612 High-throughput Allele-specific Single Cell and Single Molecule DNA Methylation Assays for the Analysis of Multiple Candidate Loci

2012 ◽  
Vol 48 ◽  
pp. S146
Author(s):  
A. How Kit ◽  
M. Krapf ◽  
M. Maleszweska ◽  
M. Goodhardt ◽  
J. Tost
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
High Throughput ◽  
Single Molecule ◽  
Allele Specific ◽  
Candidate Loci

Development of a method for identifying and functionally analyzing allele-specific DNA methylation based on BS-seq data

Epigenomics ◽  
2019 ◽  
Vol 11 (15) ◽  
pp. 1679-1692
Author(s):  
Jiang Zhu ◽  
Mu Su ◽  
Yue Gu ◽  
Xingda Zhang ◽  
Wenhua Lv ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Throughput ◽  
Bisulfite Sequencing ◽  
The Cancer Genome Atlas ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data ◽  
Allele Specific ◽  
New Perspective

Aim: To comprehensively identify allele-specific DNA methylation (ASM) at the genome-wide level. Methods: Here, we propose a new method, called GeneASM, to identify ASM using high-throughput bisulfite sequencing data in the absence of haplotype information. Results: A total of 2194 allele-specific DNA methylated genes were identified in the GM12878 lymphocyte lineage using GeneASM. These genes are mainly enriched in cell cytoplasm function, subcellular component movement or cellular linkages. GM12878 methylated DNA immunoprecipitation sequencing, and methylation sensitive restriction enzyme sequencing data were used to evaluate ASM. The relationship between ASM and disease was further analyzed using the The Cancer Genome Atlas (TCGA) data of lung adenocarcinoma (LUAD), and whole genome bisulfite sequencing data. Conclusion: GeneASM, which recognizes ASM by high-throughput bisulfite sequencing and heterozygous single-nucleotide polymorphisms, provides new perspective for studying genomic imprinting.

Single-cell multiomics sequencing reveals the functional regulatory landscape of early embryos

2019 ◽  
Author(s):  
Yang Wang ◽  
Peng Yuan ◽  
Zhiqiang Yan ◽  
Ming Yang ◽  
Ying Huo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Single Cell ◽  
Regulatory Network ◽  
Chromatin Accessibility ◽  
Epigenetic Reprogramming ◽  
Preimplantation Development ◽  
Rna Expression ◽  
Early Embryos ◽  
Allele Specific

AbstractExtensive epigenetic reprogramming occurs during preimplantation embryo development and is accompanied by zygotic genome activation (ZGA) and first cell fate specification. Recent studies using single-cell epigenome sequencing techniques have provided global views of the dynamics of different epigenetic layers during this period. However, it remains largely unclear how the drastic epigenetic reprogramming contributes to transcriptional regulatory network. Here, we developed a single-cell multiomics sequencing technology (scNOMeRe-seq) that enables profiling of genome-wide chromatin accessibility, DNA methylation and RNA expression in the same individual cell with improved performance compared to that of earlier techniques. We applied this method to analyze the global dynamics of different molecular layers and their associations in mouse preimplantation embryos. We found that global DNA methylation remodeling facilitates the reconstruction of genetic lineages in early embryos and revealed that the gradual increases in heterogeneity among blastomeres are driven by asymmetric cleavage. Allele-specific DNA methylation pattern is maintained throughout preimplantation development and is accompanied by allele-specific associations between DNA methylation and gene expression in the gene body that are inherited from oocytes and sperm. Through integrated analyses of the collective dynamics between gene expression and chromatin accessibility, we constructed a ZGA-associated regulatory network and revealed coordination among multiple epigenetic layers, transcription factors (TFs) and repeat elements that instruct the proper ZGA process. Moreover, we found that inner cell mass (ICM)/trophectoderm (TE) lineage-associated cis-regulatory elements are stepwise activated in blastomeres during post-ZGA embryo stages. TE lineage-specific TFs play dual roles in promoting the TE program while repressing the ICM program, thereby separating the TE lineage from the ICM lineage. Taken together, our findings not only depict the first single-cell triple-omics map of chromatin accessibility, DNA methylation and RNA expression during mouse preimplantation development but also enhance the fundamental understanding of epigenetic regulation in early embryos.

scholarly journals methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data

2020 ◽  
Author(s):  
Parker Knight ◽  
Marie-Pierre L. Gauthier ◽  
Carolina E. Pardo ◽  
Russell P. Darst ◽  
Alberto Riva ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Single Molecule ◽  
Nucleosome Occupancy ◽  
Chromatin Accessibility ◽  
Biologically Relevant ◽  
Shiny App ◽  
R Shiny ◽  
Long Read ◽  
Cell Data

AbstractDifferential DNA methylation and chromatin accessibility are associated with disease development, particularly cancer. Methods that allow profiling of these epigenetic mechanisms in the same reaction and at the single-molecule or single-cell level continue to emerge. However, a challenge lies in jointly visualizing and analyzing the heterogeneous nature of the data and extracting regulatory insight. Here, we developed methylscaper, a visualization framework for simultaneous analysis of DNA methylation and chromatin landscapes. Methylscaper implements a weighted principle component analysis that orders sequencing reads, each providing a record of the chromatin state of one epiallele, and reveals patterns of nucleosome positioning, transcription factor occupancy, and DNA methylation. We demonstrate methylscaper’s utility on a long-read, single-molecule methyltransferase accessibility protocol for individual templates (MAPit) dataset and a single-cell nucleosome, methylation, and transcription sequencing (scNMT-seq) dataset. In comparison to other procedures, methylscaper is able to readily identify chromatin features that are biologically relevant to transcriptional status while scaling to larger datasets.Availability and implementationMethylscaper, is available on GitHub at https://github.com/rhondabacher/[email protected]

scholarly journals A high-throughput DNA methylation analysis of a single cell

2011 ◽  
Vol 39 (7) ◽  
pp. e44-e44 ◽  
Author(s):  
Martin Kantlehner ◽  
Roland Kirchner ◽  
Petra Hartmann ◽  
Joachim W. Ellwart ◽  
Marianna Alunni-Fabbroni ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
High Throughput ◽  
Methylation Analysis ◽  
Dna Methylation Analysis

scholarly journals Ultra-Deep DNA Methylation Analysis of X-Linked Genes: GLA and AR as Model Genes

Genes ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 620
Author(s):  
Giulia De Riso ◽  
Mariella Cuomo ◽  
Teodolinda Di Risi ◽  
Rosa Della Monica ◽  
Michela Buonaiuto ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Molecule ◽  
Clinical Manifestations ◽  
X Inactivation ◽  
Distribution Analysis ◽  
Methylation Analysis ◽  
X Chromosomes ◽  
Distinct Allele ◽  
Allele Specific ◽  
Inactivation Process

Recessive X-linked disorders may occasionally evolve in clinical manifestations of variable severity also in female carriers. For some of such diseases, the frequency of the symptoms’ appearance during women’s life may be particularly relevant. This phenomenon has been largely attributed to the potential skewness of the X-inactivation process leading to variable phenotypes. Nonetheless, in many cases, no correlation with X-inactivation unbalance was demonstrated. However, methods for analyzing skewness have been mainly limited to Human Androgen Receptor methylation analysis (HUMARA). Recently, the X-inactivation process has been largely revisited, highlighting the heterogeneity existing among loci in the epigenetic state within inactive and, possibly, active X-chromosomes. We reasoned that gene-specific and ultra-deep DNA methylation analyses could greatly help to unravel details of the X-inactivation process and the roles of specific X genes inactivation in disease manifestations. We recently provided evidence that studying DNA methylation at specific autosomic loci at a single-molecule resolution (epiallele distribution analysis) allows one to analyze cell-to-cell methylation differences in a given cell population. We here apply the epiallele analysis at two X-linked loci to investigate whether females show allele-specific epiallelic patterns. Due to the high potential of this approach, the method allows us to obtain clearly distinct allele-specific epiallele profiles.

scholarly journals MethylStar: A fast and robust pre-processing pipeline for bulk or single-cell whole-genome bisulfite sequencing data

2019 ◽  
Author(s):  
Yadollah Shahryary ◽  
Rashmi R. Hazarika ◽  
Frank Johannes
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
High Throughput ◽  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Whole Genome Bisulfite Sequencing ◽  
Processing Pipeline ◽  
Link Type ◽  
Genome Bisulfite Sequencing ◽  
User Friendly

AbstractBackground:Whole-Genome Bisulfite Sequencing (WGBS) is a Next Generation Sequencing (NGS) technique for measuring DNA methylation at base resolution. Continuing drops in sequencing costs are beginning to enable high-throughput surveys of DNA methylation in large samples of individuals and/or single cells. These surveys can easily generate hundreds or even thousands of WGBS datasets in a single study. The efficient pre-processing of these large amounts of data poses major computational challenges and creates unnecessary bottlenecks for downstream analysis and biological interpretation.Results:To offer an efficient analysis solution, we present MethylStar, a fast, stable and flexible pre-processing pipeline for WGBS data. MethylStar integrates well-established tools for read trimming, alignment and methylation state calling in a highly parallelized environment, manages computational resources and performs automatic error detection. MethylStar offers easy installation through a dockerized container with all preloaded dependencies and also features a user-friendly interface designed for experts/non-experts. Application of MethylStar to WGBS from human, maize and Arabidopsis shows that it outperforms existing pre-processing pipelines in terms of speed and memory requirements.Conclusions:MethylStar is a fast, stable and flexible pipeline for high-throughput pre-processing of bulk or single-cell WGBS data. Its easy installation and user-friendly interface should make it a useful resource for the wider epigenomics community. MethylStar is distributed under GPL-3.0 license and source code is publicly available for download from github https://github.com/jlab-code/MethylStar. Installation through a docker image is available from http://jlabdata.org/methylstar.tar.gz

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