Multiplexed Reduced Representation Bisulfite Sequencing with Magnetic Bead Fragment Size Selection

  • William P. AccomandoJr.
  • Karin B. Michels
Part of the Methods in Molecular Biology book series (MIMB, volume 1708)


Reduced representation bisulfite sequencing (RRBS) is a technique for assessing genome-wide DNA methylation in an organism whose genome has been fully sequenced. It allows researchers to target gene regions with particular CpG densities, thereby selecting the desired genomic contexts. Here, we describe an approach that uses magnetic beads to accomplish this selection. In addition, the use of indexed, methylated adapters enables up to 12 samples to be pooled, and subjected to multiplexed RRBS in a single-sequencing lane. First, genomic DNA is fragmented via restriction endonuclease digestion that ensures at least two CpG loci per fragment. The fragmented DNA is then end-repaired and A-tailed. Indexed, methylated adapters are ligated to the A-tailed DNA fragments to create a DNA library. A combination of negative and positive selections, using magnetic beads that preferentially bind to larger DNA fragments, ensures that only the desired sizes of adapter-ligated DNA fragments are included in a library. This allows researchers to dictate what types of genomic regions will be sequenced, since fragment size depends on the proximity of restriction sites. The DNA libraries are then quantified, and up to 12 libraries are pooled in order to be sequenced on a single lane of an Illumina HiSeq2500. The pools are next treated with sodium bisulfite, and then PCR amplified. A final bead cleanup removes any residual contaminants prior to sequencing, which is followed by base calling and alignment to a sequenced genome.

Key words

Reduced representation bisulfite sequencing (RRBS) mRRBS Epigenetics DNA methylation 



The authors would like to acknowledge Alexander Meissner, Juan Carmona, Benedetta Izzi, and Alexandra Binder for their significant contributions to the development and optimization of this protocol. Dr. Accomando was supported by Training Grant T32CA09001 in Cancer Epidemiology from the National Cancer Institute, National Institutes of Health. Dr. Michels was supported in part by research grant R01CA158313 from the National Cancer Institute, National Institutes of Health.


  1. 1.
    Berger SL, Kouzarides T, Shiekhattar R et al (2009) An operational definition of epigenetics. Genes Dev 23:781–783CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Zaidi SK, Young DW, Montecino M et al (2011) Bookmarking the genome: maintenance of epigenetic information. J Biol Chem 286:18355–18361CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Khavari DA, Sen GL, Rinn JL (2010) DNA methylation and epigenetic control of cellular differentiation. Cell Cycle 9:3880–3883CrossRefPubMedGoogle Scholar
  4. 4.
    Shi H, Wang MX, Caldwell CW (2007) CpG islands: their potential as biomarkers for cancer. Expert Rev Mol Diagn 7:519–531CrossRefPubMedGoogle Scholar
  5. 5.
    Lande-Diner L, Cedar H (2005) Silence of the genes--mechanisms of long-term repression. Nat Rev Genet 6:648–654CrossRefPubMedGoogle Scholar
  6. 6.
    Miranda TB, Jones PA (2007) DNA methylation: the nuts and bolts of repression. J Cell Physiol 213:384–390CrossRefPubMedGoogle Scholar
  7. 7.
    Jones PA (2012) Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet 13:484–492CrossRefPubMedGoogle Scholar
  8. 8.
    Bock C, Tomazou EM, Brinkman AB et al (2010) Quantitative comparison of genome-wide DNA methylation mapping technologies. Nat Biotechnol 28:1106–1114CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Smallwood SA, Kelsey G (2012) Genome-wide analysis of DNA methylation in low cell numbers by reduced representation bisulfite sequencing. Methods Mol Biol 925:187–197CrossRefPubMedGoogle Scholar
  10. 10.
    Boyle P, Clement K, Gu H et al (2012) Gel-free multiplexed reduced representation bisulfite sequencing for large-scale DNA methylation profiling. Genome Biol 13:R92CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Gu H, Smith ZD, Bock C et al (2011) Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat Protoc 6:468–481CrossRefPubMedGoogle Scholar
  12. 12.
    Meissner A, Gnirke A, Bell GW et al (2005) Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33:5868–5877CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Krueger F, Andrews SR (2011) Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27:1571–1572CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 18:1851–1858CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Xi Y, Bock C, Muller F et al (2012) RRBSMAP: a fast, accurate and user-friendly alignment tool for reduced representation bisulfite sequencing. Bioinformatics 28:430–432CrossRefPubMedGoogle Scholar
  16. 16.
    Park Y, Figueroa ME, Rozek LS et al (2014) MethylSig: a whole genome DNA methylation analysis pipeline. Bioinformatics 30:2414–2422CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Sun Z, Baheti S, Middha S et al (2012) SAAP-RRBS: streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing. Bioinformatics 28:2180–2181CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Wang T, Liu Q, Li X et al (2013) RRBS-analyser: a comprehensive web server for reduced representation bisulfite sequencing data analysis. Hum Mutat 34:1606–1610CrossRefPubMedGoogle Scholar
  19. 19.
    Coarfa C, Yu F, Miller CA et al (2010) Pash 3.0: a versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing. BMC Bioinformatics 11:572CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Sun D, Xi Y, Rodriguez B et al (2014) MOABS: model based analysis of bisulfite sequencing data. Genome Biol 15:R38CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    NEB Next Ultra DNA Library Prep Kit for Illumina: Instruction Manual (2013). New England Biolabs, Inc., Ipswich, MAGoogle Scholar
  22. 22.
    Meissner A, Mikkelsen TS, Gu H et al (2008) Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 454:766–770PubMedPubMedCentralGoogle Scholar
  23. 23.
    Gu H, Bock C, Mikkelsen TS et al (2010) Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution. Nat Methods 7:133–136CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Darst RP, Pardo CE, Ai L et al (2010) Bisulfite sequencing of DNA. Curr Protoc Mol Biol Chapter 7:Unit 7.9.1–Unit 7.917Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2018

Authors and Affiliations

  1. 1.Department of EpidemiologyHarvard School of Public HealthBostonUSA
  2. 2.Obstetrics and Gynecology Epidemiology Center, Department of Obstetrics, Gynecology, and Reproductive BiologyBrigham and Women’s HospitalBostonUSA
  3. 3.Department of Epidemiology, Fielding School of Public HealthUniversity of CaliforniaLos AngelesUSA

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