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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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE41049 | GEO | 2012/09/24

SECONDARY ACCESSION(S): PRJNA175632

REPOSITORIES: GEO

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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. Gene expression profiled in duplicate throughout the microevolutionary timecourse using Affymetrix Gene 1.0 ST arrays.

2012-09-24 | E-GEOD-41049 | biostudies-arrayexpress

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)

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. Genomewide sequencing data is included herein: H3K27me3 profiled throughout the microevolutionary timecourse using ChIP-seq, DNA methylation profiled through the timecourse using MeDIP-seq, and H3K4me3 and CTCF profiled in late and early timepoints using ChIP-seq. Deep Bisulfite sequencing amplicon data and results can be obtained at: http://compgenomics.weizmann.ac.il/tanay/?page_id=99 .

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

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [scRNA-seq]

Project description:We subject multiple versions and single cell-derived sublines of an archetypal non-small cell lung cancer cell line to experimental scrutiny at the genomic, transcriptomic, and cell population levels. We find evidence of genetic variability among cell line versions and one subline. Additional sublines show no genetic variation but epigenetic differences are detected at the transcriptomic level. Stochastic simulations of subline growth dynamics confirm that one subline likely contains at least two genetic states while all others are isogenic. Overall, our results substantiate a view of intratumoral heterogeneity in which different genetic states give rise to multiple epigenetic “basins of attraction,” across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Deconvolving intratumoral heterogeneity into genetic, epigenetic, and stochastic components provides a lens through which to view tumor drug response and acquired treatment resistance that may lead to novel therapeutic strategies in the future.

2020-05-08 | GSE150083 | GEO

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [Bulk-RNA-seq]

2020-05-08 | GSE150025 | GEO

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

2011-09-01 | GSE31781 | GEO

Transition state dynamics during a stochastic fate choice

Project description:A stochastic differentiation programme shows stepwise separation of cell fate, with initiation of cell-type specific gene expression coupled to global transcriptome changes shared by all cells.

2019-03-28 | GSE128974 | GEO

High complexity cellular barcoding and clonal tracing reveals stochastic and deterministic parameters of radiation resistance - Photon Irradiated samples

Project description:It is elusive whether clonal selection of tumor cells in response to ionizing radiation (IR) is a deterministic or stochastic process. With high resolution clonal barcoding and tracking of over 400.000 HNSCC patient-derived tumor cells the clonal dynamics of tumor cells in response to IR was analysed. Fractionated IR induced a strong selective pressure for clonal reduction. This significantly exceeded uniform clonal survival probabilities indicative for a strong clone-to clone difference. within tumor cells. Survival to IR is driven by a deterministic clonal selection of a smaller population which commonly survives radiation, while increased clonogenic capacity is a result of clonal competition of cells which have been selected stochastically. The ratio of these parameters is amenable to radiation sensitivity which correlates to prognostic biomarkers of HNSCC. Evidence for the existence of a rare subpopulation with an intrinsically radiation resistant phenotype was found at a frequency of 0.6-3.3%. With cellular barcoding we introduce a novel functional heterogeneity associated qualitative readout for evaluating the contribution of stochastic and deterministic clonal selection processes in response to IR. To analyze transcriptomic changes of HNSCC cell lines after fractionated Photon IR (5x4Gy), RNAseq analysis was performed on irradiated cells in comparison to untreated control cells (EBI submission E-MTAB-9693)

2021-08-31 | E-MTAB-10685 | biostudies-arrayexpress

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