DNA Methylation Data Analysis Using Msuite.

Xiaojian Liu, Pengxiang Yuan, Kun Sun
Author Information
  1. Xiaojian Liu: Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, China.
  2. Pengxiang Yuan: Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, China.
  3. Kun Sun: Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, China. sunkun@szbl.ac.cn.

Abstract

DNA methylation is a widespread epigenetic modification responsible for many biological regulation pathways. The development of various powerful biochemical assays, including conventional bisulfite treatment-based and emerging bisulfite-free techniques, has promised high-resolution DNA methylome profiling and significantly propelled the DNA methylation research field. However, the analysis of large-scale data generated from such assays is still complex and challenging. In this paper, we present a step-by-step protocol for using Msuite for whole-spectrum DNA methylation data analysis, from quality control, read alignment, to methylation call and data visualization. The Msuite package and a testing dataset are freely available at https://github.com/hellosunking/Msuite.

Keywords

References

  1. Yin Y, Morgunova E, Jolma A, Kaasinen E, Sahu B, Khund-Sayeed S, Das PK, Kivioja T, Dave K, Zhong F et al (2017) Impact of cytosine methylation on DNA binding specificities of human transcription factors. Science 356:eaaj2239. https://doi.org/10.1126/science.aaj2239 [DOI: 10.1126/science.aaj2239]
  2. Baylin SB, Jones PA (2011) A decade of exploring the cancer epigenome – biological and translational implications. Nat Rev Cancer 11:726–734. https://doi.org/10.1038/nrc3130 [DOI: 10.1038/nrc3130]
  3. Zemach A, McDaniel IE, Silva P, Zilberman D (2010) Genome-wide evolutionary analysis of eukaryotic DNA methylation. Science 328:916–919. https://doi.org/10.1126/science.1186366 [DOI: 10.1126/science.1186366]
  4. Feng S, Jacobsen SE, Reik W (2010) Epigenetic reprogramming in plant and animal development. Science 330:622–627. https://doi.org/10.1126/science.1190614 [DOI: 10.1126/science.1190614]
  5. Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, Zhang X, Bernstein BE, Nusbaum C, Jaffe DB (2008) Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 454:766–770. https://doi.org/10.1038/nature07107 [DOI: 10.1038/nature07107]
  6. Boyle P, Clement K, Gu H, Smith ZD, Ziller M, Fostel JL, Holmes L, Meldrim J, Kelley F, Gnirke A (2012) Gel-free multiplexed reduced representation bisulfite sequencing for large-scale DNA methylation profiling. Genome Biol 13:1–10. https://doi.org/10.1186/gb-2012-13-10-r92 [DOI: 10.1186/gb-2012-13-10-r92]
  7. Meissner A, Gnirke A, Bell GW, Ramsahoye B, Lander ES, Jaenisch R (2005) Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33:5868–5877. https://doi.org/10.1093/nar/gki901 [DOI: 10.1093/nar/gki901]
  8. Sun K, Jiang P, Chan KCA, Wong J, Cheng YK, Liang RH, Chan WK, Ma ES, Chan SL, Cheng SH et al (2015) Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments. Proc Natl Acad Sci U S A 112:E5503–E5512. https://doi.org/10.1073/pnas.1508736112 [DOI: 10.1073/pnas.1508736112]
  9. Gu H, Smith ZD, Bock C, Boyle P, Gnirke A, Meissner A (2011) Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat Protoc 6:468–481. https://doi.org/10.1038/nprot.2010.190 [DOI: 10.1038/nprot.2010.190]
  10. Luo C, Hajkova P, Ecker JR (2018) Dynamic DNA methylation: in the right place at the right time. Science 361:1336–1340. https://doi.org/10.1126/science.aat6806 [DOI: 10.1126/science.aat6806]
  11. Greenberg MVC, Bourc’his D (2019) The diverse roles of DNA methylation in mammalian development and disease. Nat Rev Mol Cell Biol 20:590–607. https://doi.org/10.1038/s41580-019-0159-6 [DOI: 10.1038/s41580-019-0159-6]
  12. Yoder JA, Walsh CP, Bestor TH (1997) Cytosine methylation and the ecology of intragenomic parasites. Trends Genet 13:335–340. https://doi.org/10.1016/s0168-9525(97)01181-5 [DOI: 10.1016/s0168-9525(97)01181-5]
  13. Liu Y, Siejka-Zielinska P, Velikova G, Bi Y, Yuan F, Tomkova M, Bai C, Chen L, Schuster-Bockler B, Song CX (2019) Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat Biotechnol 37:424–429. https://doi.org/10.1038/s41587-019-0041-2 [DOI: 10.1038/s41587-019-0041-2]
  14. Sun K, Li L, Ma L, Zhao Y, Deng L, Wang H, Sun H (2020) Msuite: a high-performance and versatile DNA methylation data-analysis toolkit. Patterns (NY) 1:100127. https://doi.org/10.1016/j.patter.2020.100127 [DOI: 10.1016/j.patter.2020.100127]
  15. Zeng H, He B, Xia B, Bai D, Lu X, Cai J, Chen L, Zhou A, Zhu C, Meng H et al (2018) Bisulfite-free, nanoscale analysis of 5-hydroxymethylcytosine at single base resolution. J Am Chem Soc 140:13190–13194. https://doi.org/10.1021/jacs.8b08297 [DOI: 10.1021/jacs.8b08297]
  16. Sun K (2020) Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data. Bioinformatics 36:3561–3562. https://doi.org/10.1093/bioinformatics/btaa171 [DOI: 10.1093/bioinformatics/btaa171]
  17. Barnett KR, Decato BE, Scott TJ, Hansen TJ, Chen B, Attalla J, Smith AD, Hodges E (2020) ATAC-Me captures prolonged DNA methylation of dynamic chromatin accessibility loci during cell fate transitions. Mol Cell 77:1350–1364 e1356. https://doi.org/10.1016/j.molcel.2020.01.004 [DOI: 10.1016/j.molcel.2020.01.004]
  18. Sun K, Lun FFM, Jiang P, Sun H (2017) BSviewer: a genotype-preserving, nucleotide-level visualizer for bisulfite sequencing data. Bioinformatics 33:3495–3496. https://doi.org/10.1093/bioinformatics/btx505 [DOI: 10.1093/bioinformatics/btx505]
  19. Sun K, Jiang P, Wong AIC, Cheng YKY, Cheng SH, Zhang H, Chan KCA, Leung TY, Chiu RWK, Lo YMD (2018) Size-tagged preferred ends in maternal plasma DNA shed light on the production mechanism and show utility in noninvasive prenatal testing. Proc Natl Acad Sci U S A 115:E5106–E5114. https://doi.org/10.1073/pnas.1804134115 [DOI: 10.1073/pnas.1804134115]
  20. Li L, An Y, Ma L, Yang M, Yuan P, Liu X, Jin X, Zhao Y, Zhang S, Hong X, Sun K (2022) Msuite2: all-in-one DNA methylation data analysis toolkit with enhanced usability and performance. Comput Struct Biotechnol J 20:1271–1276. https://doi.org/10.1016/j.csbj.2022.03.005

MeSH Term

DNA Methylation
Epigenesis, Genetic
Data Analysis
Sequence Analysis, DNA
Sulfites
CpG Islands
Software

Chemicals

Sulfites

Word Cloud

Created with Highcharts 10.0.0DNAmethylationdataMsuiteassaysanalysisvisualizationDatawidespreadepigeneticmodificationresponsiblemanybiologicalregulationpathwaysdevelopmentvariouspowerfulbiochemicalincludingconventionalbisulfitetreatment-basedemergingbisulfite-freetechniquespromisedhigh-resolutionmethylomeprofilingsignificantlypropelledresearchfieldHoweverlarge-scalegeneratedstillcomplexchallengingpaperpresentstep-by-stepprotocolusingwhole-spectrumqualitycontrolreadalignmentcallpackagetestingdatasetfreelyavailablehttps://githubcom/hellosunking/MsuiteMethylationAnalysisUsingBisulfitesequencingCpGdinucleotides

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