Literature DB >> 35064762

Analysis and Performance Assessment of the Whole Genome Bisulfite Sequencing Data Workflow: Currently Available Tools and a Practical Guide to Advance DNA Methylation Studies.

Ting Gong1, Heather Borgard1, Zao Zhang2, Shaoqiu Chen1, Zitong Gao1, Youping Deng1.   

Abstract

DNA methylation is associated with transcriptional repression, genomic imprinting, stem cell differentiation, embryonic development, and inflammation. Aberrant DNA methylation can indicate disease states, including cancer and neurological disorders. Therefore, the prevalence and location of 5-methylcytosine in the human genome is a topic of interest. Whole-genome bisulfite sequencing (WGBS) is a high-throughput method for analyzing DNA methylation. This technique involves library preparation, alignment, and quality control. Advancements in epigenetic technology have led to an increase in DNA methylation studies. This review compares the detailed experimental methodology of WGBS using accessible and up-to-date analysis tools. Practical codes for WGBS data processing are included as a general guide to assist progress in DNA methylation studies through a comprehensive case study.
© 2022 Wiley-VCH GmbH.

Entities:  

Keywords:  DNA methylation; alignment algorithm comparison; library preparation methods; methylation data analysis pipeline; whole genome bisulfite sequencing

Mesh:

Substances:

Year:  2022        PMID: 35064762      PMCID: PMC8963483          DOI: 10.1002/smtd.202101251

Source DB:  PubMed          Journal:  Small Methods        ISSN: 2366-9608


  83 in total

Review 1.  DNA methylation and human disease.

Authors:  Keith D Robertson
Journal:  Nat Rev Genet       Date:  2005-08       Impact factor: 53.242

2.  BRAT-BW: efficient and accurate mapping of bisulfite-treated reads.

Authors:  Elena Y Harris; Nadia Ponts; Karine G Le Roch; Stefano Lonardi
Journal:  Bioinformatics       Date:  2012-05-03       Impact factor: 6.937

3.  Oxidative bisulfite sequencing of 5-methylcytosine and 5-hydroxymethylcytosine.

Authors:  Michael J Booth; Tobias W B Ost; Dario Beraldi; Neil M Bell; Miguel R Branco; Wolf Reik; Shankar Balasubramanian
Journal:  Nat Protoc       Date:  2013-09-05       Impact factor: 13.491

4.  DNA methylation restrains transposons from adopting a chromatin signature permissive for meiotic recombination.

Authors:  Natasha Zamudio; Joan Barau; Aurélie Teissandier; Marius Walter; Maté Borsos; Nicolas Servant; Déborah Bourc'his
Journal:  Genes Dev       Date:  2015-06-15       Impact factor: 11.361

5.  BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data.

Authors:  Weilong Guo; Petko Fiziev; Weihong Yan; Shawn Cokus; Xueguang Sun; Michael Q Zhang; Pao-Yang Chen; Matteo Pellegrini
Journal:  BMC Genomics       Date:  2013-11-10       Impact factor: 3.969

6.  Cluster Flow: A user-friendly bioinformatics workflow tool.

Authors:  Philip Ewels; Felix Krueger; Max Käller; Simon Andrews
Journal:  F1000Res       Date:  2016-12-06

7.  SPlinted Ligation Adapter Tagging (SPLAT), a novel library preparation method for whole genome bisulphite sequencing.

Authors:  Amanda Raine; Erika Manlig; Per Wahlberg; Ann-Christine Syvänen; Jessica Nordlund
Journal:  Nucleic Acids Res       Date:  2017-04-07       Impact factor: 16.971

8.  Systematic evaluation of library preparation methods and sequencing platforms for high-throughput whole genome bisulfite sequencing.

Authors:  Li Zhou; Hong Kiat Ng; Daniela I Drautz-Moses; Stephan C Schuster; Stephan Beck; Changhoon Kim; John Campbell Chambers; Marie Loh
Journal:  Sci Rep       Date:  2019-07-17       Impact factor: 4.379

9.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

10.  BAT: Bisulfite Analysis Toolkit: BAT is a toolkit to analyze DNA methylation sequencing data accurately and reproducibly. It covers standard processing and analysis steps from raw read mapping up to annotation data integration and calculation of correlating DMRs.

Authors:  Helene Kretzmer; Christian Otto; Steve Hoffmann
Journal:  F1000Res       Date:  2017-08-16
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