A comprehensive evaluation of alignment software for reduced representation bisulfite sequencing data

Reduced representation bisulfite sequencing (RRBS), which couples bisulfite conversion and next generation sequencing, is an innovative method that specifically enriches genomic regions with a high density of potential methylation sites and enables investigation of DNA methylation at single-nucleotide resolution. Recent advances in the Illumina DNA sample preparation protocol and sequencing technology have vastly improved sequencing throughput capacity. Although the new Illumina technology is now widely used, the unique challenges associated with multiplexed RRBS libraries on this platform have not been previously described. We have made modifications to the RRBS library preparation protocol to sequence multiplexed libraries on a single flow cell lane of the Illumina HiSeq 2000. Furthermore, our analysis incorporates a bioinformatics pipeline specifically designed to process bisulfite-converted sequencing reads and evaluate the output and quality of the sequencing data generated from the multiplexed libraries. We obtained an average of 42 million paired-end reads per sample for each flow-cell lane, with a high unique mapping efficiency to the reference human genome. Here we provide a roadmap of modifications, strategies, and trouble shooting approaches we implemented to optimize sequencing of multiplexed libraries on an a RRBS background.

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Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.671302 ◽

2021 ◽

Vol 9 ◽

Author(s):

Xubin Zheng ◽

Qiong Wu ◽

Haonan Wu ◽

Kwong-Sak Leung ◽

Man-Hon Wong ◽

...

Keyword(s):

Liver Cancer ◽

Dna Sequences ◽

Bisulfite Sequencing ◽

Differentially Methylated Region ◽

Sequencing Data ◽

Reduced Representation ◽

Targeted Bisulfite Sequencing ◽

Differentially Methylated Genes ◽

Genome Bisulfite Sequencing ◽

Bisulfite Sequencing Data

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.

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Sperm DNA methylation altered by THC and nicotine: Vulnerability of neurodevelopmental genes with bivalent chromatin

Scientific Reports ◽

10.1038/s41598-020-72783-0 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Rose Schrott ◽

Maya Rajavel ◽

Kelly Acharya ◽

Zhiqing Huang ◽

Chaitanya Acharya ◽

...

Keyword(s):

Dna Methylation ◽

Sequencing Data ◽

Oral Gavage ◽

Reduced Representation ◽

Reduced Representation Bisulfite Sequencing ◽

Sperm Dna ◽

Bisulfite Sequencing Data ◽

Sperm Epigenetics ◽

Sperm Dna Methylation ◽

Active Genes

Abstract Men consume the most nicotine and cannabis products but impacts on sperm epigenetics are poorly characterized. Evidence suggests that preconception exposure to these drugs alters offspring neurodevelopment. Epigenetics may in part facilitate heritability. We therefore compared effects of exposure to tetrahydrocannabinol (THC) and nicotine on DNA methylation in rat sperm at genes involved in neurodevelopment. Reduced representation bisulfite sequencing data from sperm of rats exposed to THC via oral gavage showed that seven neurodevelopmentally active genes were significantly differentially methylated versus controls. Pyrosequencing data revealed majority overlap in differential methylation in sperm from rats exposed to THC via injection as well as those exposed to nicotine. Neurodevelopmental genes including autism candidates are vulnerable to environmental exposures and common features may mediate this vulnerability. We discovered that autism candidate genes are significantly enriched for bivalent chromatin structure, suggesting this configuration may increase vulnerability of genes in sperm to disrupted methylation.

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Using long-read sequencing to detect imprinted DNA methylation

10.1101/445924 ◽

2018 ◽

Cited By ~ 5

Author(s):

Scott Gigante ◽

Quentin Gouil ◽

Alexis Lucattini ◽

Andrew Keniry ◽

Tamara Beck ◽

...

Keyword(s):

Critical Role ◽

Subsequent Development ◽

Sequencing Data ◽

Reduced Representation ◽

Cpg Sites ◽

Reduced Representation Bisulfite Sequencing ◽

Long Read ◽

Bisulfite Sequencing Data ◽

Reported Data ◽

Control Regions

Systematic variation in the methylation of cytosines at CpG sites plays a critical role in early development of humans and other mammals. Of particular interest are regions of differential methylation between parental alleles, as these often dictate monoallelic gene expression, resulting in parent of origin specific control of the embryonic transcriptome and subsequent development, in a phenomenon known as genomic imprinting. Using long-read nanopore sequencing we show that, with an average genomic coverage of approximately ten, it is possible to determine both the level of methylation of CpG sites and the haplotype from which each read arises. The long-read property is exploited to characterise, using novel methods, both methylation and haplotype for reads that have reduced basecalling precision compared to Sanger sequencing. We validate the analysis both through comparison of nanopore-derived methylation patterns with those from Reduced Representation Bisulfite Sequencing data and through comparison with previously reported data.Our analysis successfully identifies known imprinting control regions as well as some novel differentially methylated regions which, due to their proximity to hitherto unknown monoallelically expressed genes, may represent new imprinting control regions.

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Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18157975 ◽

2021 ◽

Vol 18 (15) ◽

pp. 7975

Author(s):

Yongjun Piao ◽

Wanxue Xu ◽

Kwang Ho Park ◽

Keun Ho Ryu ◽

Rong Xiang

Keyword(s):

Bisulfite Sequencing ◽

Comprehensive Evaluation ◽

Differential Methylation ◽

Sequencing Depth ◽

Sequencing Data ◽

Methylation Analysis ◽

Sequencing Technologies ◽

Analysis Methods ◽

Bisulfite Sequencing Data ◽

Differential Methylation Analysis

Background: With advances in next-generation sequencing technologies, the bisulfite conversion of genomic DNA followed by sequencing has become the predominant technique for quantifying genome-wide DNA methylation at single-base resolution. A large number of computational approaches are available in literature for identifying differentially methylated regions in bisulfite sequencing data, and more are being developed continuously. Results: Here, we focused on a comprehensive evaluation of commonly used differential methylation analysis methods and describe the potential strengths and limitations of each method. We found that there are large differences among methods, and no single method consistently ranked first in all benchmarking. Moreover, smoothing seemed not to improve the performance greatly, and a small number of replicates created more difficulties in the computational analysis of BS-seq data than low sequencing depth. Conclusions: Data analysis and interpretation should be performed with great care, especially when the number of replicates or sequencing depth is limited.

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BiSulfite Bolt: A bisulfite sequencing analysis platform

GigaScience ◽

10.1093/gigascience/giab033 ◽

2021 ◽

Vol 10 (5) ◽

Author(s):

Colin Farrell ◽

Michael Thompson ◽

Anela Tosevska ◽

Adewale Oyetunde ◽

Matteo Pellegrini

Keyword(s):

Data Aggregation ◽

Bisulfite Sequencing ◽

Low Complexity ◽

Sequencing Analysis ◽

Command Line ◽

Sequencing Data ◽

Bisulfite Sequencing Data ◽

Analysis Platform ◽

Python Package ◽

Bisulfite Sequencing Analysis

Abstract Background Bisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries. Findings We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy. Conclusion BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

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