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Charting the methylome

Geert Trooskens UGent, Tim De Meyer UGent, Simon Denil and Wim Van Criekinge UGent (2011) Benelux Bioinformatics Conference : proceedings of BBC11. p.73-73
abstract
Epigenetics, with DNA-methylation as its most stable feature, translates the genetic background into a particular phenotype. Massively parallel sequencing technologies opened up new possibilities for genome-wide profiling of DNA-methylation. Particularly Methyl Binding Domain capturing based Sequencing (MethylCap-Seq) is a low-cost, high-resolution technology to uncover DNA-methylation in a truly genome-wide manner and is becoming increasingly popular. Methods : To chart the map of the methylome, we used raw MethylCap-Seq data of 80 different samples, including different healthy tissues, cell lines and tumor samples. Since no normalization procedures are applied, artefacts are avoided. A Poisson background model is used to identify significantly methylated regions. A conservative set of rules was derived that identifies adjacent methylation prone regions in a single region.
 Results : Based on this methodology, we provide a reference map of ~1.5 million methylation cores. Together they make up about 10.4% of the human genome and 40% of the approximately 28 million human CpGs dinucleotides. Validation by a different MBD kit and targeted bisulfite sequencing data indicates that the Map of the Human Methylome is approximately 95% complete. Conclusions : We found that although CpG-islands (CGIs) and exon regions are higly enriched in methylation cores with high methylation levels , they show less variability between samples compared to promotor, intergenic and intronic regions. The accuracy of the methylome map will increase with more samples from different tissues and diseases. Comparing the map of the methylome with expression and other data such as histone marks will enable functional annotation of the methylation prone regions, providing a better understanding of the mechanisms involved in epigenetic regulation. This approach is a flexible methodology that can be ported to other genome wide high- throughput methods such as third generation sequencing technologies.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
DNA Methylation, Epigenetics, MethylCap, Sequencing, High-Throughput
in
Benelux Bioinformatics Conference : proceedings of BBC11
article number
abstract B8
pages
73 - 73
conference name
6th Benelux Bioinformatics Conference (BBC '11)
conference location
Luxemburg, GD Luxemburg
conference start
2011-12-12
conference end
2011-12-13
language
English
UGent publication?
yes
classification
C3
id
3143780
handle
http://hdl.handle.net/1854/LU-3143780
alternative location
http://www.bbc11.lu/documents/ConferenceProceedingsBBC2011update.pdf
date created
2013-02-26 11:35:11
date last changed
2016-12-21 15:41:01
@inproceedings{3143780,
  abstract     = {Epigenetics, with DNA-methylation as its most stable feature, translates the genetic background into a particular phenotype. Massively parallel sequencing technologies opened up new possibilities for genome-wide profiling of DNA-methylation. Particularly Methyl Binding Domain capturing based Sequencing (MethylCap-Seq) is a low-cost, high-resolution technology to uncover DNA-methylation in a truly genome-wide manner and is becoming increasingly popular.
Methods : To chart the map of the methylome, we used raw MethylCap-Seq data of 80 different samples, including different healthy tissues, cell lines and tumor samples. Since no normalization procedures are applied, artefacts are avoided. A Poisson background model is used to identify significantly methylated regions. A conservative set of rules was derived that identifies adjacent methylation prone regions in a single region.\unmatched{2028}
Results : Based on this methodology, we provide a reference map of {\texttildelow}1.5 million methylation cores. Together they make up about 10.4\% of the human genome and 40\% of the approximately 28 million human CpGs dinucleotides. Validation by a different MBD kit and targeted bisulfite sequencing data indicates that the Map of the Human Methylome is approximately 95\% complete.
Conclusions : We found that although CpG-islands (CGIs) and exon regions are higly enriched in methylation cores with high methylation levels , they show less variability  between samples compared to promotor, intergenic and intronic regions. The accuracy of the methylome map will increase with more samples from different tissues and diseases. Comparing the map of the methylome with expression and other data such as histone marks will enable functional annotation of the methylation prone regions, providing a better understanding of the mechanisms involved in epigenetic regulation. This approach is a flexible methodology that can be ported  to other genome wide high- throughput methods such as third generation sequencing technologies.},
  articleno    = {abstract B8},
  author       = {Trooskens, Geert and De Meyer, Tim and Denil, Simon and Van Criekinge, Wim},
  booktitle    = {Benelux Bioinformatics Conference : proceedings of BBC11},
  keyword      = {DNA Methylation,Epigenetics,MethylCap,Sequencing,High-Throughput},
  language     = {eng},
  location     = {Luxemburg, GD Luxemburg},
  pages        = {abstract B8:73--abstract B8:73},
  title        = {Charting the methylome},
  url          = {http://www.bbc11.lu/documents/ConferenceProceedingsBBC2011update.pdf},
  year         = {2011},
}

Chicago
Trooskens, Geert, Tim De Meyer, Simon Denil, and Wim Van Criekinge. 2011. “Charting the Methylome.” In Benelux Bioinformatics Conference : Proceedings of BBC11, 73–73.
APA
Trooskens, G., De Meyer, T., Denil, S., & Van Criekinge, W. (2011). Charting the methylome. Benelux Bioinformatics Conference : proceedings of BBC11 (pp. 73–73). Presented at the 6th Benelux Bioinformatics Conference (BBC  ’11).
Vancouver
1.
Trooskens G, De Meyer T, Denil S, Van Criekinge W. Charting the methylome. Benelux Bioinformatics Conference : proceedings of BBC11. 2011. p. 73–73.
MLA
Trooskens, Geert, Tim De Meyer, Simon Denil, et al. “Charting the Methylome.” Benelux Bioinformatics Conference : Proceedings of BBC11. 2011. 73–73. Print.