Lartillot Nicolas

Directeur de recherche

CNRS

Address: 43 bd du 11 novembre 1918
69622 VILLEURBANNE cedex

My research focusses on the general question of modeling the evolution of genetic sequences and genomes, with applications to phylogenetic inference and molecular evolution more generally.

For phylogenetic inference, my work is mostly based on Bayesian inference: once we have defined a stochastic model of genetic sequence evolution, we develop and implement algorithms for inferring probable values for the parameters of the model (including the phylogeny itself) which best explain the data. The phylogenetic models that we have developed, through multiple collaborations and with several PhD students, are then used for inferring the evolutionary history of living species (i.e. reconstructing the tree of life), but also for characterizing the adaptive regimes experienced by protein coding genes. Or particular interest is to understand which genes are under strong adaptive pressures, such as typically induced by evolutionary arms races between hosts and pathogens.

More recently, I got interested in confronting approaches working within and between species. Thus, on one side, phylogenetic analysis compares genomes of different species, whose genetic differences have accumulated over millions of years. Population genetics, on the other hand, focus on the genetic variation within species, which typically builds up over much shorter evolutionary time scales (for humans, of the order of a few 100,000 years). With increasing genomic sequences now available, it now becomes possible to integrate those two time scales and investigate to what extent the methods developed for each of them are congruent between each other -- and ultimately, how to directly integrate these macro- and micro-evolutionary perspectives in one single model. See the work of Latrille et al, 2023 and Bastian et al, 2025 on this subject.

Finally, I am also engaged in the development of theoretical and simulation-based models of genome evolution. Unlike those mentioned above, these models are not meant to be directly fitted to the currently available empirical genetic data. Instead, they can be used to explore and better understand the evolutionary phenomena that can spontaneously emerge from various aspects of the mechanisms of reproduction, mutation and recombination. In this direction, see the work of Luiselli et al, 2024, et Genestier et al, 2024

Publications

Display of 61 to 74 publications on 74 in total

Exploring Fast Computational Strategies for Probabilistic Phylogenetic analysis

Nicolas Rodrigue, Herve Philippe, Nicolas Lartillot

Hervé Philippe, Frédéric Delsuc, Henner Brinkmann, Nicolas Lartillot

Annual Review of Ecology, Evolution, and Systematics . 36 : 541-562

2005

Journal article

see the publication

Site Interdependence Attributed to Tertiary Structure in Amino Acid Sequence Evolution

N. Rodrigue, Nicolas Lartillot, D. Bryant, H. Philippe

Gene . 347 ( 2 ) : 207-217

DOI: 10.1016/j.gene.2004.12.011

2005

Journal article

see the publication

A Bayesian Mixture Model for Across-Site Heterogeneities in the Amino-Acid Replacement Process

Nicolas Lartillot, Herve Philippe

Molecular Biology and Evolution . 21 ( 6 ) : 1095-1109

DOI: 10.1093/molbev/msh112

2004

Journal article

see the publication

CAT : Un Modèle Phylogénétique Bayésien permettant de prendre en compte l'Hétérogénéité des Processus de Substitution entre Sites dans les Alignements Protéiques

Nicolas Lartillot, Herve Philippe

Biosystema 22 . 22 : 97-104

2004

Book chapter

see the publication