Literature DB >> 17068107

Inferring phylogenetic networks by the maximum parsimony criterion: a case study.

Guohua Jin1, Luay Nakhleh, Sagi Snir, Tamir Tuller.   

Abstract

Horizontal gene transfer (HGT) may result in genes whose evolutionary histories disagree with each other, as well as with the species tree. In this case, reconciling the species and gene trees results in a network of relationships, known as the "phylogenetic network" of the set of species. A phylogenetic network that incorporates HGT consists of an underlying species tree that captures vertical inheritance and a set of edges which model the "horizontal" transfer of genetic material. In a series of papers, Nakhleh and colleagues have recently formulated a maximum parsimony (MP) criterion for phylogenetic networks, provided an array of computationally efficient algorithms and heuristics for computing it, and demonstrated its plausibility on simulated data. In this article, we study the performance and robustness of this criterion on biological data. Our findings indicate that MP is very promising when its application is extended to the domain of phylogenetic network reconstruction and HGT detection. In all cases we investigated, the MP criterion detected the correct number of HGT events required to map the evolutionary history of a gene data set onto the species phylogeny. Furthermore, our results indicate that the criterion is robust with respect to both incomplete taxon sampling and the use of different site substitution matrices. Finally, our results show that the MP criterion is very promising in detecting HGT in chimeric genes, whose evolutionary histories are a mix of vertical and horizontal evolution. Besides the performance analysis of MP, our findings offer new insights into the evolution of 4 biological data sets and new possible explanations of HGT scenarios in their evolutionary history.

Mesh:

Year:  2006        PMID: 17068107     DOI: 10.1093/molbev/msl163

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  24 in total

1.  Coalescent histories on phylogenetic networks and detection of hybridization despite incomplete lineage sorting.

Authors:  Yun Yu; Cuong Than; James H Degnan; Luay Nakhleh
Journal:  Syst Biol       Date:  2011-01-19       Impact factor: 15.683

2.  Assessing Differences Between Ancestral Recombination Graphs.

Authors:  Mary K Kuhner; Jon Yamato
Journal:  J Mol Evol       Date:  2015-04-05       Impact factor: 2.395

3.  Spaces of phylogenetic networks from generalized nearest-neighbor interchange operations.

Authors:  Katharina T Huber; Simone Linz; Vincent Moulton; Taoyang Wu
Journal:  J Math Biol       Date:  2015-06-03       Impact factor: 2.259

Review 4.  Ordered orthology as a tool in prokaryotic evolutionary inference.

Authors:  Sagi Snir
Journal:  Mob Genet Elements       Date:  2015-12-30

5.  Unifying vertical and nonvertical evolution: a stochastic ARG-based framework.

Authors:  Erik W Bloomquist; Marc A Suchard
Journal:  Syst Biol       Date:  2009-11-09       Impact factor: 15.683

Review 6.  Computational approaches to species phylogeny inference and gene tree reconciliation.

Authors:  Luay Nakhleh
Journal:  Trends Ecol Evol       Date:  2013-10-01       Impact factor: 17.712

7.  A distance metric for a class of tree-sibling phylogenetic networks.

Authors:  Gabriel Cardona; Mercè Llabrés; Francesc Rosselló; Gabriel Valiente
Journal:  Bioinformatics       Date:  2008-05-12       Impact factor: 6.937

8.  Bootstrap-based support of HGT inferred by maximum parsimony.

Authors:  Hyun Jung Park; Guohua Jin; Luay Nakhleh
Journal:  BMC Evol Biol       Date:  2010-05-05       Impact factor: 3.260

9.  GIGA: a simple, efficient algorithm for gene tree inference in the genomic age.

Authors:  Paul D Thomas
Journal:  BMC Bioinformatics       Date:  2010-06-09       Impact factor: 3.169

10.  Initial implementation of a comparative data analysis ontology.

Authors:  Francisco Prosdocimi; Brandon Chisham; Enrico Pontelli; Julie D Thompson; Arlin Stoltzfus
Journal:  Evol Bioinform Online       Date:  2009-07-03       Impact factor: 1.625

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