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Guillaume Martin

Chargé(e) de recherche CNRS Equipe Métapopulations
Emailguillaume.martin@univ-montp2.fr
Tél. +33 (0)4 67 14 32 50
Localisation Bâtiment 22, 2ème étage
Mots clés modèles de paysages adaptatifs évolution expérimentale effets de mutations dynamique de l’adaptation des populations en déséquilibre

Job  Offers:

no job offer available currently, sorry.

Theoretical tools:

  • Fitness landscape models: Fisher’s model, multivariate phenotype fitness models
  • stochastic multitype models for the population genetics and demography of populations undergoing selection mutation drift and migration
  • quantiative genetics: mutation selection balance, Qst/Fst comparisons
  • frequent mathematical tools: differential equations (ODE,PDE), stochastic differential equations and diffusion, probabilistic geometry (fitness landscape), generating functions, random matrix theory. Discrete/continuous time, individual/genotype based simulations.

Applications (past and ongoing):

  • Distribution of mutation fitness effects in context (epistasis, environment dependence etc.)
  • Evolutionary and demographic dynamics of populations away from equilibrium: abrupt change, moving optimum in space or time. Mainly asexual models so far (clonal interference).
  • Selective sweeps and distribution of allele frequencies over time: biallelic, multiallelic loci, dominance
  • Try to produce testable predictions for experimental evolution: stochastic growth processes, mutation effects, adaptation trajectories, fluctuation tests, evolutionary rescue.
  • Evolution of life history traits and trade – offs in simple ecological contexts (first), but with an explicit genetic basis for life history traits: virulence/transmission, birth/death etc.
  • Impact of various factors on the speed and probability of successful adaptation to a new environment vs. extinction : epistasis, environmental variation, mutation rate and effects distribution, strength of the environmental stress, initial maladaptation and standing variance etc.
  • neutrality test on quantiative traits from common garden experiments (Qst/Fst comparisons)

Experimental evolution of bacteria (E. coli and P. fluorescens): semi-high throughput measurements (microplates).

  • empirically studying stochastic birth and death processes,
  • kill curves and antibiotic dose effects on bacterial birth and death rates
  • rescue probability and dynamics
  • distribution of antibiotic resistance and its cost.

 

R codes for multivariate Qst / Fst comparisons: here (.rar file).

This .rar archive has the R code for multivariate Qst / Fst analysis from Martin et al.(2008) and an example application on Galba truncatula data from Chapuis et al. (2008).

 

Some Publications:

Martin G., S. P. Otto, T. Lenormand (2006). “Selection for recombination in structured populations”.Genetics 172 : 593–609. here.

Martin G. & T. Lenormand (2006). “A general multivariate extension of Fisher’s Geometric model and the distribution of mutation fitness effects across species.” Evolution, 60(5) : 893–907. here.

Martin G., S.F. Elena, T. Lenormand (2007). « Distributions of epistasis in microbes fit predictions from a fitness landscape model. » Nature Genetics 39, 555 – 560 . here.

Martin G., E. Chapuis & J. Goudet (2008). « Multivariate Qst – Fst comparisons : a neutrality test for the evolution of the G-matrix in structured populations. » Genetics, 180:2135 – 2149. here.

Chapuis E., Martin G. & Goudet J. (2008) « Effects of Selection and Drift on G Matrix Evolution in a Heterogeneous Environment: A Multivariate Q(st)-F-st Test With the Freshwater Snail Galba truncatula » . Genetics 180: 2151-2161.

Martin G., S. Gandon (2010) « Lethal mutagenesis and evolutionary epidemiology ». Phil. Trans. Roy. Soc. 365 : 1953 – 1963. here.

Martin G., R. Aguilee, J. Ramsayer, O. Kaltz, and O. Ronce. (2012). « The probability of evolutionary rescue: towards a comparison of theory and evolution experiments ». Phil. Trans. R. Soc. Lond. B 368. here.

Martin G. (2014). »Fisher’s Geometrical Model Emerges as a Property of Complex Integrated Phenotypic Networks ». Genetics. here.

Martin G. & Lambert A. (2015) « A Simple, Semi-Deterministic Approximation to the Distribution of Selective Sweeps in Large Populations ». Theoretical Population Biology. here.

Martin G. & Roques L. (2016) « The Non-stationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation ». Genetics. here.

Gill  M.E., Hamel, F., Martin, G. & Roques L. (2017) « Mathematical properties of a class of integro-differential models from population genetics. » SIAM J. Appl. Mathhere

Harmand N., Gallet R., Jabbour-Zahab R., Martin G. & Lenormand T. (2016) « Fisher’s geometrical model and the mutational patterns of antibiotic resistance across dose gradients ». Evolution. here. comments from