Quantitative and multiplexed DNA methylation analysis using long-read single-molecule real-time bisulfite sequencing (SMRT-BS)

BMC Genomics

Stuart A Scott²  John F DeCoteau¹  C Ronald Geyer¹  Robert J Desnick²  Inga Peter²  Wanqiong Qiao²  Benjamin S Pullman²  Robert Sebra³  Yao Yang² 

[1] Cancer Stem Cell Research Group, University of Saskatchewan, Saskatoon S7N 4H4, SK, Canada;Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA;Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York 10029, NY, USA

关键词: Pacific Bioscience;    Single-molecule real-time (SMRT) sequencing;    Third generation sequencing;    Long-read sequencing;    Bisulfite sequencing;    CpG islands;    DNA methylation;   

Others  :  1204053
DOI  :  10.1186/s12864-015-1572-7

 received in 2014-11-17, accepted in 2015-04-23,  发布年份 2015

【 摘 要 】

Background

DNA methylation has essential roles in transcriptional regulation, imprinting, X chromosome inactivation and other cellular processes, and aberrant CpG methylation is directly involved in the pathogenesis of human imprinting disorders and many cancers. To address the need for a quantitative and highly multiplexed bisulfite sequencing method with long read lengths for targeted CpG methylation analysis, we developed single-molecule real-time bisulfite sequencing (SMRT-BS).

Results

Optimized bisulfite conversion and PCR conditions enabled the amplification of DNA fragments up to ~1.5 kb, and subjecting overlapping 625–1491 bp amplicons to SMRT-BS indicated high reproducibility across all amplicon lengths (r = 0.972) and low standard deviations (≤0.10) between individual CpG sites sequenced in triplicate. Higher variability in CpG methylation quantitation was correlated with reduced sequencing depth, particularly for intermediately methylated regions. SMRT-BS was validated by orthogonal bisulfite-based microarray (r = 0.906; 42 CpG sites) and second generation sequencing (r = 0.933; 174 CpG sites); however, longer SMRT-BS amplicons (>1.0 kb) had reduced, but very acceptable, correlation with both orthogonal methods (r = 0.836-0.897 and r = 0.892-0.927, respectively) compared to amplicons less than ~1.0 kb (r = 0.940-0.951 and r = 0.948-0.963, respectively). Multiplexing utility was assessed by simultaneously subjecting four distinct CpG island amplicons (702–866 bp; 325 CpGs) and 30 hematological malignancy cell lines to SMRT-BS (average depth of 110X), which identified a spectrum of highly quantitative methylation levels across all interrogated CpG sites and cell lines.

Conclusions

SMRT-BS is a novel, accurate and cost-effective targeted CpG methylation method that is amenable to a high degree of multiplexing with minimal clonal PCR artifacts. Increased sequencing depth is necessary when interrogating longer amplicons (>1.0 kb) and the previously reported bisulfite sequencing PCR bias towards unmethylated DNA should be considered when measuring intermediately methylated regions. Coupled with an optimized bisulfite PCR protocol, SMRT-BS is capable of interrogating ~1.5 kb amplicons, which theoretically can cover ~91% of CpG islands in the human genome.

【 授权许可】

   
2015 Yang et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

【 参考文献 】

• [1]Jaenisch R, Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet. 2003; 33 Suppl:245-54.
• [2]Mohandas T, Sparkes RS, Shapiro LJ. Reactivation of an inactive human X chromosome: evidence for X inactivation by DNA methylation. Science. 1981; 211:393-6.
• [3]Baylin SB, Herman JG. DNA hypermethylation in tumorigenesis: epigenetics joins genetics. Trends Genet. 2000; 16:168-74.
• [4]Li E, Beard C, Jaenisch R. Role for DNA methylation in genomic imprinting. Nature. 1993; 366:362-5.
• [5]Meissner A, Gnirke A, Bell GW, Ramsahoye B, Lander ES, Jaenisch R. Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res. 2005; 33:5868-77.
• [6]Yang Y, Wang W, Li Y, Tu J, Bai Y, Xiao P et al.. Identification of methylated regions with peak search based on Poisson model from massively parallel methylated DNA immunoprecipitation-sequencing data. Electrophoresis. 2010; 31:3537-44.
• [7]Fouse SD, Nagarajan RO, Costello JF. Genome-scale DNA methylation analysis. Epigenomics. 2010; 2:105-17.
• [8]Plongthongkum N, Diep DH, Zhang K. Advances in the profiling of DNA modifications: cytosine methylation and beyond. Nat Rev Genet. 2014; 15:647-61.
• [9]Shanmuganathan R, Basheer NB, Amirthalingam L, Muthukumar H, Kaliaperumal R, Shanmugam K. Conventional and nanotechniques for DNA methylation profiling. J Mol Diagn. 2013; 15:17-26.
• [10]Frommer M, McDonald LE, Millar DS, Collis CM, Watt F, Grigg 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; 89:1827-31.
• [11]Choufani S, Shapiro JS, Susiarjo M, Butcher DT, Grafodatskaya D, Lou Y et al.. A novel approach identifies new differentially methylated regions (DMRs) associated with imprinted genes. Genome Res. 2011; 21:465-76.
• [12]Bliek J, Verde G, Callaway J, Maas SM, De Crescenzo A, Sparago A et al.. Hypomethylation at multiple maternally methylated imprinted regions including PLAGL1 and GNAS loci in Beckwith-Wiedemann syndrome. Eur J Hum Genet. 2009; 17:611-9.
• [13]Uhlmann K, Brinckmann A, Toliat MR, Ritter H, Nurnberg P. Evaluation of a potential epigenetic biomarker by quantitative methyl-single nucleotide polymorphism analysis. Electrophoresis. 2002; 23:4072-9.
• [14]Tost J, El abdalaoui H, Gut IG. Serial pyrosequencing for quantitative DNA methylation analysis. Biotechniques. 2006; 40:721-2.
• [15]Taylor KH, Kramer RS, Davis JW, Guo J, Duff DJ, Xu D et al.. Ultradeep bisulfite sequencing analysis of DNA methylation patterns in multiple gene promoters by 454 sequencing. Cancer Res. 2007; 67:8511-8.
• [16]Krueger F, Kreck B, Franke A, Andrews SR. DNA methylome analysis using short bisulfite sequencing data. Nat Methods. 2012; 9:145-51.
• [17]Paul DS, Guilhamon P, Karpathakis A, Butcher LM, Thirlwell C, Feber A et al.. Assessment of RainDrop BS-seq as a method for large-scale, targeted bisulfite sequencing. Epigenetics. 2014; 9:678-84.
• [18]Tost J, Gut IG. DNA methylation analysis by pyrosequencing. Nat Protoc. 2007; 2:2265-75.
• [19]Booth MJ, Ost TW, Beraldi D, Bell NM, Branco MR, Reik W et al.. Oxidative bisulfite sequencing of 5-methylcytosine and 5-hydroxymethylcytosine. Nat Protoc. 2013; 8:1841-51.
• [20]Stewart SK, Morris TJ, Guilhamon P, Bulstrode H, Bachman M, Balasubramanian S et al.. oxBS-450 K: A method for analysing hydroxymethylation using 450 K BeadChips. Methods. 2015; 72:9-15.
• [21]Gu H, Smith ZD, Bock C, Boyle P, Gnirke A, Meissner A. Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat Protoc. 2011; 6:468-81.
• [22]Adusumalli S, Mohd Omar MF, Soong R, Benoukraf T: Methodological aspects of whole-genome bisulfite sequencing analysis. Brief Bioinform 2014. [Epub ahead of print]
• [23]Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G et al.. Real-time DNA sequencing from single polymerase molecules. Science. 2009; 323:133-8.
• [24]Grunau C, Clark SJ, Rosenthal A. Bisulfite genomic sequencing: systematic investigation of critical experimental parameters. Nucleic Acids Res. 2001; 29:E65-65.
• [25]Warnecke PM, Stirzaker C, Song J, Grunau C, Melki JR, Clark SJ. Identification and resolution of artifacts in bisulfite sequencing. Methods. 2002; 27:101-7.
• [26]Tusnady GE, Simon I, Varadi A, Aranyi T. BiSearch: primer-design and search tool for PCR on bisulfite-treated genomes. Nucleic Acids Res. 2005; 33: Article ID e9
• [27]Li Y, Tollefsbol TO. DNA methylation detection: bisulfite genomic sequencing analysis. Methods Mol Biol. 2011; 791:11-21.
• [28]Su XZ, Wu Y, Sifri CD, Wellems TE. Reduced extension temperatures required for PCR amplification of extremely A + T-rich DNA. Nucleic Acids Res. 1996; 24:1574-5.
• [29]Rohde C, Zhang Y, Reinhardt R, Jeltsch A. BISMA–fast and accurate bisulfite sequencing data analysis of individual clones from unique and repetitive sequences. BMC Bioinformatics. 2010; 11:230. BioMed Central Full Text
• [30]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; 25:4422-6.
• [31]Varley KE, Gertz J, Bowling KM, Parker SL, Reddy TE, Pauli-Behn F et al.. Dynamic DNA methylation across diverse human cell lines and tissues. Genome Res. 2013; 23:555-67.
• [32]Flusberg BA, Webster DR, Lee JH, Travers KJ, Olivares EC, Clark TA et al.. Direct detection of DNA methylation during single-molecule, real-time sequencing. Nat Methods. 2010; 7:461-5.
• [33]Moskalev EA, Zavgorodnij MG, Majorova SP, Vorobjev IA, Jandaghi P, Bure IV et al.. Correction of PCR-bias in quantitative DNA methylation studies by means of cubic polynomial regression. Nucleic Acids Res. 2011; 39: Article ID e77
• [34]Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I et al.. Recommendations for the design and analysis of epigenome-wide association studies. Nat Methods. 2013; 10:949-55.
• [35]Paul DS, Beck S. Advances in epigenome-wide association studies for common diseases. Trends Mol Med. 2014; 20:541-3.
• [36]Gardiner-Garden M, Frommer M. CpG islands in vertebrate genomes. J Mol Biol. 1987; 196:261-82.
• [37]Scott SA, Khasawneh R, Peter I, Kornreich R, Desnick RJ. Combined CYP2C9, VKORC1 and CYP4F2 frequencies among racial and ethnic groups. Pharmacogenomics. 2010; 11:781-91.
• [38]Rasko DA, Webster DR, Sahl JW, Bashir A, Boisen N, Scheutz F et al.. Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. N Engl J Med. 2011; 365:709-17.
• [39]Breese MR, Liu Y. NGSUtils: a software suite for analyzing and manipulating next-generation sequencing datasets. Bioinformatics. 2013; 29:494-6.
• [40]Krueger F, Andrews SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011; 27:1571-2.
• [41]Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012; 9:357-9.
• [42]Wang D, Yan L, Hu Q, Sucheston LE, Higgins MJ, Ambrosone CB et al.. IMA: an R package for high-throughput analysis of Illumina’s 450 K Infinium methylation data. Bioinformatics. 2012; 28:729-30.