PhylDiag: identifying complex synteny blocks that include tandem duplications using phylogenetic gene trees

BMC Bioinformatics

Research Article

Hugues Roest Crollius¹  Joseph MEX Lucas¹  Matthieu Muffato² 

[1] Ecole Normale Supérieure, Institut de Biologie de l’ENS, IBENS, 46 rue d’Ulm, 75005, Paris, France;CNRS, UMR 8197, 75005, Paris, France;Inserm, U1024, 75005, Paris, France;European Molecular Biology Laboratory, European Bioinformatics Institute Wellcome Trust Genome Campus, CB10 1SD, Hinxton, Cambridge, UK;

关键词: Comparative genomics;    Synteny;    Synteny block;    Segmental homologies;    Homology;    Gene order;    Rearrangement;    Ancestral genome;    Gene tree;   

DOI  :  10.1186/1471-2105-15-268

 received in 2014-03-21, accepted in 2014-07-17,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundExtant genomes share regions where genes have the same order and orientation, which are thought to arise from the conservation of an ancestral order of genes during evolution. Such regions of so-called conserved synteny, or synteny blocks, must be precisely identified and quantified, as a prerequisite to better understand the evolutionary history of genomes.ResultsHere we describe PhylDiag, a software that identifies statistically significant synteny blocks in pairwise comparisons of eukaryote genomes. Compared to previous methods, PhylDiag uses gene trees to define gene homologies, thus allowing gene deletions to be considered as events that may break the synteny. PhylDiag also accounts for gene orientations, blocks of tandem duplicates and lineage specific de novo gene births. Starting from two genomes and the corresponding gene trees, PhylDiag returns synteny blocks with gaps less than or equal to the maximum gap parameter gapmax. This parameter is theoretically estimated, and together with a utility to graphically display results, contributes to making PhylDiag a user friendly method. In addition, putative synteny blocks are subject to a statistical validation to verify that they are unlikely to be due to a random combination of genes.ConclusionsWe benchmark several known metrics to measure 2D-distances in a matrix of homologies and we compare PhylDiag to i-ADHoRe 3.0 on real and simulated data. We show that PhylDiag correctly identifies small synteny blocks even with insertions, deletions, incorrect annotations or micro-inversions. Finally, PhylDiag allowed us to identify the most relevant distance metric for 2D-distance calculation between homologies.

【 授权许可】

Unknown   
© Lucas et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.