A robust internal control for high-precision DNA methylation analyses by droplet digital PCR View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Heidi D. Pharo, Kim Andresen, Kaja C. G. Berg, Ragnhild A. Lothe, Marine Jeanmougin, Guro E. Lind

ABSTRACT

Background: Droplet digital PCR (ddPCR) allows absolute quantification of nucleic acids and has potential for improved non-invasive detection of DNA methylation. For increased precision of the methylation analysis, we aimed to develop a robust internal control for use in methylation-specific ddPCR. Methods: Two control design approaches were tested: (a) targeting a genomic region shared across members of a gene family and (b) combining multiple assays targeting different pericentromeric loci on different chromosomes. Through analyses of 34 colorectal cancer cell lines, the performance of the control assay candidates was optimized and evaluated, both individually and in various combinations, using the QX200™ droplet digital PCR platform (Bio-Rad). The best-performing control was tested in combination with assays targeting methylated CDO1, SEPT9, and VIM. Results: A 4Plex panel consisting of EPHA3, KBTBD4, PLEKHF1, and SYT10 was identified as the best-performing control. The use of the 4Plex for normalization reduced the variability in methylation values, corrected for differences in template amount, and diminished the effect of chromosomal aberrations. Positive Droplet Calling (PoDCall), an R-based algorithm for standardized threshold determination, was developed, ensuring consistency of the ddPCR results. Conclusion: Implementation of a robust internal control, i.e., the 4Plex, and an algorithm for automated threshold determination, PoDCall, in methylation-specific ddPCR increase the precision of DNA methylation analysis. More... »

PAGES

24

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13148-018-0456-5

DOI

http://dx.doi.org/10.1186/s13148-018-0456-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101141076

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29484034


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