Literature DB >> 17237078

Inferring phylogeny from whole genomes.

Paweł Górecki1, Jerzy Tiuryn.   

Abstract

MOTIVATION: Inferring species phylogenies with a history of gene losses and duplications is a challenging and an important task in computational biology. This problem can be solved by duplication-loss models in which the primary step is to reconcile a rooted gene tree with a rooted species tree. Most modern methods of phylogenetic reconstruction (from sequences) produce unrooted gene trees. This limitation leads to the problem of transforming unrooted gene tree into a rooted tree, and then reconciling rooted trees. The main questions are 'What about biological interpretation of choosing rooting?', 'Can we find efficiently the optimal rootings?', 'Is the optimal rooting unique?'.
RESULTS: In this paper we present a model of reconciling unrooted gene tree with a rooted species tree, which is based on a concept of choosing rooting which has minimal reconciliation cost. Our analysis leads to the surprising property that all the minimal rootings have identical distributions of gene duplications and gene losses in the species tree. It implies, in our opinion, that the concept of an optimal rooting is very robust, and thus biologically meaningful. Also, it has nice computational properties. We present a linear time and space algorithm for computing optimal rooting(s). This algorithm was used in two different ways to reconstruct the optimal species phylogeny of five known yeast genomes from approximately 4700 gene trees. Moreover, we determined locations (history) of all gene duplications and gene losses in the final species tree. It is interesting to notice that the top five species trees are the same for both methods. AVAILABILITY: Software and documentation are freely available from http://bioputer.mimuw.edu.pl/~gorecki/urec

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17237078     DOI: 10.1093/bioinformatics/btl296

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  Maximum likelihood models and algorithms for gene tree evolution with duplications and losses.

Authors:  Pawel Górecki; Gordon J Burleigh; Oliver Eulenstein
Journal:  BMC Bioinformatics       Date:  2011-02-15       Impact factor: 3.169

2.  Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence.

Authors:  Ruchi Chaudhary; J Gordon Burleigh; Oliver Eulenstein
Journal:  BMC Bioinformatics       Date:  2012-06-25       Impact factor: 3.169

3.  Algorithms: simultaneous error-correction and rooting for gene tree reconciliation and the gene duplication problem.

Authors:  Pawel Górecki; Oliver Eulenstein
Journal:  BMC Bioinformatics       Date:  2012-06-25       Impact factor: 3.169

4.  Bioinformatics and computational biology in Poland.

Authors:  Janusz M Bujnicki; Jerzy Tiuryn
Journal:  PLoS Comput Biol       Date:  2013-05-02       Impact factor: 4.475

5.  Refining discordant gene trees.

Authors:  Pawel Górecki; Oliver Eulenstein
Journal:  BMC Bioinformatics       Date:  2014-11-13       Impact factor: 3.169

6.  Genomic duplication problems for unrooted gene trees.

Authors:  Jarosław Paszek; Paweł Górecki
Journal:  BMC Genomics       Date:  2016-01-11       Impact factor: 3.969

7.  STRIDE: Species Tree Root Inference from Gene Duplication Events.

Authors:  David M Emms; Steven Kelly
Journal:  Mol Biol Evol       Date:  2017-12-01       Impact factor: 16.240

8.  Inferring duplication episodes from unrooted gene trees.

Authors:  Jarosław Paszek; Paweł Górecki
Journal:  BMC Genomics       Date:  2018-05-08       Impact factor: 3.969

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.