNA methylation may contribute to the relationship between GA and adverse health outcomes in offspring. To test this hypothesis, we evaluated the association between GA and more than 27,000 CpG sites in neonatal DNA extracted from umbilical cord blood from two prospectively-characterized cohorts: (1) a discovery cohort consisting of 259 neonates from women with a history of neuropsychiatric disorders and (2) a replication cohort consisting of 194 neonates of uncomplicated mothers. GA was determined by obstetrician report and maternal last menstrual period. The associations between proportion of DNA methylated and GA were evaluated by fitting a separate linear mixed effects model for each CpG site, adjusting for relevant covariates including neonatal sex, race, parity, birth weight percentile and chip effects. CpG sites in 39 genes were associated with GA (false discovery rate < 0.05) in the discovery cohort. The same CpG sites in 25 of these genes replicated in the replication cohort, with each association replicating in the same direction. Notably, these CpG sites were located in genes previously implicated in labor and delivery (e.g., AVP, OXT, CRHBP and ESR1) or that may influence the risk for adverse health outcomes later in life (e.g., DUOX2, TMEM176A and CASP8). All associations were independent of method of delivery or induction of labor. These results suggest neonatal DNA methylation varies with GA even in term deliveries. The potential contribution of these changes to clinically significant postnatal outcomes warrants further investigation.
| S-EPMC3256334 | biostudies-literature
Project description:BackgroundAnaplasma phagocytophilum is an obligate intracellular prokaryotic pathogen that both infects and replicates within human neutrophils. The bacterium represses multiple antimicrobial functions while simultaneously increasing proinflammatory functions by reprogramming the neutrophil genome. Previous reports show that many observed phenotypic changes are in part explained by altered gene transcription. We recently identified that large chromosomal regions of the neutrophil genome are differentially expressed during A. phagocytophilum infection. Because of this, we sought to determine whether gene expression programs altered by infection were the result of changes in the host neutrophil DNA methylome.ResultsWithin 24 h of infection, marked increases in DNA methylation were observed genome-wide as compared with mock-infected controls and pharmacologic inhibition of DNA methyltransferases resulted in decreased bacterial growth. New regions of DNA methylation were enriched at intron and exon junctions; however, intragenic methylation did not correlate with altered gene expression. In contrast, intergenic DNA methylation was associated with A. phagocytophilum-induced gene expression changes. Within the major histocompatibility complex locus on chromosome 6, a region with marked changes in infection-induced differential gene expression, new regions of methylation were localized to boundaries of active and inactive chromatin.ConclusionsThese data strongly suggest that A. phagocytophilum infection, in addition to altering histone structure, alters DNA methylation and the epigenome of its host cell to promote survival and replication, providing evidence that such bacterial infection can radically alter the epigenome of its host cell.
| S-EPMC4518890 | biostudies-literature
Project description:Mitochondrial DNA (mtDNA) variants have been traditionally used as markers to trace ancient population migrations. Although experiments relying on model organisms and cytoplasmic hybrids, as well as disease association studies, have served to underline the functionality of certain mtDNA SNPs, only little is known of the regulatory impact of ancient mtDNA variants, especially in terms of gene expression. By analyzing RNA-seq data of 454 lymphoblast cell lines from the 1000 Genomes Project, we found that mtDNA variants defining the most common African genetic background, the L haplogroup, exhibit a distinct overall mtDNA gene expression pattern, which was independent of mtDNA copy numbers. Secondly, intra-population analysis revealed subtle, yet significant, expression differences in four tRNA genes. Strikingly, the more prominent African mtDNA gene expression pattern best correlated with the expression of nuclear DNA-encoded RNA-binding proteins, and with SNPs within the mitochondrial RNA-binding proteins PTCD1 and MRPS7. Our results thus support the concept of an ancient regulatory transition of mtDNA-encoded genes as humans left Africa to populate the rest of the world.
| S-EPMC5094714 | biostudies-literature
Project description:BackgroundDNA methylation is a key epigenetic regulator contributing to cancer development. To understand the role of DNA methylation in tumorigenesis, it is important to investigate and compare differential methylation (DM) patterns between normal and case samples across different cancer types. However, current pan-cancer analyses call DM separately for each cancer, which suffers from lower statistical power and fails to provide a comprehensive view for patterns across cancers.MethodsIn this work, we propose a rigorous statistical model, PanDM, to jointly characterize DM patterns across diverse cancer types. PanDM uses the hidden correlations in the combined dataset to improve statistical power through joint modeling. PanDM takes summary statistics from separate analyses as input and performs methylation site clustering, differential methylation detection, and pan-cancer pattern discovery. We demonstrate the favorable performance of PanDM using simulation data. We apply our model to 12 cancer methylome data collected from The Cancer Genome Atlas (TCGA) project. We further conduct ontology- and pathway-enrichment analyses to gain new biological insights into the pan-cancer DM patterns learned by PanDM.ResultsPanDM outperforms two types of separate analyses in the power of DM calling in the simulation study. Application of PanDM to TCGA data reveals 37 pan-cancer DM patterns in the 12 cancer methylomes, including both common and cancer-type-specific patterns. These 37 patterns are in turn used to group cancer types. Functional ontology and biological pathways enriched in the non-common patterns not only underpin the cancer-type-specific etiology and pathogenesis but also unveil the common environmental risk factors shared by multiple cancer types. Moreover, we also identify PanDM-specific DM CpG sites that the common strategy fails to detect.ConclusionsPanDM is a powerful tool that provides a systematic way to investigate aberrant methylation patterns across multiple cancer types. Results from real data analyses suggest a novel angle for us to understand the common and specific DM patterns in different cancers. Moreover, as PanDM works on the summary statistics for each cancer type, the same framework can in principle be applied to pan-cancer analyses of other functional genomic profiles. We implement PanDM as an R package, which is freely available at http://www.sta.cuhk.edu.hk/YWei/PanDM.html .
| S-EPMC7579968 | biostudies-literature
Project description:ObjectiveExposure to stress during pregnancy may program susceptibility to the development of obesity in offspring. Our goal was to determine whether prenatal maternal stress (PNMS) due to a natural disaster was associated with child obesity, and to compare the DNA methylation profiles in obese versus non-obese children at age 13½ years. Women and their children were involved in the longitudinal natural disaster study-Project Ice Strom, which served as a human model to study PNMS. Blood was collected from 31 children (including five obese children). Infinium HumanMethylation450 BeadChip Array was performed for genome-wide DNA methylation analyses.ResultsResults demonstrated a well-defined obesity-associated genome-wide DNA methylation pattern. There were 277 CpGs, corresponding to 143 genes, were differentially-methylated. IPA analyses revealed 51 canonical pathways, and enrichment of pathways was involved in immune function. Although no significant association was found between PNMS and child obesity, the preliminary data in the study revealed obesity-associated methylation patterns on a genome-wide level in children.
| S-EPMC6434834 | biostudies-literature
Project description:Limited number of tumor types have been examined for Orthopedia Homeobox (OTP) expression. In pulmonary carcinoids, loss of expression is a strong indicator of poor prognosis. Here, we investigated OTP expression in 37 different tumor types, and the association between OTP expression and DNA methylation levels in lung neuroendocrine neoplasms. We analyzed publicly available multi-omics data (whole-exome-, whole-genome-, RNA sequencing and Epic 850K-methylation array) of 58 typical carcinoids, 27 atypical carcinoids, 69 large cell neuroendocrine carcinoma and 51 small cell lung cancer patients and TCGA (The Cancer Genome Atlas) data of 33 tumor types. 850K-methylation analysis was cross-validated using targeted pyrosequencing on 35 carcinoids. We report bimodality of OTP expression in carcinoids (OTPhigh vs OTPlow group, likelihood-ratio test P = 1.5 × 10-2 ), with the OTPhigh group specific to pulmonary carcinoids while absent from all other cohorts analyzed. Significantly different DNA methylation levels were observed between OTPhigh and OTPlow carcinoids in 12/34 OTP infinium probes (FDR < 0.05 and β-value effect size > .2). OTPlow carcinoids harbor high DNA methylation levels as compared to OTPhigh carcinoids. OTPlow carcinoids showed a significantly worse overall survival (log-rank test P = .0052). Gene set enrichment analysis for somatically mutated genes associated with hallmarks of cancer showed robust enrichment of three hallmarks in the OTPlow group, that is, sustaining proliferative signaling, evading growth suppressor and genome instability and mutation. Together our data suggest that high OTP expression is a unique feature of pulmonary carcinoids with a favorable prognosis and that in poor prognostic patients, OTP expression is lost, most likely due to changes in DNA methylation levels.
| S-EPMC9303689 | biostudies-literature
Project description:BACKGROUND: Hundreds of genes with differential DNA methylation of promoters have been identified for various cancers. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed. METHODOLOGY/PRINCIPAL FINDINGS: Using array data for seven types of cancers, we first evaluated the effects of experimental batches on differential DNA methylation detection. Second, we compared the directions of DNA methylation changes detected from different datasets for the same cancer. Third, we evaluated the concordance between methylation and gene expression changes. Finally, we compared DNA methylation changes in different cancers. For a given cancer, the directions of methylation and expression changes detected from different datasets, excluding potential batch effects, were highly consistent. In different cancers, DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression, whereas hypomethylation was only weakly correlated with the up-regulation of genes. Finally, we found that genes commonly hypomethylated in different cancers primarily performed functions associated with chronic inflammation, such as 'keratinization', 'chemotaxis' and 'immune response'. CONCLUSIONS: Batch effects could greatly affect the discovery of DNA methylation biomarkers. For a particular cancer, both differential DNA methylation and gene expression can be reproducibly detected from different studies with no batch effects. While DNA hypermethylation is significantly linked to gene down-regulation, hypomethylation is only weakly correlated with gene up-regulation and is likely to be linked to chronic inflammation.
| S-EPMC3250460 | biostudies-literature