AmpliconReconstructor integrates NGS and optical mapping to resolve the complex structures of focal amplifications

Jens Luebeck, Ceyda Coruh, Siavash R. Dehkordi, Joshua T. Lange, Kristen M. Turner, Viraj Deshpande, Dave A. Pai, Chao Zhang, Utkrisht Rajkumar, Julie A. Law, Paul S. Mischel and Vineet Bafna ()
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Jens Luebeck: University of California at San Diego
Ceyda Coruh: Salk Institute for Biological Studies
Siavash R. Dehkordi: University of California at San Diego
Joshua T. Lange: University of California at San Diego
Kristen M. Turner: University of California at San Diego
Viraj Deshpande: University of California at San Diego
Dave A. Pai: Bionano Genomics, Inc.
Chao Zhang: University of California at San Diego
Utkrisht Rajkumar: University of California at San Diego
Julie A. Law: Salk Institute for Biological Studies
Paul S. Mischel: University of California at San Diego
Vineet Bafna: University of California at San Diego

Nature Communications, 2020, vol. 11, issue 1, 1-14

Abstract: 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.

Date: 2020
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DOI: 10.1038/s41467-020-18099-z

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