Title :

Back-translation for discovering distant protein homologies in the presence of frameshift mutations

Author(s) :

Gîrdea, Marta [Auteur correspondant]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Algorithms for large scale sequence analysis [SEQUOIA2]
Noé, Laurent [Auteur correspondant]
Algorithms for large scale sequence analysis [SEQUOIA2]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Kucherov, Gregory [Auteur correspondant]
Algorithms for large scale sequence analysis [SEQUOIA2]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]

Journal title :

Algorithms for Molecular Biology

Pages :

6

Publisher :

BioMed Central

Publication date :

2010

ISSN :

1748-7188

HAL domain(s) :

Sciences du Vivant [q-bio]/Biochimie, Biologie Moléculaire/Biologie moléculaire
Informatique [cs]/Bibliothèque électronique [cs.DL]

English abstract : [en]

Background<br />Frameshift mutations in protein-coding DNA sequences produce a drastic change in the resulting protein sequence, which prevents classic protein alignment methods from revealing the proteins' common origin. ...
Show more >Background<br />Frameshift mutations in protein-coding DNA sequences produce a drastic change in the resulting protein sequence, which prevents classic protein alignment methods from revealing the proteins' common origin. Moreover, when a large number of substitutions are additionally involved in the divergence, the homology detection becomes difficult even at the DNA level.<br />Results<br />We developed a novel method to infer distant homology relations of two proteins, that accounts for frameshift and point mutations that may have affected the coding sequences. We design a dynamic programming alignment algorithm over memory-efficient graph representations of the complete set of putative DNA sequences of each protein, with the goal of determining the two putative DNA sequences which have the best scoring alignment under a powerful scoring system designed to reflect the most probable evolutionary process. Our implementation is freely available at http://bioinfo.lifl.fr/path/.<br />Conclusions<br />Our approach allows to uncover evolutionary information that is not captured by traditional alignment methods, which is confirmed by biologically significant examples.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Comparison of Complete Genomes: an algorithmic and statistical approach to investigate the mechanisms of bacterial genome evolution

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL