Les tutelles CNRS-MNHN-Université de Paris
Entité de rattachement
UMR 7206 - Anthropologie biologique et Bio-archéologie (ABBA)
Thème interdisciplinaire de recherche
Population Genetics - Cultural Evolution Modeling - Statistical Inference - Deep Learning.
+33 (0)1 44 05 73 44
PhD Title : Reconstructing demographic and cultural history of human populations from genetic and language polymorphism data.
Population genetics paradigms and methods allow reconstructing the demographic evolution of our species using genomic data from contemporary individuals. The recent development of computational and statistical tools applied to dense genetic data sets offers the opportunity to study very complex evolutionary models. However, human history is not only a biological history and multifarious approaches are needed to better understand our evolution in all its cultural, biological, and ecological complexity. In particular, one of the main characteristics of human history is the relatively recent emergence of numerous populations with varying genetic and cultural features, which have nevertheless kept substantial levels of exchanges over time, at both genetic and cultural levels.
The main aim of my PhD research is to develop methods for analyzing language and genetic polymorphism data in a unified framework, in order to infer the past history of separation, exchanges and admixture among human populations. For this purpose, I have developed a new computer program that simulates simultaneously the evolution of gene and language (cognates) diversities in a set of populations for which both types of data are available. These simulations are then compared to real genetic and cognate polymorphism data, using Approximate Bayesian Computations (ABC) methods to identify the most realistic historical scenarios underlying each type of data, and to infer the corresponding model parameters. So far, we applied this approach to Central Asia, an area where Turkic-Mongol and Indo- Iranian speaking populations historically met, and where our laboratory has already gathered both genetic (sequences, microsatellites, genome-wide genotypes) and language (vocabulary lists, cognates) data. Future developments may ambition to focus on other types of genetic and linguistic data, such as next-generation genome-wide sequences and word frequencies, gathered from other populations worldwide.
- 2017 — Genetic and Linguistic Histories in Central Asia Inferred Using Approximate Bayesian Computations. Proceedings of the Royal Society B-Biological Sciences. Vol. 284, n° 1861, p. 20170706.,