Abstract
The Breakage Fusion Bridge (BFB) process is a key marker for genomic instability, producing highly rearranged genomes in relatively small number of cell cycles. While the process itself was observed during the late 1930’s, little is known about the extent of BFB in tumor genome evolution. This is partly due to methodological requiring the rare observation of a spontaneous BFB occurence, or rigorous assays for identifying BFB-modified genomes after the process has ceased. 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 predict 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. An online Appendix, the source code of our tool, and analyses results, are available at http://cseweb.ucsd.edu/~vbafna/bfb .
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Zakov, S., Bafna, V. (2014). Reconstructing Breakage Fusion Bridge Architectures Using Noisy Copy Numbers. In: Sharan, R. (eds) Research in Computational Molecular Biology. RECOMB 2014. Lecture Notes in Computer Science(), vol 8394. Springer, Cham. https://doi.org/10.1007/978-3-319-05269-4_32
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DOI: https://doi.org/10.1007/978-3-319-05269-4_32
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