Reconciliation of Gene and Species Trees

Rusin, L.Y.; Lyubetskaya, E. V.; Gorbunov, K. Yu.; Lyubetsky, Vassily

doi:10.1155/2014/642089

Cited by 22 publications

(26 citation statements)

References 113 publications

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“…We proceed by showing that it is equivalent to axioms that are commonly used in the literature, see e.g. Górecki and Tiuryn [2006], Vernot et al [2008], Doyon et al [2011], Rusin et al [2014], Hellmuth [2017], Nøjgaard et al [2018], and the references therein.…”

Section: Reconciliation Maps Event Labelings and Orthology Relationsmentioning

confidence: 99%

Best match graphs and reconciliation of gene trees with species trees

et al. 2020

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A wide variety of problems in computational biology, most notably the assessment of orthology, are solved with the help of reciprocal best matches. Using an evolutionary definition of best matches that captures the intuition behind the concept we clarify rigorously the relationships between reciprocal best matches, orthology, and evolutionary events under the assumption of duplication/loss scenarios. We show that the orthology graph is a subgraph of the reciprocal best match graph (RBMG). We furthermore give conditions under which an RBMG that is a cograph identifies the correct orthlogy relation. Using computer simulations we find that most false positive orthology assignments can be identified as so-called good quartets -and thus corrected -in the absence of horizontal transfer. Horizontal transfer, however, may introduce also false-negative orthology assignments.

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Section: Reconciliation Maps Event Labelings and Orthology Relationsmentioning

confidence: 99%

Best match graphs and reconciliation of gene trees with species trees

et al. 2020

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“…Backing away the problem of chromosome structures, for species the algorithms reconstructing evolutionary scenarios with cubic computational complexity are given in [ 12 ]. A similar problem for regulatory systems is considered, e.g., in [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…Algorithms with such a property are called approximate algorithms. Part “Exact linear algorithm calculating the distance between chromosome structures” and [ 1 , 5 – 7 , 12 ] sets the coefficient k equal to 1, while in Part “Algorithm for the reconstruction of chromosome structures with cubic complexity and sufficient approximation ratio” it equals 2 or 11/6. These cases are fundamentally different from heuristic algorithms, whose results are in unknown relation to the minimum (“true”) solution.…”

Section: Introductionmentioning

confidence: 99%

Algorithms for reconstruction of chromosomal structures

et al. 2016

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BackgroundOne of the main aims of phylogenomics is the reconstruction of objects defined in the leaves along the whole phylogenetic tree to minimize the specified functional, which may also include the phylogenetic tree generation. Such objects can include nucleotide and amino acid sequences, chromosomal structures, etc. The structures can have any set of linear and circular chromosomes, variable gene composition and include any number of paralogs, as well as any weights of individual evolutionary operations to transform a chromosome structure. Many heuristic algorithms were proposed for this purpose, but there are just a few exact algorithms with low (linear, cubic or similar) polynomial computational complexity among them to our knowledge. The algorithms naturally start from the calculation of both the distance between two structures and the shortest sequence of operations transforming one structure into another. Such calculation per se is an NP-hard problem.ResultsA general model of chromosomal structure rearrangements is considered. Exact algorithms with almost linear or cubic polynomial complexities have been developed to solve the problems for the case of any chromosomal structure but with certain limitations on operation weights. The computer programs are tested on biological data for the problem of mitochondrial or plastid chromosomal structure reconstruction. To our knowledge, no computer programs are available for this model.ConclusionsExactness of the proposed algorithms and such low polynomial complexities were proved. The reconstructed evolutionary trees of mitochondrial and plastid chromosomal structures as well as the ancestral states of the structures appear to be reasonable.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0878-z) contains supplementary material, which is available to authorized users.

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“…Equivalent axiom systems are considered e.g. in [43][44][45]. Such reconciliation maps satisfy i.e, an event x ∈ V (T ) in the gene tree cannot be mapped to a node in the species tree below the last common ancestor of all the species In this contribution we assume that µ in addition satisfies (R4): If µ( lca T (x, y)) = µ( lca T (x, z)) ∈ V 0 (S) , then lca S (σ (x), σ (y)) = lca S (σ (x), σ (z)) .…”

Section: Reconciliation Of Gene Tree and Species Treementioning

confidence: 99%

From pairs of most similar sequences to phylogenetic best matches

Stadler

Geiß

Schaller

et al. 2020

Algorithms Mol Biol

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Background: Many of the commonly used methods for orthology detection start from mutually most similar pairs of genes (reciprocal best hits) as an approximation for evolutionary most closely related pairs of genes (reciprocal best matches). This approximation of best matches by best hits becomes exact for ultrametric dissimilarities, i.e., under the Molecular Clock Hypothesis. It fails, however, whenever there are large lineage specific rate variations among paralogous genes. In practice, this introduces a high level of noise into the input data for best-hit-based orthology detection methods.Results: If additive distances between genes are known, then evolutionary most closely related pairs can be identified by considering certain quartets of genes provided that in each quartet the outgroup relative to the remaining three genes is known. A priori knowledge of underlying species phylogeny greatly facilitates the identification of the required outgroup. Although the workflow remains a heuristic since the correct outgroup cannot be determined reliably in all cases, simulations with lineage specific biases and rate asymmetries show that nearly perfect results can be achieved. In a realistic setting, where distances data have to be estimated from sequence data and hence are noisy, it is still possible to obtain highly accurate sets of best matches.Conclusion: Improvements of tree-free orthology assessment methods can be expected from a combination of the accurate inference of best matches reported here and recent mathematical advances in the understanding of (reciprocal) best match graphs and orthology relations.Availability: Accompanying software is available at https ://githu b.com/david -schal ler/Asymm eTree .

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Reconciliation of Gene and Species Trees

Cited by 22 publications

References 113 publications

Best match graphs and reconciliation of gene trees with species trees

Best match graphs and reconciliation of gene trees with species trees

Algorithms for reconstruction of chromosomal structures

From pairs of most similar sequences to phylogenetic best matches

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