Repository: Freie Universität Berlin, Math Department

Decoil: Reconstructing extrachromosomal DNA structural heterogeneity from long-read sequencing data

Giurgiu, Mădălina and Wittstruck, Nadine and Rodriguez-Fos, Elias and Chamorro González, Rocío and Brückner, Lotte and Krienelke-Szymansky, Annabell and Helmsauer, Konstantin and Hartebrodt, Anne and Koche, Richard P. and Haase, Kerstin and Reinert, Knut and Henssen, Anton G. (2023) Decoil: Reconstructing extrachromosomal DNA structural heterogeneity from long-read sequencing data. bioRxiv - The Preprint Server for Biology .

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Circular extrachromosomal DNA (ecDNA) is a form of oncogene amplification found across cancer types and associated with poor outcome in patients. ecDNA can be structurally complex and contain rearranged DNA sequences derived from multiple chromosome locations. As the structure of ecDNA can impact oncogene regulation and may indicate mechanisms of its formation, disentangling it at high resolution from sequencing data is essential. Even though methods have been developed to identify and reconstruct ecDNA in cancer genome sequencing, it remains challenging to resolve complex ecDNA structures, in particular amplicons with shared genomic footprints. We here introduce Decoil, a computational method which combines a breakpoint-graph approach with LASSO regression to reconstruct complex ecDNA and deconvolve co-occurring ecDNA elements with overlapping genomic footprints from long-read nanopore sequencing. Decoil outperforms de-novo assembly methods in simulated long-read sequencing data for both, simple and complex ecDNAs. Applying Decoil on whole genome sequencing data uncovered different ecDNA topologies and explored ecDNA structure heterogeneity in neuroblastoma tumors and cell lines, indicating that this method may improve ecDNA structural analyzes in cancer.

Item Type:Article
Subjects:Mathematical and Computer Sciences > Computer Science
Divisions:Department of Mathematics and Computer Science > Institute of Computer Science > Algorithmic Bioinformatics Group
ID Code:3141
Deposited By: Anja Kasseckert
Deposited On:18 Apr 2024 10:45
Last Modified:18 Apr 2024 10:45

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