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ANR funded project

Blanc - SVSE 7 - Biodiversité, évolution, écologie et agronomie (Blanc SVSE 7)
Edition 2011


Revisiting the Population Genetics and Genomics of partially clonal organisms

Influence of partial clonality on the genetic composition and evolution of natural populations
Adapting population Genetics concepts and methods to partial clonality

1. Assessing the influence of partial clonality on the genetic composition of populations of partially clonal organisms and their evolutionary trajectories.
The partial asexuality features a wide variety of organisms across the Tree of Life. Understanding their evolution and dynamics requires a good appraisal of the extent and influence of clonality versus sexual reproduction. Models hitherto available in population genetics are mainly developed for exclusively sexual, or for purely clonal organismss. Yet partial asexuals include species structuring many terrestrial and marine ecosystems, including most photosynthetic species, many human pathogens, crop or cattle pests, and a large number of invasive species. Societal issues are thus important and numerous. Clonix consortium aims at contributing to a better prediction of the consequences of clonality on the genetic structure of populations in a variety of evolutionary scenarios, in order to develop reliable inference methods of the clonal rate, c. The goal is twofold: improve the understanding of the influence of c on the clonal (i.e. genotypic) and genetic composition and thus the evolutionary trajectory of populations, and in return, develop a methodological framework that to reliably infer c from data empirical.

2. Understand the influence of partial clonality and in return , estimate its rate : models , simulations and re- analysis of empirical data sets
The core of the project is the development of analytical and predictive tools to assess the influence of clonal reproduction on the clonal (i.e. genotypic) and genetic composition of populations, and estimators conventionally used to describe it. Mathematical models and simulations are developed to describe the influence of clonality at increasing rates, and in return to compare the relevance of analytical approaches based on discrimination of clonal lineages versus genetic based approaches to estimate its rate. This step allows a radical improvement in the analysis and interpretation of empirical data. The spatial component will also be taken into account to understand the effect of the clonality on dispersal in different demographic contexts. Ultimately, the goal is to deliver analytical tools (computer programs for data analysis and simulation tools) and to test them with the diversity of datasets of Clonix partners to propose new expectations of genotypic and genetic composition under the assumption of clonality, in order to enhance our understanding of the ecological dynamics and evolutionary trajectories in partially clonal populations.


The models and simulations Clonix allowed exploring, beyond the expected equilibrium state, the evolutionary trajectories toward this state. These have shown to be so slowed by clonality that it is unrealistic to expect equilibrium state in most cases. Thus, the partial clonality profoundly affects not only the clonal structure (repeated genotypes), but also the genetic composition of populations and their evolutionary path in different demographic contexts (i.e. bottlenecks ). Although genotypic parameters remain the most relevants, genetic parameters can therefore also contribute increasing the accuracy of the estimates of clonal rates.


Improvements are planned in the coming months because the amount of information produced could still not be valorized published entirely. In view of the first empirical data analyzes interpreted in light of these theoretical advances, a clear gain is obtained in terms of understanding of the ecological and evolutionary dynamics of partially clonal species and the estimate of the rate of clonality in natural populations. However, it also appears that improvements are still necessary in order to take into account the considerable bias introduced by sampling still part of natural populations in the estimation of clonal rates. Amon other, the emergence of large scale genome scan data through NGS may contribute unlocking this still important issue.

Scientific outputs and patents

A total of 18 scientific articles have been published and nearly ten are being written. The consortium contributed to 14 communication in national or international events, produced 3 softwares for data analysis (Edenetwork, RClone et Cloneestimate), one mathematical model (Pasex) and three simulation routines (SimuClone for ‘simple’ partial asexuality, and two routines for cyclical parthenogenesis). A website was opened to disclose the main results of the consortium, that will keep on being maintained for the next few years (


Divers public




ANR grant: 329 890 euros
Beginning and duration: juin 2012 - 48 mois

Submission abstract

Clonality is life history trait widespread across the Tree of Life. Partial asexuality characterizes a broad range of eukaryotes: a majority of primary producers (phytoplancton, algae, plants, trees), a large amount of human pathogens, culture pests and invasive species, and the species structuring the most important coastal ecosystems. Understanding the dynamics and evolution of clonal and partially clonal species is a major challenge both on a fundamental point of view, and for applied purposes related to human and environmental health. For most species the direct survey and tracking of individuals in space and time is a challenging or even impossible task. Indirect approaches based on the advent of powerful molecular and population genetics tools therefore have an increasing role in the study of dynamics and evolution of populations requiring management efforts. Paradoxically, population genetics concepts and models underlying the interpretation of molecular data are based on the assumption of pure sexual reproduction. Biologists are thus often left alone, and constraint to use inappropriate tools and models, thereby deriving erroneous conclusions with direct consequences on management strategies.
This project gather a consortium of ecologists, population geneticists and parasitologists involved for several years in attempts to solve this issue on a wide range of organisms ranging from agriculture pests to declining structural marine species or invasive and exploited algae. This diversity of scientific profiles reflects both the complexity of the problem and the need for a concerted/synergistic effort to overcome the preliminary work of punctual improvements specific to some particular life cycles, and propose a more thorough revision of concepts and models.
The ground of the project is to assess, from modelling approaches, the consequences of clonal reproduction on the genetic characteristics and structure of populations under a variety of evolutionary scenarii and thereby properly inferring clonal rates of natural populations. The description of the influence of clonal rates on the dynamics of populations and on their evolutionary trajectories will constitute a first step towards an improvement of expectations in terms of genetic descriptors of populations under a broad range of evolutionary scenario under equilibrium and in several specific scenario involving disequilibrium (extinctions, recolonizations, fluctuations of population sizes..). The comparison will allow a drastic improvement of the analysis and interpretation of empirical data. Simulation will further allow testing for the influence of distinct sampling strategies on the reliability of clonal estimates, and comparing the accuracy of two sets of analytic methods based on the discrimination of clonal lineages or on genetic multi-criteria characterizations. The spatial component describing the influence of dispersal on the clonal structure will also be taken into account in implementing clonal dispersion in a lattice from the former modelling approach. The diversity of datasets brought in this project by the partners, including comprehensive spatio-temporal data, will permit the empirical use of the theoretical findings obtained on synthetic populations, in order to translate them into guidelines for a reliable analysis of datasets on « natural » populations.


ANR Programme: Blanc - SVSE 7 - Biodiversité, évolution, écologie et agronomie (Blanc SVSE 7) 2011

Project ID: ANR-11-BSV7-0007

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The project coordinator is the author of this abstract and is therefore responsible for the content of the summary. The ANR disclaims all responsibility in connection with its content.