In the context of climate change and increased perturbations caused by human activities, understanding the evolvability and resilience of populations colonizing new areas is of critical importance. Although reproduction is the most influential trait governing evolutionary responses to environmental changes, little attention has been paid to the influence of partial clonality on the genetic sustainability in invading populations. As shown in our previously funded project Clonix, even moderate rates of clonality can profoudnly affect the evolutionary trajectory of isolated populations. Clonix2D will extend our understanding of the evolutionary consequences of partial clonality on genetic diversity and structure during colonization events. We will use a multidisciplinary approach involving mathematical modelling, simulations, and population genomics using various model species across the eurkaryotic domain. The proposed consortium has the necessary expertise for all aspects of the project. Clonix2D is subdivided into three tasks:
Task1 will formalize the theoretical consequences of increasing rates of clonality using simulations and mathematics of stochastic processes on 1a) dispersal modes, 1b) partial and complete geographical isolation, and 1c) the effect of repeated bottlenecks and sequential founder events on genetic diversity and structure.
Task2 will concentrate on empirically inferring the evolutionary histories of partially clonal populations that have colonized new areas by 2a) formalizing coalescent-based and forward inference methods, 2b) studying their compared accuracies in identifying known demographic scenarios (including clonal rate), and 2c) using real datasets obtained by the different partners to infer demographic parameters on a range of organisms with contrasted ecology and colonization history to test for robustness of the method.
Task3 will focus on discriminating the signatures of demographical events (e.g., founder effects, demographic expansion) from selective pressures by 3a) identifying typical genome-wide signatures of soft and hard selection in partial clonality, and 3b) by quantitatively delimiting when those signatures can be identified from typical signatures studied in Task1. This last task is obviously the most challenging as clonal reproduction generates strong linkage across genome that impedes the detection of loci under selection. Here, we hypothesize that uncoupling the effects of selection from demographic histories and reproductive modes on a population of genomes can be achieved using temporal data and adapted methods to correct for demographic scenarios with identifiable signals.
This project relies on a strong body of theoretical developments. In this respect, three out of five partners have a longstanding collaboration in software development from source code to the release of user proved program. Risks are, thus, under control and manageable. In particular, a strong methodological strength of this project is the complementarity of the two modeling approaches retained for simulations of population genetics datasets: a forward algorithm based on genotype matrix transition and a reverse coalescent based program. This complementarity will be useful both for exploring theoretical questions but also in particular for a cross validation of inference methods. Another strength and originality of the project is to consider mixed reproductive modes and variable rates of clonality which will increase matching between modelling and biological data analysis.
Clonix2D brings together researchers and technical staff that have long been studying convergent issues on population genetics and ecology of partially clonal invading species. We have complementary expertise covering the full spectrum needed to tackle the objectives of this project. As such, we have already authored flagship papers on some of these themes, and developed synergistic and innovative research.
Monsieur Solenn Stoeckel (Institut de Génétique Environnement et Protection des Plantes)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
EBEA Evolutionary Biology and Ecology of Algae
INRA - BIOGECO Biodiversité, Gènes et Communautés
University of Kansas / Department of Ecology & Evolutionary Biology
The University of Alabama at Birmingham / Department of Biology
IGEPP Institut de Génétique Environnement et Protection des Plantes
MARBEC Centre pour la biodiversité marine, l'exploitation et la conservation
IAM Interactions Arbres-Microorganismes
Help of the ANR 437,706 euros
Beginning and duration of the scientific project: March 2019 - 48 Months