Literature DB >> 21412275

Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling.

Hongcang Gu1, Zachary D Smith, Christoph Bock, Patrick Boyle, Andreas Gnirke, Alexander Meissner.   

Abstract

Genome-wide mapping of 5-methylcytosine is of broad interest to many fields of biology and medicine. A variety of methods have been developed, and several have recently been advanced to genome-wide scale using arrays and next-generation sequencing approaches. We have previously reported reduced representation bisulfite sequencing (RRBS), a bisulfite-based protocol that enriches CG-rich parts of the genome, thereby reducing the amount of sequencing required while capturing the majority of promoters and other relevant genomic regions. The approach provides single-nucleotide resolution, is highly sensitive and provides quantitative DNA methylation measurements. This protocol should enable any standard molecular biology laboratory to generate RRBS libraries of high quality. Briefly, purified genomic DNA is digested by the methylation-insensitive restriction enzyme MspI to generate short fragments that contain CpG dinucleotides at the ends. After end-repair, A-tailing and ligation to methylated Illumina adapters, the CpG-rich DNA fragments (40-220 bp) are size selected, subjected to bisulfite conversion, PCR amplified and end sequenced on an Illumina Genome Analyzer. Note that alignment and analysis of RRBS sequencing reads are not covered in this protocol. The extremely low input requirements (10-300 ng), the applicability of the protocol to formalin-fixed and paraffin-embedded samples, and the technique's single-nucleotide resolution extends RRBS to a wide range of biological and clinical samples and research applications. The entire process of RRBS library construction takes ∼9 d.

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Year:  2011        PMID: 21412275     DOI: 10.1038/nprot.2010.190

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  31 in total

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Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

2.  Comprehensive high-throughput arrays for relative methylation (CHARM).

Authors:  Rafael A Irizarry; Christine Ladd-Acosta; Benilton Carvalho; Hao Wu; Sheri A Brandenburg; Jeffrey A Jeddeloh; Bo Wen; Andrew P Feinberg
Journal:  Genome Res       Date:  2008-03-03       Impact factor: 9.043

3.  Mapping short DNA sequencing reads and calling variants using mapping quality scores.

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Journal:  Genome Res       Date:  2008-08-19       Impact factor: 9.043

4.  Non-CpG methylation is prevalent in embryonic stem cells and may be mediated by DNA methyltransferase 3a.

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Journal:  Proc Natl Acad Sci U S A       Date:  2000-05-09       Impact factor: 11.205

5.  Methylated-CpG island recovery assay: a new technique for the rapid detection of methylated-CpG islands in cancer.

Authors:  Tibor Rauch; Gerd P Pfeifer
Journal:  Lab Invest       Date:  2005-09       Impact factor: 5.662

6.  Dynamic changes in the human methylome during differentiation.

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Journal:  Genome Res       Date:  2010-02-04       Impact factor: 9.043

7.  A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis.

Authors:  Thomas A Down; Vardhman K Rakyan; Daniel J Turner; Paul Flicek; Heng Li; Eugene Kulesha; Stefan Gräf; Nathan Johnson; Javier Herrero; Eleni M Tomazou; Natalie P Thorne; Liselotte Bäckdahl; Marlis Herberth; Kevin L Howe; David K Jackson; Marcos M Miretti; John C Marioni; Ewan Birney; Tim J P Hubbard; Richard Durbin; Simon Tavaré; Stephan Beck
Journal:  Nat Biotechnol       Date:  2008-07       Impact factor: 54.908

8.  High-resolution genome-wide cytosine methylation profiling with simultaneous copy number analysis and optimization for limited cell numbers.

Authors:  Mayumi Oda; Jacob L Glass; Reid F Thompson; Yongkai Mo; Emmanuel N Olivier; Maria E Figueroa; Rebecca R Selzer; Todd A Richmond; Xinmin Zhang; Luke Dannenberg; Roland D Green; Ari Melnick; Eli Hatchwell; Eric E Bouhassira; Amit Verma; Masako Suzuki; John M Greally
Journal:  Nucleic Acids Res       Date:  2009-04-22       Impact factor: 16.971

9.  Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution.

Authors:  Hongcang Gu; Christoph Bock; Tarjei S Mikkelsen; Natalie Jäger; Zachary D Smith; Eleni Tomazou; Andreas Gnirke; Eric S Lander; Alexander Meissner
Journal:  Nat Methods       Date:  2010-01-10       Impact factor: 28.547

10.  DNA methylation profiling of human chromosomes 6, 20 and 22.

Authors:  Florian Eckhardt; Joern Lewin; Rene Cortese; Vardhman K Rakyan; John Attwood; Matthias Burger; John Burton; Tony V Cox; Rob Davies; Thomas A Down; Carolina Haefliger; Roger Horton; Kevin Howe; David K Jackson; Jan Kunde; Christoph Koenig; Jennifer Liddle; David Niblett; Thomas Otto; Roger Pettett; Stefanie Seemann; Christian Thompson; Tony West; Jane Rogers; Alex Olek; Kurt Berlin; Stephan Beck
Journal:  Nat Genet       Date:  2006-10-29       Impact factor: 38.330

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  319 in total

1.  RRBSMAP: a fast, accurate and user-friendly alignment tool for reduced representation bisulfite sequencing.

Authors:  Yuanxin Xi; Christoph Bock; Fabian Müller; Deqiang Sun; Alexander Meissner; Wei Li
Journal:  Bioinformatics       Date:  2011-12-06       Impact factor: 6.937

Review 2.  Using DNA methylation to understand biological consequences of genetic variability.

Authors:  Dena G Hernandez; Andrew B Singleton
Journal:  Neurodegener Dis       Date:  2011-11-26       Impact factor: 2.977

3.  Isolation and cultivation of naive-like human pluripotent stem cells based on HERVH expression.

Authors:  Jichang Wang; Manvendra Singh; Chuanbo Sun; Daniel Besser; Alessandro Prigione; Zoltán Ivics; Laurence D Hurst; Zsuzsanna Izsvák
Journal:  Nat Protoc       Date:  2016-01-21       Impact factor: 13.491

4.  epiGBS: reference-free reduced representation bisulfite sequencing.

Authors:  Thomas P van Gurp; Niels C A M Wagemaker; Björn Wouters; Philippine Vergeer; Joop N J Ouborg; Koen J F Verhoeven
Journal:  Nat Methods       Date:  2016-02-08       Impact factor: 28.547

5.  Dysregulation of BRD4 Function Underlies the Functional Abnormalities of MeCP2 Mutant Neurons.

Authors:  Yangfei Xiang; Yoshiaki Tanaka; Benjamin Patterson; Sung-Min Hwang; Eriona Hysolli; Bilal Cakir; Kun-Yong Kim; Wanshan Wang; Young-Jin Kang; Ethan M Clement; Mei Zhong; Sang-Hun Lee; Yee Sook Cho; Prabir Patra; Gareth J Sullivan; Sherman M Weissman; In-Hyun Park
Journal:  Mol Cell       Date:  2020-06-10       Impact factor: 17.970

6.  Obesity-Associated Alterations in Inflammation, Epigenetics, and Mammary Tumor Growth Persist in Formerly Obese Mice.

Authors:  Emily L Rossi; Rebecca E de Angel; Laura W Bowers; Subreen A Khatib; Laura A Smith; Eric Van Buren; Priya Bhardwaj; Dilip Giri; Marcos R Estecio; Melissa A Troester; Brionna Y Hair; Erin L Kirk; Ting Gong; Jianjun Shen; Andrew J Dannenberg; Stephen D Hursting
Journal:  Cancer Prev Res (Phila)       Date:  2016-02-11

7.  Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing.

Authors:  Hongshan Guo; Ping Zhu; Fan Guo; Xianlong Li; Xinglong Wu; Xiaoying Fan; Lu Wen; Fuchou Tang
Journal:  Nat Protoc       Date:  2015-04-02       Impact factor: 13.491

8.  Inferring and modeling inheritance of differentially methylated changes across multiple generations.

Authors:  Pascal Belleau; Astrid Deschênes; Marie-Pier Scott-Boyer; Romain Lambrot; Mathieu Dalvai; Sarah Kimmins; Janice Bailey; Arnaud Droit
Journal:  Nucleic Acids Res       Date:  2018-08-21       Impact factor: 16.971

9.  Influence of the Prader-Willi syndrome imprinting center on the DNA methylation landscape in the mouse brain.

Authors:  Jason O Brant; Alberto Riva; James L Resnick; Thomas P Yang
Journal:  Epigenetics       Date:  2014-11       Impact factor: 4.528

10.  Role of DNA De Novo (De)Methylation in the Kidney in Salt-Induced Hypertension.

Authors:  Pengyuan Liu; Yong Liu; Han Liu; Xiaoqing Pan; Yingchuan Li; Kristie Usa; Manoj K Mishra; Jing Nie; Mingyu Liang
Journal:  Hypertension       Date:  2018-11       Impact factor: 10.190

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