HARDY Olivier J's profile
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HARDY Olivier J

  • Evolutionary Biology and Ecology, Université Libre de Bruxelles, Brussels, Belgium
  • Hybridization / Introgression, Phylogeography & Biogeography, Population Genetics / Genomics
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Recommendation:  1

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Educational and work
2004-present: Researcher from the F.R.S-FNRS (Belgian Fund for Scientific Research) at the Université Libre de Bruxelles. Leader of the team “Plant population genetics and community diversity in tropical rain forests” within the Evolutionary Biology and Ecology Unit (http://ebe.ulb.ac.be) 2001 - 2004: Postdoc FNRS (collaboration with INRA in French Guiana and Bordeaux) 2000: Postdoc at the University of Montpellier II (ISEM) 1996-2000: PhD at the Université Libre de Bruxelles (Research on population genetics of the polyploid complex Centaurea jacea) 1995: Agricultural Bioengineer from Gembloux Agro-Bio Tech

Recommendation:  1

2019-11-07
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New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations

Recommended by based on reviews by Stacy Krueger-Hadfield, Ludwig TRIEST and 1 anonymous reviewer

Inferring rates of clonal versus sexual reproduction from population genetics data

In partially clonal organisms, genetic markers are often used to characterize the genotypic diversity of populations and infer thereof the relative importance of clonal versus sexual reproduction. Most studies report a measure of genotypic diversity based on a ratio, R, of the number of distinct multilocus genotypes over the sample size, and qualitatively interpret high / low R as indicating the prevalence of sexual / clonal reproduction. However, a theoretical framework allowing to quantify the relative rates of clonal versus sexual reproduction from genotypic diversity is still lacking, except using temporal sampling. Moreover, R is intrinsically highly dependent on sample size and sample design, while alternative measures of genotypic diversity are more robust to sample size, like D*, which is equivalent to the Gini-Simpson diversity index applied to multilocus genotypes. Another potential indicator of reproductive strategies is the inbreeding coefficient, Fis, because population genetics theory predicts that clonal reproduction should lead to negative Fis, at least when the sexual reproduction component occurs through random mating. Taking advantage of this prediction, Arnaud-Haond et al. [1] reanalysed genetic data from 165 populations of four partially clonal seagrass species sampled in a standardized way. They found positive correlations between Fis and both R and D* within each species, reflecting variation in the relative rates of sexual versus clonal reproduction among populations. Moreover, the differences of mean genotypic diversity and Fis values among species were also consistent with their known differences in reproductive strategies. Arnaud-Haond et al. [1] also conclude that previous works based on the interpretation of R generally lead to underestimate the prevalence of clonality in seagrasses. Arnaud-Haond et al. [1] confirm experimentally that Fis merits to be interpreted more properly than usually done when inferring rates of clonal reproduction from population genetics data of species reproducing both sexually and clonally. An advantage of Fis is that it is much less affected by sample size than R, and thus should be more reliable when comparing studies differing in sample design. Hence, when the rate of clonal reproduction becomes significant, we expect Fis < 0 and D* < 1. I expect these two indicators of clonality to be complementary because they rely on different consequences of clonality on pattern of genetic variation. Nevertheless, both measures can be affected by other factors. For example, null alleles, selfing or biparental inbreeding can pull Fis upwards, potentially eliminating the signature of clonal reproduction. Similarly, D* (and other measures of genotypic diversity) can be low because the polymorphism of the genetic markers used is too limited or because sexual reproduction often occurs through selfing, eventually resulting in highly similar homozygous genotypes.
The work of Arnaud-Haond et al. [1] shows that the populations genetics of partially clonal organisms should be better studied, an endeavour encompassed in a companion paper using numerical simulations [2]. A further step that remains to be accomplished is to build a mathematical framework for developing estimators of rates of clonal versus sexual reproduction based on genotypic diversity.

References

[1] Arnaud-Haond, S., Stoeckel, S., and Bailleul, D. (2019). New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations. ArXiv:1902.10240 [q-Bio], v6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from http://arxiv.org/abs/1902.10240
[2] Stoeckel, S., Porro, B., and Arnaud-Haond, S. (2019). The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates. ArXiv:1902.09365 [q-Bio], v4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from http://arxiv.org/abs/1902.09365

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HARDY Olivier J

  • Evolutionary Biology and Ecology, Université Libre de Bruxelles, Brussels, Belgium
  • Hybridization / Introgression, Phylogeography & Biogeography, Population Genetics / Genomics
  • recommender

Recommendation:  1

Reviews:  0

Educational and work
2004-present: Researcher from the F.R.S-FNRS (Belgian Fund for Scientific Research) at the Université Libre de Bruxelles. Leader of the team “Plant population genetics and community diversity in tropical rain forests” within the Evolutionary Biology and Ecology Unit (http://ebe.ulb.ac.be) 2001 - 2004: Postdoc FNRS (collaboration with INRA in French Guiana and Bordeaux) 2000: Postdoc at the University of Montpellier II (ISEM) 1996-2000: PhD at the Université Libre de Bruxelles (Research on population genetics of the polyploid complex Centaurea jacea) 1995: Agricultural Bioengineer from Gembloux Agro-Bio Tech