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

Abstract

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, 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, which may help us better understand and interpret population genetics data obtained for partial asexuals. Here, in the light of these recent theoretical developments, we revisited population genetics data for 165 meadows of four seagrass species. Contrasting shoot lifespan and rhizome turnover led to the prediction that the influence of asexual reproduction would increase along a gradient from Zostera noltii to Zostera marina, Cymodocea nodosa and Posidonia oceanica, with increasing departure from Hardy–Weinberg equilibrium (Fis), mostly towards heterozygote excess, and decreasing genotypic richness (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 only the strongly sampling‐sensitive R to assess the importance of clonal reproduction (c), 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.

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

“…In fact, revising the numerous data acquired on clonal plants, including seagrasses, in light of the present results reveals very frequent negative F IS values, suggesting a much higher contribution of clonality than previously thought (Evans et al, 2014; Sinclair et al, 2014; Stoeckel et al, 2006) on the basis of their average R values (see Arnaud‐Haond et al, 2020 for a meta‐analysis). Unfortunately, F IS is often neglected in ecological studies, possibly due to difficulties in disentangling the influence of technical shortcomings such as null alleles from true impacts of reproductive mode (such as selfing).…”

Population transcriptomic sequencing reveals allopatric divergence and local adaptation in Pseudotaxus chienii (Taxaceae)

“…Positive F IS values were observed in all sampled populations, suggesting significant heterozygote deficits. Heterozygote deficits are probably caused by several factors, including inbreeding, linkage disequilibrium, null alleles, recent admixture, and partial clonality [33,34]. In our study, inbreeding and/or recent admixture seemed to be the most likely driver of the positive F IS values, as investigations of Taxus yunnanensis (F IS = 0.228) and Taxus wallichiana (F IS = 0.290) showed prevalent inbreeding [35,36].…”

Genomic signatures of clonality in the deep water kelp Laminaria rodriguezii

“…Signatures of clonality in natural populations are usually inferred from repeated genotypes, along with mean negative values of F IS , and linkage disequilibrium across loci (Balloux et al, 2003; Halkett, et al, 2005). Nevertheless, recent studies reported that one of these signatures, genotypic richness, had poor relevance for measuring the relative importance of sexual versus clonal reproduction (Arnaud‐Haond et al, 2020), even using relatively large sample sizes (from 100 to 500 individuals) (Stoeckel et al, 2020). This is because the estimates of genotypic richness are strongly dependent on sampling strategy and density, basically decreasing with increasing sampling effort (Arnaud‐Haond, Duarte, et al, 2007; Becheler et al, 2017; Gorospe et al, 2015).…”