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Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (Gene Expression data)

ABSTRACT: DNA methylation has been comprehensively profiled in normal and cancer cells, but the dynamics that form, maintain and reprogram differentially methylated regions remain enigmatic. We show that methylation patterns within populations of cells from individual somatic tissues are heterogeneous and polymorphic. Using in vitro evolution of immortalized fibroblasts for over 300 generations, we track the dynamics of polymorphic methylation at regions developing significant differential methylation on average. The data indicate that changes in population-averaged methylation occur through a stochastic process that generates a stream of local and uncorrelated methylation aberrations. Despite the stochastic nature of the process, nearly deterministic epigenetic remodeling emerges on average at loci that lose or gain resistance to methylation accumulation. Changes in the susceptibility to methylation accumulation are correlated with changes in histone modifications and CTCF occupancy. Characterizing epigenomic polymorphism within cell populations is therefore critical for understanding methylation dynamics in normal and cancer cells. Gene expression profiled in duplicate throughout the microevolutionary timecourse using Affymetrix Gene 1.0 ST arrays.

ORGANISM(S): Homo sapiens

SUBMITTER: Gilad Landan

PROVIDER: E-GEOD-41049 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (Gene Expression data)

Project description:DNA methylation has been comprehensively profiled in normal and cancer cells, but the dynamics that form, maintain and reprogram differentially methylated regions remain enigmatic. We show that methylation patterns within populations of cells from individual somatic tissues are heterogeneous and polymorphic. Using in vitro evolution of immortalized fibroblasts for over 300 generations, we track the dynamics of polymorphic methylation at regions developing significant differential methylation on average. The data indicate that changes in population-averaged methylation occur through a stochastic process that generates a stream of local and uncorrelated methylation aberrations. Despite the stochastic nature of the process, nearly deterministic epigenetic remodeling emerges on average at loci that lose or gain resistance to methylation accumulation. Changes in the susceptibility to methylation accumulation are correlated with changes in histone modifications and CTCF occupancy. Characterizing epigenomic polymorphism within cell populations is therefore critical for understanding methylation dynamics in normal and cancer cells.

2012-09-24 | GSE41049 | GEO

Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (ChIP-Seq and MeDIP-Seq)

2012-09-24 | GSE41048 | GEO

Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (ChIP-Seq and MeDIP-Seq)

2012-09-24 | E-GEOD-41048 | biostudies-arrayexpress

Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues

Project description:This SuperSeries is composed of the following subset Series: GSE41048: Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (ChIP-Seq and MeDIP-Seq) GSE41049: Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (Gene Expression data) Refer to individual Series

2012-09-24 | E-GEOD-41050 | biostudies-arrayexpress

An optogenetic switch for the Set2 methyltransferase provides evidence for transcription-dependent and independent dynamics of H3K36 methylation

Project description:Histone H3 lysine 36 methylation (H3K36me) is a conserved histone modification associated with transcription and DNA repair. Although the effects of H3K36 methylation have been studied, the genome-wide dynamics of H3K36me deposition and removal are not known. We established rapid and reversible optogenetic control for Set2, the sole H3K36 methyltransferase in yeast, by fusing the enzyme with the light activated nuclear shuttle (LANS) domain. Early H3K36me3 dynamics identified methylation in vivo, with total H3K36me3 levels correlating with RNA abundance. Although genes exhibited disparate levels of H3K36 methylation, relative rates of H3K36me3 accumulation were largely linear and consistent across genes, suggesting that H3K36me3 deposition occurs uniformly across all genes in a directed fashion regardless of transcription frequency. Removal of H3K36me3 was highly dependent on the demethylase Rph1. However, the per-gene rate of H3K36me3 loss weakly correlated with RNA abundance and followed exponential decay, suggesting H3K36 demethylases act in a global, stochastic manner. Altogether, these data provide a detailed temporal view of H3K36 methylation and demethylation that suggest transcription-dependent and independent mechanisms for H3K36me deposition and removal, respectively.

2020-07-01 | GSE153539 | GEO

Replicative senescence is associated with nuclear reorganization and DNA methylation at specific transcription factor binding sites (MBD-seq)

Project description:Primary cells enter replicative senescence after a limited number of cell divisions. This process is associated with reproducible changes in DNA methylation (DNAm) at specific sites in the genome. The mechanism that drives senescence-associated DNAm changes remains unknown and may arise through drift in DNAm or through regulated, senescence dependent modifications at specific sites in the genome. In this study, we analyzed the reorganization of nuclear architecture and DNA methylation during long-term culture of human fibroblasts and mesenchymal stromal cells (MSCs). [MethylCap-seq] Fibroblasts of two female donors (both 43 years old) were culture expanded and DNA was harvested of 10,000,000 cells at early passage (P3 or P5) and late passage (P30 and P33). DNA methylation changes were subsequently analyzed by MethylCap-Seq.

2015-03-26 | E-GEOD-59960 | biostudies-arrayexpress

Evidence for widespread changes in promoter methylation profile in human placenta in response to increasing gestational age and environmental/stochastic factors.

Project description:Background: the human placenta facilitates the exchange of nutrients, gas and waste between the fetal and maternal circulations. It also protects the fetus from the maternal immune response. Due to its role at the feto-maternal interface, the placenta is subject to many environmental exposures that can potentially alter its epigenetic profile. Previous studies have reported gene expression differences in placenta over gestation, as well as inter-individual variation in expression of some genes. However, the factors contributing to this variation in gene expression remain poorly understood. Results: in this study, we performed a genome-wide DNA methylation analysis of gene promoters in placenta tissue from three pregnancy trimesters. We identified large-scale differences in global DNA methylation levels between first, second and third trimesters, with an overall progressive increase in average methylation from first to third trimester. The most differentially methylated genes included many immune regulators, reflecting the change in placental immuno-modulation as pregnancy progresses. We also detected increased inter-individual variation in the third trimester relative to first and second, supporting an accumulation of environmentally induced (or stochastic) changes in DNA methylation pattern. These highly variable genes were enriched for those involved in amino acid and other metabolic pathways, potentially reflecting the adaptation of the human placenta to different environments. Conclusions : the identification of cellular pathways subject to drift in response to environmental influences provide a basis for future studies examining the role of specific environmental factors on DNA methylation pattern and placenta-associated adverse pregnancy outcomes. A total of 42 samples, with 18 first trimester, 10 second trimester, 14 full term placenta

2011-08-31 | E-GEOD-31781 | biostudies-arrayexpress

Transition state dynamics during a stochastic fate choice

Project description:Transition state dynamics during a stochastic fate choice

| PRJNA529608 | ENA

LTR retrotransposons transcribed in oocytes drive species-specific and heritable changes in DNA methylation

Project description:De novo DNA methylation (DNAme) occurs coincident with transcription during mouse oogenesis. As many oocyte transcripts originate in Long Terminal Repeats (LTRs), which are divergent across species, we examined whether polymorphic LTR-initiated transcription units (LITs) shape the oocyte methylome. We identified thousands of syntenic regions in mouse, rat and human, including CpG islands (CGIs), that show divergent DNAme associated with polymorphic LITs. Notably, many CGI promoters methylated exclusively in mouse and/or rat are embedded within rodent-specific LITs, and show persistent maternal methylation in the blastocyst. Polymorphic LITs are also responsible for divergent methylation of CGI promoters in distantly related mouse strains, revealing that LITs also promote intra-species diversification of promoter DNAme.

2018-07-06 | GSE112622 | GEO

Gene expression in the mouse embryonic small intestinal epithelium in the presence or absence of GATA4 and GATA6

Project description:Gene expression was compared between E18.5 Gata4Gata6 double conditional knockout (cKO) small intestinal epithelium and E18.5 control mouse small intestinal epithleium. E18.5 mouse small intestine was collected from control and Gata4Gata6 double conditional knockout mice. Epithelial cells were isolated, and RNA was prepared. Affymetrix Mouse Gene 1.0 gene arrays were used to interrogate gene expression. Data was analyzed using dChip software.

2014-04-30 | E-GEOD-49471 | biostudies-arrayexpress

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