Partial clonality is widespread across the tree of life, but most population genetic 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 genetic 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 genetic 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 β was 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 genetic data.
How can we explain morphological variations in a holobiont? The genetic determinism of phenotypes is not always obvious and could be circumstantial in complex organisms. In symbiotic cnidarians, it is known that morphology or colour can misrepresent a complex genetic and symbiotic diversity. Anemonia viridis is a symbiotic sea anemone from temperate seas. This species displays different colour morphs based on pigment content and lives in a wide geographical range. Here, we investigated whether colour morph differentiation correlated with host genetic diversity or associated symbiotic genetic diversity by using RAD sequencing and symbiotic dinoଏagellate typing of 140 sea anemones from the English Channel and the Mediterranean Sea. We did not observe genetic differentiation among colour morphs of A. viridis at the animal host or symbiont level, rejecting the hypothesis that A. viridis colour morphs correspond to species level differences. Interestingly, we however identiଏed at least four independent animal host genetic lineages in A. viridis that differed in their associated symbiont populations. In conclusion, although the functional role of the different morphotypes of A. viridis remains to be determined, our approach provides new insights on the existence of cryptic species within A. viridis.
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 β was 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.
Tropical coral reefs are among the worst affected ecosystems by climate change with predictions ranging between a 70-90% loss of reefs in the coming decades. Effective conservation strategies that maximize ecosystem resilience, and potential for recovery, must be informed by the accurate characterization of extant genetic diversity and population structure together with an understanding of the adaptive potential of keystone species. Here, we analyzed samples from the Tara Pacific Expedition (2016 to 2018) that completed an 18,000 km longitudinal transect of the Pacific Ocean sampling three widespread corals - Pocillopora meandrina, Porites lobata, and Millepora cf. platyphylla - across 33 sites from 11 islands. Using ultra-deep metagenomic sequencing of 269 colonies in conjunction with morphological analyses and climate variability data we can show that the sampled transect encompasses multiple morphologically cryptic species that exhibit disparate biogeographic patterns, and most importantly, distinct evolutionary patterns, despite exposure to identical environmental regimes. Our findings demonstrate on a basin-scale that evolutionary trajectories are species-specific and complex, and can only in part be predicted from the environment. This highlights that conservation strategies must integrate multi-species investigations to consider the distinct genomic footprints shaped by selection as well as the genetic potential for adaptive change.
Health and resilience of the coral holobiont depend on diverse bacterial communities often dominated by key marine symbionts of the Endozoicomonadaceae family. The factors controlling their distribution and their functional diversity remain, however, poorly known. Here, we study the ecology of Endozoicomonadaceae at an ocean basin-scale by sampling specimens from three coral genera (Pocillopora, Porites, Millepora) on 99 reefs from 32 islands across the Pacific Ocean. The analysis of 2447 metabarcoding and 270 metagenomic samples reveals that each coral genus harbored a distinct new species of Endozoicomonadaceae. These species are composed of nine lineages that have distinct biogeographic patterns. The most common one, found in Pocillopora, appears to be a globally distributed symbiont with distinct metabolic capabilities, including the synthesis of amino acids and vitamins not produced by the host. The other lineages are structured partly by the host genetic lineage in Pocillopora and mainly by the geographic location in Porites. Millepora is more rarely associated to Endozoicomonadaceae. Our results show that different coral genera exhibit distinct strategies of host-Endozoicomonadaceae associations that are defined at the bacteria lineage level.
Tropical coral reefs are among the most affected ecosystems by climate change and face increasing loss in the coming decades. Effective conservation strategies that maximize ecosystem resilience must be informed by the accurate characterization of extant genetic diversity and population structure together with an understanding of the adaptive potential of keystone species. Here we analyzed samples from the Tara Pacific Expedition (2016–2018) that completed an 18,000 km longitudinal transect of the Pacific Ocean sampling three widespread corals—Pocillopora meandrina, Porites lobata, and Millepora cf. platyphylla—across 33 sites from 11 islands. Using deep metagenomic sequencing of 269 colonies in conjunction with morphological analyses and climate variability data, we can show that despite a targeted sampling the transect encompasses multiple cryptic species. These species exhibit disparate biogeographic patterns and, most importantly, distinct evolutionary patterns in identical environmental regimes. Our findings demonstrate on a basin scale that evolutionary trajectories are species-specific and can only in part be predicted from the environment. This highlights that conservation strategies must integrate multi-species investigations to discern the distinct genomic footprints shaped by selection as well as the genetic potential for adaptive change.
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