scholarly journals Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis

2005 ◽  
Vol 33 (18) ◽  
pp. 5868-5877 ◽  
Author(s):  
A. Meissner
Keyword(s):  
Dna Methylation ◽  
High Resolution ◽  
Bisulfite Sequencing ◽  
Methylation Analysis ◽  
Reduced Representation ◽  
Reduced Representation Bisulfite Sequencing ◽  
Dna Methylation Analysis

Differential DNA methylation analysis reveals key genes in Chinese Qingyu and Landrace pigs

Genome ◽  
2021 ◽  
Author(s):  
Kai Wang ◽  
Pingxian Wu ◽  
Shujie Wang ◽  
Xiang Ji ◽  
Dong Chen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Muscle Development ◽  
Methylation Analysis ◽  
Reduced Representation ◽  
Phenotypic Differences ◽  
Reduced Representation Bisulfite Sequencing ◽  
A Genome ◽  
The Difference ◽  
Dna Methylation Analysis ◽  
Landrace Pig

The Chinese Qingyu pig is a typical domestic fatty pig breed and an invaluable indigenous genetic resource in China. Compared with Landrace pig, Qingyu pig has unique meat characteristics, including muscle development, intramuscular fat, and other meat quality traits. At present, few studies have explored the epigenetic difference due to DNA methylation between Qingyu pig and Landrace pig. In this study, 30 Qingyu pigs and 31 Landrace pig were subjected to reduced representation bisulfite sequencing (RRBS). A genome wide differential DNA methylation analysis was conducted. Six genomic regions, including regions on sus scrofa chromosome (SSC) 1: 266.09-274.23Mb, SSC5:0.88-10.68Mb, SSC8:41.23-48.51Mb, SSC12:45.43-54.38Mb, SSC13:202.15-207.95Mb, and SSC14:126.43-139.85Mb, were regarded as key regions that may be associated with phenotypic differences between Qingyu pig and Landrace pig. Furthermore, according to the further analysis, 5 differential methylated genes (ADCY1, FUBP3, GRIN2B, KIT, and PIK3R6) were deemed as key candidate genes that might be associated with meat characteristics. Our findings provide new insights into the difference of DNA methylation between Qingyu pig and Landrace pig. The results enrich the epigenetic research of Chinese Qingyu pigs.

scholarly journals Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 2055 ◽  
Author(s):  
Yunshun Chen ◽  
Bhupinder Pal ◽  
Jane E. Visvader ◽  
Gordon K. Smyth
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Differential Methylation ◽  
Complete Analysis ◽  
Methylation Analysis ◽  
Model Framework ◽  
Experimental Conditions ◽  
Reduced Representation ◽  
Reduced Representation Bisulfite Sequencing

Studies in epigenetics have shown that DNA methylation is a key factor in regulating gene expression. Aberrant DNA methylation is often associated with DNA instability, which could lead to development of diseases such as cancer. DNA methylation typically occurs in CpG context. When located in a gene promoter, DNA methylation often acts to repress transcription and gene expression. The most commonly used technology of studying DNA methylation is bisulfite sequencing (BS-seq), which can be used to measure genomewide methylation levels on the single-nucleotide scale. Notably, BS-seq can also be combined with enrichment strategies, such as reduced representation bisulfite sequencing (RRBS), to target CpG-rich regions in order to save per-sample costs. A typical DNA methylation analysis involves identifying differentially methylated regions (DMRs) between different experimental conditions. Many statistical methods have been developed for finding DMRs in BS-seq data. In this workflow, we propose a novel approach of detecting DMRs using edgeR. By providing a complete analysis of RRBS profiles of epithelial populations in the mouse mammary gland, we will demonstrate that differential methylation analyses can be fit into the existing pipelines specifically designed for RNA-seq differential expression studies. In addition, the edgeR generalized linear model framework offers great flexibilities for complex experimental design, while still accounting for the biological variability. The analysis approach illustrated in this article can be applied to any BS-seq data that includes some replication, but it is especially appropriate for RRBS data with small numbers of biological replicates.

scholarly journals Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR

F1000Research ◽  
2018 ◽  
Vol 6 ◽  
pp. 2055 ◽  
Author(s):  
Yunshun Chen ◽  
Bhupinder Pal ◽  
Jane E. Visvader ◽  
Gordon K. Smyth
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Epigenetic Modification ◽  
Differential Methylation ◽  
Design Matrix ◽  
Rna Seq ◽  
Methylation Analysis ◽  
Reduced Representation ◽  
Reduced Representation Bisulfite Sequencing ◽  
Differential Methylation Analysis

Cytosine methylation is an important DNA epigenetic modification. In vertebrates, methylation occurs at CpG sites, which are dinucleotides where a cytosine is immediately followed by a guanine in the DNA sequence from 5' to 3'. When located in the promoter region of a gene, DNA methylation is often associated with transcriptional silencing of the gene. Aberrant DNA methylation is associated with the development of various diseases such as cancer. Bisulfite sequencing (BS-seq) is the current "gold-standard" technology for high-resolution profiling of DNA methylation. Reduced representation bisulfite sequencing (RRBS) is an efficient form of BS-seq that targets CpG-rich DNA regions in order to save sequencing costs. A typical bioinformatics aim is to identify CpGs that are differentially methylated (DM) between experimental conditions. This workflow demonstrates that differential methylation analysis of RRBS data can be conducted using software and methodology originally developed for RNA-seq data. The RNA-seq pipeline is adapted to methylation by adding extra columns to the design matrix to account for read coverage at each CpG, after which the RRBS and RNA-seq pipelines are almost identical. This approach is statistically natural and gives analysts access to a rich collection of analysis tools including generalized linear models, gene set testing and pathway analysis. The article presents a complete start to finish case study analysis of RRBS profiles of different cell populations from the mouse mammary gland using the Bioconductor package edgeR. We show that lineage-committed cells are typically hyper-methylated compared to progenitor cells and this is true on all the autosomes but not the sex chromosomes. We demonstrate a strong negative correlation between methylation of promoter regions and gene expression as measured by RNA-seq for the same cell types, showing that methylation is a regulatory mechanism involved in epithelial linear commitment.

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