Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process

Breakage-Fusion-Bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. The process has parallels with paper folding sequences that arise when a piece of paper is folded several times and then unfolded. Here we adapt such methods to study the breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are 2^(n(n-1)/2) qualitatively distinct evolutions involving n breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the fold positions, to determine evolution likelihoods, and also describe how amplicons become localised. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples

DNA secondary structures are associated with recombination in major Plasmodium falciparum variable surface antigen gene families

Many bacterial, viral and parasitic pathogens undergo antigenic variation to counter host immune defense mechanisms. In Plasmodium falciparum, the most lethal of human malaria parasites, switching of var gene expression results in alternating expression of the adhesion proteins of the Plasmodium falciparum-erythrocyte membrane protein 1 class on the infected erythrocyte surface. Recombination clearly generates var diversity, but the nature and control of the genetic exchanges involved remain unclear. By experimental and bioinformatic identification of recombination events and genome-wide recombination hotspots in var genes, we show that during the parasite’s sexual stages, ectopic recombination between isogenous var paralogs occurs near low folding free energy DNA 50-mers and that these sequences are heavily concentrated at the boundaries of regions encoding individual Plasmodium falciparum-erythrocyte membrane protein 1 structural domains. The recombinogenic potential of these 50-mers is not parasite-specific because these sequences also induce recombination when transferred to the yeast Saccharomyces cerevisiae. Genetic cross data suggest that DNA secondary structures (DSS) act as inducers of recombination during DNA replication in P. falciparum sexual stages, and that these DSS-regulated genetic exchanges generate functional and diverse P. falciparum adhesion antigens. DSS-induced recombination may represent a common mechanism for optimizing the evolvability of virulence gene families in pathogens

ViennaRNA Package 2.0

<p>Abstract</p> <p>Background</p> <p>Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties.</p> <p>Results</p> <p>The <monospace>ViennaRNA</monospace> Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the <it>Turner 2004 </it>parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying <monospace>RNAlib</monospace> and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as <it>centroid </it>structures and <it>maximum expected accuracy </it>structures derived from base pairing probabilities, or <it>z</it>-<it>scores </it>for locally stable secondary structures, and support for input in <monospace>fasta</monospace> format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions.</p> <p>Conclusions</p> <p>The <monospace>ViennaRNA Package 2.0</monospace>, supporting concurrent computations <monospace>via OpenMP</monospace>, can be downloaded from <url>http://www.tbi.univie.ac.at/RNA</url>.</p

Copy number signatures and mutational processes in ovarian carcinoma.

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.NIHR, Ovarian Cancer Action, Cancer Research UK Cambridge Centre, Cambridge Experimental Cancer Medicine Centr

Faster Algorithms for RNA-folding using the Four-Russians method

The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n 3) time using dynamic programming. Four-Russians is a technique that will reduce the running time for certain dynamic programming algorithms by a factor after a preprocessing step where solutions to all smaller subproblems of a fixed size are exhaustively enumerated. Frid and Gusfield designed an O ( n3) algorithm for RNA folding using the Four-Russians technique. However, in their log n algorithm the preprocessing is interleaved with the algorithm computation. We simplify the algorithm and the analysis by doing the preprocessing once prior to the algorithm computation. We call this the two-vector method. We also show variants where instead of exhaustive preprocessing, we only solve the subproblems encountered in the main algorithm once and memoize the results. We give a proof of correctness and explore the practical advantages over the earlier method. The Nussinov algorithm admits an O(n 2) parallel algorithm. We show an parallel algorithm using the two-vector idea that improves the time bound to O(n 2 / log n). We have implemented the parallel algorithm on Graphical processing units using CUDA platform. We discuss the organization of the data structures to exploit coalesced memory access for fast running time. These ideas also help in improving the running time of the serial algorithms. For sequences of up to 6000 bases the parallel algorithm takes only about 2 secs, the two-vector and memoized versions are faster than the Frid-Gusfield algorithm by a factor of 3, and faster than Nussinov by a factor of 20.

Predicting RNA Secondary Structures: One-grammar-fits-all Solution

LNCS v. 9096 entitled: Bioinformatics Research and Applications: 11th International Symposium, ISBRA 2015 Norfolk, USA, June 7-10, 2015 ProceedingsRNA secondary structures are known to be important in many biological processes. Many available programs have been developed for RNA secondary structure prediction. Based on our knowledge, however, there still exist secondary structures of known RNA sequences which cannot be covered by these algorithms. In this paper, we provide an efficient algorithm that can handle all RNA secondary structures found in Rfam database. We designed a new stochastic context-free grammar named Rectangle Tree Grammar (RTG) which significantly expands the classes of structures that can be modelled. Our algorithm runs in O(n 6) time and the accuracy is reasonably high, with average PPV and sensitivity over 75%. In addition, the structures that RTG predicts are very similar to the real ones

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

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 (&gt;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