Dataset Information

An algorithmic approach for breakage-fusion-bridge detection in tumor genomes.

ABSTRACT: Breakage-fusion-bridge (BFB) is a mechanism of genomic instability characterized by the joining and subsequent tearing apart of sister chromatids. When this process is repeated during multiple rounds of cell division, it leads to patterns of copy number increases of chromosomal segments as well as fold-back inversions where duplicated segments are arranged head-to-head. These structural variations can then drive tumorigenesis. BFB can be observed in progress using cytogenetic techniques, but generally BFB must be inferred from data such as microarrays or sequencing collected after BFB has ceased. Making correct inferences from this data is not straightforward, particularly given the complexity of some cancer genomes and BFB's ability to generate a wide range of rearrangement patterns. Here we present algorithms to aid the interpretation of evidence for BFB. We first pose the BFB count-vector problem: given a chromosome segmentation and segment copy numbers, decide whether BFB can yield a chromosome with the given segment counts. We present a linear time algorithm for the problem, in contrast to a previous exponential time algorithm. We then combine this algorithm with fold-back inversions to develop tests for BFB. We show that, contingent on assumptions about cancer genome evolution, count vectors and fold-back inversions are sufficient evidence for detecting BFB. We apply the presented techniques to paired-end sequencing data from pancreatic tumors and confirm a previous finding of BFB as well as identify a chromosomal region likely rearranged by BFB cycles, demonstrating the practicality of our approach.

SUBMITTER: Zakov S

PROVIDER: S-EPMC3619374 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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An algorithmic approach for breakage-fusion-bridge detection in tumor genomes.

Zakov Shay S Kinsella Marcus M Bafna Vineet V

Proceedings of the National Academy of Sciences of the United States of America 20130315 14

Breakage-fusion-bridge (BFB) is a mechanism of genomic instability characterized by the joining and subsequent tearing apart of sister chromatids. When this process is repeated during multiple rounds of cell division, it leads to patterns of copy number increases of chromosomal segments as well as fold-back inversions where duplicated segments are arranged head-to-head. These structural variations can then drive tumorigenesis. BFB can be observed in progress using cytogenetic techniques, but gen ...[more]

PMID: 23503850

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Project description:Chromosomal rearrangements are a major driver of eukaryotic genome evolution, affecting speciation, pathogenicity and cancer progression. Changes in chromosome structure are often initiated by mis-repair of double-strand breaks in the DNA. Mis-repair is particularly likely when telomeres are lost or when dispersed repeats misalign during crossing-over. Fungi carry highly polymorphic chromosomal complements showing substantial variation in chromosome length and number. The mechanisms driving chromosome polymorphism in fungi are poorly understood. We aimed to identify mechanisms of chromosomal rearrangements in the fungal wheat pathogen Zymoseptoria tritici. We combined population genomic resequencing and chromosomal segment PCR assays with electrophoretic karyotyping and resequencing of parents and offspring from experimental crosses to show that this pathogen harbors a highly diverse complement of accessory chromosomes that exhibits strong global geographic differentiation in numbers and lengths of chromosomes. Homologous chromosomes carried highly differentiated gene contents due to numerous insertions and deletions. The largest accessory chromosome recently doubled in length through insertions totaling 380 kb. Based on comparative genomics, we identified the precise breakpoint locations of these insertions. Nondisjunction during meiosis led to chromosome losses in progeny of three different crosses. We showed that a new accessory chromosome emerged in two viable offspring through a fusion between sister chromatids. Such chromosome fusion is likely to initiate a breakage-fusion-bridge (BFB) cycle that can rapidly degenerate chromosomal structure. We suggest that the accessory chromosomes of Z. tritici originated mainly from ancient core chromosomes through a degeneration process that included BFB cycles, nondisjunction and mutational decay of duplicated sequences. The rapidly evolving accessory chromosome complement may serve as a cradle for adaptive evolution in this and other fungal pathogens.

Project description:BackgroundAtrial fibrillation (AFib) is the most common cardiac arrhythmia associated with stroke, blood clots, heart failure, coronary artery disease, and/or death. Multiple methods have been proposed for AFib detection, with varying performances, but no single approach appears to be optimal. We hypothesized that each state-of-the-art algorithm is appropriate for different subsets of patients and provides some independent information. Therefore, a set of suitably chosen algorithms, combined in a weighted voting framework, will provide a superior performance to any single algorithm.MethodsWe investigate and modify 38 state-of-the-art AFib classification algorithms for a single-lead ambulatory electrocardiogram (ECG) monitoring device. All algorithms are ranked using a random forest classifier and an expert-labeled training dataset of 2,532 recordings. The seven top-ranked algorithms are combined by using an optimized weighting approach.ResultsThe proposed fusion algorithm, when validated on a separate test dataset consisting of 4,644 recordings, resulted in an area under the receiver operating characteristic (ROC) curve of 0.99. The sensitivity, specificity, positive-predictive-value (PPV), negative-predictive-value (NPV), and F1-score of the proposed algorithm were 0.93, 0.97, 0.87, 0.99, and 0.90, respectively, which were all superior to any single algorithm or any previously published.ConclusionThis study demonstrates how a set of well-chosen independent algorithms and a voting mechanism to fuse the outputs of the algorithms, outperforms any single state-of-the-art algorithm for AFib detection. The proposed framework is a case study for the general notion of crowdsourcing between open-source algorithms in healthcare applications. The extension of this framework to similar applications may significantly save time, effort, and resources, by combining readily existing algorithms. It is also a step toward the democratization of artificial intelligence and its application in healthcare.

Dataset Information

An algorithmic approach for breakage-fusion-bridge detection in tumor genomes.

Publications

An algorithmic approach for breakage-fusion-bridge detection in tumor genomes.

Similar Datasets

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