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Strand-specific single-cell methylomics reveals distinct modes of DNA demethylation dynamics in preimplantation mouse and human embryos

ABSTRACT: Strand-specific single-cell methylomics reveals distinct modes of DNA demethylation dynamics in preimplantation mouse and human embryos

PROVIDER: PRJNA587784 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10402117.fastq.gz	Fastqsanger.gz
	SRR10402118.fastq.gz	Fastqsanger.gz
	SRR10402119.fastq.gz	Fastqsanger.gz
	SRR10402120.fastq.gz	Fastqsanger.gz
	SRR10402121.fastq.gz	Fastqsanger.gz

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Strand-specific single-cell methylomics reveals distinct modes of DNA demethylation dynamics in preimplantation mouse and human embryos

Project description:DNA methylation (5mC) is central to cellular identity and the global erasure of 5mC from the parental genomes during preimplantation mammalian development. This process is critical to reset the methylome of terminally differentiated gametes to the become pluripotent cells in the blastocyst. While active and passive modes of demethylation have both been suggested to play a role in this process, the relative contribution of these two mechanisms to genome-wide 5mC erasure remains unclear. Here, we report a new high-throughput single-cell method (scMspJI-seq) that enables strand-specific quantification of 5mC, thereby allowing us to systematically probe the dynamics of global demethylation. First, when applied to hybrid mouse embryonic stem cells, we identified substantial cell-to-cell strand-specific 5mC heterogeneity with a small group of cells displaying asymmetric levels of 5mCpG between the two DNA strands of a chromosome and suggesting loss of maintenance methylation. Next, using scMspJI-seq in preimplantation mouse development, we discovered that maintenance methylation is active till the 16-cell stage followed by passive demethylation in a fraction of cells within 2 the early blastocyst at the 32-cell stage of development. Finally, we found that human preimplantation embryos qualitatively show slower yet similar demethylation dynamics as mouse preimplantation embryos. Collectively, these results demonstrate that scMspJI-seq is a sensitive and cost effective method to map the strand-specific genome- wide patterns of 5mC in single cells, thereby enabling quantitative investigation of methylation dynamics in developmental systems.

2020-02-13 | GSE139984 | GEO

Strand-specific single-cell methylomics reveals distinct modes of DNA demethylation dynamics during early mammalian development.

Project description:DNA methylation (5mC) is central to cellular identity. The global erasure of 5mC from the parental genomes during preimplantation mammalian development is critical to reset the methylome of gametes to the cells in the blastocyst. While active and passive modes of demethylation have both been suggested to play a role in this process, the relative contribution of these two mechanisms to 5mC erasure remains unclear. Here, we report a single-cell method (scMspJI-seq) that enables strand-specific quantification of 5mC, allowing us to systematically probe the dynamics of global demethylation. When applied to mouse embryonic stem cells, we identified substantial cell-to-cell strand-specific 5mC heterogeneity, with a small group of cells displaying asymmetric levels of 5mCpG between the two DNA strands of a chromosome suggesting loss of maintenance methylation. Next, in preimplantation mouse embryos, we discovered that methylation maintenance is active till the 16-cell stage followed by passive demethylation in a fraction of cells within the early blastocyst at the 32-cell stage of development. Finally, human preimplantation embryos qualitatively show temporally delayed yet similar demethylation dynamics as mouse embryos. Collectively, these results demonstrate that scMspJI-seq is a sensitive and cost-effective method to map the strand-specific genome-wide patterns of 5mC in single cells.

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Quartet Methylomics

Project description:Quartet Methylomics

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PRMT5 protects genomic integrity during global DNA demethylation in primordial germ cells and preimplantation embryos

Project description:Primordial germ cells (PGCs) and preimplantation embryos undergo epigenetic reprogramming, which entails comprehensive erasure of DNA methylation. We found that PRMT5, an arginine methyltransferase, translocates from the cytoplasm to the nucleus during this process. Here we show that conditional loss of PRMT5 in early PGCs caused complete male and female sterility, which is preceded by upregulation of LINE1 and IAP transposons and DNA damage response. Similarly, loss of maternal-zygotic PRMT5 also leads to IAP upregulation and early embryonic lethality. We detected the PRMT5-catalysed repressive H2A/H4R3me2s modification on LINE1 and IAP in early wildtype PGCs, directly implicating this mark in the maintenance of transposon silencing during DNA hypomethylation. PRMT5 subsequently translocates back to the cytoplasm of PGCs to participate in the previously described PIWI-interacting RNA (piRNA) pathway that promotes transposon silencing via de novo DNA re-methylation. Thus, PRMT5 has a novel direct role in genome defense during preimplantation development and in PGCs at the time of global DNA demethylation PGCs mRNA profiles of embryonic day 11.5 dpc control (Blimp1Cre;Prmt5flox/+) and Prmt5 germ cell knockout (Blimp1Cre;Prmt5 flox/flox) were generated by deep sequencing (SOLiD next generation sequencing).

2014-09-09 | E-GEOD-61216 | biostudies-arrayexpress

PRMT5 protects genomic integrity during global DNA demethylation in primordial germ cells and preimplantation embryos

2014-11-14 | E-GEOD-60875 | biostudies-arrayexpress

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Project description:We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: (a) implication of three different normalization techniques, and (b) implication of differential analysis using the generalized linear model (GLM). We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.

2019-07-18 | GSE134052 | GEO

methylomics

Project description:Methylomics analysis results formatted as a beta matrix

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Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data [Methylomics]

Project description:Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data [Methylomics]

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PRMT5 protects genomic integrity during global DNA demethylation in primordial germ cells and preimplantation embryos

2014-11-14 | GSE60875 | GEO

Wax and Wane of genome-wide DNA methylation during monkey preimplantation embryogenesis

Project description:This study reports, for the first time, the genome scale methylome of nonhuman primate preimplantation development and proposes a perspective of DNA methylation dynamic equilibrium involving both DNA demethylation and de novoremethylation during primate early embryogenesis.

2015-01-01 | GSE60166 | GEO

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