Project title : Genetic Fingerprinting of Host-Parasitoid Dispersal and Trophic Interactions (GENPRINT)
Location : Université Paris-Est Créteil, 61 avenue du général de Gaulle, 94000 Créteil, iEES-Paris laboratory, EcoMeco department, i-SOL team
Laboratory description : The Institute of Ecology and Environmental Sciences of Paris (IEES-Paris) develops an integrative approach to ecology and environmental sciences. The laboratory’s research focuses on changes in ecosystems in response to environmental change in the broadest sense, in order to understand their resilience and predict their capacity to adapt. The research focuses on terrestrial and aquatic ecosystems subject to varying degrees of anthropisation, and is carried out at different spatial and temporal scales. Within iEES, the EcoMeco department focuses more specifically on the structure, dynamics and functioning of communities and ecosystems. Among the teams that make up this department, i-SOL explores in particular how ecological and evolutionary constraints interact and condition the distribution of species and the interactions between them.
Project summary : Understanding the movement of individuals on a landscape scale and accurately quantifying their ability to disperse is essential for predicting their responses to environmental change. Species that are able to disperse are able to escape from habitats where conditions may become unfavourable and colonise others that are more favourable.
However, this ability to disperse can be limited. This is particularly the case for species involved in strong trophic interactions. In parasitoids, for example, their distribution also depends directly on that of their hosts. Studying how interactions between species affect their ability to disperse is a means of gaining a detailed understanding of what determines the stability of populations and assessing their ability to adapt to short- and long-term changes through dispersal.
The GENPRINT project takes advantage of large-scale sampling of nettle-feeding butterflies in Sweden and their host parasitoids.
First, we have shown that parasitoids massively structure the population dynamics of their host butterflies. We then sought to genetically characterise these interactions between species. Molecular tools such as RADseq provide access to thousands of SNP markers. We wanted to explore the extent to which these markers, developed in a butterflyparasitoid pair, would allow us to characterise both the genetic fingerprint of interactions between species and their specific ability to disperse. As part of a collaboration with the National Genomic Infrastructure in Stockholm, we obtained genomic data using high-throughput RAD-seq sequencing on 96 samples of the butterfly Aglais urticae and 96 samples of the parasitoid Phobocampe confusa.
The genomic analysis of these data is the subject of this postdoctoral project.
Main tasks and activities:
1. Identification of SNP molecular markers: bioinformatics analysis of the genomic data (RAD - seq) obtained in 2020 will make it possible to identify SNP molecular markers and genotype individuals of the two species.
2. Characterisation of the genetic structure of the populations of each species: the genotypes obtained will be used to characterise the genetic structure of the populations of each species and thus to estimate their respective capacity to disperse. These genetic structures will then be compared to estimate the intensity of interactions between the two species.
3. Relating the genetic structure of the species to the elements of the landscape matrix in order to understand, beyond the dispersal capacities specific to the species and the interactions that link them, the elements of the landscape that influence the dispersal processes of the species of the host-parasitoid pair.
Contract duration : from 01/10/2025 to 30/09/2026
Gross annual salary : €33,600
How to apply : Send your CV (including a list of publications and the contact details of two scientific
referees) and a covering letter to Lise Dupont (lise.dupont@u-pec.fr) before 10 July 2025.
Qualifications :
PhD in population genomics and/or bioinformatics.
Experience of analysing data from next-generation sequencing, preferably RADSeq data.
Expertise in existing analysis tools (e.g. Stacks), statistical tools, and R software.
Knowledge of landscape genetics is advantageous.
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