Revisiting the Population Genetics and Genomics of partially clonal organisms – CLONIX
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.
Clonal reproduction (also named asexuality, i.e. reproduction without genetic modification) is a reproductive mode that has been adopted (at least partially) by 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 clonal versus sexual reproduction. Theoretical models hitherto available in population genetics are mainly developed for exclusively sexual, or (more rarely) for purely clonal organisms. Yet partial asexuals include species structuring many terrestrial and marine ecosystems, including most photosynthetic species, species cultivated for biotechnologies, many human pathogens, crop or cattle pests, and a large number of invasive species. Societal issues are thus numerous and matter for human development. Our project contributed to improve predictions of the consequences of clonality on the genetic composition and structure of natural populations in a diversity of evolutionary scenarios. Our ultimate goal was to develop reliable inferences of the clonal rate, c. Expectations were twofold: improve the understanding of the influence of c on the clonal (i.e. genotypic) and genetic composition (thus on the evolutionary trajectories) of populations, and in return, develop a methodological framework to reliably infer c from empirical population genetics data.
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.
Mathematical models and simulation tools have been 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 allowed a radical improvement in the analysis and interpretation of empirical data. The spatial component has also been taken into account to understand the effect of the clonality on dispersal in different demographic contexts. In fine, we delivered new analytical tools (computer programs for data analysis and simulation tools) and tested them with datasets produced by Clonix consortium. This allowed us to propose new expectations of genotypic and genetic composition under the assumption of clonality, enhancing our understanding of the ecological dynamics and evolutionary trajectories in partially clonal populations. In particular, those results allowed us to question some paradigms about the origin of atypical genetics patterns in natural populations, such as deviations from Hardy-Weinberg equilibrium that have been shown to be classically expected under partial (and not only strict or nearly strict) clonality.
Clonix’s models and simulations allowed exploring, beyond the expected equilibrium state, the evolutionary trajectories toward this state. One of the major outcomes is that trajectories were so slowed by clonality, even at modest rates, that it is unrealistic to use equilibrium predictions to interpret data - in most cases. Thus, partial clonality profoundly affects not only clonal structures (repeated genotypes), but also genetic composition of populations and their evolutionary path in different demographic contexts (i.e. bottlenecks). Although genotypic parameters remained relevant estimator, genetic parameters also contributed in increasing the accuracy of clonal rates estimates.
The Clonix consortium completed, or exceeded the achievements initially planned for all Deliverable and Tasks initially listed, except those of Task 4, largely due to the time dedicated to interpret results from Tasks 3 and 5, and also due to the nature of these results revealing the complexity of the relationships between clonality and genotypic and genetic estimators, particularly as the equilibrium state was shown to be a misleading expectation in most cases. In view of the first data analyzes of Task 6, interpreted in light of these theoretical advances, a major step is however achieved in terms of understanding of the ecological and evolutionary dynamics of partially clonal species, and the roadmap toward improved estimates of the rate of clonality in natural populations. Future major improvements will require building on those findings to take into account the considerable bias introduced by i) the partial sampling of natural populations in the estimation of clonal rates and ii) the drastic unlikelihood of equilibrium in most clonal systems. Finally, we identified the initial steps (initial colonization due to local depletion or of range expansion) as having a major influence on the trajectory and architecture of populations (Arnaud-Haond et al. 2014b; Becheler et al. 2014; Becheler et al. 2016).
The consortium has thus achieved the initial goals of the project, and is now ready to apply the new models, methods and analytic tools developed on New Generation Sequencing data to take advantage of enhanced access to genomes to pursue and improve the revision of population genomics of partial asexuals. The next step shall include the production of NGS data to help refining the models and tools to estimate c. Our perspective is to focus on early steps of the formation or extension of clonal populations, with a broad range of societal applications as detailed above, including biological invasions, pathogen spread and species range shifts.
A total of 23 scientific articles have been published and nearly ten more are being written. The consortium contributed to 18 communication in national or international events, produced 3 softwares for data analysis (Edenetwork, RClone et ClonEstiMate), one mathematical model (Pasex), one library for numerical computation in population genetics (Mamoth) 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, which will keep on being maintained for the next few years (http://wwz.ifremer.fr/clonix/).
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.
Madame Sophie ARNAUD HAOND (INSTITUT FRANCAIS DE RECHERCHE POUR L'EXPLOITATION DE LA MER (IFREMER)) – email@example.com
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.
UMR 1136 IAM INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE - CENTRE DE RECHERCHE DE NANCY
UMR 1099 Bio3P INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE - CENTRE DE RECHERCHE DE RENNES
IFREMER INSTITUT FRANCAIS DE RECHERCHE POUR L'EXPLOITATION DE LA MER (IFREMER)
Help of the ANR 329,890 euros
Beginning and duration of the scientific project: May 2012 - 48 Months