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A flexible ancestral genome reconstruction method based on gapped adjacencies

BACKGROUND: The "small phylogeny" problem consists in inferring ancestral genomes associated with each internal node of a phylogenetic tree of a set of extant species. Existing methods can be grouped into two main categories: the distance-based methods aiming at minimizing a total branch l...

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Detalles Bibliográficos
Autores principales: Gagnon, Yves, Blanchette, Mathieu, El-Mabrouk, Nadia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526437/
https://www.ncbi.nlm.nih.gov/pubmed/23281872
http://dx.doi.org/10.1186/1471-2105-13-S19-S4
Descripción
Sumario:BACKGROUND: The "small phylogeny" problem consists in inferring ancestral genomes associated with each internal node of a phylogenetic tree of a set of extant species. Existing methods can be grouped into two main categories: the distance-based methods aiming at minimizing a total branch length, and the synteny-based (or mapping) methods that first predict a collection of relations between ancestral markers in term of "synteny", and then assemble this collection into a set of Contiguous Ancestral Regions (CARs). The predicted CARs are likely to be more reliable as they are more directly deduced from observed conservations in extant species. However the challenge is to end up with a completely assembled genome. RESULTS: We develop a new synteny-based method that is flexible enough to handle a model of evolution involving whole genome duplication events, in addition to rearrangements, gene insertions, and losses. Ancestral relationships between markers are defined in term of Gapped Adjacencies, i.e. pairs of markers separated by up to a given number of markers. It improves on a previous restricted to direct adjacencies, which revealed a high accuracy for adjacency prediction, but with the drawback of being overly conservative, i.e. of generating a large number of CARs. Applying our algorithm on various simulated data sets reveals good performance as we usually end up with a completely assembled genome, while keeping a low error rate. AVAILABILITY: All source code is available at http://www.iro.umontreal.ca/~mabrouk.