17 research outputs found

    Gene rearrangement analysis and ancestral order inference from chloroplast genomes with inverted repeat

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    Background Genome evolution is shaped not only by nucleotide substitutions, but also by structural changes including gene and genome duplications, insertions, deletions and gene order rearrangements. The most popular methods for reconstructing phylogeny from genome rearrangements include GRAPPA and MGR. However these methods are limited to cases where equal gene content or few deletions can be assumed. Since conserved duplicated regions are present in many chloroplast genomes, the inference of inverted repeats is needed in chloroplast phylogeny analysis and ancestral genome reconstruction. Results We extend GRAPPA and develop a new method GRAPPA-IR to handle chloroplast genomes. A test of GRAPPA-IR using divergent chloroplast genomes from land plants and green algae recovers the phylogeny congruent with prior studies, while analysis that do not consider IR structure fail to obtain the accepted topology. Our extensive simulation study also confirms that GRAPPA has better accuracy then the existing methods. Conclusions Tests on a biological and simulated dataset show GRAPPA-IR can accurately recover the genome phylogeny as well as ancestral gene orders. Close analysis of the ancestral genome structure suggests that genome rearrangement in chloroplasts is probably limited by inverted repeats with a conserved core region. In addition, the boundaries of inverted repeats are hot spots for gene duplications or deletions. The new GRAPPA-IR is available from http://phylo.cse.sc.ed

    Phylogenetic reconstruction from transpositions

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    Background Because of the advent of high-throughput sequencing and the consequent reduction in the cost of sequencing, many organisms have been completely sequenced and most of their genes identified. It thus has become possible to represent whole genomes as ordered lists of gene identifiers and to study the rearrangement of these entities through computational means. As a result, genome rearrangement data has attracted increasing attentions from both biologists and computer scientists as a new type of data for phylogenetic analysis. The main events of genome rearrangements include inversions, transpositions and transversions. To date, GRAPPA and MGR are the most accurate methods for rearrangement phylogeny, both assuming inversion as the only event. However, due to the complexity of computing transposition distance, it is very difficult to analyze datasets when transpositions are dominant. Results We extend GRAPPA to handle transpositions. The new method is named GRAPPA-TP, with two major extensions: a heuristic method to estimate transposition distance, and a new transposition median solver for three genomes. Although GRAPPA-TP uses a greedy approach to compute the transposition distance, it is very accurate when genomes are relatively close. The new GRAPPA-TP is available from http://phylo.cse.sc.edu/ Conclusion Our extensive testing using simulated datasets shows that GRAPPA-TP is very accurate in terms of ancestor genome inference and phylogenetic reconstruction. Simulation results also suggest that model match is critical in genome rearrangement analysis: it is not accurate to simulate transpositions with other events including inversions

    Conserved Interval Distance Computation Between Non-trivial Genomes

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    Recently, several studies taking into account the ability for a gene to be absent or to have some copies in genomes have been proposed, as the examplar distance [6,11] or the gene matching computation between two genomes [3,10]. In this paper, we study the time complexity of the conserved interval distance computation considering duplicated genes using both those two strategies

    Genomic distances under deletions and insertions

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    As more and more genomes are sequenced, evolutionary biologists are becoming increasingly interested in evolution at the level of whole genomes, in scenarios in which the genome evolves through insertions, deletions, and movements of genes along its chromosomes. In the mathematical model pioneered by Sankoff and others, a unichromosomal genome is represented by a signed permutation of a multiset of genes; Hannenhalli and Pevzner showed that the edit distance between two signed permutations of the same set can be computed in polynomial time when all operations are inversions. El-Mabrouk extended that result to allow deletions (or conversely, a limited form of insertions which forbids duplications). In this paper, we extend El-Mabrouk's work to handle duplications as well as insertions and present an alternate framework for computing (near) minimal edit sequences involving insertions, deletions, and inversions. We derive an error bound for our polynomial-time distance computation under various assumptions and present preliminary experimental results that suggest that performance in practice may be excellent, within a few percent of the actual distance

    A fast algorithm for the multiple genome rearrangement problem with weighted reversals and transpositions

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    <p>Abstract</p> <p>Background</p> <p>Due to recent progress in genome sequencing, more and more data for phylogenetic reconstruction based on rearrangement distances between genomes become available. However, this phylogenetic reconstruction is a very challenging task. For the most simple distance measures (the breakpoint distance and the reversal distance), the problem is NP-hard even if one considers only three genomes.</p> <p>Results</p> <p>In this paper, we present a new heuristic algorithm that directly constructs a phylogenetic tree w.r.t. the weighted reversal and transposition distance. Experimental results on previously published datasets show that constructing phylogenetic trees in this way results in better trees than constructing the trees w.r.t. the reversal distance, and recalculating the weight of the trees with the weighted reversal and transposition distance. An implementation of the algorithm can be obtained from the authors.</p> <p>Conclusion</p> <p>The possibility of creating phylogenetic trees directly w.r.t. the weighted reversal and transposition distance results in biologically more realistic scenarios. Our algorithm can solve today's most challenging biological datasets in a reasonable amount of time.</p

    Rec-DCM-Eigen: Reconstructing a Less Parsimonious but More Accurate Tree in Shorter Time

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    Maximum parsimony (MP) methods aim to reconstruct the phylogeny of extant species by finding the most parsimonious evolutionary scenario using the species' genome data. MP methods are considered to be accurate, but they are also computationally expensive especially for a large number of species. Several disk-covering methods (DCMs), which decompose the input species to multiple overlapping subgroups (or disks), have been proposed to solve the problem in a divide-and-conquer way

    Inversion medians outperform breakpoint medians in phylogeny reconstruction from gene-order data

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    Abstract. Phylogeny reconstruction from gene-order data has attracted much attention over the last few years. The two software packages used for that purpose, BPAnalysis and GRAPPA, both use so-called breakpoint medians in their computations. Some of our past results indicate that using inversion scores rather than breakpoint scores in evaluating trees leads to the selection of better trees. On that basis, we conjectured that phylogeny reconstructions could be improved by using inversion medians, which minimize evolutionary distance under an inversionsonly model of genome rearrangement. Recent algorithmic developments have made it possible to compute inversion medians for problems of realistic size. Our experimental studies unequivocally show that inversion medians are strongly preferable to breakpoint medians in the context of phylogenetic reconstruction from gene-order data. Improvements are most pronounced in the reconstruction of ancestral genomes, but are also evident in the topological accuracy of the reconstruction as well as, surprisingly, in the overall running time. Improvements are strongest for small average distances along tree edges and for evolutionary scenarios with a preponderance of inversion events, but occur in all cases, including evolutionary scenarios with high proportions of transpositions. All of our tests were run using our GRAPPA package, available (under GPL) at www.cs.unm.edu/∼moret/GRAPPA/; the next release will include the inversion median software we used in this study. The software used includes RevMed, developed by the authors and available at www.cs.unm.edu/∼acs/, and A. Caprara’s inversion median code, generously made available for testing
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