Internship offers
If interested contact me @ : fanny [dot] pouyet [at] universite-paris-saclay [dot] fr
Offer n°1: Impact of cultural processes on genomic diversity
Cultural transmission of reproductive success (CTRS) has been observed in several human populations: children from large families have more children on average than children from small families (Heyer, et al. 2005). This non-genetic transmission of reproductive success affects the genetic evolution of populations, leading to a decrease in genetic diversity and an increase in frequency of severe genetic diseases (Austerlitz and Heyer 1998). We showed that CTRS yields an imbalanced coalescent tree, the genealogical tree of a sample of genes in a population, on the uniparentally transmitted Y-chromosome and mitochondrial DNA, and also on the nuclear genome (Guez et al, 2023). Human populations are also affected by polygenic selection, i.e. selection on traits coded by many loci distributed along the genome. Natural selection occurring at such traits should lead to a correlation of reproductive success between parents and offspring, as the offspring will inherit at least partially the favourable phenotype of their parents (Fagny and Austerlitz, 2021 for a review). Preliminary work shows that polygenic selection also leaves a signal of unbalanced trees at theselected loci in the genome. The question remains whether it is possible to distinguish this phenomenon from CTRS, using current population genomics data.
On the long term, we aim at performing a simulation study to assess the extent to which these processes shape the genomic diversity of populations, independently and in conjunction. For this project, we will simulate populations connected by migration submitted to CTRS, based on an existing program (Slim 4, Haller & Messer, 2023). Individuals will be characterised by their genotypes at many loci. The simulations will measure genomic diversity with summary statistics such as Tajima’s D, Fay and Wu’s H, Zeng’s E, among-population differentiation (FST) as well as tree imbalance statistics such as B2 or IS* computed on the coalescent tree shape. Indeed our previous study on polygenic selection has shown that these statistics help identifying regions under selection and we will determine the impact of CTRS on their behaviour. CTRS will be modelled by an increased probability of having children for individuals from large families, independently of their genotype. Populations will also be submitted to demographic expansions or contractions, and variations of the migration rates through time. The student will thus have to combine in-depth knowledge of population genetics with computer and statistical skills. S/He will develop new modelling and statistical tools by adapting simulations programs and developing the necessary scripts to analyse the outputs.
Supervisors: Fanny Pouyet (Laboratoire Interdisciplinaire des Sciences du Numérique, Université Paris-Saclay), Maud Fagny (Génétique Quantitative et Évolution, Université Paris-Saclay, INRAE) and Frédéric Austerlitz (Eco-Anthropologie, CNRS, Musée de l’Homme, Paris).
Programming: bash, python, R
Softwares: SLiM (simulation of linked mutations)
Offer n°2: Comparison of demographic inference softwares in the case of facultative sexual reproduction
Saccharomyces cerevisiae, known as ‘baker's yeast’, is a model eukaryotic organism in biology. Yeast also plays a crucial role in the agri-food industry, particularly in the manufacture of bread and alcoholic beverages, and has a history of domestication dating back more than 9,000 years. Its life cycle is different from that of humans, comprising phases of clonal expansion, sexual reproduction and rest. It turns out that mutation, which allows genetic diversity to emerge, and natural selection take place at each cell division, whether clonal or sexual. Conversely, meiotic recombination, which allows genetic diversity to be mixed and maintained, only occurs during sexual reproduction, and more specifically during meiosis. Preliminary work in our team suggests that in the case of episodic recombination, natural selection impacts the entire genome. This could have consequences for our knowledge of the evolutionary history of this species and our ability to estimate its history.
To do this, the trainee will begin with simulations based on the explicit representation of individual genomes (forward-in-time or individual-based) according to different demographic histories. We will then compare different demographic inference software in order to estimate their robustness to a non-canonical reproduction strategy. The internship will take place at the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN, UMR9015), which is located on the Plateau du Moulon at the Université Paris-Saclay. The Bioinfo team, part of the Data Sciences department, aims to design and develop new computational methods for efficiently tackling biological problems
Supervisors: Flora Jay (CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, Université Paris-Saclay) and Fanny Pouyet (Laboratoire Interdisciplinaire des Sciences du Numérique, Université Paris-Saclay)
Programming : bash, python, R
Software: SLiM (simulation of linked mutations)