DMAP2: A Pipeline for Analysis of Whole-Genome-Scale DNA Methylation Sequencing Data.
DNA methylation
RRBS
WGBS
bisulfite sequencing
Journal
Current protocols
ISSN: 2691-1299
Titre abrégé: Curr Protoc
Pays: United States
ID NLM: 101773894
Informations de publication
Date de publication:
Sep 2024
Sep 2024
Historique:
medline:
11
9
2024
pubmed:
11
9
2024
entrez:
11
9
2024
Statut:
ppublish
Résumé
DNA methylation is well-established as a major epigenetic mechanism that can control gene expression and is involved in both normal development and disease. Analysis of high-throughput-sequencing-based DNA methylation data is a step toward understanding the relationship between disease and phenotype. Analysis of CpG methylation at single-base resolution is routinely done by bisulfite sequencing, in which methylated Cs remain as C while unmethylated Cs are converted to U, subsequently seen as T nucleotides. Sequence reads are aligned to the reference genome using mapping tools that accept the C-T ambiguity. Then, various statistical packages are used to identify differences in methylation between (groups of) samples. We have previously developed the Differential Methylation Analysis Pipeline (DMAP) as an efficient, fast, and flexible tool for this work, both for whole-genome bisulfite sequencing (WGBS) and reduced-representation bisulfite sequencing (RRBS). The protocol described here includes a series of scripts that simplify the use of DMAP tools and that can accommodate the wider range of input formats now in use to perform analysis of whole-genome-scale DNA methylation sequencing data in various biological and clinical contexts. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: DMAP2 workflow for whole-genome bisulfite sequencing (WGBS) and reduced-representation bisulfite sequencing (RRBS).
Substances chimiques
Sulfites
0
hydrogen sulfite
OJ9787WBLU
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e70003Informations de copyright
© 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC.
Références
Ahn, A., Rodger, E. J., Motwani, J., Gimenez, G., Stockwell, P. A., Parry, M., Hersey, P., Chatterjee, A., & Eccles, M. R. (2021). Transcriptional reprogramming and constitutive PD‐L1 expression in melanoma are associated with dedifferentiation and activation of interferon and tumour necrosis factor signalling pathways. Cancers, 13(17), 4250. https://doi.org/10.3390/cancers13174250
Akalin, A., Kormaksson, M., Li, S., Garrett‐Bakelman, F. E., Figueroa, M. E., Melnick, A., & Mason, C. E. (2012). methylKit: A comprehensive R package for the analysis of genome‐wide DNA methylatsion profiles. Genome Biology, 13(10), R87. https://doi.org/10.1186/gb‐2012‐13‐10‐r87
Bock, C., Tomazou, E. M., Brinkman, A. B., Muller, F., Simmer, F., Gu, H., Jager, N., Gnirke, A., Stunnenberg, H. G., & Meissner, A. (2010). Quantitative comparison of genome‐wide DNA methylation mapping technologies. Nature Biotechnology, 28(10), 1106–1114. https://doi.org/10.1038/nbt.1681
Bowden, S. A., Rodger, E. J., Bates, M., Chatterjee, A., Eccles, M. R., & Stayner, C. (2018). Genome‐scale single nucleotide resolution analysis of DNA methylation in human autosomal dominant polycystic kidney disease. American Journal of Nephrology, 48(6), 415–424. https://doi.org/10.1159/000494739
Brown, C. M., Dalphin, M. E., Stockwell, P. A., & Tate, W. P. (1993). The translational termination signal database. Nucleic Acids Research, 21(13), 3119–3123. https://doi.org/10.1093/nar/21.13.3119
Brown, C. M., Stockwell, P. A., Dalphin, M. E., & Tate, W. P. (1994). The translational termination signal database (TransTerm) now also includes initiation contexts. Nucleic Acids Research, 22(17), 3620–3624. https://doi.org/10.1093/nar/22.17.3620
Brown, C. M., Stockwell, P. A., Trotman, C. N., & Tate, W. P. (1990). The signal for the termination of protein synthesis in procaryotes. Nucleic Acids Research, 18(8), 2079–2086. https://doi.org/10.1093/nar/18.8.2079
Chatterjee, A., Lagisz, M., Rodger, E. J., Zhen, L., Stockwell, P. A., Duncan, E. J., Horsfield, J. A., Jeyakani, J., Mathavan, S., Ozaki, Y., & Nakagawa, S. (2016). Sex differences in DNA methylation and expression in zebrafish brain: A test of an extended ‘male sex drive’ hypothesis. Gene, 590(2), 307–316. https://doi.org/10.1016/j.gene.2016.05.042
Chatterjee, A., Macaulay, E. C., Ahn, A., Ludgate, J. L., Stockwell, P. A., Weeks, R. J., Parry, M. F., Foster, T. J., Knarston, I. M., Eccles, M. R., & Morison, I. M. (2017). Comparative assessment of DNA methylation patterns between reduced representation bisulfite sequencing and Sequenom EpiTyper methylation analysis. Epigenomics, 9(6), 823–832. https://doi.org/10.2217/epi‐2016‐0176
Chatterjee, A., Macaulay, E. C., Rodger, E. J., Stockwell, P. A., Parry, M. F., Roberts, H. E., Slatter, T. L., Hung, N. A., Devenish, C. J., & Morison, I. M. (2016). Placental hypomethylation is more pronounced in genomic loci devoid of retroelements. G3 Genes|Genomes|Genetics, 6(7), 1911–1921. https://doi.org/10.1534/g3.116.030379
Chatterjee, A., Ozaki, Y., Stockwell, P. A., Horsfield, J. A., Morison, I. M., & Nakagawa, S. (2013). Mapping the zebrafish brain methylome using reduced representation bisulfite sequencing. Epigenetics, 8(9), 979–989. https://doi.org/10.4161/epi.25797
Chatterjee, A., Rodger, E. J., Ahn, A., Stockwell, P. A., Parry, M., Motwani, J., Gallagher, S. J., Shklovskaya, E., Tiffen, J., Eccles, M. R., & Hersey, P. (2018). Marked global DNA hypomethylation is associated with constitutive PD‐L1 expression in melanoma. Iscience, 4, 312–325. https://doi.org/10.1016/j.isci.2018.05.021
Chatterjee, A., Rodger, E. J., Morison, I. M., Eccles, M. R., & Stockwell, P. A. (2017). Tools and strategies for analysis of genome‐wide and gene‐specific DNA methylation patterns. Methods in Molecular Biology, 1537, 249–277. https://doi.org/10.1007/978‐1‐4939‐6685‐1_15
Chatterjee, A., Stockwell, P. A., Ahn, A., Rodger, E. J., Leichter, A. L., & Eccles, M. R. (2017). Genome‐wide methylation sequencing of paired primary and metastatic cell lines identifies common DNA methylation changes and a role for EBF3 as a candidate epigenetic driver of melanoma metastasis. Oncotarget, 8(4), 6085–6101. https://doi.org/10.18632/oncotarget.14042
Chatterjee, A., Stockwell, P. A., Rodger, E. J., Duncan, E. J., Parry, M. F., Weeks, R. J., & Morison, I. M. (2015). Genome‐wide DNA methylation map of human neutrophils reveals widespread inter‐individual epigenetic variation. Scientific Reports, 5, 17328. https://doi.org/10.1038/srep17328
Chatterjee, A., Stockwell, P. A., Rodger, E. J., & Morison, I. M. (2012). Comparison of alignment software for genome‐wide bisulphite sequence data. Nucleic Acids Research, 40(10), e79. https://doi.org/10.1093/nar/gks150
Chatterjee, A., Stockwell, P. A., Rodger, E. J., & Morison, I. M. (2016). Genome‐scale DNA methylome and transcriptome profiling of human neutrophils. Scientific Data, 3, 160019. https://doi.org/10.1038/sdata.2016.19
Chatterjee, A., Stockwell, P. A., Horsfield, J. A., Morison, I. M., & Nakagawa, S. (2014). Base‐resolution DNA methylation landscape of zebrafish brain and liver. Genomics Data, 2(2014), 342–344. https://doi.org/10.1016/j.gdata.2014.10.008
Falisse, E., Ducos, B., Stockwell, P. A., Morison, I. M., Chatterjee, A., & Silvestre, F. (2018). DNA methylation and gene expression alterations in zebrafish early‐life stages exposed to the antibacterial agent triclosan. Environmental Pollution, 243(Pt B), 1867–1877. https://doi.org/10.1016/j.envpol.2018.10.004
Greenberg, M. V. C., & Bourc'his, D. (2019). The diverse roles of DNA methylation in mammalian development and disease. Nature Reviews Molecular Cell Biology, 20(10), 590–607. https://doi.org/10.1038/s41580‐019‐0159‐6
Guo, W., Fiziev, P., Yan, W., Cokus, S., Sun, X., Zhang, M. Q., Chen, P. Y., & Pellegrini, M. (2013). BS‐Seeker2: A versatile aligning pipeline for bisulfite sequencing data. BMC Genomics, 14, 774. https://doi.org/10.1186/1471‐2164‐14‐774
Hansen, K. D., Langmead, B., & Irizarry, R. A. (2012). BSmooth: From whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biology, 13(10), R83. https://doi.org/10.1186/gb‐2012‐13‐10‐r83
Hebestreit, K., Dugas, M., & Klein, H. U. (2013). Detection of significantly differentially methylated regions in targeted bisulfite sequencing data. Bioinformatics, 29(13), 1647–1653. https://doi.org/10.1093/bioinformatics/btt263
Helliwell, A. M., Sweetman, E. C., Stockwell, P. A., Edgar, C. D., Chatterjee, A., & Tate, W. P. (2020). Changes in DNA methylation profiles of myalgic encephalomyelitis/chronic fatigue syndrome patients reflect systemic dysfunctions. Clinical Epigenetics, 12(1), 167. https://doi.org/10.1186/s13148‐020‐00960‐z
Huh, I., Wu, X., Park, T., & Yi, S. V. (2019). Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species. Briefings in Bioinformatics, 20(1), 33–46. https://doi.org/10.1093/bib/bbx077
Jang, H. S., Shin, W. J., Lee, J. E., & Do, J. T. (2017). CpG and non‐CpG methylation in epigenetic gene regulation and brain function. Genes, 8(6), 148. https://doi.org/10.3390/genes8060148
Krueger, F., & Andrews, S. R. (2011). Bismark: A flexible aligner and methylation caller for Bisulfite‐Seq applications. Bioinformatics, 27(11), 1571–1572. https://doi.org/10.1093/bioinformatics/btr167
Lindroth, A. M., Cao, X., Jackson, J. P., Zilberman, D., McCallum, C. M., Henikoff, S., & Jacobsen, S. E. (2001). Requirement of CHROMOMETHYLASE3 for maintenance of CpXpG methylation. Science, 292(5524), 2077–2080. https://doi.org/10.1126/science.1059745
Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti‐Filippini, J., Nery, J. R., Lee, L., Ye, Z., Ngo, Q. M., Edsall, L., Antosiewicz‐Bourget, J., Stewart, R., Ruotti, V., Millar, A. H., Thomson, J. A., Ren, B., & Ecker, J. R. (2009). Human DNA methylomes at base resolution show widespread epigenomic differences. Nature, 462(7271), 315–322. https://doi.org/10.1038/nature08514
Mattei, A. L., Bailly, N., & Meissner, A. (2022). DNA methylation: A historical perspective. Trends in Genetics, 38(7), 676–707. https://doi.org/10.1016/j.tig.2022.03.010
Meissner, A., Gnirke, A., Bell, G. W., Ramsahoye, B., Lander, E. S., & Jaenisch, R. (2005). Reduced representation bisulfite sequencing for comparative high‐resolution DNA methylation analysis. Nucleic Acids Research, 33(18), 5868–5877. https://doi.org/10.1093/nar/gki901
Meissner, A., Mikkelsen, T. S., Gu, H., Wernig, M., Hanna, J., Sivachenko, A., Zhang, X., Bernstein, B. E., Nusbaum, C., Jaffe, D. B., Gnirke, A., Jaenisch, R., & Lander, E. S. (2008). Genome‐scale DNA methylation maps of pluripotent and differentiated cells. Nature, 454(7205), 766–770. https://doi.org/10.1038/nature07107
Moore, L. D., Le, T., & Fan, G. (2013). DNA methylation and its basic function. Neuropsychopharmacology, 38(1), 23–38. https://doi.org/10.1038/npp.2012.112
Rodger, E., Gimenez, G., Ajithkumar, P., Stockwell, P., Almomani, S., Bowden, S., Leichter, A., Ahn, A., Pattison, S., McCall, J., Schmeier, S., Frizelle, F., Eccles, M., Purcell, R., & Chatterjee, A. (2023). An epigenetic signature of advanced colorectal cancer metastasis. iScience (Cell), 26(6), 106986. https://doi.org/10.1016/j.isci.2023.106986
Rodger, E. J., Almomani, S. N., Ludgate, J. L., Stockwell, P. A., Baguley, B. C., Eccles, M. R., & Chatterjee, A. (2021). Comparison of global DNA methylation patterns in human melanoma tissues and their derivative cell lines. Cancers, 13(9), 2123. https://doi.org/10.3390/cancers13092123
Rodger, E. J., Gimenez, G., Ajithkumar, P., Stockwell, P. A., Almomani, S., Bowden, S. A., Leichter, A. L., Ahn, A., Pattison, S., McCall, J. L., Schmeier, S., Frizelle, F. A., Eccles, M. R., Purcell, R. V., & Chatterjee, A. (2023). An epigenetic signature of advanced colorectal cancer metastasis. Iscience, 26(6), 106986. https://doi.org/10.1016/j.isci.2023.106986
Song, X., Huang, F., Liu, J., Li, C., Gao, S., Wu, W., Zhai, M., Yu, X., Xiong, W., Xie, J., & Li, B. (2017). Genome‐wide DNA methylomes from discrete developmental stages reveal the predominance of non‐CpG methylation in Tribolium castaneum. DNA Research, 24(5), 445–457. https://doi.org/10.1093/dnares/dsx016
Stockwell, P. A., Chatterjee, A., Rodger, E. J., & Morison, I. M. (2014). DMAP: Differential methylation analysis package for RRBS and WGBS data. Bioinformatics, 30(13), 1814–1822. https://doi.org/10.1093/bioinformatics/btu126
Stockwell, P. A., Lynch‐Sutherland, C. F., Chatterjee, A., Macaulay, E. C., & Eccles, M. R. (2021). RepExpress: A novel pipeline for the quantification and characterization of transposable element expression from RNA‐seq data. Current Protocols, 1(8), e206. https://doi.org/10.1002/cpz1.206
Thunders, M., Chinn, V., Bilewitch, J., & Stockwell, P. (2018). Identification of potential 'lifestyle‐responsive' epigenomic biomarkers in healthy women aged 18‐40. Biomarkers, 23(5), 453–461. https://doi.org/10.1080/1354750X.2018.1443512
Thunders, M., Holley, A., Harding, S., Stockwell, P., & Larsen, P. (2019). Using NGS‐methylation profiling to understand the molecular pathogenesis of young MI patients who have subsequent cardiac events. Epigenetics, 14(6), 536–544. https://doi.org/10.1080/15592294.2019.1605815
Tschirley, A. M., Stockwell, P. A., Rodger, E. J., Eltherington, O., Morison, I. M., Christensen, N., Chatterjee, A., & Hibma, M. (2021). The mouse papillomavirus epigenetic signature is characterised by DNA hypermethylation after lesion regression. Viruses, 13(10), 2045. https://doi.org/10.3390/v13102045
Voisin, A. S., Suarez Ulloa, V., Stockwell, P., Chatterjee, A., & Silvestre, F. (2021). Genome‐wide DNA methylation of the liver reveals delayed effects of early‐life exposure to 17‐alpha‐ethinylestradiol in the self‐fertilizing mangrove rivulus. Epigenetics, 17(5), 473–497. https://doi.org/10.1080/15592294.2021.1921337
Xi, Y., & Li, W. (2009). BSMAP: Whole genome bisulfite sequence MAPping program. BMC Bioinformatics, 10, 232. https://doi.org/10.1186/1471‐2105‐10‐232