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Yun S. Song,
Zhihong Ding,
Dan Gusfield,
Charles Langley and
Yufeng Wu. Algorithms to Distinguish the Role of Gene-Conversion from Single-Crossover Recombination in the Derivation of SNP Sequences in Populations. In JCB, Vol. 14(10):1273-1286, 2007.
Keywords: ARG, from sequences, phylogenetic network, phylogeny, Program SHRUB, reconstruction.
Note: http://dx.doi.org/10.1089/cmb.2007.0096.
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"Meiotic recombination is a fundamental biological event and one of the principal evolutionary forces responsible for shaping genetic variation within species. In addition to its fundamental role, recombination is central to several critical applied problems. The most important example is "association mapping" in populations, which is widely hoped to help find genes that influence genetic diseases (Carlson et al., 2004; Clark, 2003). Hence, a great deal of recent attention has focused on problems of inferring the historical derivation of sequences in populations when both mutations and recombinations have occurred. In the algorithms literature, most of that recent work has been directed to single-crossover recombination. However, gene-conversion is an important, and more common, form of (two-crossover) recombination which has been much less investigated in the algorithms literature. In this paper, we explicitly incorporate gene-conversion into discrete methods to study historical recombination. We are concerned with algorithms for identifying and locating the extent of historical crossing-over and gene-conversion (along with single-nucleotide mutation), and problems of constructing full putative histories of those events. The novel technical issues concern the incorporation of gene-conversion into recently developed discrete methods (Myers and Griffiths, 2003; Song et al., 2005) that compute lower and upper-bound information on the amount of needed recombination without gene-conversion. We first examine the most natural extension of the lower bound methods from Myers and Griffiths (2003), showing that the extension can be computed efficiently, but that this extension can only yield weak lower bounds. We then develop additional ideas that lead to higher lower bounds, and show how to solve, via integer-linear programming, a more biologically realistic version of the lower bound problem. We also show how to compute effective upper bounds on the number of needed single-crossovers and gene-conversions, along with explicit networks showing a putative history of mutations, single-crossovers and gene-conversions. Both lower and upper bound methods can handle data with missing entries, and the upper bound method can be used to infer missing entries with high accuracy. We validate the significance of these methods by showing that they can be effectively used to distinguish simulation-derived sequences generated without gene-conversion from sequences that were generated with gene-conversion. We apply the methods to recently studied sequences of Arabidopsis thaliana, identifying many more regions in the sequences than were previously identified (Plagnol et al., 2006), where gene-conversion may have played a significant role. Demonstration software is available at www.csif.cs.ucdavis.edu/∼gusfield. © 2007 Mary Ann Liebert, Inc."
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Dan Gusfield,
Satish Eddhu and
Charles Langley. The fine structure of galls in phylogenetic networks. In INCOMP, Vol. 16(4):459-469, 2004.
Keywords: explicit network, from sequences, galled tree, phylogenetic network, phylogeny, reconstruction.
Note: http://wwwcsif.cs.ucdavis.edu/~gusfield/informs.pdf.
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"A phylogenetic network is a generalization of a phylogenetic tree, allowing properties that are not tree-like. With the growth of genomic data, much of which does not fit ideal tree models, there is greater need to understand the algorithmics and combinatorics of phylogenetic networks (Posada and Crandall 2001, Schierup and Hein 2000). Wang et al. (2001) studied the problem of constructing a phylogenetic network for a set of n binary sequences derived from the all-zero ancestral sequence, when each site in the sequence can mutate from zero to one at most once in the network, and recombination between sequences is allowed. They showed that the problem of minimizing the number of recombinations in such networks is NP-hard, but introduced a special case of the problem, i.e., to determine whether the sequences could be derived on a phylogenetic network where the recombination cycles are node-disjoint. Wang et al. (2001) provide a sufficient, but not a necessary test, for such solutions. Gusfield et al. (2003, 2004) gave a polynomial-time algorithm that is both a necessary and sufficient test. In this paper, we study in much more detail the fine combinatorial structure of node-disjoint cycles in phylogenetic networks, both for purposes of insight into phylogenetic networks and to speed up parts of the previous algorithm. We explicitly characterize all the ways in which mutations can be arranged on a disjoint cycle, and prove a strong necessary condition for a set of mutations to be on a disjoint cycle. The main contribution here is to show how structure in the phylogenetic network is reflected in the structure of an efficiently-computable graph, called the conflict graph. The success of this approach suggests that additional insight into the structure of phylogenetic networks can be obtained by exploring structural properties of the conflict graph."
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Dan Gusfield,
Satish Eddhu and
Charles Langley. Optimal, Efficient Reconstruction of Phylogenetic Networks with Constrained Recombination. In JBCB, Vol. 2(1):173-213, 2004.
Keywords: explicit network, from sequences, galled tree, phylogenetic network, phylogeny, recombination, reconstruction.
Note: http://wwwcsif.cs.ucdavis.edu/~gusfield/exfinalrec.pdf.
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"A phylogenetic network is a generalization of a phylogenetic tree, allowing structural properties that are not tree-like. In a seminal paper, Wang et al.1 studied the problem of constructing a phylogenetic network, allowing recombination between sequences, with the constraint that the resulting cycles must be disjoint. We call such a phylogenetic network a "galled-tree". They gave a polynomial-time algorithm that was intended to determine whether or not a set of sequences could be generated on galled-tree. Unfortunately, the algorithm by Wang et al.1 is incomplete and does not constitute a necessary test for the existence of a galled-tree for the data. In this paper, we completely solve the problem. Moreover, we prove that if there is a galled-tree, then the one produced by our algorithm minimizes the number of recombinations over all phylogenetic networks for the data, even allowing multiple-crossover recombinations. We also prove that when there is a galled-tree for the data, the galled-tree minimizing the number of recombinations is "essentially unique" . We. also note two additional results: first, any set of sequences that can be derived on a galled tree can be derived on a true tree (without recombination cycles), where at most one back mutation per site is allowed; second, the site compatibility problem (which is NP-hard in general) can be solved in polynomial time for any set of sequences that can be derived on a galled tree. Perhaps more important than the specific results about galled-trees, we introduce an approach that can be used to study recombination in general phylogenetic networks. This paper greatly extends the conference version that appears in an earlier work.8 PowerPoint slides of the conference talk can be found at our website. © Imperial College Press."
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- forked on GitHub.