Modelling the Variability of Evolutionary Processes

Olivier Gascuel 1 Stéphane Guindon 1
1 MAB - Méthodes et Algorithmes pour la Bioinformatique
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The evolutionary processes that act at the molecular level are highly variable. For example, the substitution rates and the natural selection regimes vary extensively during the course of evolution and across sequence sites. This chapter describes the mathematical tools and concepts to describe and understand these variations. We show how the standard Markov models of sequence evolution are extended through mixture models to account for variability among sites, and how the mixture approach is further generalised by Markov-modulated Markov models (MMM) to incorporate variability among lineages. We illustrate these models using data sets from plants and human immunodeficiency virus type 1 (HIV-1). Both data sets are processed under the 3-component mixture codon-based model of Nielsen and Yang (1998) and its MMM extension (Guindon, 2004). We show that these models allow to get insight into important biological features such as positively selected sites at the surface of the envelope protein of HIV-1 and site-specific changes within selection regimes correlated to duplication events in plant genes.
Type de document :
Chapitre d'ouvrage
Olivier Gascuel; M. Steel. Reconstructing Evolution: New Mathematical and Computational Advances, II Models of sequence evolution, pp.65-99, 2007, 0199208220
Liste complète des métadonnées

https://hal-lirmm.ccsd.cnrs.fr/lirmm-00171206
Contributeur : Stephane Guindon <>
Soumis le : mardi 11 septembre 2007 - 23:31:57
Dernière modification le : jeudi 24 mai 2018 - 15:59:22

Identifiants

  • HAL Id : lirmm-00171206, version 1

Collections

Citation

Olivier Gascuel, Stéphane Guindon. Modelling the Variability of Evolutionary Processes. Olivier Gascuel; M. Steel. Reconstructing Evolution: New Mathematical and Computational Advances, II Models of sequence evolution, pp.65-99, 2007, 0199208220. 〈lirmm-00171206〉

Partager

Métriques

Consultations de la notice

158