Methodological aspects of whole-genome bisulfite sequencing analysis

Briefings in Bioinformatics

Volumn 16, Issue 3, 2014, Pages 369-379

  Adusumalli, Swarnaseetha ^a   Omar, Mohd Feroz Mohd ^b   Soong, Richie ^b,c,d   Benoukraf, Touati ^b,c  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^d Cardiovascular Research Institute   (Singapore)

Author keywords

Bisulfite sequencing; DNA methylation; Epigenetics; High throughput sequencing

Indexed keywords

DNA; HYDROGEN SULFITE; SULFITE;

ALGORITHM; CHEMISTRY; CHROMOSOMAL MAPPING; CPG ISLAND; DNA METHYLATION; DNA SEQUENCE; GENETICS; HIGH THROUGHPUT SEQUENCING; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; PROCEDURES;

ALGORITHMS; BASE SEQUENCE; CHROMOSOME MAPPING; CPG ISLANDS; DNA; DNA METHYLATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; MOLECULAR SEQUENCE DATA; SEQUENCE ANALYSIS, DNA; SULFITES;

EID: 84925867764     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbu016     Document Type: Article

References (106)

1. Franchini D-M, Schmitz K-M, Petersen-Mahrt SK. 5-methylcytosine DNA demethylation: more than losing a methyl group. Annu Rev Genet 2012;46:419-41.
2. Fujimoto M, Kitazawa R, Maeda S, et al. Methylation adjacent to negatively regulating AP-1 site reactivates TrkA gene expression during cancer progression. Oncogene 2005;24:5108-18.
3. Zhu W-G, Srinivasan K, Dai Z, et al. Methylation of adjacent CpG sites affects Sp1/Sp3 binding and activity in the p21(Cip1) promoter. Mol Cell Biol 2003;23:4056-65.
4. Hu S, Wan J, Su Y, et al. DNA methylation presents distinct binding sites for human transcription factors. Elife 2013;2:e00726.
5. Jones PA. The DNA methylation paradox. Trends Genet 1999;15:34-7.
6. Tatetsu H, Ueno S, Hata H, et al. Down-regulation of PU.1 by methylation of distal regulatory elements and the promoter is required for myeloma cell growth. CancerRes 2007;67:5328-36.
7. Lai AY, Fatemi M, Dhasarathy A, et al. DNA methylation prevents CTCF-mediated silencing of the oncogene BCL6 in B cell lymphomas. J ExpMed 2010;207:1939-50.
8. Lister R, O'Malley RC, Tonti-Filippini J, et al. Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell 2008;133:523-36.
9. Cokus SJ, Feng S, Zhang X, et al. Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature 2008;452:215-9.
10. Lister R, Pelizzola M, Kida YS, et al. Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells. Nature 2011;471:68-73.
11. Xie W, Barr CL, Kim A, et al. Base-resolution analyses of sequence and parent-of-origin dependent DNA methylation in the mouse genome. Cell 2012;148:816-31.
12. Lister R, Mukamel EA, Nery JR, et al. Global epigenomic reconfiguration during mammalian brain development. Science 2013;341:1237905.
13. Guo JU, Su Y, Shin JH, et al. Distribution, recognition and regulation of non-CpG methylation in the adult mammalian brain. NatNeurosci 2014;17:215-22.
14. Harrison A, Parle-McDermott A. DNA methylation:a timeline of methods and applications. Front Genet 2011;2:74.
15. Wang RY, Gehrke CW, Ehrlich M. Comparison of bisulfite modification of 5-methyldeoxycytidine and deoxycytidine residues. Nucleic Acids Res 1980;8:4777-90.
16. El-Maarri O. Methods: DNA methylation. Adv Exp Med Biol 2003;544:197-204.
17. Hayatsu H. Discovery of bisulfite-mediated cytosine conversion to uracil, the key reaction for DNA methylation analysis-a personal account. Proc Jpn Acad Ser B Phys Biol Sci 2008;84:321-30.
18. Akalin A, Kormaksson M, Li S, et al. methylKit. https://code.google.com/p/methylkit/(14 April 2014, date last accessed).
19. Benoukraf T, Wongphayak S, Hadi LHA, et al. GBSA. http://ctrad-csi.nus.edu.sg/gbsa/(14 April 2014, date last accessed).
20. Zhang T, Luo Y, Liu K, et al. BIGpre: a quality assessment package for next-generation sequencing data. Genomics Proteomics Bioinformatics 2011;9:238-44.
21. Lin X, Sun D, Rodriguez B, et al. BSeQC: quality control of bisulfite sequencing experiments. Bioinformatics 2013;29:3227-9.
22. Andrews S. FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.bab raham.ac.uk/projects/fastqc/(14 April 2014, date last accessed).
23. Yang X, Liu D, Liu F, et al. HTQC: a fast quality control toolkit for Illumina sequencing data. BMC Bioinformatics 2013;14:33.
24. Patel RK, Jain M. NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoSOne 2012;7:e30619.
25. Martínez-Alcántara A, Ballesteros E, Feng C, et al. PIQA:pipeline for Illumina G1 genome analyzer data quality assessment. Bioinformatics 2009;25:2438-9.
26. Zhou Q, Su X, Wang A, et al. QC-Chain: fast and holistic quality control method for next-generation sequencing data. PLoS One 2013;8:e60234.
27. Cox MP, Peterson DA, Biggs PJ. Solexa QA: At-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinformatics 2010;11:485.
28. Rubio-Camarillo M, Gómez-López G, Fernández JM, et al. RUbioSeq: a suite of parallelized pipelines to automate exome variation and bisulfite-seq analyses. Bioinformatics 2013;29:1687-9.
29. Liang F, Tang B, Wang Y, et al. WBSA: Web Service for Bisulfite Sequencing Data Analysis. PLoS One 2014;9:e86707.
30. Harris EY, Ponts N, Levchuk A, et al. BRAT:bisulfite-treated reads analysis tool. Bioinformatics 2010;26:572-3.
31. Harris EY, Ponts N, Le Roch KG, et al. BRAT-BW: efficient and accurate mapping of bisulfite-treated reads. Bioinformatics 2012;28:1795-6.
32. Xi Y, Li W. BSMAP: whole genome bisulfite sequence MAPping program. BMC Bioinformatics 2009;10:232.
33. Chen P-Y, Cokus SJ, Pellegrini M. BS Seeker: precise mapping for bisulfite sequencing. BMC Bioinformatics 2010;11:203.
34. Wu TD, Nacu S. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 2010;26:873-81.
35. Li R, Li Y, Kristiansen K, et al. SOAP: short oligonucleotide alignment program. Bioinformatics 2008;24:713-4.
36. Lim J-Q, Tennakoon C, Li G, et al. BatMeth: improved mapper for bisulfite sequencing reads on DNA methylation. Genome Biol 2012;13:R82.
37. Krueger F, Andrews SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 2011;27:1571-2.
38. Guo W, Fiziev P, Yan W, et al. BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data. BMC Genomics 2013;14:774.
39. Pedersen B, Hsieh T-F, Ibarra C, et al. MethylCoder: software pipeline for bisulfite-treated sequences. Bioinformatics 2011;27:2435-6.
40. Sun S, Noviski A, Yu X. MethyQA: a pipeline for bisulfitetreated methylation sequencing quality assessment. BMC Bioinformatics 2013;14:259.
41. Campagna D, Telatin A, Forcato C, et al. PASS-bis: a bisulfite aligner suitable for whole methylome analysis of Illumina and SOLiD reads. Bioinformatics 2013;29:268-70.
42. Song Q, Decato B, Hong EE, et al. A reference methylome database and analysis pipeline to facilitate integrative and comparative epigenomics. PLoS One 2013;8:e81148.
43. He J, Sun X, Shao X, et al. DMEAS: DNA methylation entropy analysis software. Bioinformatics 2013;29:2044-5.
44. Su J, Yan H, Wei Y, et al. CpG_MPs: identification of CpG methylation patterns of genomic regions from highthroughput bisulfite sequencing data. Nucleic Acids Res 2012;41:1-15.
45. Benoukraf T, Wongphayak S, Hadi LHA, et al. GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data. Nucleic Acids Res 2013;41:e55.
46. Akalin A, Kormaksson M, Li S, et al. methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biol 2012;13:R87.
47. Meyer LR, Zweig AS, Hinrichs AS, et al. The UCSC Genome Browser database: extensions and updates 2013. Nucleic Acids Res 2012;41:D64-9.
48. McLaren W, Pritchard B, Rios D, et al. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 2010;26:2069-70.
49. Cock PJA, Fields CJ, Goto N, et al. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res 2010;38:1767-71.
50. Falgueras J, Lara AJ, Fernández-Pozo N, et al. SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read. BMC Bioinformatics 2010;11:38.
51. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 2014;30:2114-20.
52. The FASTX-Toolkit. http://hannonlab.cshl.edu/fastx_toolkit/ (14 April 2014, date last accessed).
53. Ewing B, Hillier L, Wendl MC, et al. Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res 1998;8:175-85.
54. Liu Q, Guo Y, Li J, et al. Steps to ensure accuracy in genotype and SNP calling from Illumina sequencing data. BMC Genomics 2012;13(Suppl 8):S8.
55. Trimarchi MP, Murphy M, Frankhouser D, et al. Enrichment-based DNA methylation analysis using nextgeneration sequencing: sample exclusion, estimating changes in global methylation, and the contribution of replicate lanes. BMCGenomics 2012;13(Suppl 8):S6.
56. Lisanti S, von Zglinicki T, Mathers JC. Standardization and quality controls for the methylated DNA immunoprecipitation technique. Epigenetics 2012;7:615-25.
57. Langmead B, Trapnell C, Pop M, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009;10:R25.
58. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009;25:1754-60.
59. Li H, Ruan J, Durbin R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 2008;18:1851-8.
60. Bock C. Analysing and interpreting DNA methylation data. Nat Rev Genet 2012;13:705-19.
61. Smith AD, Chung W-Y, Hodges E, et al. Updates to the RMAP short-read mapping software. Bioinformatics 2009;25:2841-2.
62. Hoffmann S, Otto C, Kurtz S, et al. Fast mapping of short sequences with mismatches, insertions and deletions using index structures. PLoSComput Biol 2009;5:e1000502.
63. Li H, Handsaker B, Wysoker A, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009;25:2078-9.
64. Law JA, Jacobsen SE. Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat Rev Genet 2010;11:204-20.
65. Choi JK, Bae J-B, Lyu J, et al. Nucleosome deposition and DNA methylation at coding region boundaries. GenomeBiol 2009;10:R89.
66. Chodavarapu RK, Feng S, Bernatavichute Y V, et al. Relationship between nucleosome positioning and DNA methylation. Nature 2010;466:388-92.
67. Fenouil R, Cauchy P, Koch F, et al. CpG islands and GC content dictate nucleosome depletion in a transcriptionindependent manner at mammalian promoters. Genome Res 2012;22:2399-408.
68. Collings CK, Waddell PJ, Anderson JN. Effects of DNA methylation on nucleosome stability. NucleicAcidsRes 2013;41:2918-31.
69. Guo W, Chung W-Y, Qian M, et al. Characterizing the strand-specific distribution of non-CpG methylation in human pluripotent cells. NucleicAcidsRes 2013;42:3009-16.
70. Laird PW. Principles and challenges of genomewide DNA methylation analysis. Nat Rev Genet 2010;11:191-203.
71. Laurent L, Wong E, Li G, et al. Dynamic changes in the human methylome during differentiation. GenomeRes 2010;20:320-31.
72. Schultz MD, Schmitz RJ, Ecker JR. 'Leveling' the playing field for analyses of single-base resolution DNA methylomes. TrendsGenet 2012;28:583-5.
73. Xie H, Wang M, de Andrade A, et al. Genome-wide quantitative assessment of variation in DNA methylation patterns. Nucleic Acids Res 2011;39:4099-108.
74. Nicol JW, Helt GA, Blanchard SG, et al. The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets. Bioinformatics 2009;25:2730-1.
75. Thorvaldsdóttir H, Robinson JT, Mesirov JP. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 2013;14:178-92.
76. Krzywinski M, Schein J, Birol I, et al. Circos: an information aesthetic for comparative genomics. Genome Res 2009;19:1639-45.
77. Dorff KC, Chambwe N, Zeno Z, et al. GobyWeb:simplified management and analysis of gene expression and DNA methylation sequencing data. PLoS One 2013;8:e69666.
78. Hodges E, Molaro A, Dos Santos CO, et al. Directional DNA methylation changes and complex intermediate states accompany lineage specificity in the adult hematopoietic compartment. Mol Cell 2011;44:17-28.
79. Li Y, Zhu J, Tian G, et al. The DNA methylome of human peripheral blood mononuclear cells. PLoS Biol 2010;8:e1000533.
80. Zilberman D, Gehring M, Tran RK, et al. Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interdependence between methylation and transcription. Nat Genet 2007;39:61-9.
81. Hellman A, Chess A. Gene body-specific methylation on the active X chromosome. Science 2007;315:1141-3.
82. Ball MP, Li JB, Gao Y, et al. Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells. Nat Biotechnol 2009;27:361-8.
83. Eckhardt F, Lewin J, Cortese R, et al. DNA methylation profiling of human chromosomes 6, 20 and 22. Nat Genet 2006;38:1378-85.
84. Straussman R, Nejman D, Roberts D, et al. Developmental programming of CpG island methylation profiles in the human genome. Nat StructMol Biol 2009;16:564-71.
85. Bergman Y, Cedar H. DNA methylation dynamics in health and disease. Nat StructMol Biol 2013;20:274-81.
86. Breitling LP, Yang R, Korn B, et al. Tobacco-smokingrelated differential DNA methylation: 27K discovery and replication. AmJHum Genet 2011;88:450-7.
87. Bartolomei MS, Ferguson-Smith AC. Mammalian genomic imprinting. Cold Spring Harb Perspect Biol 2011;3:a002592.
88. Tarutani Y, Takayama S. Monoallelic gene expression and its mechanisms. Curr Opin Plant Biol 2011;14:608-13.
89. Abu-Amero S, Monk D, Apostolidou S, et al. Imprinted genes and their role in human fetal growth. Cytogenet. Genome Res 2006;113:262-70.
90. Edwards CA, Ferguson-Smith AC. Mechanisms regulating imprinted genes in clusters. CurrOpinCellBiol 2007;19:281-9.
91. Butler MG. Genomic imprinting disorders in humans: a mini-review. JAssist Reprod Genet 2009;26:477-86.
92. Fang F, Hodges E, Molaro A, et al. Genomic landscape of human allele-specific DNA methylation. Proc Natl Acad Sci USA 2012;109:7332-7.
93. Kantlehner M, Kirchner R, Hartmann P, et al. A highthroughput DNA methylation analysis of a single cell. Nucleic Acids Res 2011;39:e44.
94. Kriaucionis S, Heintz N. The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain. Science 2009;324:929-30.
95. Tahiliani M, Koh KP, Shen Y, et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 2009;324:930-5.
96. Branco MR, Ficz G, Reik W. Uncovering the role of 5-hydroxymethylcytosine in the epigenome. Nat Rev Genet 2012;13:7-13.
97. Nestor C, Ruzov A, Meehan R, et al. Enzymatic approaches and bisulfite sequencing cannot distinguish between 5-methylcytosine and 5-hydroxymethylcytosine in DNA. Biotechniques 2010;48:317-9.
98. Booth MJ, Branco MR, Ficz G, et al. Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution. Science 2012;336:934-7.
99. Yu M, Hon GC, Szulwach KE, et al. Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell 2012;149:1368-80.
100. Shim J, Humphreys GI, Venkatesan BM, et al. Detection and quantification of methylation in DNA using solid-state nanopores. Sci Rep 2013;3:1389.
101. Laszlo AH, Derrington IM, Brinkerhoff H, et al. Detection and mapping of 5-methylcytosine and 5-hydroxymethylcytosine with nanopore MspA. Proc Natl Acad Sci USA 2013;110:18904-9.
102. Doi A, Park I-H, Wen B, et al. Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts. Nat Genet 2009;41:1350-3.
103. Kozlenkov A, Roussos P, Timashpolsky A, et al. Differences in DNA methylation between human neuronal and glial cells are concentrated in enhancers and non-CpG sites. Nucleic Acids Res 2013;9000:1-19.
104. Kulis M, Queirós AC, Beekman R, et al. Intragenic DNA methylation in transcriptional regulation, normal differentiation and cancer. Biochim Biophys Acta 2013;1829:1161-74.
105. Boyle AP, Hong EL, Hariharan M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res 2012;22:1790-7.
106. Makarov V, O'Grady T, Cai G, et al. AnnTools: a comprehensive and versatile annotation toolkit for genomic variants. Bioinformatics 2012;28:724-5.