Literature DB >> 29036576

cuRRBS: simple and robust evaluation of enzyme combinations for reduced representation approaches.

Daniel E Martin-Herranz1, António J M Ribeiro1, Felix Krueger2, Janet M Thornton1, Wolf Reik3,4,5, Thomas M Stubbs3.   

Abstract

DNA methylation is an important epigenetic modification in many species that is critical for development, and implicated in ageing and many complex diseases, such as cancer. Many cost-effective genome-wide analyses of DNA modifications rely on restriction enzymes capable of digesting genomic DNA at defined sequence motifs. There are hundreds of restriction enzyme families but few are used to date, because no tool is available for the systematic evaluation of restriction enzyme combinations that can enrich for certain sites of interest in a genome. Herein, we present customised Reduced Representation Bisulfite Sequencing (cuRRBS), a novel and easy-to-use computational method that solves this problem. By computing the optimal enzymatic digestions and size selection steps required, cuRRBS generalises the traditional MspI-based Reduced Representation Bisulfite Sequencing (RRBS) protocol to all restriction enzyme combinations. In addition, cuRRBS estimates the fold-reduction in sequencing costs and provides a robustness value for the personalised RRBS protocol, allowing users to tailor the protocol to their experimental needs. Moreover, we show in silico that cuRRBS-defined restriction enzymes consistently out-perform MspI digestion in many biological systems, considering both CpG and CHG contexts. Finally, we have validated the accuracy of cuRRBS predictions for single and double enzyme digestions using two independent experimental datasets.
© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2017        PMID: 29036576      PMCID: PMC5714207          DOI: 10.1093/nar/gkx814

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  63 in total

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Journal:  Genome Res       Date:  2011-07-14       Impact factor: 9.043

2.  Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates.

Authors:  Hao Wu; Tianlei Xu; Hao Feng; Li Chen; Ben Li; Bing Yao; Zhaohui Qin; Peng Jin; Karen N Conneely
Journal:  Nucleic Acids Res       Date:  2015-07-15       Impact factor: 16.971

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6.  Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements.

Authors:  Weiwei Zhang; Tim D Spector; Panos Deloukas; Jordana T Bell; Barbara E Engelhardt
Journal:  Genome Biol       Date:  2015-01-24       Impact factor: 13.583

7.  Multi-tissue DNA methylation age predictor in mouse.

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8.  Double restriction-enzyme digestion improves the coverage and accuracy of genome-wide CpG methylation profiling by reduced representation bisulfite sequencing.

Authors:  Junwen Wang; Yudong Xia; Lili Li; Desheng Gong; Yu Yao; Huijuan Luo; Hanlin Lu; Na Yi; Honglong Wu; Xiuqing Zhang; Qian Tao; Fei Gao
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Journal:  Nucleic Acids Res       Date:  2015-11-03       Impact factor: 16.971

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Journal:  Nucleic Acids Res       Date:  2018-04-06       Impact factor: 16.971

3.  "Same difference": comprehensive evaluation of four DNA methylation measurement platforms.

Authors:  Thadeous J Kacmarczyk; Mame P Fall; Xihui Zhang; Yuan Xin; Yushan Li; Alicia Alonso; Doron Betel
Journal:  Epigenetics Chromatin       Date:  2018-05-25       Impact factor: 4.954

4.  Screening for genes that accelerate the epigenetic aging clock in humans reveals a role for the H3K36 methyltransferase NSD1.

Authors:  Daniel E Martin-Herranz; Erfan Aref-Eshghi; Marc Jan Bonder; Thomas M Stubbs; Sanaa Choufani; Rosanna Weksberg; Oliver Stegle; Bekim Sadikovic; Wolf Reik; Janet M Thornton
Journal:  Genome Biol       Date:  2019-08-14       Impact factor: 13.583

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