An optimization approach to detect differentially methylated regions from Whole Genome Bisulfite Sequencing data

A Genome ◽

Whole genome bisulfite sequencing (WGBS) is the current method of choice to obtain the methylation status of each single CpG dinucleotide in a genome. The typical analysis asks for regions that are differentially methylated (DMRs) between samples of two classes, such as different cell types. However, even with current low sequencing costs, many studies need to cope with few samples and medium coverage to stay within budget. We present a method to conservatively estimate the methylation difference between the two classes. Starting from a Bayesian paradigm, we formulate an optimization problem related to LASSO approaches. We present a dynamic programming approach to efficiently compute the optimal solution and its implementation diffmer. We discuss the dependency of the resulting DMRs on the free parameters of our approach and compare the results to those obtained by other DMR discovery tools (BSmooth and RADMeth). We showcase that our method discovers DMRs that are missed by the other tools.

An optimization approach to detect differentially methylated regions from Whole Genome Bisulfite Sequencing data

10.7287/peerj.preprints.1287v1 ◽

2015 ◽

Author(s):

Nina Hesse ◽

Christopher Schröder ◽

Sven Rahmann

Keyword(s):

Bisulfite Sequencing ◽

Methylation Status ◽

Optimal Solution ◽

Programming Approach ◽

Optimization Approach ◽

Whole Genome ◽

Sequencing Data ◽

A Genome ◽

Whole genome bisulfite sequencing (WGBS) is the current method of choice to obtain the methylation status of each single CpG dinucleotide in a genome. The typical analysis asks for regions that are differentially methylated (DMRs) between samples of two classes, such as different cell types. However, even with current low sequencing costs, many studies need to cope with few samples and medium coverage to stay within budget. We present a method to conservatively estimate the methylation difference between the two classes. Starting from a Bayesian paradigm, we formulate an optimization problem related to LASSO approaches. We present a dynamic programming approach to efficiently compute the optimal solution and its implementation diffmer. We discuss the dependency of the resulting DMRs on the free parameters of our approach and compare the results to those obtained by other DMR discovery tools (BSmooth and RADMeth). We showcase that our method discovers DMRs that are missed by the other tools.

An optimization approach to detect differentially methylated regions from Whole Genome Bisulfite Sequencing data

10.7287/peerj.preprints.1287 ◽

2015 ◽

Author(s):

Nina Hesse ◽

Christopher Schröder ◽

Sven Rahmann

Keyword(s):

Bisulfite Sequencing ◽

Methylation Status ◽

Optimal Solution ◽

Programming Approach ◽

Optimization Approach ◽

Whole Genome ◽

Sequencing Data ◽

A Genome ◽

Whole genome bisulfite sequencing (WGBS) is the current method of choice to obtain the methylation status of each single CpG dinucleotide in a genome. The typical analysis asks for regions that are differentially methylated (DMRs) between samples of two classes, such as different cell types. However, even with current low sequencing costs, many studies need to cope with few samples and medium coverage to stay within budget. We present a method to conservatively estimate the methylation difference between the two classes. Starting from a Bayesian paradigm, we formulate an optimization problem related to LASSO approaches. We present a dynamic programming approach to efficiently compute the optimal solution and its implementation diffmer. We discuss the dependency of the resulting DMRs on the free parameters of our approach and compare the results to those obtained by other DMR discovery tools (BSmooth and RADMeth). We showcase that our method discovers DMRs that are missed by the other tools.

A Bayesian Approach for Analysis of Whole-Genome Bisulfite Sequencing Data Identifies Disease-Associated Changes in DNA Methylation

Genetics ◽

10.1534/genetics.116.195008 ◽

2017 ◽

Vol 205 (4) ◽

pp. 1443-1458 ◽

Cited By ~ 10

Author(s):

Owen J. L. Rackham ◽

Sarah R. Langley ◽

Thomas Oates ◽

Eleni Vradi ◽

Nathan Harmston ◽

...

Keyword(s):

Dna Methylation ◽

Bayesian Approach ◽

Bisulfite Sequencing ◽

Whole Genome ◽

Sequencing Data ◽

Genome Bisulfite Sequencing ◽

Bisulfite Sequencing Data

GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data

Nucleic Acids Research ◽

10.1093/nar/gks1281 ◽

2012 ◽

Vol 41 (4) ◽

pp. e55-e55 ◽

Cited By ~ 22

Author(s):

Touati Benoukraf ◽

Sarawut Wongphayak ◽

Luqman Hakim Abdul Hadi ◽

Mengchu Wu ◽

Richie Soong

Keyword(s):

Bisulfite Sequencing ◽

Whole Genome ◽

Sequencing Data ◽

Genome Bisulfite Sequencing ◽

Bisulfite Sequencing Data

MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data

BMC Genomics ◽

10.1186/1471-2164-16-s12-s11 ◽

2015 ◽

Vol 16 (Suppl 12) ◽

pp. S11 ◽

Cited By ~ 12

Author(s):

Wen-Wei Liao ◽

Ming-Ren Yen ◽

Evaline Ju ◽

Fei-Man Hsu ◽

Larry Lam ◽

...

Keyword(s):

Bisulfite Sequencing ◽

Whole Genome ◽

Sequencing Data ◽

Genome Bisulfite Sequencing ◽

Bisulfite Sequencing Data

Efficient and accurate determination of genome-wide DNA methylation patterns in Arabidopsis thaliana with enzymatic methyl sequencing

Epigenetics & Chromatin ◽

10.1186/s13072-020-00361-9 ◽

2020 ◽

Vol 13 (1) ◽

Cited By ~ 1

Author(s):

Suhua Feng ◽

Zhenhui Zhong ◽

Ming Wang ◽

Steven E. Jacobsen

Keyword(s):

Dna Methylation ◽

Bisulfite Sequencing ◽

Accurate Determination ◽

Gc Content ◽

Epigenetic Mark ◽

Whole Genome ◽

Genome Wide ◽

A Genome ◽

Abstract Background 5′ methylation of cytosines in DNA molecules is an important epigenetic mark in eukaryotes. Bisulfite sequencing is the gold standard of DNA methylation detection, and whole-genome bisulfite sequencing (WGBS) has been widely used to detect methylation at single-nucleotide resolution on a genome-wide scale. However, sodium bisulfite is known to severely degrade DNA, which, in combination with biases introduced during PCR amplification, leads to unbalanced base representation in the final sequencing libraries. Enzymatic conversion of unmethylated cytosines to uracils can achieve the same end product for sequencing as does bisulfite treatment and does not affect the integrity of the DNA; enzymatic methylation sequencing may, thus, provide advantages over bisulfite sequencing. Results Using an enzymatic methyl-seq (EM-seq) technique to selectively deaminate unmethylated cytosines to uracils, we generated and sequenced libraries based on different amounts of Arabidopsis input DNA and different numbers of PCR cycles, and compared these data to results from traditional whole-genome bisulfite sequencing. We found that EM-seq libraries were more consistent between replicates and had higher mapping and lower duplication rates, lower background noise, higher average coverage, and higher coverage of total cytosines. Differential methylation region (DMR) analysis showed that WGBS tended to over-estimate methylation levels especially in CHG and CHH contexts, whereas EM-seq detected higher CG methylation levels in certain highly methylated areas. These phenomena can be mostly explained by a correlation of WGBS methylation estimation with GC content and methylated cytosine density. We used EM-seq to compare methylation between leaves and flowers, and found that CHG methylation level is greatly elevated in flowers, especially in pericentromeric regions. Conclusion We suggest that EM-seq is a more accurate and reliable approach than WGBS to detect methylation. Compared to WGBS, the results of EM-seq are less affected by differences in library preparation conditions or by the skewed base composition in the converted DNA. It may therefore be more desirable to use EM-seq in methylation studies.