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. 2025 Jan 2;15(1):e70771. doi: 10.1002/ece3.70771

Whole Genome Sequencing Reveals Genetic Differences Between Symbiodiniaceae Populations Among Reproductively and Geographically Isolated Acropora Colonies in Western Australia

Sanna Y Eriksson 1,2,✉, Mikhail V Matz 3, Peter D Vize 4, Natalie L Rosser 1,5
PMCID: PMC11695670  PMID: 39758704

ABSTRACT

Significant genetic differentiation between Symbiodiniaceae populations in coral hosts can be induced by a range of factors including geography, latitude, depth, temperature and light utilisation. The conventional method of measuring Symbiodiniaceae diversity involving the ITS2 region of rDNA has several limitations, stemming from insufficient genetic resolution and the multi‐copy nature of the marker. This could be improved by using higher throughput whole genome sequencing to identify fine‐scale population genetic differences and provide new insight into factors influencing coral‐Symbiodiniaceae associations. The aim of this study was to investigate the genetic diversity of Symbiodiniaceae populations using low‐coverage whole genome sequencing in sympatric populations of Acropora cf. secale and allopatric populations of Acropora millepora that reproduce in different seasons in Western Australia. Genetic diversity of Symbiodiniaceae populations in these two species was examined using principal coordinates analysis and permutational analysis of variance. This analysis revealed that while all colonies were dominated by Cladocopium, there was a significant genetic difference between Symbiodiniaceae populations in both species. In A. millepora , this variation could be due to the latitudinal variation between populations or differences in reproductive seasonality, but in sympatric populations of A. cf. secale, genetic differences between Symbiodiniaceae populations were clearly aligned with the reproductive seasonality of the coral host. The use of whole genome sequencing improved the sensitivity to detect Symbiodiniaceae genetic population structure between coral populations, which increases our ability to identify genetic and potentially functional differences associated with variation in Symbiodiniaceae populations.

Keywords: Acropora cf. secale, Acropora millepora , genetic variation, temporal reproductive isolation, whole genome sequencing

In this study, we used a whole genome sequencing approach to determine whether reproductively and geographically isolated Acropora colonies in Western Australia harbour genetically different Symbiodiniaceae populations. We found that both allopatric and sympatric populations have significantly genetically different symbionts, potentially due to environmental or genetic factors.

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1. Introduction

Symbiodiniaceae is a family of unicellular photosynthetic microalgae that commonly form endosymbiotic relationships with reef‐building corals (LaJeunesse et al. 2018). Most broadcast‐spawning coral species obtain Symbiodiniaceae from their environment through horizontal transmission (Yakovleva et al. 2009) and rely on the photosynthesis of these acquired Symbiodiniaceae as the source of the majority of their energy (Muscatine 1990; Rädecker et al. 2018). Notably, there is a high level of genetic diversity in the Symbiodiniaceae family, which is accompanied by extensive physiological and ecological variation between different Symbiodiniaceae species. Thus, coral‐Symbiodiniaceae associations can be strongly influenced by both host identity (LaJeunesse et al. 2010; Lewis, Chan, and LaJeunesse 2019) and environmental factors (Cooper et al. 2011; Chen et al. 2019; Matias et al. 2022).

Among geographically separated coral populations, there is often significant genetic differentiation between Symbiodiniaceae populations due to limited dispersal and microevolutionary forces such as genetic drift and mutation (van Oppen et al. 2001; Thornhill et al. 2017; Ziegler et al. 2017; Cooke et al. 2020; Jain et al. 2021; Ong et al. 2022). In addition, differences in physiological tolerance to temperature and light of different Symbiodiniaceae species also results in localised adaptation and variation in the community composition of Symbiodiniaceae among populations at different latitudes (Huang et al. 2011; Silverstein et al. 2011; Chen et al. 2019; Terraneo et al. 2019). In sympatric populations where there is an absence of geographical boundaries, marine species often diverge across environmental boundaries (Forsman et al. 2020). Environmental factors that can influence coral‐Symbiodiniaceae associations in sympatry include turbidity (LaJeunesse et al. 2010; Picciani et al. 2016; Chen et al. 2019), depth (Winters et al. 2003; Iglesias‐Prieto et al. 2004; Mass et al. 2007; Sampayo et al. 2007; Byler et al. 2013) and sun exposure (Ulstrup and Van Oppen 2003; Tan et al. 2020).

An additional factor that could influence coral‐Symbiodiniaceae associations that has received little attention is differences in the timing of reproduction of the coral host. On many Western Australian reefs, there are two mass‐spawning events each year (autumn and spring) with most broadcast‐spawning corals participating in one or the other (Rosser and Gilmour 2008; Gilmour, Speed, and Babcock 2016). Genetically distinct cohorts of colonies spawning either in spring or autumn exist in multiple Acropora species (Rosser 2015, 2016; Gilmour et al. 2016; Rosser et al. 2017), resulting from each individual colony spawning at the same time each year. As photosynthetically derived carbon from Symbiodiniaceae contributes substantially to energy reserves required for gametogenesis (Padilla‐Gamiño et al. 2013; Rodrigues and Padilla‐Gamiño 2022; Jaffe et al. 2023), variation between Symbiodiniaceae species/genotypes in light harvesting efficiency and ability to transfer energy to the coral host (Robison and Warner 2006; Ragni et al. 2010; Karim et al. 2015; Suggett et al. 2015; terHorst and Coffroth 2022) could affect the energy available to coral hosts for reproduction. Thus, Symbiodiniaceae strains more efficient in light acquisition and carbon transfer may allow their hosts to reproduce during times where environmental conditions otherwise limit their energy resources.

To understand how Symbiodiniaceae diversity impacts coral host traits, we must be able to accurately assess Symbiodiniaceae diversity. The multi‐copy internal transcribed spacer 2 (ITS2) region of rDNA is the most commonly used marker for resolving Symbiodiniaceae species or types (Stat et al. 2012). Due to the multi‐copy nature of this region, individual Symbiodiniaceae cells often contain more than one ITS2 sequence type. This, along with the intragenomic variability of the ITS2 region, can lead to difficulty in interpreting diversity among coral samples. Different combinations of ITS2 sequences are known as ITS2 profiles, which are used to distinguish between types or species. However, some Symbiodiniaceae species share ITS2 sequences, and this is problematic when assessing the diversity of species in Symbiodiniaceae communities within a coral colony (Thornhill, LaJeunesse, and Santos 2007). This makes it difficult to interpret Symbiodiniaceae composition without knowing how many individual species or types are present in an assemblage. Increasing sampling effort has been shown to increase the number of reported ITS2 sequences, which further complicates the marker's use (Stat et al. 2011). Next‐generation sequencing methods such as 454 pyrosequencing have been used to detect Symbiodiniaceae operational taxonomic units at a significantly higher sensitivity to traditional ITS2 methods (Quigley et al. 2014; Thomas et al. 2014). More modern whole genome sequencing technologies such as Illumina provide higher throughput and greater accuracy with genome‐wide insights, which can potentially reveal even finer‐scale differences between groups (Zhang 2023).

The aim of this study was to investigate genetic differences between Symbiodiniaceae populations using whole genome sequencing to determine whether this method could detect fine‐scale genetic differences among coral host populations in Western Australia and provide new insight into factors influencing coral‐Symbiodiniaceae associations. Currently, other methods have not detected significant genetic differences in Symbiodiniaceae populations within Acropora species in Western Australia. For example, Thomas et al. (2014) found no difference in symbiont populations in Acropora assemblages between geographic regions in Western Australia using 454 amplicon sequencing. Similarly, Gilmour, Speed, and Babcock (2016); Gilmour et al. (2016) found no difference in Symbiodiniaceae populations between spring‐ and autumn‐spawning colonies of Acropora tenuis in Western Australia using ITS2 profiling. The objectives of this study were to investigate genetic structure of Symbiodiniaceae populations using whole genome sequencing in (1) sympatric populations of Acropora cf. secale that reproduce in different seasons (autumn and spring) at Ningaloo Reef and (2) geographically distinct (allopatric) populations of Acropora millepora separated by 11° of latitude that also spawn in different seasons (autumn and spring).

2. Materials and Methods

2.1. Study Sites

Acropora millepora samples were collected from a single site (~25 m radius) at each location—northern populations (n = 16) at Ashmore Reef (12.2686° S, 123.0539° E) in Western Australia (WA), and southern populations (n = 16) at Ningaloo Reef (23.1419° S, 113.7564° E) in WA. Acropora cf. secale samples were all collected from a single site (~25 m radius) at Ningaloo Reef, but from two different reproductive cohorts, a cohort that spawned in spring (n = 5) and a cohort that spawned in autumn (n = 5). Reproductive sampling was conducted in both species in autumn and spring, whereby colonies were examined in situ for the presence of mature eggs prior to the upcoming spawning event and identified as an autumn or spring spawner (after Baird, Guest, and Willis 2009). Each sample was stored in 95% ethanol, which was replaced after 24 h and again after 1 week. The samples were stored at room temperature before DNA extraction was performed. DNA was extracted from branch tips (without prior enrichment for Symbiodiniaceae) using DNeasy DNA extraction kits for animal tissue (Qiagen, USA) following the manufacturer's instructions.

2.2. Genome Sequencing

A low‐coverage whole genome sequencing approach was used in this study. For all A. millepora samples, paired‐end 150 bp Illumina sequencing was performed across a single lane on a NovaSeq 6000 at the Ramaciotti Centre (UNSW, Sydney). For all A. cf. secale samples, paired‐end 150 bp MGI sequencing was performed across three lanes at BGI Hong Kong on a DNBseq PE150 platform. To prepare the samples for further analysis, the data were demultiplexed into FASTQ files using the tool bcl2fastq2. Each sample contained reads from both the coral host and any Symbiodiniaceae present at the time of sampling (along with minor contributions from other microbial life living in the coral).

All analysis (unless otherwise specified) was done remotely using the High‐Performance Computer at the Texas Advanced Computing Centre (TACC) in the United States. To determine whether there were any issues with the quality of the sequences, the tool FastQC (Andrews 2010) was used. Each sample was analysed using this tool, and then MultiQC (Ewels et al. 2016) was used to consolidate the results from the FastQC analysis.

To increase the quality of the reads and remove any remaining adapters, low‐quality (less than Q = 15) forward and reverse reads were removed using cutadapt (Martin 2011). Cutadapt was also used to remove reads that were too short (< 25 base pairs). The trimmed samples were subsequently aligned to a custom genome containing both Acropora millepora (Fuller et al. 2020) and four Symbiodiniaceae genomes (one each from genera Symbiodinium (Shoguchi et al. 2018), Breviolum (Shoguchi et al. 2015), Cladocopium (Shoguchi et al. 2018) and Durusdinium (Shoguchi et al. 2020) using bowtie2 (Langmead and Salzberg 2012)). SAMtools was then used to create new files containing only the reads which had aligned to the Symbiodiniaceae genomes, to be used in any analysis concerning variation in the Symbiodiniaceae. SAMtools was subsequently used to create files containing only the reads which had aligned to the A. millepora genome, to be used in any analysis concerning variation in host genes.

2.3. Symbiodiniaceae Identification

A custom perl script zooxType.pl. (Manzello et al. 2019) was used to count the relative proportion of reads mapping to each Symbiodiniaceae genome (from genera Symbiodinium, Breviolum, Cladocopium and Durusdinium). All samples contained predominantly Symbiodiniaceae from genus Cladocopium, and therefore all downstream Symbiodiniaceae analysis was focused on within‐genus diversity, using only reads which had mapped to the Cladocopium genome.

2.4. Population Structure of Host and Symbiodiniaceae

To estimate genotype likelihoods, ANGSD (Korneliussen, Albrechtsen, and Nielsen 2014) was used, as it is the most widely accepted programme for analyses involving low‐coverage population genomic data (Therkildsen and Palumbi 2017; Matz 2018). ANGSD utilises ‘soft calling’ to estimate genotype likelihoods by incorporating statistical uncertainties due to potential sequencing errors and missing data in genomic datasets with low coverage (Kim et al. 2011). ANGSD was run with the following filters: minimum mapping quality scores of 20, minimum base quality scores of 20, p‐value that an SNP is true of 10−5, minimum p‐value for strand bias of 10−5, at least 80% of non‐missing genotypes across samples, and a filter that removed any tri‐allelic SNPs.

ANGSD was used to produce two identity‐by‐state (IBS) matrices—one using only host reads and one using only Symbiodiniaceae reads. All further analysis was performed on both matrices, to identify population structure of host colonies, and their Symbiodiniaceae communities. The IBS approach compares individuals by calculating the proportion of times that reads at a certain locus are the same or different between the individuals. This method is robust to variation in sequencing coverage among samples (Korneliussen, Albrechtsen, and Nielsen 2014). The pairwise IBS matrices were provided to the function hclust in RStudio (version 2022.02.2 + 485) to calculate a cluster dendrogram to identify any naturally occurring clones showing genetic similarity as high as technical clones produced for this purpose. None of the samples appeared to be clones, so the same IBS matrix was used for further analysis.

To visualise any population structure present, a principal coordinates analysis (PCoA) was performed using the function capscale from the vegan package in R, using the IBS matrix as an input. To statistically assess the genetic variation between sample groups, permutational multivariate analysis of variance (PERMANOVA) based on distance matrices was used. This analysis was done using RStudio (version 2022.02.2 + 485) using the function adonis2 from R package vegan, with the IBS matrix as the input.

To calculate F st values between populations in each species, ANGSD was used to calculate .saf files for each population. Consequently, realSFS (a programme within ANGSD) was used to calculate site frequency spectra for each pair, and to extract the F st values between each population pair of interest.

3. Results

We used whole genome sequencing to quantify genomic variation and Symbiodiniaceae associations in a final 34 samples (after poor quality sequences were removed), comprising 24 samples of A. millepora (14 autumn spawners from Ningaloo Reef and 10 spring spawners from Ashmore Reef) and 10 samples of A. cf. secale (five autumn and five spring spawners). Based on parameters such as read length, total number of reads and genome size, the average coverage of A. millepora samples was 1.8×, and the average coverage of A. cf. secale samples was 2.1×. The FastQC analysis did not flag any samples as poor quality, with every position along all reads being above the threshold of Q = 30. Over 99% of reads remained after quality trimming with cutadapt (using a quality score > 15), with mapping resulting in an alignment rate of > 95% across all samples.

3.1. Population Structure of Host

A PCoA of genome‐wide variation showed clear genetic differentiation between spring‐spawning A. millepora colonies from Ashmore Reef and autumn‐spawning A. millepora colonies from Ningaloo Reef (Figure 1a). This result was supported by a PERMANOVA which showed that geographic location (or alternatively, spawning time) had a significant effect on genetic variation between these groups (Adonis, R 2 = 0.1970, p = 0.001). A PCoA also showed genetic differentiation between sympatric spring and autumn spawners of A. cf. secale (Figure 1b). Similarly, this was supported by PERMANOVA results showing significant genetic variation between spring‐ and autumn‐spawning groups in A. cf. secale (Adonis, R 2 = 0.3494, p = 0.01). This high level of genetic variation between populations within species was also supported by genome‐wide estimates of F st ( A. millepora F st = 0.112; A. cf. secale F st = 0.112).

FIGURE 1.

FIGURE 1

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Results of principal coordinates analysis (PCoA) showing the first two principal coordinates, and the percentage of variation explained by each axis. PCoA based on IBS matrix of genomic distance between (a, b) coral hosts in (a) allopatric populations of Acropora millepora, (b) sympatric populations of A. cf. secale, and (c, d) Cladocopium Symbiodiniaceae in (c) allopatric populations of A. millepora , (d) sympatric populations of A. cf. secale.

3.2. Population Structure of Symbiodiniaceae

Based on the relative proportion of reads classified as Symbiodiniaceae, all samples from both species were found to contain predominantly Symbiodiniaceae from the genus Cladocopium, with very minor contributions from other genera (Figure 2). A PCoA of genome‐wide variation showed clear genetic differentiation of Symbiodiniaceae populations between spring‐spawning A. millepora colonies from Ashmore Reef and autumn‐spawning A. millepora colonies from Ningaloo Reef (Figure 1c). This result was supported by a PERMANOVA which showed that geographic location (alternatively spawning time) had a significant effect on genetic variation of Symbiodiniaceae populations between these groups (Adonis, R 2 = 0.2616, p = 0.001). A PCoA also showed genetic differentiation between sympatric spring and autumn spawners of A. cf. secale (Figure 1d). Similarly, this was supported by PERMANOVA results showing significant genetic variation of Symbiodiniaceae among spring‐ and autumn‐spawning groups in A. cf. secale (Adonis, R 2 = 0.3029, p = 0.015).

FIGURE 2.

FIGURE 2

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Box plot showing log10 of number of reads assigned to each genus of Symbiodiniaceae in four sample groups (Acropora cf. secale autumn spawners, A. cf. secale spring spawners, Acropora millepora autumn spawners, A. millepora spring spawners). Line inside box represents median, and dots represent outliners.

4. Discussion

This study found significant genetic differences in Symbiodiniaceae populations between geographic regions and spawning seasons, demonstrating that this novel analysis using whole genome sequencing improved the sensitivity to detect genetic population structure within species that has not been detected in other studies (e.g. Thomas et al. 2014; Gilmour, Speed, and Babcock 2016; Gilmour et al. 2016). We show that this method can reveal fine‐scale patterns of differentiation among Symbiodiniaceae populations, based on relatively small genetic differences, improving our ability to identify genetic and potentially functional differences associated with variation in Symbiodiniaceae populations, and furthering our understanding of this critical symbiotic relationship.

In this study, we found a significant genetic differences in Symbiodiniaceae hosted by Acropora millepora cohorts separated by 11° of latitude that spawn in different seasons (Ashmore Reef colonies spawn in spring, and Ningaloo Reef colonies spawn in autumn). The effects of location and spawning season could not be disentangled in our analysis, so we are unable to say whether one factor had a greater effect than the other. Significant differences in Symbiodiniaceae communities between geographical populations have been observed in other studies (van Oppen et al. 2001; Ziegler et al. 2017; Cooke et al. 2020; Jain et al. 2021; Ong et al. 2022) and have been attributed to limited dispersal (Santos, Gutierrez‐Rodriguez, and Coffroth 2003; Thornhill et al. 2009; LaJeunesse et al. 2010), the light environment (Finney et al. 2010; Eckert et al. 2020; Kaniewska and Sampayo 2022), and differences in thermal tolerance (Howells et al. 2012; Byler et al. 2013; Pettay and LaJeunesse 2013). These factors could be contributing to the genetic differences between Symbiodiniaceae populations in A. millepora populations here. Interestingly, however, there was also a significant genetic difference between Symbiodiniaceae populations in sympatric populations of Acropora cf. secale that reproduce in different seasons (autumn and spring), suggesting that differences in spawning time could also play a role in A. millepora .

Sympatric populations of A. cf. secale are theoretically exposed to a common pool of Symbiodiniaceae as adults. However, the results of this study show that these corals associate with distinct genotypes, strongly suggesting that there is host‐Symbiodiniaceae specificity associated with differences in the timing of reproduction by the coral host. Though the populations of A. cf. secale studied here come from the same environment, the temporal separation in their time of reproduction each year (spring or autumn) means that each is exposed to different environmental conditions as they undergo gametogenesis. Gametogenesis requires a large energy investment from coral colonies (Gomez et al. 2018), particularly in the form of lipids which are incorporated into gametes to provide an energy resource for offspring (Padilla‐Gamiño et al. 2013) and photosynthetically derived carbon from Symbiodiniaceae that contribute greatly to energy reserves in gamete bundles (Rodrigues and Padilla‐Gamiño 2022; Jaffe et al. 2023). Thus, differences in photosynthetic efficiency (terHorst and Coffroth 2022) and ability to transport autotrophic carbon to the coral host (Pernice et al. 2015) between Symbiodiniaceae species or genotypes could lead to variation in the energetic budget available for coral reproduction. This could lead to host‐Symbiodiniaceae specificity, with natural selection encouraging association with Symbiodiniaceae genotypes that contribute more energy to the holobiont during these times of high energy demand, particularly to spring spawners which require more energy to sustain gametogenesis over winter. In addition, differentiation of autumn and spring Symbiodiniaceae populations may also be driven by genetic differentiation of their host populations, as has been observed in other studies (Santos et al. 2004; Prada et al. 2014). Importantly, this can be due to genetic drift influencing host‐Symbiodiniaceae recognition, without natural selection for metabolic adaptations. The importance of this neutral process relative to the adaptive process generating different metabolic phenotypes would be a great subject for future research.

Author Contributions

Sanna Y. Eriksson: conceptualization (equal), formal analysis (lead), investigation (lead), project administration (lead), writing – original draft (lead), writing – review and editing (equal). Mikhail V. Matz: methodology (supporting), resources (lead), software (lead), supervision (supporting), writing – review and editing (supporting). Peter D. Vize: methodology (supporting), supervision (supporting), writing – review and editing (supporting). Natalie L. Rosser: conceptualization (equal), data curation (lead), funding acquisition (lead), supervision (lead), writing – review and editing (equal).

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgements

We acknowledge the Jinigudera, Baiyungu, Thalanyji, and Wunembal Gaambera (Uunguu) Traditional Owners and their role as the first ecologists and custodians of the land and sea country on which this work was undertaken. We thank Chris Fulton, Karen Miller, and an anonymous reviewer for their comments which significantly improved the manuscript. We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas, Austin, for providing HPC resources that have contributed to the research results reported within this paper. This project was supported by the Minderoo Foundation through the Minderoo Exmouth Research Laboratory (MERL) and its staff via a grant awarded to Natalie Rosser and an NSERC Discovery Award to Peter Vize. M.V.M. participation was supported by the grant from the National Science Foundation OCE‐2318775. Open access publishing facilitated by University of Wollongong, as part of the Wiley ‐ University of Wollongong agreement via the Council of Australian University Librarians.

Funding: This work was supported by the Minderoo Foundation through the Minderoo Exmouth Research Laboratory (MERL) and its staff via a grant awarded to Natalie Rosser and an NSERC Discovery Award to Peter Vize. M.V.M. participation was supported by the grant from the National Science Foundation OCE‐2318775.

Data Availability Statement

Scripts and code available at: https://github.com/sanna2110/SYMBIO_WA. Raw reads available at BioProject: PRJNA1098905. Other data: https://datadryad.org/stash/share/Y58vw5M5VOg45qhYINXHE6dieGMTX3LFcUO1U3jcDio.

References

  1. Andrews, S. 2010. FastQC: A Quality Control Tool for High Throughput Sequence Data. Cambridge, UK: Babraham Bioinformatics, Babraham Institute. [Google Scholar]
  2. Baird, A. H. , Guest J. R., and Willis B. L.. 2009. “Systematic and Biogeographical Patterns in the Reproductive Biology of Scleractinian Corals.” Annual Review of Ecology, Evolution, and Systematics 40: 551–571. [Google Scholar]
  3. Byler, K. A. , Carmi‐Veal M., Fine M., and Goulet T. L.. 2013. “Multiple Symbiont Acquisition Strategies as an Adaptive Mechanism in the Coral Stylophora pistillata .” PLoS One 8, no. 3: 2120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Chen, B. , Yu K., Liang J., et al. 2019. “Latitudinal Variation in the Molecular Diversity and Community Composition of Symbiodiniaceae in Coral From the South China Sea.” Frontiers in Microbiology 10: 1278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cooke, I. , Ying H., Forêt S., et al. 2020. “Genomic Signatures in the Coral Holobiont Reveal Host Adaptations Driven by Holocene Climate Change and Reef Specific Symbionts.” Science Advances 6, no. 48: 6318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cooper, T. F. , Berkelmans R., Ulstrup K. E., et al. 2011. “Environmental Factors Controlling the Distribution of Symbiodinium Harboured by the Coral Acropora millepora on the Great Barrier Reef.” PLoS One 6, no. 10: 25536. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Eckert, R. J. , Reaume A. M., Sturm A. B., Studivan M. S., and Voss J. D.. 2020. “Depth Influences Symbiodiniaceae Associations Among Montastraea cavernosa Corals on the Belize Barrier Reef.” Frontiers in Microbiology 11: 518. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Ewels, P. , Magnusson M., Lundin S., and Käller M.. 2016. “MultiQC: Summarize Analysis Results for Multiple Tools and Samples in a Single Report.” Bioinformatics 32, no. 19: 3047–3048. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Finney, J. C. , Pettay D. T., Sampayo E. M., Warner M. E., Oxenford H. A., and LaJeunesse T. C.. 2010. “The Relative Significance of Host‐Habitat, Depth, and Geography on the Ecology, Endemism, and Speciation of Coral Endosymbionts in the Genus Symbiodinium .” Microbial Ecology 60, no. 1: 250–263. [DOI] [PubMed] [Google Scholar]
  10. Forsman, Z. H. , Ritson‐Williams R., Tisthammer K. H., Knapp I. S. S., and Toonen R. J.. 2020. “Host‐Symbiont Coevolution, Cryptic Structure, and Bleaching Susceptibility, in a Coral Species Complex (Scleractinia; Poritidae).” Scientific Reports 10, no. 1: 16995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Fuller, Z. L. , Mocellin V. J. L., Morris L. A., et al. 2020. “Population Genetics of the Coral Acropora millepora : Toward Genomic Prediction of Bleaching.” Science 369, no. 6501: eaba4674. [DOI] [PubMed] [Google Scholar]
  12. Gilmour, J. , Speed C. W., and Babcock R.. 2016. “Coral Reproduction in Western Australia.” PeerJ 4: e2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gilmour, J. P. , Underwood J. N., Howells E. J., Gates E., and Heyward A. J.. 2016. “Biannual Spawning and Temporal Reproductive Isolation in Acropora Corals.” PLoS One 11, no. 3: 50916. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gomez, E. J. , Jamodiong E. A., Maboloc E. A., et al. 2018. “Gametogenesis and Reproductive Pattern of the Reef‐Building Coral Acropora millepora in Northwestern Philippines.” Invertebrate Reproduction and Development 62, no. 4: 202–208. [Google Scholar]
  15. Howells, E. J. , Beltran V. H., Larsen N. W., Bay L. K., Willis B. L., and van Oppen M. J. H.. 2012. “Coral Thermal Tolerance Shaped by Local Adaptation of Photosymbionts.” Nature Climate Change 2: 116–120. [Google Scholar]
  16. Huang, H. , Dong Z., Huang L., et al. 2011. “Latitudinal Variation in Algal Symbionts Within the Scleractinian Coral Galaxea fascicularis in the South China Sea.” Marine Biology Research 7, no. 2: 208–211. [Google Scholar]
  17. Iglesias‐Prieto, R. , Beltrán V. H., LaJeunesse T. C., Reyes‐Bonilla H., and Thomé P. E.. 2004. “Different Algal Symbionts Explain the Vertical Distribution of Dominant Reef Corals in the Eastern Pacific.” Proceedings of the Royal Society B: Biological Sciences 271, no. 1549: 1757–1763. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Jaffe, M. D. , Padilla‐Gamiño J. L., Nunn B. L., and Rodrigues L. J.. 2023. “Coral Trophic Pathways Impact the Allocation of Carbon and Nitrogen for Egg Development After Bleaching.” Frontiers in Ecology and Evolution 11: 1220. [Google Scholar]
  19. Jain, S. S. , Afiq‐Rosli L., Feldman B., et al. 2021. “Endosymbiont Communities in Pachyseris speciosa Highlight Geographical and Methodological Variations.” Frontiers in Marine Science 8: 759744. [Google Scholar]
  20. Kaniewska, P. , and Sampayo E. M.. 2022. “Macro‐ and Micro‐Scale Adaptations Allow Distinct Stylophora pistillata ‐Symbiodiniaceae Holobionts to Optimize Performance Across a Broad Light Habitat.” Journal of Phycology 58, no. 1: 55–70. [DOI] [PubMed] [Google Scholar]
  21. Karim, W. , Seidi A., Hill R., et al. 2015. “Novel Characteristics of Photodamage to PSII in a High‐Light‐Sensitive Symbiodinium Phylotype.” Plant and Cell Physiology 56, no. 6: 1162–1171. [DOI] [PubMed] [Google Scholar]
  22. Kim, S. Y. , Lohmueller K. E., Albrechtsen A., et al. 2011. “Estimation of Allele Frequency and Association Mapping Using Next‐Generation Sequencing Data.” BMC Bioinformatics 12: 231. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Korneliussen, T. S. , Albrechtsen A., and Nielsen R.. 2014. “ANGSD: Analysis of Next Generation Sequencing Data.” BMC Bioinformatics 15: 356. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. LaJeunesse, T. C. , Parkinson J. E., Gabrielson P. W., et al. 2018. “Systematic Revision of Symbiodiniaceae Highlights the Antiquity and Diversity of Coral Endosymbionts.” Current Biology 28, no. 16: 2570–2580. [DOI] [PubMed] [Google Scholar]
  25. LaJeunesse, T. C. , Pettay D. T., Sampayo E. M., et al. 2010. “Long‐Standing Environmental Conditions, Geographic Isolation and Host‐Symbiont Specificity Influence the Relative Ecological Dominance and Genetic Diversification of Coral Endosymbionts in the Genus Symbiodinium .” Journal of Biogeography 37, no. 5: 785–800. [Google Scholar]
  26. Langmead, B. , and Salzberg S. L.. 2012. “Fast Gapped‐Read Alignment With Bowtie 2.” Nature Methods 9, no. 4: 357–359. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lewis, A. M. , Chan A. N., and LaJeunesse T. C.. 2019. “New Species of Closely Related Endosymbiotic Dinoflagellates in the Greater Caribbean Have Niches Corresponding to Host Coral Phylogeny.” Journal of Eukaryotic Microbiology 66, no. 3: 469–482. [DOI] [PubMed] [Google Scholar]
  28. Manzello, D. P. , Matz M. V., Enochs I. C., et al. 2019. “Role of Host Genetics and Heat‐Tolerant Algal Symbionts in Sustaining Populations of the Endangered Coral Orbicella Faveolata in the Florida Keys With Ocean Warming.” Global Change Biology 25, no. 3: 1016–1031. [DOI] [PubMed] [Google Scholar]
  29. Martin, M. 2011. “Cutadapt Removes Adapter Sequences From High‐Throughput Sequencing Reads.” EMBnet.Journal 17, no. 1: 3. [Google Scholar]
  30. Mass, T. , Einbinder S., Brokovich E., et al. 2007. “Photoacclimation of Stylophora pistillata to Light Extremes: Metabolism and Calcification.” Marine Ecology Progress Series 334: 93–102. [Google Scholar]
  31. Matias, A. M. A. , Popovic I., Thia J. A., et al. 2022. “Cryptic Diversity and Spatial Genetic Variation in the Coral Acropora Tenuis and Its Endosymbionts Across the Great Barrier Reef.” Evolutionary Applications 00: 1–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Matz, M. V. 2018. “Fantastic Beasts and How to Sequence Them: Ecological Genomics for Obscure Model Organisms.” Trends in Genetics 34, no. 2: 121–132. [DOI] [PubMed] [Google Scholar]
  33. Muscatine, L. 1990. “The Role of Symbiotic Algae in Carbon and Energy Flux in Reef Corals.” Ecosystems of the World 25: 75–87. [Google Scholar]
  34. Ong, J. H. , Wainwright B. J., Jain S. S., Afiq‐Rosli L., Lee J. N., and Huang D.. 2022. “Species and Spatio‐Environmental Effects on Coral Endosymbiont Communities in Southeast Asia.” Coral Reefs 41, no. 4: 1131–1145. [Google Scholar]
  35. Padilla‐Gamiño, J. L. , Bidigare R. R., Barshis D. J., et al. 2013. “Are all Eggs Created Equal? A Case Study From the Hawaiian Reef‐Building Coral Montipora capitata .” Coral Reefs 32, no. 1: 137–152. [Google Scholar]
  36. Pernice, M. , Dunn S. R., Tonk L., et al. 2015. “A Nanoscale Secondary Ion Mass Spectrometry Study of Dinoflagellate Functional Diversity in Reef‐Building Corals.” Environmental Microbiology 17, no. 10: 3570–3580. [DOI] [PubMed] [Google Scholar]
  37. Pettay, D. T. , and LaJeunesse T. C.. 2013. “Long‐Range Dispersal and High‐Latitude Environments Influence the Population Structure of a “Stress‐Tolerant” Dinoflagellate Endosymbiont.” PLoS One 8: e79208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Picciani, N. , de Lossio e Seiblitz I. G., de Paiva P. C., e Castro C. B., and Zilberberg C.. 2016. “Geographic Patterns of Symbiodinium Diversity Associated With the Coral Mussismilia hispida (Cnidaria, Scleractinia) Correlate With Major Reef Regions in the Southwestern Atlantic Ocean.” Marine Biology 163, no. 11: 1259. [Google Scholar]
  39. Prada, C. , McIlroy S. E., Beltrán D. M., et al. 2014. “Cryptic Diversity Hides Host and Habitat Specialization in a Gorgonian‐Algal Symbiosis.” Molecular Ecology 23, no. 13: 3330–3340. [DOI] [PubMed] [Google Scholar]
  40. Quigley, K. M. , Davies S. W., Kenkel C. D., Willis B. L., Matz M. V., and Bay L. K.. 2014. “Deep‐Sequencing Method for Quantifying Background Abundances of Symbiodinium Types: Exploring the Rare Symbiodinium Biosphere in Reef‐Building Corals.” PLoS One 9, no. 4: e94297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Rädecker, N. , Raina J.‐B., Pernice M., et al. 2018. “Using Aiptasia as a Model to Study Metabolic Interactions in Cnidarian‐Symbiodinium Symbioses.” Frontiers in Physiology 9: 214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Ragni, M. , Airs R. L., Hennige S. J., Suggett D. J., Warner M. E., and Geider R. J.. 2010. “PSII Photoinhibition and Photorepair in Symbiodinium (Pyrrhophyta) Differs Between Thermally Tolerant and Sensitive Phylotypes.” Marine Ecology Progress Series 406: 57–70. [Google Scholar]
  43. Robison, J. D. , and Warner M. E.. 2006. “Differential Impacts of Photoacclimation and Thermal Stress on the Photobiology of Four Different Phylotypes of Symbiodinium (Pyrrhophyta).” Journal of Phycology 42, no. 3: 568–579. [Google Scholar]
  44. Rodrigues, L. J. , and Padilla‐Gamiño J. L.. 2022. “Trophic Provisioning and Parental Trade‐Offs Lead to Successful Reproductive Performance in Corals After a Bleaching Event.” Scientific Reports 12, no. 1: 18702. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Rosser, N. L. 2015. “Asynchronous Spawning in Sympatric Populations of a Hard Coral Reveals Cryptic Species and Ancient Genetic Lineages.” Molecular Ecology 24: 5006–5019. [DOI] [PubMed] [Google Scholar]
  46. Rosser, N. L. 2016. “Demographic History and Asynchronous Spawning Shape Genetic Differentiation Among Populations of the Hard Coral Acropora tenuis in Western Australia.” Molecular Phylogenetics and Evolution 98: 89–96. [DOI] [PubMed] [Google Scholar]
  47. Rosser, N. L. , and Gilmour J. P.. 2008. “New Insights Into Patterns of Coral Spawning on Western Australian Reefs.” Coral Reefs 27, no. 2: 345–349. [Google Scholar]
  48. Rosser, N. L. , Thomas L., Stankowski S., Richards Z. T., Kennington W. J., and Johnson M. S.. 2017. “Phylogenomics Provides New Insight Into Evolutionary Relationships and Genealogical Discordance in the Reef‐Building Coral Genus Acropora .” Proceedings of the Royal Society B: Biological Sciences 284: 1846. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Sampayo, E. M. , Franceschinis L., Hoegh‐Guldberg O., and Dove S.. 2007. “Niche Partitioning of Closely Related Symbiotic Dinoflagellates.” Molecular Ecology 16, no. 17: 3721–3733. [DOI] [PubMed] [Google Scholar]
  50. Santos, S. R. , Gutierrez‐Rodriguez C., and Coffroth M. A.. 2003. “Phylogenetic Identification of Symbiotic Dinoflagellates via Length Heteroplasmy in Domain V of Chloroplast Large Subunit (cp23S)—Ribosomal DNA Sequences.” Marine Biotechnology 5, no. 2: 130–140. [DOI] [PubMed] [Google Scholar]
  51. Santos, S. R. , Shearer T. L., Hannes A. R., and Coffroth M. A.. 2004. “Fine‐Scale Diversity and Specificity in the Most Prevalent Lineage of Symbiotic Dinoflagellates (Symbiodinium, Dinophyceae) of the Caribbean.” Molecular Ecology 13, no. 2: 459–469. [DOI] [PubMed] [Google Scholar]
  52. Shoguchi, E. , Beedessee G., Hisata K., et al. 2020. “A New Dinoflagellate Genome Illuminates a Conserved Gene Cluster Involved in Sunscreen Biosynthesis.” Genome Biology and Evolution 13: evaa235. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Shoguchi, E. , Beedessee G., Tada I., et al. 2018. “Two Divergent Symbiodinium Genomes Reveal Conservation of a Gene Cluster for Sunscreen Biosynthesis and Recently Lost Genes.” BMC Genomics 19: 458. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Shoguchi, E. , Shinzato C., Hisata K., Satoh N., and Mungpakdee S.. 2015. “The Large Mitochondrial Genome of Symbiodinium Minutum Reveals Conserved Noncoding Sequences Between Dinoflagellates and Apicomplexans.” Genome Biology and Evolution 7, no. 8: 2237–2244. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Silverstein, R. N. , Correa A. M. S., LaJeunesse T. C., and Baker A. C.. 2011. “Novel Algal Symbiont (Symbiodinium Spp.) Diversity in Reef Corals of Western Australia.” Marine Ecology Progress Series 422: 63–75. [Google Scholar]
  56. Stat, M. , Baker A. C., Bourne D. G., et al. 2012. “Molecular Delineation of Species in the Coral Holobiont.” Advances in Marine Biology 63: 1–65. [DOI] [PubMed] [Google Scholar]
  57. Stat, M. , Bird C. E., Pochon X., et al. 2011. “Variation in Symbiodinium ITS2 Sequence Assemblages Among Coral Colonies.” PLoS One 6, no. 1: e15854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Suggett, D. J. , Goyen S., Evenhuis C., et al. 2015. “Functional Diversity of Photobiological Traits Within the Genus Symbiodinium Appears to Be Governed by the Interaction of Cell Size With Cladal Designation.” New Phytologist 208, no. 2: 370–381. [DOI] [PubMed] [Google Scholar]
  59. Tan, Y. T. R. , Wainwright B. J., Afiq‐Rosli L., et al. 2020. “Endosymbiont Diversity and Community Structure in Porites lutea From Southeast Asia Are Driven by a Suite of Environmental Variables.” Symbiosis 80, no. 3: 269–277. [Google Scholar]
  60. terHorst, C. P. , and Coffroth M. A.. 2022. “Individual Variation in Growth and Physiology of Symbionts in Response to Temperature.” Ecology and Evolution 12, no. 6: e9000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Terraneo, T. I. , Fusi M., Hume B. C. C., et al. 2019. “Environmental Latitudinal Gradients and Host‐Specificity Shape Symbiodiniaceae Distribution in Red Sea Porites Corals.” Journal of Biogeography 46, no. 10: 2323–2335. [Google Scholar]
  62. Therkildsen, N. O. , and Palumbi S. R.. 2017. “Practical Low‐Coverage Genomewide Sequencing of Hundreds of Individually Barcoded Samples for Population and Evolutionary Genomics in Nonmodel Species.” Molecular Ecology Resources 17, no. 2: 194–208. [DOI] [PubMed] [Google Scholar]
  63. Thomas, L. , Kendrick G. A., Kennington W. J., Richards Z. T., and Stat M.. 2014. “Exploring Symbiodinium Diversity and Host Specificity in Acropora Corals From Geographical Extremes of Western Australia With 454 Amplicon Pyrosequencing.” Molecular Ecology 23, no. 12: 3113–3126. [DOI] [PubMed] [Google Scholar]
  64. Thornhill, D. J. , Howells E. J., Wham D. C., Steury T. D., and Santos S. R.. 2017. “Population Genetics of Reef Coral Endosymbionts (Symbiodinium, Dinophyceae).” Molecular Ecology 26, no. 10: 2640–2659. [DOI] [PubMed] [Google Scholar]
  65. Thornhill, D. J. , LaJeunesse T. C., and Santos S. R.. 2007. “Measuring rDNA Diversity in Eukaryotic Microbial Systems: How Intragenomic Variation, Pseudogenes, and PCR Artifact Confound Biodiversity Estimates.” Molecular Ecology 16: 5326–5340. [DOI] [PubMed] [Google Scholar]
  66. Thornhill, D. J. , Xiang Y., Fitt W. K., and Santos S. R.. 2009. “Reef Endemism, Host Specificity and Temporal Stability in Populations of Symbiotic Dinoflagellates From Two Ecologically Dominant Caribbean Corals.” PLoS One 4, no. 7: e6262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Ulstrup, K. E. , and Van Oppen M. J. H.. 2003. “Geographic and Habitat Partitioning of Genetically Distinct Zooxanthellae (Symbiodinium) in Acropora Corals on the Great Barrier Reef.” Molecular Ecology 12, no. 12: 3477–3484. [DOI] [PubMed] [Google Scholar]
  68. Van Oppen, M. J. H. , Palstra F. P., Piquet A. M. T., and Miller D. J.. 2001. “Patterns of Coral‐Dinoflagellate Associations in Acropora: Significance of Local Availability and Physiology of Symbiodinium Strains and Host‐Symbiont Selectivity.” Proceedings of the Royal Society B: Biological Sciences 268, no. 1478: 1759–1767. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Winters, G. , Loya Y., Röttgers R., and Beer S.. 2003. “Photoinhibition in Shallow‐Water Colonies of the Coral Stylophora pistillata as Measured In Situ.” Limnology and Oceanography 48, no. 4: 1388–1393. [Google Scholar]
  70. Yakovleva, I. M. , Baird A. H., Yamamoto H. H., Bhagooli R., Nonaka M., and Hidaka M.. 2009. “Algal Symbionts Increase Oxidative Damage and Death in Coral Larvae at High Temperatures.” Marine Ecology Progress Series 378: 105–112. [Google Scholar]
  71. Zhang, J. 2023. Exploiting Whole‐Genome Sequencing to Understand the Evolution of Corals and Their Symbionts’, PhD thesis. Townsville, Qld: James Cooke University. [Google Scholar]
  72. Ziegler, M. , Arif C., Burt J. A., et al. 2017. “Biogeography and Molecular Diversity of Coral Symbionts in the Genus Symbiodinium Around the Arabian Peninsula.” Journal of Biogeography 44, no. 3: 674–686. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Scripts and code available at: https://github.com/sanna2110/SYMBIO_WA. Raw reads available at BioProject: PRJNA1098905. Other data: https://datadryad.org/stash/share/Y58vw5M5VOg45qhYINXHE6dieGMTX3LFcUO1U3jcDio.

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