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Comprehensive high-throughput arrays for relative methylation (CHARM)
Open accessAbstract
This study was originally conceived to test in a rigorous way the specificity of three major approaches to high-throughput array-based DNA methylation analysis: (1) MeDIP, or methylated DNA immunoprecipitation, an example of antibody-mediated methyl-specific fractionation; (2) HELP, or HpaII tiny fragment enrichment by ligation-mediated PCR, an example of differential amplification of methylated DNA; and (3) fractionation by McrBC, an enzyme that cuts most methylated DNA. These results were validated using 1466 Illumina methylation probes on the GoldenGate methylation assay and further resolved discrepancies among the methods through quantitative methylation pyrosequencing analysis. While all three methods provide useful information, there were significant limitations to each, specifically bias toward CpG islands in MeDIP, relatively incomplete coverage in HELP, and location imprecision in McrBC. However, we found that with an original array design strategy using tiling arrays and statistical procedures that average information from neighboring genomic locations, much improved specificity and sensitivity could be achieved, e.g., ∼100% sensitivity at 90% specificity with McrBC. We term this approach “comprehensive high-throughput arrays for relative methylation” (CHARM). While this approach was applied to McrBC analysis, the array design and computational algorithms are fractionation method-independent and make this a simple, general, relatively inexpensive tool suitable for genome-wide analysis, and in which individual samples can be assayed reliably at very high density, allowing locus-level genome-wide epigenetic discrimination of individuals, not just groups of samples. Furthermore, unlike the other approaches, CHARM is highly quantitative, a substantial advantage in application to the study of human disease.
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Cites
Genome-wide maps of chromatin state in pluripotent and lineage-committed cells
Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T.-K., Koche, R. P., et al. (2007) · Nature · doi:10.1038/nature06008 · Cited by 4,129
Microarray data analysis: from disarray to consolidation and consensus
Allison, D. B., Cui, X., Page, G. P., & Sabripour, M. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1749 · Cited by 1,339 · cited 1×
“For each microarray hybridization, we used the raw feature intensities to form log ratios and denoted these with M, as done in most of the microarray literature (Allison et al. 2006).”
Molecular characterization of the tumor microenvironment in breast cancer
Allinen, M., Beroukhim, R., Cai, L., Brennan, C., Lahti-Domenici, J., Huang, H., Porter, D., Hu, M., Chin, L., Richardson, A., et al. (2004) · Cancer Cell · doi:10.1016/j.ccr.2004.06.010 · Cited by 1,299
De novo quantitative bisulfite sequencing using the pyrosequencing technology
Dupont, J.-M., Tost, J., Jammes, H., & Gut, I. G. (2004) · Analytical Biochemistry · doi:10.1016/j.ab.2004.05.007 · Cited by 253
Cited by
Coming of age: ten years of next-generation sequencing technologies
Goodwin, S., McPherson, J. D., & McCombie, W. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.49 · Cited by 4,352
DNA methylation landscapes: Provocative insights from epigenomics
Suzuki, M. M., & Bird, A. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2341 · Cited by 3,039
Irizarry, R. A., Ladd-Acosta, C., Wen, B., Wu, Z., Montano, C., Onyango, P., Cui, H., Gabo, K., Rongione, M., Webster, M., et al. (2009) · Nature Genetics · doi:10.1038/ng.298 · Cited by 2,177
Self-citationDu, P., Zhang, X., Huang, C.-C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-587 · Cited by 2,136
Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome
Sandoval, J., Heyn, H., Moran, S., Serra-Musach, J., Pujana, M. A., Bibikova, M., & Esteller, M. (2011) · Epigenetics · doi:10.4161/epi.6.6.16196 · Cited by 990
Metadata
- Authors
- Irizarry, R. A., Ladd-Acosta, C., Carvalho, B., Wu, H., Brandenburg, S. A., Jeddeloh, J. A., Wen, B., & Feinberg, A. P.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2008-03-03
- Volume
- 18
- Issue
- 5
- Pages
- 780-790
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2107776519
- Cited by
- 433
- References
- 4
- Type
- posted content
- Language
- en
- Open access
- hybrid
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- Irizarry, R. A., Ladd-Acosta, C., Carvalho, B., Wu, H., Brandenburg, S. A., Jeddeloh, J. A., Wen, B., & Feinberg, A. P. (2008). Comprehensive high-throughput arrays for relative methylation (CHARM). Genome Research. https://doi.org/10.1101/gr.7301508
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