Single-cell DNA methylome sequencing and bioinformatic inference of epigenetic cell state dynamics
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ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE65196 | GEO | 2015/02/25
SECONDARY ACCESSION(S): PRJNA273381
REPOSITORIES: GEO
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Project description:Here we describe a method for whole genome bisulfite sequencing in very small cell populations (µWGBS) and in single cells (scWGBS). Our method is optimized for profiling DNA methylation in many samples at low coverage, and we developed a bioinformatic method that uses collections of single-cell methylomes to infer cell state dynamics. Using these technological advances, we studied epigenetic cell state dynamics in three in vitro models of cellular differentiation and pluripotency and identified patterns of epigenetic remodeling and cell-to-cell heterogeneity. 1-cell or 4-cell samples were collected from a variety of human and mouse cell lines (KBM7, CCE, K562, 32D, HL60). We also included negative controls (no cells), and cross controls (cells of one species aligned to the other). K562 cells were treated with 5-azacytidine in a final concentration of 1µM to induce demethylation. HL60 cells were treated with 1α,25-dihydroxyvitamin D3 in a final concentration of 10nM to induce differentiation. Naïve pluripotency of CCE ES cells was induced by culturing the cells in ESGRO-2i medium with the addition of 1% FCS. Differentiation of CCE ES cells was induced by treating the cells with all-trans retinoic acid (ATRA) in a final concentration of 0,3µM every third day along with complete LIF-free medium exchange. Embryoid body formation from CCE ES cells was induced by hanging-drop culture for 5 days, followed by 9 days on gelatinized dishes (see treatment annotation). Each experiment, with treated and untreated cells, was performed in multiple biological replicates. We then measured DNA methylation in the individual 1-cell or 4-cell experiments with bisulfite treatment and high-throughput sequencing. For sequencing, most experiments pooled a 4-cell experiment from one species with a 1-cell experiment from the other, but some replicates were sequenced as a single cell (indicated with SC in the replicate annotation). Two samples (marked as “deep”) were sequenced much deeper than the others. See Farlik et al. (2015) Cell Reports for complete study details.
2015-02-25 | E-GEOD-65196 | biostudies-arrayexpress
Project description:Single-cell DNA methylome sequencing and bioinformatic inference of epigenetic cell state dynamics
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Project description:Single cell RNA-sequencing revealed extensive transcriptional cell state diversity in cancer, often observed independently from genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, we performed multi-omics single-cell profiling – integrating DNA methylation, transcriptome, and genotyping within the same cells – of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories, and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to measure cell state heritability and transition dynamics based on high resolution lineage trees directly in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal vs. plastic cell state architectures in IDH-mutant glioma vs. IDH-wildtype glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.
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2014-10-23 | E-ERAD-336 | biostudies-arrayexpress
Project description:<p>We describe methclone, a novel method to identify epigenetic loci that harbor large changes in the clonality of their epialleles (epigenetic alleles). Methclone efficiently analyzes genome-wide DNA methylation sequencing data. We quantify the changes using a composition entropy difference calculation and also introduce a new measure of global clonality shift, loci with epiallele shift per million loci covered, which enables comparisons between different samples to gauge overall epiallelic dynamics. Finally, we demonstrate the utility of methclone in capturing functional epiallele shifts in leukemia patients from diagnosis to relapse. Methclone is open-source and freely available at <a href="https://code.google.com/p/methclone">https://code.google.com/p/methclone</a>. Reprinted with permission from BMC Publishing (Genome Biology).</p> <p> <img src="GetImage.cgi?study_id=phs000793&image_name=Methclone.jpg"/> </p>
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Project description:Insights into the forces that shape the plant methylome contribute to the understanding of the evolutionary significance of epigenetic diversity in plants. Previous research has mainly focused on herbaceous annual plants but it is currently unclear how much epigenetic variation is stably induced in long-lived woody perennials. There is also a need to demonstrate the role of parental environments and epigenetic variation on fitness. : We present detailed methylome analyses of the long-lived Lombardy poplar, Populus nigra cv. ‘Italica‘ Duroi. Trees of this widespread clonal cultivar descended from a common ancestor at least two centuries ago. We analyzed genome-wide methylomes of in total 29 pooled and individual DNA-samples. We found that ramets collected over Europe and raised in common conditions have stable methylomes in symmetrical CG-contexts over at least two years and across vegetatively produced generations. In contrast, seasonal dynamics occurred in methylation patterns in CHH-context.
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