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Sophie Arnaud-Haond

Publications and source records attributed to Sophie Arnaud-Haond.

5 recordsLinked to original sources

New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations

Seagrass meadows are among the most important coastal ecosystems, in terms of both spatial extent and ecosystem services, but they are also declining worldwide. Understanding the drivers of seagrass meadow dynamics is essential for designing sound management, conservation, and restoration strategies. However, the poor knowledge of the effect of clonality on the population genetics of natural populations severely limits our understanding of the dynamics and connectivity of meadows. Recent modelling approaches have described the expected distributions of genotypic and genetic descriptors under increasing clonal rates. Here, in light of these recent theoretical developments, we revisited population genetic data for 165 meadows of four seagrass species. Contrasting shoot life span and rhizome turnover led to the prediction that the influence of asexual reproduction will increase along a gradient from Zostera noltii to Zostera marina, Cymodocea nodosa and Posidonia oceanica, which should be reflected by an increasing departure from Hardy-Weinberg equilibrium (Fis) and decreasing genotypic diversity (R). This meta-analysis provides a nested validation of this hypothesis at both the species and meadow scales through a significant relationship between Fis and R within each species. By empirically demonstrating the theoretical expectations derived from recent modelling approaches, this work calls for the use of Hardy-Weinberg equilibrium (Fis) rather than the strongly sampling-sensitive genotypic index R to assess the importance of clonal reproduction, at least when the impact of selfing on Fis can be neglected. The results also emphasize the need to revise our appraisal of the extent of clonality and its influence on the dynamics, connectivity and evolutionary trajectory of partial asexuals in general, including in seagrass meadows, to develop the most accurate management strategies.

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The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates

Partial clonality is widespread across the tree of life, but most population genetics models are designed for exclusively clonal or sexual organisms. This gap hampers our understanding of the influence of clonality on evolutionary trajectories and the interpretation of population genetics data. We performed forward simulations of diploid populations at increasing rates of clonality (c), analysed their relationships with genotypic (clonal richness, R, and distribution of clonal sizes, Pareto β) and genetic (FIS and linkage disequilibrium) indices, and tested predictions of c from population genetics data through supervised machine learning. Two complementary behaviours emerged from the probability distributions of genotypic and genetic indices with increasing c. While the impact of c on R and Pareto βwas easily described by simple mathematical equations, its effects on genetic indices were noticeable only at the highest levels (c>0.95). Consequently, genotypic indices allowed reliable estimates of c, while genetic descriptors led to poorer performances when c<0.95. These results provide clear baseline expectations for genotypic and genetic diversity and dynamics under partial clonality. Worryingly, however, the use of realistic sample sizes to acquire empirical data systematically led to gross underestimates (often of one to two orders of magnitude) of c, suggesting that many interpretations hitherto proposed in the literature, mostly based on genotypic richness, should be reappraised. We propose future avenues to derive realistic confidence intervals for c and show that, although still approximate, a supervised learning method would greatly improve the estimation of c from population genetics data.

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Genetic flow directionality and geographical segregation in a Cymodocea nodosa genetic diversity network

We analyse a large data set of genetic markers obtained from populations of Cymodocea nodosa, a marine plant occurring from the East Mediterranean to the Iberian-African coasts in the Atlantic Ocean. We fully develop and test a recently introduced methodology to infer the directionality of gene flow based on the concept of geographical segregation. Using the Jensen-Shannon divergence, we are able to extract a directed network of gene flow describing the evolutionary patterns of Cymodocea nodosa. In particular we recover the genetic segregation that the marine plant underwent during its evolution. The results are confirmed by natural evidence and are consistent with an independent cross analysis.

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Network analysis identifies weak and strong links in a metapopulation system

The identification of key populations shaping the structure and connectivity of metapopulation systems is a major challenge in population ecology. The use of molecular markers in the theoretical framework of population genetics has allowed great advances in this field, but the prime question of quantifying the role of each population in the system remains unresolved. Furthermore, the use and interpretation of classical methods are still bounded by the need for a priori information and underlying assumptions that are seldom respected in natural systems. Network theory was applied to map the genetic structure in a metapopulation system using microsatellite data from populations of a threatened seagrass, Posidonia oceanica, across its whole geographical range. The network approach, free from a priori assumptions and of usual underlying hypothesis required for the interpretation of classical analysis, allows both the straightforward characterization of hierarchical population structure and the detection of populations acting as hubs critical for relaying gene flow or sustaining the metapopulation system. This development opens major perspectives in ecology and evolution in general, particularly in areas such as conservation biology and epidemiology, where targeting specific populations is crucial.

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Spectrum of genetic diversity and networks of clonal organisms

Clonal organisms present a particular challenge in population genetics because, in addition to the possible existence of replicates of the same genotype in a given sample, some of the hypotheses and concepts underlying classical population genetics models are irreconcilable with clonality. The genetic structure and diversity of clonal populations was examined using a combination of new tools to analyze microsatellite data in the marine angiosperm Posidonia oceanica. These tools were based on examination of the frequency distribution of the genetic distance among ramets, termed the spectrum of genetic diversity (GDS), and of networks built on the basis of pairwise genetic distances among genets. The properties and topology of networks based on genetic distances showed a "small-world" topology, characterized by a high degree of connectivity among nodes, and a substantial amount of substructure, revealing organization in sub-families of closely related individuals. Keywords: genetic networks; small-world networks; genetic diversity; clonal organisms

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