title: Reconstructing breakage fusion bridge architectures using noisy copy numbers.
abstract: The Breakage Fusion Bridge (BFB) process is a key marker for genomic instability, producing highly rearranged genomes in relatively small numbers of cell cycles. While the process itself was observed during the late 1930s, little is known about the extent of BFB in tumor genome evolution. Moreover, BFB can dramatically increase copy numbers of chromosomal segments, which in turn hardens the tasks of both reference-assisted and ab initio genome assembly. Based on available data such as Next Generation Sequencing (NGS) and Array Comparative Genomic Hybridization (aCGH) data, we show here how BFB evidence may be identified, and how to enumerate all possible evolutions of the process with respect to observed data. Specifically, we describe practical algorithms that, given a chromosomal arm segmentation and noisy segment copy number estimates, produce all segment count vectors supported by the data that can be produced by BFB, and all corresponding BFB architectures. This extends the scope of analyses described in our previous work, which produced a single count vector and architecture per instance. We apply these analyses to a comprehensive human cancer dataset, demonstrate the effectiveness and efficiency of the computation, and suggest methods for further assertions of candidate BFB samples. Source code of our tool can be found online.
authors.affiliation: Department of Computer Science and Engineering, University of California San Diego, La Jolla, California.
authors.forename: Shay
authors.initials: S
authors.lastname: Zakov
authors.affiliation: Department of Computer Science and Engineering, University of California San Diego, La Jolla, California.
authors.forename: Vineet
authors.initials: V
authors.lastname: Bafna
mesh_terms: D000465:Algorithms; D002875:Chromosomes / Q000235:genetics*; D055028:Comparative Genomic Hybridization; D005784:Gene Amplification / Q000235:genetics; D018628:Gene Dosage / Q000235:genetics*; D015894:Genome, Human / Q000235:genetics*; D042822:Genomic Instability / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D009369:Neoplasms / Q000235:genetics
keywords: RNA; algorithms; combinatorial proteomics; computational molecular biology; dynamic programming; genetic variation; sequence analysis.