Discipline: Computer Sciences & Information Management
Subcategory: STEM Research
Matthew Hayes - Xavier University of Louisiana
Co-Author(s): Angela Nguyen, Xavier University of Louisiana, New Orleans, LA; Ethan Tran, Xavier University of Louisiana, New Orleans, LA; Derrick Mullins, Xavier University of Louisiana, New Orleans, LA
Double minute chromosomes are acentric, extrachromosomal circular fragments of DNA that are frequently observed in tumor cells of numerous cancer subtypes, engendering the malignancy cancer. They are highly amplified and contain oncogenes and drug resistance genes, making their presence a challenge for effective cancer treatment. Algorithmic discovery of double minutes (DM) can potentially improve bench-derived therapies for cancer treatment. A hindrance to this task is that DMs evolve, yielding circular chromatin that shares segments from progenitor double minutes. This creates double minutes with overlapping amplicon coordinates. Existing DM discovery algorithms largely use whole genome shotgun sequencing in isolation, which could potentially incorrectly classify DMs that share overlapping coordinates. In this study, we describe a pipeline to predict double minutes in tumor genomes by integrating whole genome shotgun sequencing and Hi-C sequencing data. The consolidation of these sources of information resolves ambiguity in double minute amplicon prediction that exists in DM prediction with whole genome sequencing data used in isolation.
Funder Acknowledgement(s): NSF HBCU-UP Research Initiation Award: HRD-1901258
Faculty Advisor: None Listed,
NSF Affiliation: HBCU-UP