CoChat
Sign Up
Cited by 374Epigenetics and DNA MethylationGenomics and Chromatin DynamicsGenetic Syndromes and Imprinting

Profiling genome-wide DNA methylation

Open access
Yong, Wai-Shin, Hsu, Fei-Man, Chen, Pao-Yang·2016·Epigenetics & Chromatin
DOI 10.1186/s13072-016-0075-3PMC PMC4926291
Open this paper in CoChat — free accountOpen PDF

Abstract

DNA methylation is an epigenetic modification that plays an important role in regulating gene expression and therefore a broad range of biological processes and diseases. DNA methylation is tissue-specific, dynamic, sequence-context-dependent and trans-generationally heritable, and these complex patterns of methylation highlight the significance of profiling DNA methylation to answer biological questions. In this review, we surveyed major methylation assays, along with comparisons and biological examples, to provide an overview of DNA methylation profiling techniques. The advances in microarray and sequencing technologies make genome-wide profiling possible at a single-nucleotide or even a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, genomic region coverage, and bioinformatics analysis, and selecting a feasible method requires knowledge of these methods. We first introduce the biological background of DNA methylation and its pattern in plants, animals and fungi. We present an overview of major experimental approaches to profiling genome-wide DNA methylation and hydroxymethylation and then extend to the single-cell methylome. To evaluate these methods, we outline their strengths and weaknesses and perform comparisons across the different platforms. Due to the increasing need to compute high-throughput epigenomic data, we interrogate the computational pipeline for bisulfite sequencing data and also discuss the concept of identifying differentially methylated regions (DMRs). This review summarizes the experimental and computational concepts for profiling genome-wide DNA methylation, followed by biological examples. Overall, this review provides researchers useful guidance for the selection of a profiling method suited to specific research questions.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13072-016-0075-3

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • 5mC is detectable by RT-PCR using methylation-specific primers, resulting in amplicons that can then be sequenced via next-generation sequencing or identified by whole-genome methylation arrays.

    “5mC is then detectable by a subsequent RT-PCR step by use of methylation-specific primers (these vary per study), which will result in thousands of amplicons that can then be sequenced via next-generation sequencing or identified by whole-genome methylation arrays (Yong et al., 2016).”

    From The Epigenetics of Anxiety Pathophysiology: A DNA Methylation and Histone Modification Focused Review (2023) · cites this paper as Yong et al., 2016

    The Bisulfite conversion-based methods section (page unavailable) says methylation can be assessed after bisulfite treatment and PCR, and describes both sequencing and methylation arrays. It does not describe an RT-PCR step using methylation-specific primers, thousands of resulting amplicons, or those amplicons being identified by whole-genome methylation arrays; its array protocol instead uses amplification followed by hybridization to predesigned probes. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 123 · Cited by 374

Research works printed but not linked: 114

  1. [2]Kim KD El Baidouri M Jackson SA Accessing epigenetic variation in the plant methylome Brief Funct Genomics 2014 13 318 327 10.1093/bfgp/elu003 24562692 · DOI
  2. [3]Berkyurek AC Suetake I Arita K Takeshita K Nakagawa A Shirakawa M The DNA methyltransferase Dnmt1 directly interacts with the SET and RING finger-associated (SRA) domain of the multifunctional protein Uhrf1 to facilitate accession of the catalytic center to hemi-methylated DNA J Biol Chem 2014 289 379 386 10.1074/jbc.M113.523209 24253042 PMC3879560 · DOI
  3. [4]Okano M Bell DW Haber DA Li E DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development Cell 1999 99 247 257 10.1016/S0092-8674(00)81656-6 10555141 · DOI · Paper page
  4. [5]Kinde B Gabel HW Gilbert CS Griffith EC Greenberg ME Reading the unique DNA methylation landscape of the brain: non-CpG methylation, hydroxymethylation, and MeCP2 Proc Natl Acad Sci USA 2015 112 6800 6806 10.1073/pnas.1411269112 25739960 PMC4460470 · DOI · Paper page
  5. [6]Wilson GA Dhami P Feber A Cortázar D Suzuki Y Schulz R Resources for methylome analysis suitable for gene knockout studies of potential epigenome modifiers Gigascience. 2012 1 3 10.1186/2047-217X-1-3 23587164 PMC3617451 · DOI
  6. [7]Jones PA Functions of DNA methylation: islands, start sites, gene bodies and beyond Nat Rev Genet 2012 13 484 492 10.1038/nrg3230 22641018 · DOI · Paper page
  7. [8]Li Q Xu W Cui Y Ma L Richards J Li W A preliminary exploration on DNA methylation of transgene across generations in transgenic rats Sci Rep 2015 5 8292 10.1038/srep08292 25659774 PMC4321119 · DOI
  8. [9]Hackett JA Surani MA DNA methylation dynamics during the mammalian life cycle Philos Trans R Soc Lond B Biol Sci 2013 368 20110328 10.1098/rstb.2011.0328 23166392 PMC3539357 · DOI
  9. [10]Fu Y Luo GZ Chen K Deng X Yu M Han D N6-methyldeoxyadenosine marks active transcription start sites in Chlamydomonas Cell 2015 161 879 892 10.1016/j.cell.2015.04.010 25936837 PMC4427561 · DOI
  10. [11]Greer EL Blanco MA Gu L Sendinc E Liu J Aristizábal-Corrales D DNA methylation on N6-Adenine in C. elegans Cell 2015 161 868 878 10.1016/j.cell.2015.04.005 25936839 PMC4427530 · DOI
  11. [12]Zhang G Huang H Liu D Cheng Y Liu X Zhang W N6-methyladenine DNA modification in Drosophila Cell 2015 161 893 906 10.1016/j.cell.2015.04.018 25936838 · DOI
  12. [13]Koziol MJ Bradshaw CR Allen GE Costa AS Frezza C Gurdon JB Identification of methylated deoxyadenosines in vertebrates reveals diversity in DNA modifications Nat Struct Mol Biol 2016 23 24 30 10.1038/nsmb.3145 26689968 PMC4941928 · DOI
  13. [14]Plongthongkum N Diep DH Zhang K Advances in the profiling of DNA modifications: cytosine methylation and beyond Nat Rev Genet 2014 15 647 661 10.1038/nrg3772 25159599 · DOI
  14. [15]Chen PY Feng S Joo JW Jacobsen SE Pellegrini M A comparative analysis of DNA methylation across human embryonic stem cell lines Genome Biol 2011 12 R62 10.1186/gb-2011-12-7-r62 21733148 PMC3218824 · DOI
  15. [16]Lyko F Ramsahoye BH Jaenisch R DNA methylation in Drosophila melanogaster Nature 2000 408 538 540 10.1038/35046205 11117732 · DOI
  16. [17]Xiang H Zhu J Chen Q Dai F Li X Li M Single base-resolution methylome of the silkworm reveals a sparse epigenomic map Nat Biotechnol 2010 28 516 520 10.1038/nbt.1626 20436463 · DOI
  17. [18]Cokus SJ Feng S Zhang X Chen Z Merriman B Haudenschild CD Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning Nature 2008 452 215 219 10.1038/nature06745 18278030 PMC2377394 · DOI
  18. [19]Gent JI Ellis NA Guo L Harkess AE Yao Y Zhang X CHH islands: de novo DNA methylation in near-gene chromatin regulation in maize Genome Res 2013 23 628 637 10.1101/gr.146985.112 23269663 PMC3613580 · DOI
  19. [20]Law JA Jacobsen SE Establishing, maintaining and modifying DNA methylation patterns in plants and animals Nat Rev Genet 2010 11 204 220 10.1038/nrg2719 20142834 PMC3034103 · DOI
  20. [21]Montanini B Chen PY Morselli M Jaroszewicz A Lopez D Martin F Non-exhaustive DNA methylation-mediated transposon silencing in the black truffle genome, a complex fungal genome with massive repeat element content Genome Biol 2014 15 411 10.1186/s13059-014-0411-5 25091826 PMC4165359 · DOI
  21. [22]Lister R Pelizzola M Dowen RH Hawkins RD Hon G Tonti-Filippini J Human DNA methylomes at base resolution show widespread epigenomic differences Nature 2009 462 315 322 10.1038/nature08514 19829295 PMC2857523 · DOI · Paper page
  22. [23]Feng S Cokus SJ Zhang X Chen PY Bostick M Goll MG Conservation and divergence of methylation patterning in plants and animals Proc Natl Acad Sci USA 2010 107 8689 8694 10.1073/pnas.1002720107 20395551 PMC2889301 · DOI · Paper page
  23. [24]Yoder JA Walsh CP Bestor TH Cytosine methylation and the ecology of intragenomic parasites Trends Genet 1997 13 335 340 10.1016/S0168-9525(97)01181-5 9260521 · DOI
  24. [25]Laurent L Wong E Li G Huynh T Tsirigos A Ong CT Dynamic changes in the human methylome during differentiation Genome Res 2010 20 320 331 10.1101/gr.101907.109 20133333 PMC2840979 · DOI
  25. [27]Lu X Wang W Ren W Chai Z Guo W Chen R Genome-wide epigenetic regulation of gene transcription in maize seeds PLoS ONE 2015 10 e0139582 10.1371/journal.pone.0139582 26469520 PMC4607434 · DOI
  26. [28]Regulski M Lu Z Kendall J Donoghue MT Reinders J Llaca V The maize methylome influences mRNA splice sites and reveals widespread paramutation-like switches guided by small RNA Genome Res 2013 23 1651 1662 10.1101/gr.153510.112 23739895 PMC3787262 · DOI
  27. [29]Lisanti S Omar WA Tomaszewski B De Prins S Jacobs G Koppen G Comparison of methods for quantification of global DNA methylation in human cells and tissues PLoS ONE 2013 8 e79044 10.1371/journal.pone.0079044 24260150 PMC3832524 · DOI
  28. [30]Laird PW Principles and challenges of genomewide DNA methylation analysis Nat Rev Genet 2010 11 191 203 10.1038/nrg2732 20125086 · DOI
  29. [32]Maunakea AK Nagarajan RP Bilenky M Ballinger TJ D’Souza C Fouse SD Conserved role of intragenic DNA methylation in regulating alternative promoters Nature 2010 466 253 257 10.1038/nature09165 20613842 PMC3998662 · DOI · Paper page
  30. [33]Li D Zhang B Xing X Wang T Combining MeDIP-seq and MRE-seq to investigate genome-wide CpG methylation Methods 2015 72 29 40 10.1016/j.ymeth.2014.10.032 25448294 PMC4300244 · DOI
  31. [34]Irizarry RA Ladd-Acosta C Carvalho B Wu H Brandenburg SA Jeddeloh JA Comprehensive high-throughput arrays for relative methylation (CHARM) Genome Res 2008 18 780 790 10.1101/gr.7301508 18316654 PMC2336799 · DOI
  32. [35]Sutherland E Coe L Raleigh EA McrBC: a multisubunit GTP-dependent restriction endonuclease J Mol Biol 1992 225 327 348 10.1016/0022-2836(92)90925-A 1317461 · DOI
  33. [36]Irizarry RA Ladd-Acosta C Wen B Wu Z Montano C Onyango P The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores Nat Genet 2009 41 178 186 10.1038/ng.298 19151715 PMC2729128 · DOI · Paper page
  34. [37]Brinkman AB Simmer F Ma K Kaan A Zhu J Stunnenberg HG Whole-genome DNA methylation profiling using MethylCap-seq Methods 2010 52 232 236 10.1016/j.ymeth.2010.06.012 20542119 · DOI
  35. [38]Serre D Lee BH Ting AH MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome Nucleic Acids Res 2010 38 391 399 10.1093/nar/gkp992 19906696 PMC2811030 · DOI · Paper page
  36. [39]Zhao MT Whyte JJ Hopkins GM Kirk MD Prather RS Methylated DNA immunoprecipitation and high-throughput sequencing (MeDIP-seq) using low amounts of genomic DNA Cell Reprogram. 2014 16 175 184 10.1089/cell.2014.0002 24773292 · DOI
  37. [40]Weng YI Huang TH Yan PS Methylated DNA immunoprecipitation and microarray-based analysis: detection of DNA methylation in breast cancer cell lines Methods Mol Biol 2009 590 165 176 10.1007/978-1-60327-378-7_10 19763503 PMC2845920 · DOI
  38. [41]Clark C Palta P Joyce CJ Scott C Grundberg E Deloukas P A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip((R)) for methylome profiling PLoS ONE 2012 7 e50233 10.1371/journal.pone.0050233 23209683 PMC3510246 · DOI
  39. [42]Taiwo O Wilson GA Morris T Seisenberger S Reik W Pearce D Methylome analysis using MeDIP-seq with low DNA concentrations Nat Protoc 2012 7 617 636 10.1038/nprot.2012.012 22402632 · DOI
  40. [43]Robinson MD Stirzaker C Statham AL Coolen MW Song JZ Nair SS Evaluation of affinity-based genome-wide DNA methylation data: effects of CpG density, amplification bias, and copy number variation Genome Res 2010 20 1719 1729 10.1101/gr.110601.110 21045081 PMC2989998 · DOI
  41. [44]Down TA Rakyan VK Turner DJ Flicek P Li H Kulesha E A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis Nat Biotechnol 2008 26 779 785 10.1038/nbt1414 18612301 PMC2644410 · DOI
  42. [45]Bock C Tomazou EM Brinkman AB Muller F Simmer F Gu H Quantitative comparison of genome-wide DNA methylation mapping technologies Nat Biotechnol 2010 28 1106 1114 10.1038/nbt.1681 20852634 PMC3066564 · DOI
  43. [46]Frommer M McDonald LE Millar DS Collis CM Watt F Grigg GW 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 10.1073/pnas.89.5.1827 1542678 PMC48546 · DOI · Paper page
  44. [48]Stirzaker C Taberlay PC Statham AL Clark SJ Mining cancer methylomes: prospects and challenges Trends Genet 2014 30 75 84 10.1016/j.tig.2013.11.004 24368016 · DOI
  45. [49]Bakulski KM Feinberg JI Andrews SV Yang J Brown S McKenney SL DNA methylation of cord blood cell types: applications for mixed cell birth studies Epigenetics 2014 11 354 362 10.1080/15592294.2016.1161875 27019159 PMC4889293 · DOI
  46. [50]Moran S Arribas C Esteller M Validation of a DNA methylation microarray for 850,000 CpG sites of the human genome enriched in enhancer sequences Epigenomics. 2016 8 389 399 10.2217/epi.15.114 26673039 PMC4864062 · DOI
  47. [51]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 6 468 481 10.1038/nprot.2010.190 21412275 · DOI
  48. [52]Urich MA Nery JR Lister R Schmitz RJ Ecker JR MethylC-seq library preparation for base-resolution whole-genome bisulfite sequencing Nat Protoc 2015 10 475 483 10.1038/nprot.2014.114 25692984 PMC4465251 · DOI
  49. [53]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 5 341 10.3389/fgene.2014.00341 25374580 PMC4204604 · DOI
  50. [54]Lister R O’Malley RC Tonti-Filippini J Gregory BD Berry CC Millar AH Highly integrated single-base resolution maps of the epigenome in Arabidopsis Cell 2008 133 523 536 10.1016/j.cell.2008.03.029 18423832 PMC2723732 · DOI
  51. [55]Hsieh TF Ibarra CA Silva P Zemach A Eshed-Williams L Fischer RL Genome-wide demethylation of Arabidopsis endosperm Science 2009 324 1451 1454 10.1126/science.1172417 19520962 PMC4044190 · DOI
  52. [56]Bernstein BE Stamatoyannopoulos JA Costello JF Ren B Milosavljevic A Meissner A The NIH roadmap epigenomics mapping consortium Nat Biotechnol 2010 28 1045 1048 10.1038/nbt1010-1045 20944595 PMC3607281 · DOI · Paper page
  53. [57]Encode Project Consortium An integrated encyclopedia of DNA elements in the human genome Nature 2012 489 57 74 10.1038/nature11247 22955616 PMC3439153 · DOI · Paper page
  54. [58]Adams D Altucci L Antonarakis SE Ballesteros J Beck S Bird A BLUEPRINT to decode the epigenetic signature written in blood Nat Biotechnol 2012 30 224 226 10.1038/nbt.2153 22398613 · DOI
  55. [61]Smith ZD Gu H Bock C Gnirke A Meissner A High-throughput bisulfite sequencing in mammalian genomes Methods 2009 48 226 232 10.1016/j.ymeth.2009.05.003 19442738 PMC2864123 · DOI
  56. [62]Orozco LD Morselli M Rubbi L Guo W Go J Shi H Epigenome-wide association of liver methylation patterns and complex metabolic traits in mice Cell Metab 2015 21 905 917 10.1016/j.cmet.2015.04.025 26039453 PMC4454894 · DOI
  57. [63]Chatterjee A Ozaki Y Stockwell PA Horsfield JA Morison IM Nakagawa S Mapping the zebrafish brain methylome using reduced representation bisulfite sequencing Epigenetics. 2013 8 979 989 10.4161/epi.25797 23975027 PMC3883775 · DOI
  58. [64]Pegoraro M Bafna A Davies NJ Shuker DM Tauber E DNA methylation changes induced by long and short photoperiods in Nasonia Genome Res 2016 26 203 210 10.1101/gr.196204.115 26672019 PMC4728373 · DOI
  59. [65]Platt A Gugger PF Pellegrini M Sork VL Genome-wide signature of local adaptation linked to variable CpG methylation in oak populations Mol Ecol 2015 24 3823 3830 10.1111/mec.13230 25951436 · DOI
  60. [66]Chen X Ge X Wang J Tan C King GJ Liu K Genome-wide DNA methylation profiling by modified reduced representation bisulfite sequencing in Brassica rapa suggests that epigenetic modifications play a key role in polyploid genome evolution Front Plant Sci. 2015 6 836 26500672 PMC4598586
  61. [70]Guo H Zhu P Guo F Li X Wu X Fan X Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing Nat Protoc 2015 10 645 659 10.1038/nprot.2015.039 25837417 · DOI · Paper page
  62. [71]Schwartzman O Tanay A Single-cell epigenomics: techniques and emerging applications Nat Rev Genet 2015 16 716 726 10.1038/nrg3980 26460349 · DOI
  63. [72]Smallwood SA Lee HJ Angermueller C Krueger F Saadeh H Peat J Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity Nat Methods 2014 11 817 820 10.1038/nmeth.3035 25042786 PMC4117646 · DOI · Paper page
  64. [73]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 10.1093/nar/gks454 22649061 PMC3458524 · DOI
  65. [74]Farlik M Sheffield NC Nuzzo A Datlinger P Schönegger A Klughammer J Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics Cell Rep. 2015 10 1386 1397 10.1016/j.celrep.2015.02.001 25732828 PMC4542311 · DOI · Paper page
  66. [75]Bachman M Uribe-Lewis S Yang X Williams M Murrell A Balasubramanian S 5-Hydroxymethylcytosine is a predominantly stable DNA modification Nat Chem. 2014 6 1049 1055 10.1038/nchem.2064 25411882 PMC4382525 · DOI
  67. [76]Wu H Zhang Y Charting oxidized methylcytosines at base resolution Nat Struct Mol Biol 2015 22 656 661 10.1038/nsmb.3136 26333715 PMC4671372 · DOI
  68. [77]Huang Y Pastor WA Shen Y Tahiliani M Liu DR Rao A The behaviour of 5-hydroxymethylcytosine in bisulfite sequencing PLoS ONE 2010 5 e8888 10.1371/journal.pone.0008888 20126651 PMC2811190 · DOI
  69. [78]Nestor CE Meehan RR Hydroxymethylated DNA immunoprecipitation (hmeDIP) Methods Mol Biol 2014 1094 259 267 10.1007/978-1-62703-706-8_20 24162994 · DOI
  70. [79]Booth MJ Ost TW Beraldi D Bell NM Branco MR Reik W Oxidative bisulfite sequencing of 5-methylcytosine and 5-hydroxymethylcytosine Nat Protoc 2013 8 1841 1851 10.1038/nprot.2013.115 24008380 PMC3919000 · DOI
  71. [80]Song CX Yi C He C Mapping recently identified nucleotide variants in the genome and transcriptome Nat Biotechnol 2012 30 1107 1116 10.1038/nbt.2398 23138310 PMC3537840 · DOI
  72. [81]Yu M Hon GC Szulwach KE Song CX Jin P Ren B Tet-assisted bisulfite sequencing of 5-hydroxymethylcytosine Nat Protoc 2012 7 2159 2170 10.1038/nprot.2012.137 23196972 PMC3641661 · DOI
  73. [82]Nazor KL Boland MJ Bibikova M Klotzle B Yu M Glenn-Pratola VL Application of a low cost array-based technique—TAB-Array—for quantifying and mapping both 5mC and 5hmC at single base resolution in human pluripotent stem cells Genomics 2014 104 358 367 10.1016/j.ygeno.2014.08.014 25179373 PMC4342188 · DOI
  74. [83]Gkountela S Zhang KX Shafiq TA Liao WW Hargan-Calvopina J Chen PY DNA Demethylation Dynamics in the Human Prenatal Germline Cell 2015 161 1425 1436 10.1016/j.cell.2015.05.012 26004067 PMC4458157 · DOI
  75. [84]Schadt EE Turner S Kasarskis A A window into third-generation sequencing Hum Mol Genet 2010 19 R227 R240 10.1093/hmg/ddq416 20858600 · DOI
  76. [85]Eid J Fehr A Gray J Luong K Lyle J Otto G Real-time DNA sequencing from single polymerase molecules Science 2009 323 133 138 10.1126/science.1162986 19023044 · DOI · Paper page
  77. [86]Chen PY Pellegrini M Meyers RA Methylomes Reviews in cell biology and molecular medicine 2012 Hoboken, NJ Wiley
  78. [87]Roberts RJ Carneiro MO Schatz MC The advantages of SMRT sequencing Genome Biol 2013 14 405 10.1186/gb-2013-14-6-405 23822731 PMC3953343 · DOI
  79. [88]Wu TP Wang T Seetin MG Lai Y Zhu S Lin K DNA methylation on N(6)-adenine in mammalian embryonic stem cells Nature 2016 532 329 333 10.1038/nature17640 27027282 PMC4977844 · DOI · Paper page
  80. [90]Rhoads A Au KF PacBio sequencing and its applications Genomics Proteomics Bioinf 2015 13 278 289 10.1016/j.gpb.2015.08.002 PMC4678779 26542840 · DOI
  81. [91]Bock C Analysing and interpreting DNA methylation data Nat Rev Genet 2012 13 705 719 10.1038/nrg3273 22986265 · DOI
  82. [93]Benoukraf T Wongphayak S Hadi LH Wu M Soong R GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data Nucleic Acids Res 2013 41 e55 10.1093/nar/gks1281 23268441 PMC3575794 · DOI
  83. [94]Sun Z Baheti S Middha S Kanwar R Zhang Y Li X SAAP-RRBS: streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing Bioinformatics 2012 28 2180 2181 10.1093/bioinformatics/bts337 22689387 PMC3413387 · DOI
  84. [95]Gao S Zou D Mao L Zhou Q Jia W Huang Y SMAP: a streamlined methylation analysis pipeline for bisulfite sequencing Gigascience. 2015 4 29 10.1186/s13742-015-0070-9 26140213 PMC4488126 · DOI
  85. [96]Krueger F Andrews SR Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications Bioinformatics 2011 27 1571 1572 10.1093/bioinformatics/btr167 21493656 PMC3102221 · DOI
  86. [97]Harris EY Ponts N Le Roch KG Lonardi S BRAT-BW: efficient and accurate mapping of bisulfite-treated reads Bioinformatics 2012 28 1795 1796 10.1093/bioinformatics/bts264 22563065 PMC3381974 · DOI
  87. [98]Guo W Fiziev P Yan W Cokus S Sun X Zhang MQ BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data BMC Genom 2013 14 774 10.1186/1471-2164-14-774 PMC3840619 24206606 · DOI
  88. [99]Pedersen B Hsieh TF Ibarra C Fischer RL MethylCoder: software pipeline for bisulfite-treated sequences Bioinformatics 2011 27 2435 2436 10.1093/bioinformatics/btr394 21724594 PMC3157921 · DOI
  89. [100]Wu TD Reeder J Lawrence M Becker G Brauer MJ GMAP and GSNAP for genomic sequence alignment: enhancements to speed, accuracy, and functionality Methods Mol Biol 2016 1418 283 334 10.1007/978-1-4939-3578-9_15 27008021 · DOI
  90. [101]Kielbasa SM Wan R Sato K Horton P Frith MC Adaptive seeds tame genomic sequence comparison Genome Res 2011 21 487 493 10.1101/gr.113985.110 21209072 PMC3044862 · DOI
  91. [102]Sun Z Cunningham J Slager S Kocher JP Base resolution methylome profiling: considerations in platform selection, data preprocessing and analysis Epigenomics. 2015 7 813 828 10.2217/epi.15.21 26366945 PMC4790440 · DOI
  92. [103]Xi Y Li W BSMAP: whole genome bisulfite sequence MAPping program BMC Bioinf 2009 10 232 10.1186/1471-2105-10-232 PMC2724425 19635165 · DOI
  93. [104]Fujita PA Rhead B Zweig AS Hinrichs AS Karolchik D Cline MS The UCSC genome browser database: update 2011 Nucleic Acids Res 2011 39 D876 D882 10.1093/nar/gkq963 20959295 PMC3242726 · DOI
  94. [105]Liang F Tang B Wang Y Wang J Yu C Chen X WBSA: web service for bisulfite sequencing data analysis PLoS ONE 2014 9 e86707 10.1371/journal.pone.0086707 24497972 PMC3907392 · DOI
  95. [106]Thorvaldsdóttir H Robinson JT Mesirov JP Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration Brief Bioinform. 2013 14 178 192 10.1093/bib/bbs017 22517427 PMC3603213 · DOI · Paper page
  96. [107]Mallona I Díez-Villanueva A Peinado MA Methylation plotter: a web tool for dynamic visualization of DNA methylation data Source Code Biol Med 2014 9 11 10.1186/1751-0473-9-11 25260021 PMC4066318 · DOI
  97. [108]Hu K Ting AH Li J BSPAT: a fast online tool for DNA methylation co-occurrence pattern analysis based on high-throughput bisulfite sequencing data BMC Bioinformatics 2015 16 220 10.1186/s12859-015-0649-2 26163275 PMC4499179 · DOI
  98. [109]Liao WW Yen MR Ju E Hsu FM Lam L Chen PY MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data BMC Genom 2015 16 Suppl 12 S11 10.1186/1471-2164-16-S12-S11 PMC4682368 26680022 · DOI
  99. [110]Hansen KD Langmead B Irizarry RA BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions Genome Biol 2012 13 R83 10.1186/gb-2012-13-10-r83 23034175 PMC3491411 · DOI
  100. [111]Choufani S Shapiro JS Susiarjo M Butcher DT Grafodatskaya D Lou Y A novel approach identifies new differentially methylated regions (DMRs) associated with imprinted genes Genome Res 2011 21 465 476 10.1101/gr.111922.110 21324877 PMC3044860 · DOI
  101. [112]Akalin A Kormaksson M Li S Garrett-Bakelman FE Figueroa ME Melnick A methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles Genome Biol 2012 13 R87 10.1186/gb-2012-13-10-r87 23034086 PMC3491415 · DOI
  102. [113]Park Y Figueroa ME Rozek LS Sartor MA MethylSig: a whole genome DNA methylation analysis pipeline Bioinformatics 2014 30 2414 2422 10.1093/bioinformatics/btu339 24836530 PMC4147891 · DOI
  103. [114]Kishore K de Pretis S Lister R Morelli MJ Bianchi V Amati B methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data BMC Bioinf 2015 16 313 10.1186/s12859-015-0742-6 PMC4587815 26415965 · DOI
  104. [115]Hebestreit K Dugas M Klein HU Detection of significantly differentially methylated regions in targeted bisulfite sequencing data Bioinformatics 2013 29 1647 1653 10.1093/bioinformatics/btt263 23658421 · DOI
  105. [116]Schmitz RJ Schultz MD Urich MA Nery JR Pelizzola M Libiger O Patterns of population epigenomic diversity Nature 2013 495 193 198 10.1038/nature11968 23467092 PMC3798000 · DOI
  106. [117]Robinson MD Kahraman A Law CW Lindsay H Nowicka M Weber LM Statistical methods for detecting differentially methylated loci and regions Front Genet. 2014 5 324 10.3389/fgene.2014.00324 25278959 PMC4165320 · DOI
  107. [118]Kurdyukov S Bullock M DNA methylation analysis: choosing the right method Biology 2016 5 3 10.3390/biology5010003 PMC4810160 26751487 · DOI
  108. [119]Kader F Ghai M DNA methylation and application in forensic sciences Forensic Sci Int 2015 249 255 265 10.1016/j.forsciint.2015.01.037 25732744 · DOI
  109. [120]Mikeska T Craig JM DNA methylation biomarkers: cancer and beyond Genes (Basel). 2014 5 821 864 25229548 PMC4198933
  110. [121]Legendre C Gooden GC Johnson K Martinez RA Liang WS Salhia B Whole-genome bisulfite sequencing of cell-free DNA identifies signature associated with metastatic breast cancer Clin Epigenetics. 2015 7 100 10.1186/s13148-015-0135-8 26380585 PMC4573288 · DOI
  111. [122]Farkas SA Milutin-Gašperov N Grce M Nilsson TK Genome-wide DNA methylation assay reveals novel candidate biomarker genes in cervical cancer Epigenetics. 2013 8 1213 1225 10.4161/epi.26346 24030264 · DOI
  112. [123]Uribe-Lewis S Stark R Carroll T Dunning MJ Bachman M Ito Y 5-hydroxymethylcytosine marks promoters in colon that resist DNA hypermethylation in cancer Genome Biol 2015 16 69 10.1186/s13059-015-0605-5 25853800 PMC4380107 · DOI
  113. [124]Agardh E Lundstig A Perfilyev A Volkov P Freiburghaus T Lindholm E Genome-wide analysis of DNA methylation in subjects with type 1 diabetes identifies epigenetic modifications associated with proliferative diabetic retinopathy BMC Med 2015 13 182 10.1186/s12916-015-0421-5 26248552 PMC4527111 · DOI
  114. [125]Nygren AO Dean J Jensen TJ Kruse S Kwong W van den Boom D Quantification of fetal DNA by use of methylation-based DNA discrimination Clin Chem 2010 56 1627 1635 10.1373/clinchem.2010.146290 20729299 · DOI

Authors
Yong, W.-S., Hsu, F.-M., & Chen, P.-Y.
Affiliations
  • Institute of Plant and Microbial Biology, Academia Sinica (TW)
  • The University of Tokyo (JP)
Corresponding author
Chen, Pao-Yang
ORCID
Venue
Epigenetics & Chromatin
Publisher
Springer Science and Business Media LLC
Published
2016-06-29
Volume
9
Issue
1
Pages
26-26
ISSN
1756-8935 (ISSN-L)
DOI
10.1186/s13072-016-0075-3
PMC
PMC4926291
OpenAlex
W2471080239
Cited by
374
References
123
Citations by year
2026: 13 · 2025: 35 · 2024: 44 · 2023: 35 · 2022: 32 · 2021: 43 · 2020: 44 · 2019: 54 · 2018: 37 · 2017: 35 · 2016: 2
FWCI
3.86
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Epigenetics & Chromatin (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Science Council (MOST-103-2313-B-001-003-MY3, MOST-103-2633-B-001-002)
  • National Health Research Institutes (EX104-10324SC)
  • Todai Fellowship
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Syndromes and Imprinting
Keywords
DNA methylation, genome-wide methylation profiling, hydroxymethylation, bisulfite sequencing, DNA methylation microarrays, differentially methylated regions, computational pipeline, epigenetics, plants, animals, fungi

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review