METHimpute: Imputation-guided construction of complete methylomes from WGBS 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.

Highly efficient single-stranded DNA ligation technique improves low-input whole-genome bisulfite sequencing by post-bisulfite adaptor tagging

Nucleic Acids Research ◽

10.1093/nar/gkz435 ◽

2019 ◽

Vol 47 (15) ◽

pp. e85-e85 ◽

Cited By ~ 15

Author(s):

Fumihito Miura ◽

Yukiko Shibata ◽

Miki Miura ◽

Yuhei Sangatsuda ◽

Osamu Hisano ◽

...

Keyword(s):

Bisulfite Sequencing ◽

High Efficiency ◽

High Sensitivity ◽

Cost Effective ◽

Whole Genome ◽

Single Stranded Dna ◽

Random Priming ◽

Genome Bisulfite Sequencing ◽

Color Compensation

Abstract Whole-genome bisulfite sequencing (WGBS) is the current gold standard of methylome analysis. Post-bisulfite adaptor tagging (PBAT) is an increasingly popular WGBS protocol because of high sensitivity and low bias. PBAT originally relied on two rounds of random priming for adaptor-tagging of single-stranded DNA (ssDNA) to attain high efficiency but at a cost of library insert length. To overcome this limitation, we developed terminal deoxyribonucleotidyl transferase (TdT)-assisted adenylate connector-mediated ssDNA (TACS) ligation as an alternative to random priming. In this method, TdT attaches adenylates to the 3′-end of input ssDNA, which are then utilized by RNA ligase as an efficient connector to the ssDNA adaptor. A protocol that uses TACS ligation instead of the second random priming step substantially increased the lengths of PBAT library fragments. Moreover, we devised a dual-library strategy that splits the input DNA to prepare two libraries with reciprocal adaptor polarity, combining them prior to sequencing. This strategy ensured an ideal base–color balance to eliminate the need for DNA spike-in for color compensation, further improving the throughput and quality of WGBS. Adopting the above strategies to the HiSeq X Ten and NovaSeq 6000 platforms, we established a cost-effective, high-quality WGBS, which should accelerate various methylome analyses.

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.1287v3 ◽

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.

OMIC-06. MOLECULAR SUBGROUPING OF MEDULLOBLASTOMA VIA LOW-DEPTH WHOLE GENOME BISULFITE SEQUENCING

Neuro-Oncology ◽

10.1093/neuonc/noab090.153 ◽

2021 ◽

Vol 23 (Supplement_1) ◽

pp. i38-i38

Author(s):

Dean Thompson ◽

Jemma Castle ◽

Debbie Hicks ◽

Steve Clifford ◽

Ed Schwalbe

Keyword(s):

Dna Methylation ◽

Bisulfite Sequencing ◽

Methylation Status ◽

Unmet Need ◽

Whole Genome ◽

Molecular Subgroups ◽

International Consensus ◽

Molecular Features ◽

Abstract Introduction International consensus recognises four molecular subgroups of medulloblastoma, each with distinct molecular features and clinical outcomes. The current gold-standard for subgroup assignment is DNA methylation microarray. There is an unmet need to develop platform-independent subgrouping assays which are both non-proprietary and compatible with rapidly-expanding WGS capacity in healthcare. Whole Genome Bisulfite Sequencing (WGBS) enables the assessment of genome-wide methylation status at single-base resolution. Previously, WGBS adoption has been limited by cost and sample quality/quantity requirements. Its application for routine detection of medulloblastoma subgroups has not previously been reported. Methodology Two datasets were utilised; 36 newly-sequenced low-depth (10x coverage) and 34 publicly-available high-depth (30x) WGBS medulloblastomas, all with matched DNA methylation microarray data. We compared platform concordance and identified molecular subgroups. Machine-learning WGBS-based subgroup classifiers were optimised and compared between platforms. Aneuploidy and mutation detection using WGBS was optimised and compared to microarray-derived estimates where possible. Finally, comprehensive subgroup-specific DNA methylation signatures were identified. Results We optimised a pipeline for processing, quality control and analysis of low-depth WGBS data, suitable for routine molecular subgrouping and aneuploidy assessment. We demonstrated the suitability of fresh-frozen and FFPE DNA for WGBS, and, using downsampling, showed that subgroup calling is robust at coverages as low as 2x. We identified differentially methylated regions that, due to poor representation, could not be detected using methylation microarrays. Molecular subgroups of medulloblastoma assigned using WGBS were concordant with array-based definitions, and WGBS-derived classifier performance measures exceeded microarray-derived classifiers. Conclusion We describe a platform-independent assay for molecular subgrouping of medulloblastoma using WGBS. It performs equivalently to current array-based methods at comparable cost ($405 vs $596) and provides a proof-of-concept for its routine clinical adoption using standard WGS technology. Finally, the full methylome enabled elucidation of additional biological heterogeneity that has hitherto been inaccessible.

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.

Benchmarking DNA Methylation Assays for Marine Invertebrates

10.1101/2020.02.10.943092 ◽

2020 ◽

Author(s):

Groves Dixon ◽

Mikhail Matz

Keyword(s):

Dna Methylation ◽

Bisulfite Sequencing ◽

Restriction Site ◽

Marine Invertebrates ◽

Cost Effective ◽

Whole Genome ◽

Ecological Research ◽

Chromatin Modifications ◽

AbstractInterrogation of chromatin modifications, such as DNA methylation, has potential to improve forecasting and conservation of marine ecosystems. The standard method for assaying DNA methylation (Whole Genome Bisulfite Sequencing), however, is too costly to apply at the scales required for ecological research. Here we evaluate different methods for measuring DNA methylation for ecological epigenetics. We compare Whole Genome Bisulfite Sequencing (WGBS) with Methylated CpG Binding Domain Sequencing (MBD-seq), and a modified version of MethylRAD we term methylation-dependent Restriction site-Associated DNA sequencing (mdRAD). We evaluate these three assays in measuring variation in methylation across the genome, between genotypes, and between polyp types in the reef-building coral Acropora millepora. We find that all three assays measure absolute methylation levels similarly, with tight correlations for methylation of gene bodies (gbM), as well as exons and 1Kb windows. Correlations for differential gbM between genotypes were weaker, but still concurrent across assays. We detected little to no reproducible differences in gbM between polyp types. We conclude that MBD-seq and mdRAD are reliable cost-effective alternatives to WGBS. Moreover, the considerably lower sequencing effort required for mdRAD to produce comparable methylation estimates makes it particularly useful for ecological epigenetics.