Robust single-cell DNA methylome profiling with snmC-seq2.
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ABSTRACT:
SUBMITTER: Luo C
PROVIDER: S-EPMC6147798 | biostudies-other | 2018 Sep
REPOSITORIES: biostudies-other
Publications
Robust single-cell DNA methylome profiling with snmC-seq2.
Luo Chongyuan C Rivkin Angeline A Zhou Jingtian J Sandoval Justin P JP Kurihara Laurie L Lucero Jacinta J Castanon Rosa R Nery Joseph R JR Pinto-Duarte António A Bui Brian B Fitzpatrick Conor C O'Connor Carolyn C Ruga Seth S Van Eden Marc E ME Davis David A DA Mash Deborah C DC Behrens M Margarita MM Ecker Joseph R JR
Nature communications 20180920 1
Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large-s ...[more]
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Project description:Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artificial reads, enhanced throughput, and increased library complexity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large scale single-cell epigenomic studies.
2018-09-20 | GSE112471 | GEO
Project description:Single-cell transcriptome and single-cell methylome technologies have become powerful tools to study RNA and DNA methylation profiles of single cells at a genome-wide scale. A major challenge has been to understand the direct correlation of DNA methylation and gene expression within single-cells. Due to large cell-to-cell variability and the lack of direct measurements of transcriptome and methylome of the same cell, the association is still unclear.Here, we describe a novel method (scMT-seq) that simultaneously profiles both DNA methylome and transcriptome from the same cell. In sensory neurons, we consistently identify transcriptome and methylome heterogeneity among single cells but the majority of the expression variance is not explained by proximal promoter methylation, with the exception of genes that do not contain CpG islands. By contrast, gene body methylation is positively associated with gene expression for only those genes that contain a CpG island promoter. Furthermore, using single nucleotide polymorphism patterns from our hybrid mouse model, we also find positive correlation of allelic gene body methylation with allelic expression.Our method can be used to detect transcriptome, methylome, and single nucleotide polymorphism information within single cells to dissect the mechanisms of epigenetic gene regulation.
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Project description:Robust single-cell DNA methylome profiling with snmC-seq2
| PRJNA447435 | ENA
Project description:BackgroundDetection of DNA methylome at single-base resolution is a significant challenge but promises to shed considerable light on human disease etiology. Current technologies could not detect DNA methylation genome-wide at single-base resolution with small amount of sequencing data and could not avoid detecting the methylation of repetitive elements which are considered as "junk DNA".MethodsIn this study, we have developed a novel DNA methylome profiling technology named MB-seq with its ability to identify genome-wide 5mC and quantify DNA methylation levels by introduced an assistant adapter AluI-linker This linker can be ligated to sonicated DNA and then be digested after the bisulfite treatment and amplification, which has no effect of MeDIP enrichment. Because many researchers are interested in investigating the methylation of functional regions such as promoters and gene bodies, we have also developed a novel alternative method named MRB-seq, which can be used to investigate the DNA methylation of functional regions by removing the repeats with Cot-1 DNA.ResultsIn this study, we have developed MB-seq, a novel DNA methylome profiling technology combining MeDIP-seq with bisulfite conversion, which can precisely detect the 5mC sites and determine their DNA methylation level at single-base resolution in a cost-effective way. In addition, we have developed a new alternative method, MRB-seq (MeDIP-repetitive elements removal-bisulfite sequencing), which interrogates 5mCs in functional regions by depleting nearly half of repeat fragments enriched by MeDIP. Comparing MB-seq and MRB-seq to whole-genome BS-seq using the same batch of DNA from YH peripheral blood mononuclear cells. We found that the sequencing data of MB-seq and MRB-seq almost reaches saturation after generating 7-8 Gbp data, whereas BS-seq requires about 100 Gbp data to achieve the same effect. In comparison to MeDIP-seq and BS-seq, MB-seq offers several key advantages, including single-base resolution, discriminating the methylated sites within a CpG and non-CpG pattern and overcoming the false positive of MeDIP-seq due to the non-specific binding of 5-methylcytidine antibody to genomic fragments.ConclusionOur novel developed method MB-seq can accelerate the decoding process of DNA methylation mechanism in human diseases because it requires 7-8 Gbp data to measure human methylome with enough coverage and sequencing depth, affording it a direct and practical application in the study of multiple samples. In addition, we have also provided a novel alternative MRB-seq method, which removes most repetitive sequences and allows researchers to genome-wide characterize DNA methylation of functional regions.
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Project description:Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (?WGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples.
| S-EPMC4542311 | biostudies-literature
Project description:Oocyte maturation is a coordinated process that is tightly linked to reproductive potential. A better understanding of gene regulation during human oocyte maturation will not only answer an important question in biology, but also facilitate the development of in vitro maturation technology as a fertility treatment. We generated single-cell transcriptome and used our previously published single-cell methylome data from human oocytes at different maturation stages to investigate how genes are regulated during oocyte maturation, focusing on the potential regulatory role of non-CpG methylation. DNMT3B, a gene encoding a key non-CpG methylation enzyme, is one of the 1,077 genes upregulated in mature oocytes, which may be at least partially responsible for the increased non-CpG methylation as oocytes mature. Non-CpG differentially methylated regions (DMRs) between mature and immature oocytes have multiple binding motifs for transcription factors, some of which bind with DNMT3B and may be important regulators of oocyte maturation through non-CpG methylation. Over 98% of non-CpG DMRs locate in transposable elements, and these DMRs are correlated with expression changes of the nearby genes. Taken together, this data indicates that global non-CpG hypermethylation during oocyte maturation may play an active role in gene expression regulation, potentially through the interaction with transcription factors.
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Project description:The assay for transposase-accessible chromatin using sequencing (ATAC-seq) is widely used to identify regulatory regions throughout the genome. However, very few studies have been performed at the single cell level (scATAC-seq) due to technical challenges. Here we developed a simple and robust plate-based scATAC-seq method, combining upfront bulk Tn5 tagging with single-nuclei sorting. We demonstrate that our method works robustly across various systems, including fresh and cryopreserved cells from primary tissues. By profiling over 3000 splenocytes, we identify distinct immune cell types and reveal cell type-specific regulatory regions and related transcription factors.
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Project description:Organisms and cells, in response to environmental influences or during development, undergo considerable changes in DNA methylation on a genome-wide scale, which are linked to a variety of biological processes. Using MethylC-seq to decipher DNA methylome at single-base resolution is prohibitively costly. In this study, we develop a novel approach, named MBRidge, to detect the methylation levels of repertoire CpGs, by innovatively introducing C-hydroxylmethylated adapters and bisulfate treatment into the MeDIP-seq protocol and employing ridge regression in data analysis. A systematic evaluation of DNA methylome in a human ovarian cell line T29 showed that MBRidge achieved high correlation (R > 0.90) with much less cost (?10%) in comparison with MethylC-seq. We further applied MBRidge to profiling DNA methylome in T29H, an oncogenic counterpart of T29's. By comparing methylomes of T29H and T29, we identified 131790 differential methylation regions (DMRs), which are mainly enriched in carcinogenesis-related pathways. These are substantially different from 7567 DMRs that were obtained by RRBS and related with cell development or differentiation. The integrated analysis of DMRs in the promoter and expression of DMR-corresponding genes revealed that DNA methylation enforced reverse regulation of gene expression, depending on the distance from the proximal DMR to transcription starting sites in both mRNA and lncRNA. Taken together, our results demonstrate that MBRidge is an efficient and cost-effective method that can be widely applied to profiling DNA methylomes.
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