Comparison of whole-genome bisulfite sequencing library preparation strategies identifies sources of biases affecting DNA methylation data

Nelly Olova, Felix Krueger, Simon Andrews and 4 more

Genome Biology · 2018

Abstract

Background. Whole-genome bisulfite sequencing (WGBS) is becoming an increasingly accessible technique, used widely for both fundamental and disease-oriented research. Library preparation methods benefit from a variety of available kits, polymerases and bisulfite conversion protocols. Although some steps in the procedure, such as PCR amplification, are known to introduce biases, a systematic evaluation of biases in WGBS strategies is missing.

Results. We perform a comparative analysis of several commonly used pre- and post-bisulfite WGBS library preparation protocols for their performance and quality of sequencing outputs. Our results show that bisulfite conversion per se is the main trigger of pronounced sequencing biases, and PCR amplification builds on these underlying artefacts. The majority of standard library preparation methods yield a significantly biased sequence output and overestimate global methylation. Importantly, both absolute and relative methylation levels at specific genomic regions vary substantially between methods, with clear implications for DNA methylation studies.

Conclusions. We show that amplification-free library preparation is the least biased approach for WGBS. In protocols with amplification, the choice of bisulfite conversion protocol or polymerase can significantly minimize artefacts. To aid with the quality assessment of existing WGBS datasets, we have integrated a bias diagnostic tool in the Bismark package and offer several approaches for consideration during the preparation and analysis of WGBS datasets.

Electronic supplementary material. The online version of this article (10.1186/s13059-018-1408-2) contains supplementary material, which is available to authorized users.

References 70

1.
Frommer M, Mcdonald LE, Millar DS, Collist CM, Wattt F, Griggt GW, et al. A genomic sequencing protocol that yields a positive display of 5-methylcytosine residues in individual DNA strands. Proc Natl Acad Sci U S A. 1992;89:1827-1831.
Not in our library10.1073/pnas.89.5.1827
2.
Grunau C, Clark SJ, Rosenthal A. Bisulfite genomic sequencing: systematic investigation of critical experimental parameters. Nucleic Acids Res. 2001;29:E65.
Not in our library10.1093/nar/29.13.e65
3.
Warnecke PM, Stirzaker C, Song J, Grunau C, Melki JR, Clark SJ. Identification and resolution of artifacts in bisulfite sequencing. Methods. 2002;27:101-107.
Not in our library10.1016/s1046-2023(02)00060-9
4.
Harris RA, Wang T, Coarfa C, Nagarajan RP, Hong C, Downey SL, et al. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications. Nat Biotechnol. 2010;28:1097-1105.
Not in our library10.1038/nbt.1682
5.
Genereux DP, Johnson WC, Burden AF, Stöger R, Laird CD. Errors in the bisulfite conversion of DNA: modulating inappropriate- and failed-conversion frequencies. Nucleic Acids Res. 2008;36:e150.
Not in our library10.1093/nar/gkn691
6.
Warnecke PM, Stirzaker C, Melki JR, Millar DS, Paul CL, Clark SJ. Detection and measurement of PCR bias in quantitative methylation analysis of bisulphite-treated DNA. Nucleic Acids Res. 1997;25:4422-4426.
Not in our library10.1093/nar/25.21.4422
7.
Raizis AM, Schmitt F, Jost JP. A bisulfite method of 5-methylcytosine mapping that minimizes template degradation. Anal Biochem. 1995;226(1):161-166.
Not in our library10.1006/abio.1995.1204
8.
Holmes EE, Jung M, Meller S, Leisse A, Sailer V, Zech J, et al. Performance evaluation of kits for bisulfite-conversion of DNA from tissues, cell lines, FFPE tissues, aspirates, lavages, effusions, plasma, serum, and urine. PLoS One. 2014;9:1-15.
Not in our library10.1371/journal.pone.0093933
9.
Henderson IR, Chan SR, Cao X, Johnson L, Jacobsen SE. Accurate sodium bisulfite sequencing in plants. Epigenetics. 2010;5:47-49.
Not in our library10.4161/epi.5.1.10560
10.
Hayatsu H, Tsuji K, Negishi K. Does urea promote the bisulfite-mediated deamination of cytosine in DNA? Investigation aiming at speeding-up the procedure for DNA methylation analysis. Nucleic Acids Symp Ser (Oxf). 2006;50:69-70.
Not in our library10.1093/nass/nrl034
11.
Harrison J, Stirzaker C, Clark SJ. Cytosines adjacent to methylated CpG sites can be partially resistant to conversion in genomic bisulfite sequencing leading to methylation artifacts. Anal Biochem. 1998;264:129-132.
Not in our library10.1006/abio.1998.2833
12.
Chhibber A, Schroeder BG. Single-molecule polymerase chain reaction reduces bias: application to DNA methylation analysis by bisulfite sequencing. Anal Biochem. 2008;377:46-54.
Not in our library10.1016/j.ab.2008.02.026
13.
Voss KO, Roos KP, Nonay RL, Dovichi NJ. Combating PCR bias in bisulfite-based cytosine methylation analysis. Betaine-modified cytosine deamination PCR. Anal Chem. 1998;70:3818-3823.
Not in our library10.1021/ac980067t
14.
Shiraishi M, Hayatsu H. High-speed conversion of cytosine to uracil in bisulfite genomic sequencing analysis of DNA methylation. DNA Res. 2004;11:409-415.
Not in our library10.1093/dnares/11.6.409
15.
Candiloro ILM, Mikeska T, Dobrovic A. Assessing alternative base substitutions at primer CpG sites to optimise unbiased PCR amplification of methylated sequences. Clin Epigenetics. 2017;9:1-9.
Not in our library10.1186/s13148-017-0328-4
16.
Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries · 2011
No notice
17.
Dabney J, Meyer M. Length and GC-biases during sequencing library amplification: a comparison of various polymerase-buffer systems with ancient and modern DNA sequencing libraries. Biotechniques. 2012;52(2):87-94.
Not in our library10.2144/000113809
18.
Characterizing and measuring bias in sequence data · 2013
No notice
19.
Quail MA, Otto TD, Gu Y, Harris SR, Skelly TF, McQuillan JA, et al. Optimal enzymes for amplifying sequencing libraries. Nat Methods. 2011;9:10-11.
Not in our library10.1038/nmeth.1814
20.
Optimizing illumina next-generation sequencing library preparation for extremely at-biased genomes · 2012
No notice
21.
Sources of PCR-induced distortions in high-throughput sequencing data sets · 2015
No notice
22.
Kozarewa I, Ning Z, Quail MA, Sanders MJ, Berriman M, Turner DJ, et al. Amplification-free Illumina sequencing-library preparation facilitates improved mapping and assembly of (G+C)-biased genomes. Nat Methods. 2009;6:291-295.
Not in our library10.1038/nmeth.1311
23.
Ji L, Sasaki T, Sun X, Ma P, Lewis ZA, Schmitz RJ. Methylated DNA is over-represented in whole-genome bisulfite sequencing data. Front Genet. 2014;5:1-10.
Not in our library10.3389/fgene.2014.00341
24.
Tanaka K, Okamoto A. Degradation of DNA by bisulfite treatment. Bioorg Med Chem Lett. 2007;17:1912-1915.
Not in our library10.1016/j.bmcl.2007.01.040
25.
Hayatsu H, Negishi K, Shiraishi M. DNA methylation analysis: speedup of bisulfite-mediated deamination of cytosine in the genomic sequencing procedure. Proc Japan Acad Ser B. 2004;80:189-194.
Not in our library10.2183/pjab.80.189
26.
Lister R, O’Malley RC, Tonti-Filippini J, Gregory BD, Berry CC, Millar AH, et al. Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell. 2008;133:523-536.
Not in our library10.1016/j.cell.2008.03.029
27.
Cokus SJ, Feng S, Zhang X, Chen Z, Merriman B, Haudenschild CD, et al. Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature. 2008;452:215-219.
Not in our library10.1038/nature06745
28.
Miura F, Enomoto Y, Dairiki R, Ito T. Amplification-free whole-genome bisulfite sequencing by post-bisulfite adaptor tagging. Nucleic Acids Res. 2012;40:e136.
Not in our library10.1093/nar/gks454
29.
Contribution of Intragenic DNA Methylation in Mouse Gametic DNA Methylomes to Establish Oocyte-Specific Heritable Marks · 2012
No notice
30.
Mouse Oocyte Methylomes at Base Resolution Reveal Genome-Wide Accumulation of Non-CpG Methylation and Role of DNA Methyltransferases · 2013
No notice
31.
Smallwood S, Lee HJ, Angermueller C, Krueger F, Saadeh H, Peat J, et al. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods. 2014;11:817–20.
Not in our library10.1038/nmeth.3035
32.
Genome-wide Bisulfite Sequencing in Zygotes Identifies Demethylation Targets and Maps the Contribution of TET3 Oxidation · 2014
Not checked
33.
Genome-Wide Analysis of DNA Methylation Dynamics during Early Human Development · 2014
No notice
34.
Dai H-Q, Wang B-A, Yang L, Chen J-J, Zhu G-C, Sun M-L, et al. TET-mediated DNA demethylation controls gastrulation by regulating Lefty–Nodal signalling. Nature. 2016;538:528-532.
Not in our library10.1038/nature20095
35.
Khanna A, Czyz A, Syed F. EpiGnome™ Methyl-Seq Kit: a novel post-bisulfite conversion library prep method for methylation analysis. Nat Publ Gr. 2013;10:iii-iiv.
Not in our library
36.
Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics · 2015
No notice
37.
Ficz G, Branco MR, Seisenberger S, Santos F, Krueger F, Hore TA, et al. Dynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation. Nature. 2011;473:398-402.
Not in our library10.1038/nature10008
38.
Comprehensive genome and epigenome characterization of CHO cells in response to evolutionary pressures and over time · 2016
No notice
39.
Milagre I, Stubbs TM, King MR, Spindel J, Santos F, Krueger F, et al. Gender differences in global but not targeted demethylation in iPSC reprogramming. Cell Rep. 2017;18:1079-1089.
Not in our library10.1016/j.celrep.2017.01.008
40.
The Dynamics of Genome-wide DNA Methylation Reprogramming in Mouse Primordial Germ Cells · 2012
No notice

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