Host–symbiont combinations dictate the photo-physiological response of reef-building corals to thermal stress

Hoadley, Kenneth D.; Lewis, Allison M.; Wham, Drew C.; Pettay, D. Tye; Grasso, Chris; Smith, Robin T.; Kemp, Dustin W.; LaJeunesse, Todd C.; Warner, Mark E.

doi:10.1038/s41598-019-46412-4

Cited by 84 publications

(104 citation statements)

References 92 publications

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“…Breviolum and S. 'fitti', a combination of symbionts shown to be intermittent in A. cervicornis 706 through profiling the ITS2 gene (Thornhill et al 2006). Further, symbiont genera detected in 707 nearshore (=Durusdinium) and offshore (=Cladocopium) A. muricata samples were consistent 708 with a recent study by Hoadley et al (2019), although this taxon of Cladocopium 709 (Cladocopium_2) was distinctly different from the other Cladocopium taxon (Cladocopium) 710 containing both Caribbean and Pacific hosts (Fig. 6).…”

Section: Discussion 611supporting

confidence: 82%

STAGdb: a 30K SNP genotyping array and Science Gateway for Acropora corals and their dinoflagellate symbionts

Kitchen

Kuster

Kuntz

et al. 2020

Preprint

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29Standardized identification of genotypes is necessary in animals that reproduce asexually and 30 form large clonal populations such as coral. We developed a high-resolution hybridization-based 31 genotype array coupled with an analysis workflow and database for the most speciose genus of 32 coral, Acropora, and their symbionts. We designed the array to co-analyze host and symbionts 33 based on bi-allelic single nucleotide polymorphisms (SNP) markers identified from genomic data 34 of the two Caribbean Acropora species as well as their dominant dinoflagellate symbiont, 35Symbiodinium 'fitti'. SNPs were selected to resolve multi-locus genotypes of host (called 36 genets) and symbionts (called strains), distinguish host populations and determine ancestry of the 37 coral hybrids in Caribbean acroporids. Pacific acroporids can also be genotyped using a subset of 38 the SNP loci and additional markers enable the detection of symbionts belonging to the genera 39 Breviolum, Cladocopium, and Durusdinium. Analytic tools to produce multi-locus genotypes of 40 hosts based on these SNP markers were combined in a workflow called the Standard Tools for 41 Acroporid Genotyping (STAG). In the workflow the user's data is compared to the database of 42 previously genotyped samples and generates a report of genet identification. The STAG 43 workflow and database are contained within a customized Galaxy environment 44 (https://coralsnp.science.psu.edu/galaxy/), which allows for consistent identification of host 45 genet and symbiont strains and serves as a template for the development of arrays for additional 46 coral genera. STAG data can be used to track temporal and spatial changes of sampled genets 47 49 Genotype identification and tracking are required for well-replicated basic research 50 experiments and in applied research such as designing restoration projects. High-resolution 51 genetic tools are necessary for large clonal populations where genets can only be delineated via 52 genotyping. The advent of reduced representation sequencing methods such as Genotype-By-53 Sequencing (GBS) or Restriction-site Associated DNA Sequencing (RADseq) have made it 54 possible to assay a large number of single-nucleotide polymorphism (SNP) loci in any organism 55 at a reasonable cost (Altshuler et al. 2000). These methods are widely used in population 56 genomics but have the disadvantage that the SNP loci are anonymous. Thus, there is no 57 guarantee that the same set of SNP loci will be recovered from each sample within an experiment 58 or between experiments, making it more difficult to design standardized workflows. To 59 circumvent this issue, standardized SNP probes can be designed for reproducible genotyping and 60 analysis from hundreds of samples using modified RAD-based approaches like Rapture (Ali et 61 al. 2016), RADcap (Hoffberg et al. 2016), and quaddRAD (Franchini et al. 2017) or using 62 hybridization-based SNP genotyping arrays. Hybridization-based SNP arrays tend to have lower 63 error rates then RADseq methods (Darrier ...

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Section: Discussion 611supporting

confidence: 82%

STAGdb: a 30K SNP genotyping array and Science Gateway for Acropora corals and their dinoflagellate symbionts

Kitchen

Kuster

Kuntz

et al. 2020

Preprint

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“…Given the mortality suffered by Worst‐27, there is no indication that Durusdinium types provided that genet with tolerance to elevated temperature, p CO 2 , additions of V. owensii , or combinations thereof in this experiment. Although significant hopes for the survival of reefs into the future often rest upon corals acclimatizing to stress by harboring Durusdinium symbionts, this finding and some other studies indicate that hosting Durusdinium is not a panacea; only some Durusdinium types/species may impart stress tolerance to some coral hosts under certain circumstances and/or abundances (e.g., Hoadley et al, ; LaJeunesse et al, ; Morikawa & Palumbi, ). If complementarity effects are important in coral–Symbiodiniaceae mutualisms, then symbiont community diversity metrics may help reveal particular contexts in which Durusdinium (or other Symbiodiniaceae) types/species contribute to holobiont stress tolerance.…”

Section: Discussionmentioning

confidence: 94%

Symbiont community diversity is more variable in corals that respond poorly to stress

Howe‐Kerr

Bachelot

Wright

et al. 2020

Global Change Biology

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Coral reefs are declining globally as climate change and local water quality press environmental conditions beyond the physiological tolerances of holobionts—the collective of the host and its microbial symbionts. To assess the relationship between symbiont composition and holobiont stress tolerance, community diversity metrics were quantified for dinoflagellate endosymbionts (Family: Symbiodiniaceae) from eight Acropora millepora genets that thrived under or responded poorly to various stressors. These eight selected genets represent the upper and lower tails of the response distribution of 40 coral genets that were exposed to four stress treatments (and control conditions) in a 10‐day experiment. Specifically, four ‘best performer’ coral genets were analyzed at the end of the experiment because they survived high temperature, high pCO2, bacterial exposure, or combined stressors, whereas four ‘worst performer’ genets were characterized because they experienced substantial mortality under these stressors. At the end of the experiment, seven of eight coral genets mainly hosted Cladocopium symbionts, whereas the eighth genet was dominated by both Cladocopium and Durusdinium symbionts. Symbiodiniaceae alpha and beta diversity were higher in worst performing genets than in best performing genets. Symbiont communities in worst performers also differed more after stress exposure relative to their controls (based on normalized proportional differences in beta diversity), than did best performers. A generalized joint attribute model estimated the influence of host genet and treatment on Symbiodiniaceae community composition and identified strong associations among particular symbionts and host genet performance, as well as weaker associations with treatment. Although dominant symbiont physiology and function contribute to host performance, these findings emphasize the importance of symbiont community diversity and stochasticity as components of host performance. Our findings also suggest that symbiont community diversity metrics may function as indicators of resilience and have potential applications in diverse disciplines from climate change adaptation to agriculture and medicine.

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“…A major limitation at present is therefore whether selection for enhanced tolerance promotors to any one stressor (e.g., heat) also gains a competitive advantage for any other environmental (metabolic network) combinations. For example, hosting heat tolerant Symbiodiniaceae strains can enhance bleaching tolerance (e.g., Hoadley et al, ; Howells et al, ), but may not necessarily support fitness under environmental “norms” (Ortiz, González‐Rivero, & Mumby, ). The fundamental unknowns of—and predictive outcomes from—“fitness trade‐offs” have been tackled in other fields by moving to metabolic pathway analysis (“fluxomics”; e.g., Salon et al, ), based on knowledge of the entire biological system of the organism of interest, to predict an integrated functional response to changing environments—or in the case of synthetic biology, to a manipulated gene or set of genes of interest.…”

Section: Operationalizing Management In the Framework Of Bleaching‐dementioning

confidence: 99%

Coral bleaching patterns are the outcome of complex biological and environmental networking

Suggett

Smith

2019

Global Change Biology

123

110

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Continued declines in coral reef health over the past three decades have been punctuated by severe mass coral bleaching‐induced mortality events that have grown in intensity and frequency under climate change. Intensive global research efforts have therefore persistently focused on bleaching phenomena to understand where corals bleach, when and why—resulting in a large—yet still somewhat patchy—knowledge base. Particularly catastrophic bleaching‐induced coral mortality events in the past 5 years have catalyzed calls for a more diverse set of reef management tools, extending far beyond climate mitigation and reef protection, to also include more aggressive interventions. However, the effectiveness of these various tools now rests on rapidly assimilating our knowledge base of coral bleaching into more integrated frameworks. Here, we consider how the past three decades of intensive coral bleaching research has established the basis for complex biological and environmental networks, which together regulate outcomes of bleaching severity. We discuss how we now have enough scaffold for conceptual biological and environmental frameworks underpinning bleaching susceptibility, but that new tools are urgently required to translate this to an operational system informing—and testing—bleaching outcomes. Specifically, adopting network models that can fully describe and predict metabolic functioning of coral holobionts, and how this functioning is regulated by complex doses and interactions among environmental factors. Identifying knowledge gaps limiting operation of such models is the logical step to immediately guide and prioritize future experiments and observations. We are at a time‐critical point where we can implement new capacity to resolve how coral bleaching patterns emerge from complex biological–environmental networks, and so more effectively inform rapidly evolving ecological management and social adaptation frameworks aimed at securing the future of coral reefs.

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Host–symbiont combinations dictate the photo-physiological response of reef-building corals to thermal stress

Cited by 84 publications

References 92 publications

STAGdb: a 30K SNP genotyping array and Science Gateway for Acropora corals and their dinoflagellate symbionts

STAGdb: a 30K SNP genotyping array and Science Gateway for Acropora corals and their dinoflagellate symbionts

Symbiont community diversity is more variable in corals that respond poorly to stress

Coral bleaching patterns are the outcome of complex biological and environmental networking

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