Evolution of genes neighborhood within reconciled phylogenies: an ensemble approach

Chauve, Cédric; Ponty, Yann; Zanetti, Joao Paulo Peirera

doi:10.1101/026310

Cited by 5 publications

(18 citation statements)

References 26 publications

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“…Our main contributions are the introduction of the Small Parsimony Problem under the SCJ model with adjacency weights, together with an exact parameterized algorithm for the optimization and sampling versions of the problem. The motivation for this problem is twofold: incorporating sequence signal from aDNA data when it is available, and recent works showing that the reconstruction of ancestral genomes through the independent analysis of adjacencies is an interesting approach [5], [12], [17], [27].…”

Section: Resultsmentioning

confidence: 99%

“…However, we can observe a significant difference with a DCJ-based ancestral reconstruction, a phenomenon that deserves to be explored further. Our algorithm, which is based on the Sankoff-Rousseau algorithm similarly to several recent ancestral reconstruction algorithms [5], [12], [27], is a parameterized algorithm that can handle real instances containing a moderate level of syntenic conflict. Our experimental results on both the mammalian and bacterial datasets suggest that introducing prior weights on adjacencies in the objective function has a significant impact in reducing the fragmentation of ancestral gene orders, even with an objective function with balanced contributions of the SCJ evolution and adjacency weights.…”

Section: Resultsmentioning

confidence: 99%

“…From a more applied point of view, one would like to incorporate duplicated and deleted markers into our Small Parsimony Problem. There exist efficient algorithms for the case of a single adjacency [5], [12] that can provide adjacency weights, and natural extensions of the SCJ model to incorporate duplicated genes. However it remains to effectively combine these ideas.…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

The SCJ Small Parsimony Problem for Weighted Gene Adjacencies

Luhmann

Thévenin

Ouangraoua

et al. 2016

Bioinformatics Research and Applications

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Reconstructing ancestral gene orders in a given phylogeny is a classical problem in comparative genomics. Most existing methods compare conserved features in extant genomes in the phylogeny to define potential ancestral gene adjacencies, and either try to reconstruct all ancestral genomes under a global evolutionary parsimony criterion, or, focusing on a single ancestral genome, use a scaffolding approach to select a subset of ancestral gene adjacencies, generally aiming at reducing the fragmentation of the reconstructed ancestral genome. In this paper, we describe an exact algorithm for the Small Parsimony Problem that combines both approaches. We consider that gene adjacencies at internal nodes of the species phylogeny are weighted, and we introduce an objective function defined as a convex combination of these weights and the evolutionary cost under the Single-Cut-or-Join (SCJ) model. The weights of ancestral gene adjacencies can e. g. be obtained through the recent availability of ancient DNA sequencing data, which provide a direct hint at the genome structure of the considered ancestor, or through probabilistic analysis of gene adjacencies evolution. We show the NP-hardness of our problem variant and propose a Fixed-Parameter Tractable algorithm based on the Sankoff-Rousseau dynamic programming algorithm that also allows to sample co-optimal solutions. We apply our approach to mammalian and bacterial data providing different degrees of complexity. We show that including adjacency weights in the objective has a significant impact in reducing the fragmentation of the reconstructed ancestral gene orders. An implementation is available at

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The SCJ Small Parsimony Problem for Weighted Gene Adjacencies

Luhmann

Thévenin

Ouangraoua

et al. 2016

Bioinformatics Research and Applications

Self Cite

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“…We then considered the robustness of individual ancestral adjacencies. Using the variant DeClone of DeCo that explores the set of all evolutionary scenarios [6], we extracted, for each instance, the set of ancestral adjacencies that belong to all parsimonious solutions for the cost scheme (1,1), and computed their robustness as defined in the previous sections. This set of ancestral adjacencies contains 87, 019 adjacencies covering 106, 903 ancestral genes.…”

Section: Resultsmentioning

confidence: 99%

Assessing the Robustness of Parsimonious Predictions for Gene Neighborhoods from Reconciled Phylogenies: Supplementary Material

Rajaraman

Chauve

Ponty

2015

Lecture Notes in Computer Science

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The availability of many assembled genomes opens the way to study the evolution of syntenic character within a phylogenetic context. The DeCo algorithm, recently introduced by Bérard et al., computes parsimonious evolutionary scenarios for gene adjacencies, from pairs of reconciled gene trees. Following the approach pioneered by Sturmfels and Pachter, we describe how to modify the DeCo dynamic programming algorithm to identify classes of cost schemes that generate similar parsimonious evolutionary scenarios for gene adjacencies. We also describe how to assess the robustness, again to changes of the cost scheme, of the presence or absence of specific ancestral gene adjacencies in parsimonious evolutionary scenarios. We apply our method to six thousands mammalian gene families, and show that computing the robustness to changes of cost schemes provides interesting insights on the DeCo model.

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“…2012), DeCoLT (Patterson et�al. 2013), DeClone (Chauve et�al. 2015), and ART-DeCo (Anselmetti et�al.…”

Section: Features and Implementationmentioning

confidence: 99%

DeCoSTAR: Reconstructing the Ancestral Organization of Genes or Genomes Using Reconciled Phylogenies

Duchemin

Anselmetti

Patterson

et al. 2017

Genome Biology and Evolution

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DeCoSTAR is a software that aims at reconstructing the organization of ancestral genes or genomes in the form of sets of neighborhood relations (adjacencies) between pairs of ancestral genes or gene domains. It can also improve the assembly of fragmented genomes by proposing evolutionary-induced adjacencies between scaffolding fragments. Ancestral genes or domains are deduced from reconciled phylogenetic trees under an evolutionary model that considers gains, losses, speciations, duplications, and transfers as possible events for gene evolution. Reconciliations are either given as input or computed with the ecceTERA package, into which DeCoSTAR is integrated. DeCoSTAR computes adjacency evolutionary scenarios using a scoring scheme based on a weighted sum of adjacency gains and breakages. Solutions, both optimal and near-optimal, are sampled according to the Boltzmann–Gibbs distribution centered around parsimonious solutions, and statistical supports on ancestral and extant adjacencies are provided. DeCoSTAR supports the features of previously contributed tools that reconstruct ancestral adjacencies, namely DeCo, DeCoLT, ART-DeCo, and DeClone. In a few minutes, DeCoSTAR can reconstruct the evolutionary history of domains inside genes, of gene fusion and fission events, or of gene order along chromosomes, for large data sets including dozens of whole genomes from all kingdoms of life. We illustrate the potential of DeCoSTAR with several applications: ancestral reconstruction of gene orders for Anopheles mosquito genomes, multidomain proteins in Drosophila, and gene fusion and fission detection in Actinobacteria. Availability: http://pbil.univ-lyon1.fr/software/DeCoSTAR (Last accessed April 24, 2017).

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Evolution of genes neighborhood within reconciled phylogenies: an ensemble approach

Cited by 5 publications

References 26 publications

The SCJ Small Parsimony Problem for Weighted Gene Adjacencies

The SCJ Small Parsimony Problem for Weighted Gene Adjacencies

Assessing the Robustness of Parsimonious Predictions for Gene Neighborhoods from Reconciled Phylogenies: Supplementary Material

DeCoSTAR: Reconstructing the Ancestral Organization of Genes or Genomes Using Reconciled Phylogenies

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