Identification of symmetric methylation and hemimethylation patterns
The American Association for Cancer Research (AACR) annual meeting was shifted to a virtual session this year. Programs, presentations, papers, lectures, symposia, and sessions were held online, instead of in person. This included poster presentations, which were held in a virtual format for the first time.
IDT was proud to present a series of posters at #AACR20, including this one, titled: “Identification of Fully Methylation and Hemimethylation Patterns with Optimal Design, Library Preparation, and Error Correction.”
Developed by Hsiao-Yun Huang (Staff Scientist, Product Development), Kevin Lai (Bioinformatics Staff Scientist) and Jessica Sheu (Bioinformatics Scientist II), the poster addresses DNA methylation patterns, which are epigenetic modifications with direct implications in gene expression and chromatin structure regulation. Cancer-associated DNA hypomethylation and hemimethylation appear to contribute to tumor formation and progression. The methylation profile of cell-free DNA (cfDNA) from plasma can be exploited to detect and identify tissue pathologies. IDT has adapted xGen Prism library prep for accurate and sensitive methylation detection in whole genome bisulfite sequencing and target capture workflow in research.
Here is the poster presentation from AACR: