Sa526 DNA METHYLATION LANDSCAPE AND SIGNATURE OF CD4+ LYMPHOCYTES IN CROHN'S PATIENTS BY REDUCED REPRESENTATION AND BISULFITE SEQUENCING

2021 ◽  
Vol 160 (6) ◽  
pp. S-536
Author(s):  
Zhifu Sun ◽  
Manuel Bonfim Braga Neto ◽  
Yuning Xiong ◽  
Saurabh Baheti ◽  
Jessica J. Friton ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Reduced Representation ◽  
Cd4 Lymphocytes

scholarly journals How to Design a Whole-Genome Bisulfite Sequencing Experiment

Epigenomes ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 21 ◽  
Author(s):  
Claudius Grehl ◽  
Markus Kuhlmann ◽  
Claude Becker ◽  
Bruno Glaser ◽  
Ivo Grosse
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Alternative Methods ◽  
Transcriptional Gene Silencing ◽  
Whole Genome ◽  
Reduced Representation ◽  
Genome Region ◽  
Whole Genome Bisulfite Sequencing ◽  
Sequencing Experiment ◽  
Genome Bisulfite Sequencing

Aside from post-translational histone modifications and small RNA populations, the epigenome of an organism is defined by the level and spectrum of DNA methylation. Methyl groups can be covalently bound to the carbon-5 of cytosines or the carbon-6 of adenine bases. DNA methylation can be found in both prokaryotes and eukaryotes. In the latter, dynamic variation is shown across species, along development, and by cell type. DNA methylation usually leads to a lower binding affinity of DNA-interacting proteins and often results in a lower expression rate of the subsequent genome region, a process also referred to as transcriptional gene silencing. We give an overview of the current state of research facilitating the planning and implementation of whole-genome bisulfite-sequencing (WGBS) experiments. We refrain from discussing alternative methods for DNA methylation analysis, such as reduced representation bisulfite sequencing (rrBS) and methylated DNA immunoprecipitation sequencing (MeDIPSeq), which have value in specific experimental contexts but are generally disadvantageous compared to WGBS.

Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling

2011 ◽  
Vol 6 (4) ◽  
pp. 468-481 ◽  
Author(s):  
Hongcang Gu ◽  
Zachary D Smith ◽  
Christoph Bock ◽  
Patrick Boyle ◽  
Andreas Gnirke ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Reduced Representation ◽  
Reduced Representation Bisulfite Sequencing ◽  
Dna Methylation Profiling ◽  
Genome Scale ◽  
Methylation Profiling

scholarly journals DNA methylation estimation using methylation-sensitive restriction enzyme bisulfite sequencing (MREBS)

2017 ◽  
Author(s):  
Giancarlo Bonora ◽  
Liudmilla Rubbi ◽  
Marco Morselli ◽  
Constantinos Chronis ◽  
Kathrin Plath ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Restriction Enzyme ◽  
Large Scale ◽  
Bisulfite Sequencing ◽  
Multiple Regression Model ◽  
Reduced Representation ◽  
A Genome ◽  
Genome Bisulfite Sequencing ◽  
Methylation Sensitive Restriction Enzyme ◽  
Wide Scale

ABSTRACTWhole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) are widely used for measuring DNA methylation levels on a genome-wide scale(1). Both methods have limitations: WGBS is expensive and prohibitive for most large-scale projects; RRBS only interrogates 6-12% of the CpGs in the human genome(16,19). Here, we introduce methylation-sensitive restriction enzyme bisulfite sequencing (MREBS) which has the reduced sequencing requirements of RRBS, but significantly expands the coverage of CpG sites in the genome. We built a multiple regression model that combines the two features of MREBS: the bisulfite conversion ratios of single cytosines (as in WGBS and RRBS) as well as the number of reads that cover each locus (as in MRE-seq(12)). This combined approach allowed us to estimate differential methylation across 60% of the genome using read count data alone, and where counts were sufficiently high in both samples (about 1.5% of the genome), our estimates were significantly improved by the single CpG conversion information. We show that differential DNA methylation values based on MREBS data correlate well with those based on WGBS and RRBS. This newly developed technique combines the sequencing cost of RRBS and DNA methylation estimates on a portion of the genome similar to WGBS, making it ideal for large-scale projects of mammalian genomes.

scholarly journals GENE-40. CHARACTERIZING EPIGENETIC INTRATUMORAL HETEROGENEITY IN GLIOMA USING SINGLE-CELL BISULFITE SEQUENCING

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi106-vi106
Author(s):  
Kevin C Johnson ◽  
Kevin Anderson ◽  
Elise Courtois ◽  
Floris Barthel ◽  
Michael Samuels ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Bisulfite Sequencing ◽  
Cpg Island ◽  
Regulatory Element ◽  
Cell Types ◽  
Intratumoral Heterogeneity ◽  
Gene Promoters ◽  
Cpg Island Methylator Phenotype ◽  
Reduced Representation

Abstract Genetic and epigenetic alterations contribute to the observed intratumoral heterogeneity in adult glioma. Current glioma classification, based on genotype (e.g., IDH1 mutations) and DNA methylation profiles (e.g., glioma CpG Island Methylator Phenotype), can provide clinically relevant tumor subgroups. However, traditional bulk sampling fails to adequately capture the full complement of epigenomic heterogeneity, and may mask deadly features present in less abundant glioma cells. To more precisely characterize the glioma epigenome, we separately profiled single-cell DNA methylation (Reduced Representation Bisulfite Sequencing, RRBS), single-cell RNA expression (10X genomics), and bulk whole genome sequencing in nine gliomas. The genomic regions profiled by scRRBS were primarily gene promoters, but adequate coverage was also reached for glioma-specific enhancer elements and binding sites of chromatin remodelers. Unsupervised clustering of single-cell DNA methylation data revealed intratumoral variability in epigenetic classification and these cell types were distinguished by regulatory element DNA methylation. We further integrated single-cell epigenetic, single-cell transcriptomic, and genomic features to better understand gene regulation and reconstruct each tumor’s lineage history. Together, our study aims to generate a glioma cellular hierarchy shaped by the epigenetic programs that drive tumor growth.

scholarly journals Copy number-aware deconvolution of tumor-normal DNA methylation profiles

2020 ◽  
Author(s):  
Elizabeth Larose Cadieux ◽  
Miljana Tanić ◽  
Gareth A. Wilson ◽  
Toby Baker ◽  
Michelle Dietzen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Copy Number ◽  
Bisulfite Sequencing ◽  
Data Interpretation ◽  
Deconvolution Analysis ◽  
Reduced Representation ◽  
Lung Cancers ◽  
Allele Specific ◽  
Aberrant Dna Methylation ◽  
Copy Number Changes

SUMMARYAberrant DNA methylation is a hallmark of cancer development. Bisulfite sequencing of tumor samples can be used to study changes in the cancer methylome, but data interpretation is confounded by admixed normal cells and copy number changes. Here, we introduce CAMDAC, a novel method for Copy number-Aware Methylation Deconvolution Analysis of Cancers, enabling tumor purity, allele-specific copy number and deconvolved tumor methylation rate profiling from bulk tumor samples. We apply CAMDAC to 122 multi-region samples from 38 non-small cell lung cancers profiled by reduced representation bisulfite sequencing as part of TRACERx study. CAMDAC-derived purity and copy number profiles confirm those derived from matched whole-genome and whole-exome sequencing. Purified tumor methylation rates greatly enhance the accuracy of tumor-normal and tumor-tumor differential methylation calling and, in contrast to bulk signals, capture phylogenetic relationships between tumor clones. CAMDAC directly links genetic mutations and epigenetic changes, yields insights into allele-specific methylation and reveals (epi)genetic heterogeneity in solid tumors.

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