Abstract

Oncogene amplification, a major driver of cancer pathogenicity, is often mediated through focal amplification of genomic segments. Recent results implicate extrachromosomal DNA (ecDNA) as the primary driver of focal copy number amplification (fCNA) - enabling gene amplification, rapid tumor evolution, and the rewiring of regulatory circuitry. Resolving an fCNA’s structure is a first step in deciphering the mechanisms of its genesis and the fCNA’s subsequent biological consequences. We introduce a computational method, AmpliconReconstructor (AR), for integrating optical mapping (OM) of long DNA fragments (>150 kb) with next-generation sequencing (NGS) to resolve fCNAs at single-nucleotide resolution. AR uses an NGS-derived breakpoint graph alongside OM scaffolds to produce high-fidelity reconstructions. After validating its performance through multiple simulation strategies, AR reconstructed fCNAs in seven cancer cell lines to reveal the complex architecture of ecDNA, a breakage-fusion-bridge and other complex rearrangements. By reconstructing the rearrangement signatures associated with an fCNA’s generative mechanism, AR enables a more thorough understanding of the origins of fCNAs.

Focal copy number amplifications (fCNAs), which drive cancer pathogenicity, arise by a number of mechanisms and can be challenging to call. Here the authors present AmpliconReconstructor for precise and scalable fCNA reconstruction using optical mapping and next-generation sequencing data.

Details

Title
AmpliconReconstructor integrates NGS and optical mapping to resolve the complex structures of focal amplifications
Author
Luebeck Jens 1 ; Coruh Ceyda 2 ; Dehkordi, Siavash R 3 ; Lange, Joshua T 4 ; Turner, Kristen M 5 ; Deshpande Viraj 3   VIAFID ORCID Logo  ; Pai, Dave A 6 ; Zhang, Chao 7   VIAFID ORCID Logo  ; Utkrisht, Rajkumar 3 ; Law, Julie A 2   VIAFID ORCID Logo  ; Mischel, Paul S 8   VIAFID ORCID Logo  ; Bafna Vineet 3 

 University of California at San Diego, Bioinformatics and Systems Biology Graduate Program, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); University of California at San Diego, Department of Computer Science and Engineering, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
 Salk Institute for Biological Studies, Plant Molecular and Cellular Biology Laboratory, La Jolla, USA (GRID:grid.250671.7) (ISNI:0000 0001 0662 7144) 
 University of California at San Diego, Department of Computer Science and Engineering, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
 University of California at San Diego, Biomedical Sciences Graduate Program, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); University of California at San Diego, Ludwig Institute for Cancer Research, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
 University of California at San Diego, Ludwig Institute for Cancer Research, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
 Bionano Genomics, Inc., San Diego, USA (GRID:grid.470262.5) (ISNI:0000 0004 0473 1353) 
 University of California at San Diego, Bioinformatics and Systems Biology Graduate Program, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
 University of California at San Diego, Ludwig Institute for Cancer Research, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); University of California at San Diego, Moores Cancer Center, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); University of California at San Diego, Department of Pathology, La Jolla, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2439113525
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.