Abstract
BackgroundA cancer genome is derived from the germline genome through a series of somatic mutations. Somatic structural variants - including duplications, deletions, inversions, translocations, and other rearrangements - result in a cancer genome that is a scrambling of intervals, or "blocks" of the germline genome sequence. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data.ResultsBy aligning paired reads from a cancer genome - and a matched germline genome, if available - to the human reference genome, we derive: (i) a partition of the reference genome into intervals; (ii) adjacencies between these intervals in the cancer genome; (iii) an estimated copy number for each interval. We formulate the Copy Number and Adjacency Genome Reconstruction Problem of determining the cancer genome as a sequence of the derived intervals that is consistent with the measured adjacencies and copy numbers. We design an efficient algorithm, called Paired-end Reconstruction of Genome Organization (PREGO), to solve this problem by reducing it to an optimization problem on an interval-adjacency graph constructed from the data. The solution to the optimization problem results in an Eulerian graph, containing an alternating Eulerian tour that corresponds to a cancer genome that is consistent with the sequencing data. We apply our algorithm to five ovarian cancer genomes that were sequenced as part of The Cancer Genome Atlas. We identify numerous rearrangements, or structural variants, in these genomes, analyze reciprocal vs. non-reciprocal rearrangements, and identify rearrangements consistent with known mechanisms of duplication such as tandem duplications and breakage/fusion/bridge (B/F/B) cycles.ConclusionsWe demonstrate that PREGO efficiently identifies complex and biologically relevant rearrangements in cancer genome sequencing data. An implementation of the PREGO algorithm is available at http://compbio.cs.brown.edu/software/.
Highlights
A cancer genome is derived from the germline genome through a series of somatic mutations that accumulate during the lifetime of an individual
In this paper we address the problem of reconstructing the organization of the cancer genome(s) present in a cancer DNA sample from the adjacencies and copy number information revealed by the concordant and discordant pairs from a paired-end resequencing approach
Ovarian sequencing data We analyzed DNA sequencing data from 5 ovarian cancer genomes and matched normal samples that were sequenced as part of The Cancer Genome Atlas (TCGA) (Table 1 and Additional file 1)
Summary
A cancer genome is derived from the germline genome through a series of somatic mutations that accumulate during the lifetime of an individual. These range in size from single nucleotide mutations through larger structural variants (SVs), that duplicate, delete, or rearrange segments of DNA sequence. These structural variants may amplify genes that promote cancer (oncogenes) or delete genes that inhibit cancer development Estimating the number of copies of these amplicons is extremely difficult Determining whether such extensive rearrangements occurred over many cell divisions or nearly simultaneously (e.g. chromothripsis) is difficult [6]. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data
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