CIRB
Probabilistic models of evolution are used to infer the historical patterns of species diversification from the knowledge of genotypes and phenotypes of contemporary species: reconstruction of character states in ancestral species, estimation of divergence times or correlation of quantitative traits with environmental variables, or with other traits.
The approaches used in evolution modeling can be divided into: a) the bottom-up approach, used in population genetics and ecology, where evolution emerges from the interaction of its microscopic components, namely organisms and their genes, which handles microscopic, measurable parameters (fecundity, survival probability, dispersal probability, mutation rate, recombination rate,...), and builds models on this microscopic description; b) the top-down approach used in phylogenetics and comparative systematics, where macro-evolutionary processes are described by stochastic models that have little empirical justification and are treated by sophisticated statistical methods (e.g., Markov chain Monte Carlo in tree space).
The most used approach in data analysis is the top-down approach. It proposes simple null models of genotype/phenotype evolution and rates them according to their ability to reproduce present day data. However, the relative good performance of a phenomenological model is rarely informative of the biological reality of evolution at the bottom level. In addition, there is no guarantee that the model selected as the best one, indeed is a good one.
On the other hand, in bottom-up models, the confidence we have in the model stems from the knowledge we have of the microscopic scale and in particular from the fact that microscopic parameters are measurable. Sometimes, scaling limit techniques yield macroscopic objects which emerge as the limit of the fine scale description. The standard coalescent is the best example of such a universal object, emerging from a very general class of models with large, fixed population size.
Our first line of research is to contribute to push this effort further by proposing other models of macro-evolution arising as scaling limits of microscopically described biological populations. This line will contribute to the utilization of possibly slightly more complex, but more reliable models for phylogenetic trees and for the evolutionary dynamics of quantitative traits. Our group focuses on the spatial structuring of populations on large time scales (dynamic landscapes) and on phenotypic evolution driven by intraspecific selection, under the assumption of rare mutations (adaptive dynamics).
Our second line of research consists in developing mathematical and numerical techniques for the analysis of macro-evolution models. We rely in particular on the theory of branching processes and colaescent processes, and on numerical methods of the divide-and-conquer type. This line will not only solve some current challenges in phylogenetics but also help get round computationally demanding statistical procedures, which in turn should pave the way for new ways of modelling evolution.
Our third line of research concerns the history of genetic sequences in the macro-evolutionary timescale. In particular, we study the evolutionary constraints governing the order in which successive mutations occur at the same locus. We are interested in the origin of such constraints and in the subsequent predictability of evolutionary pathways in the case when they are strong and pervasive.
Our way of doing research is to promote the discussion between personalities from different research areas or from different backgrounds. This is reflected by the wealth of specialties represented in our group: probability, statistics, bio-informatics, ecology, evolutionary biology.
Selected Publication 2004-2012
- Mariadassou M., Bar-Hen A. & Kishino H. (2012), Taxon Influence: Assessing Taxon-Induced Incongruities in Phylogenetic Inference. Systematic Biology, Jan 5.
- Puillandre N., Lambert A., Brouillet S. & Achaz G. (2011), ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol Ecol. Aug 29.
- Lambert A. (2011), Species abundance distributions in neutral models with immigration or mutation and general lifetimes. J. Math. Biol. 63: 57-72.
- Aguilée A., Lambert A. & Claessen D. (2011), Ecological speciation in dynamic landscapes. J. Evol. Biol. 24: 2663-2677.
- Lambert A. (2010), The contour of splitting trees is a Lévy process. Ann. Probab. 38, 348-395.
- Mariadassou M. & Bar-Hen A. (2009), Concentration inequality for evolutionary trees. Journal of Multivariate Analysis 100:9, 2055-2064
- Lambert A. (2009), The allelic partition for coalescent point processes. Markov Proc. Relat. Fields, 15: 359-386.
- Cheddadi R. & Bar-Hen A. (2009), Spatial gradient of temperature and potential vegetation feedback across Europe during the late Quaternary. Climate Dynamics, 32:2-3, 371-379.
- Achaz G. (2009), Frequency spectrum neutrality tests: one for all and all for one. Genetics, 183(1):249-58.
- Loire E., Praz F., Higuet D., Netter P. & Achaz G. (2009), Hypermutability of genes in Homo sapiens due to the hosting of long mono-SSR. Molecular Biology and Evolution, 26(1):111-21.
- Bar-Hen A., Mariadassou M., Poursat M.-A. & Vandenkoornhuyse Ph. (2008), Influence Function for Robust Phylogenetic Reconstructions. Molecular Biology and Evolution, 25:5, 869-873
- Lambert A. (2008), Population Dynamics and Random Genealogies. Stochastic Models, Vol. 24, Supplement 1: 45-163.
People
Director:Lambert Amaury, PR, UPMC (Univ Paris 06)
Senior researchers:
Achaz Guillaume, MC HDR, UPMC
Bar-Hen Avner, PR, Paris Descartes (Univ Paris 05)
Post-doctoral fellows:
Ma Chunhua
Richard Mathieu
Doctorate students:
Behdenna Abdelkader
Delaporte Cécile
Labbé Cyril
Masters students:
Davila Miraine
Dessalles Renaud
Manceau Marc
External collaborators:
Austerlitz Frédéric
Cazelles Bernard
Ferrière Régis
Mona Stefano
Morlon Hélène