Genome of elegance coral Catalaphyllia jardinei (Euphylliidae)

Abstract

Coral reefs are under stress throughout the world. To better understand the molecular mechanisms underlying coral biology and their genomic evolution, here we sequenced the genome and transcriptomes of elegance coral Catalaphyllia jardinei (Euphylliidae). This monotypic genus stony coral is widespread but rare, being found across the Indo-West Pacific, from the northern Indian Ocean, Australia, Philippines, to the South China Sea. Due to its popularity among aquarium hobbyists, it is an overexploited species collected in large quantities from the wild for aquarium trade. The assembled genome is ~ 651.3 Mb in total length and of high physical contiguity with a scaffold N50 size of 28.9 Mb. The gene copy numbers of abiotic stress regulator (heat shock protein family genes) and neuropeptides (GLWamide, GRFamide, PRGamide and HIRamide) are similar to other sequenced anthozoans, and we have also identified the first set of sesquiterpenoid biosynthetic pathway genes in coral. Sequencing of small RNAs allows us to identify 35 microRNAs in C. jardinei and update the number of conserved microRNAs in cnidarians. This study established a foundation for further investigation into the roles of sesquiterpenoids and microRNAs in development of coral and understand their responses to climate change. Due to the easiness to culture C. jardinei in reef tanks and the established resources in this study, we propose this species be adopted as a new laboratory model in environmental and ecological experiments aiming to understand coral biology and responses to environmental stressors.

Introduction

The elegance coral Catalaphyllia jardinei was first described as Pectinia jardinei found in the shallow water on the reefs at the Warrior Reef (latitude 9° 45’ S), Thursday Island (latitude 10° 35’ S), and Albany Pass (latitude 10° 45’ S) (Saville-Kent, 1893). Based on the morphological and color identification, the species was later determined to be a new genus under Euphylliidae (Yonge and Nicholls, 1931; Catala, 1964). Given that its skeleton is homomorphic to that of Euphyllia, and in recognition of Catala’s contribution to tropical marine fauna, Pectinia was changed to Catalaphyllia (Wells, 1971). Today, the genus Catalaphyllia is considered monospecific with C. jardinei as its only member (Fujii et al., 2020).

Coral reef ecosystems are important in providing a favorable habitat for its associated organisms (Bellwood et al., 2004). Throughout the world coral reefs are under stresses that include habitat destruction (Yeung et al., 2021), overexploitation (Jackson et al., 2001; Pandolfi et al., 2003), pollution (Williams et al., 2002; McCulloch et al., 2003), diseases (Harvell et al., 2002), predation (Qiu et al., 2014), and climate change (Wilkinson, 2002; Hughes et al., 2003; Gardener et al., 2003; Schlager, 1981; Dullo, 2005; Xie et al., 2020). The reef-building coral C. jardinei has a broad geographical distribution and can be found both in the Indian Ocean and Pacific Ocean (Veron and Stafford-Smith, 2000), including Australia, Indonesia, Japan, Maldives, Malaysia, Papua New Guinea, Philippines, Seychelles and Vietnam (UNEP, 2005). Nevertheless, given its small population size and overexploitation, it is considered by the IUCN Red List as having a “Vulnerable” status (IUCN, 2020).

Since the late 1980s, the popularity of keeping live corals at home has increased rapidly (Delbeek, 2001). Large-scale culture of C. jardinei is a current business in Indonesia and corals are exported globally (Akbar and Asadi, 2021). In addition to its appearance as described in its common name, C. jardinei is a popular coral species due to its easiness to culture ex situ. Naturally found in deep flats (greater than 35 meters) with sandy/silty bottoms, lagoons, and nearshore mudflats (Richard, 2005), C. jardinei can tolerate and survive in fluctuating or less favorable environmental conditions (Richard, 2005; http://www.edgeofexistence.org/species/elegance-coral/), making it a potential new model in the laboratory to study coral biology and their responses to environmental stressors.

To facilitate the use of C. jardinei to study the molecular mechanisms underlying coral biology, this study sequenced and provided the first genome and transcriptomic resources of this coral species.

Materials and methods

Sample collection and genome sequencing

Adult Catalaphyllia jardinei (Euphylliidae) (Figure 1A) were purchased from mainland China (original source from Indonesia) and Hong Kong suppliers (original source from Australia), and were cultured in an aquarium tank with circulating artificial seawater (salinity: 30-35 ppt) at around 23 ± 1°C and other equipment to simulate pristine waters at The Chinese University of Hong Kong. Corals were allowed to acclimatize under the laboratory conditions for 15 days prior to be used for DNA and RNA extraction.

Figure 1

Sample for genome sequencing originated from tentacles from a single individual (Figure 1A). Genomic DNA (gDNA) was extracted using the QIAamp DNA minikit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. Extracted gDNA was subjected to quality control using a Nanodrop spectrophotometer (Thermo Scientific) and gel electrophoresis. Qualified samples were sent to Novogene and Dovetail Genomics for library preparation and sequencing. The resulting library was sequenced on an Illumina HiSeq X platform to produce 2 × 150 paired-end sequences. The length-weighted mean molecule length was 17.9 Kb, and details of the sequencing data were highlighted in Supplementary Information S1.

Dovetail Omni-C library preparation and sequencing

For each Dovetail Omni-C library, chromatin was fixed with formaldehyde and extracted. Fixed chromatin was digested with DNase I, and chromatin ends were repaired and ligated to a biotinylated bridge adapter followed by proximity ligation of adapter containing ends. After proximity ligation, crosslinks were reversed and the DNA was purified. Purified DNA was treated to remove biotin that was not internal to ligated fragments. Sequencing libraries were generated using NEBNext Ultra enzymes and Illumina-compatible adapters. Biotin-containing fragments were isolated using streptavidin beads before PCR enrichment of each library. The library was sequenced on an Illumina HiSeqX platform to produce 196.9 millions of 150 bp reads, and the raw data were listed in Supplementary Information S1.

Transcriptome sequencing

Total RNA, including messenger RNA and small RNA, from tentacles from single individual was isolated using mirVana™ miRNA Isolation Kit (Ambion) according to the manufacturer’s instructions, and subjected to quality control using a Nanodrop spectrophotometer (Thermo Scientific), gel electrophoresis, and Agilent 2100 Bioanalyzer (Agilent RNA 6000 Nano Kit). Qualified samples underwent library construction and 150 bp paired-end (PE) sequencing at Novogene; polyA-selected RNA-Sequencing libraries were prepared using TruSeq RNA Sample Prep Kit v2. Insert sizes and library concentrations of final libraries were determined using an Agilent 2100 bioanalyzer instrument (Agilent DNA 1000 Reagents) and real-time quantitative PCR (TaqMan Probe) respectively. Small RNA was submitted to BGI Hong Kong for HiSeq Small RNA library construction and 50 bp single-end (SE) sequencing. Details of the sequencing data can be found in Supplementary Information S1.

Genome assembly

K-mers of the HiseqXten 150PE (Chromium WGS) were counted using jellyfish version 2.2.5 (Marçais and Kingsford, 2011) with k-mers = 21, and estimation of genome size, repeat content, and heterozygosity were analyzed based on a k-mer-based statistical approach in the GenomeScope2 webtool (Ranallo-Benavidez et al., 2020, Supplementary Information S3). Kraken2 (Wood et al., 2019) (k2_standard_20210517 (kraken2 standard database) from https://benlangmead.github.io/aws-indexes/k2, which contains archaea, bacteria, viral, plasmid, human1, UniVec_Core) was used to mark and remove the contamination from the gDNA and transcriptome reads, 3.75% and 0.29% of contaminated reads were removed respectively. Processed Chromium WGS reads were used to construct a de novo assembly using Supernova (v 2.1.1) with default parameters (raw coverage = 78.86x), which generates phased, whole-genome de novo assemblies from a Chromium-prepared library (Weisenfeld et al., 2017) (https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/using/running). The supernova output pseudohap assembly were used to generate the dedupe assembly by dedupe.sh (version 19Feb, 2020) of BBMap (Bushnell B. - sourceforge.net/projects/bbmap/), and then scaffolded using Dovetail Omni-C library reads by HiRise, a software pipeline designed specifically for using proximity ligation data to scaffold genome assemblies (Putnam et al., 2016). Dovetail Omni-C library sequences were aligned to the draft input assembly using bwa (https://github.com/lh3/bwa). The separations of Dovetail Omni-C read pairs mapped within draft scaffolds were analyzed by HiRise to produce a likelihood model for genomic distance between read pairs, and the model was used to identify and break putative misjoins, to score prospective joins, and make joins above a threshold. To further check for potential symbiotic contamination, 11 symbiodinium genomes were downloaded from NCBI (Supplementary Information S2) and BLASTN (Altschul et al., 1990) were carried out on the assembled genomes (e-value 1e-3). Scaffolds with alignment lengths >= 500 bp were further searched on nt database with BLASTN, and no symbiotic contamination was found in the final assembly genome.

Gene model prediction

Gene models were predicted as described in the jellyfish genomes (Nong et al., 2020). Briefly, the gene models were trained and predicted using funannotate (v1.8.9, https://github.com/nextgenusfs/funannotate) (Palmer and Stajich, 2020) with the following parameters: “–protein_evidence uniprot_sprot.fasta –genemark_mode ET –busco_seed_species fly –optimize_augustus –busco_db arthropoda –organism other –max_intronlen 350000”. In the “funannotate predict” step, GeneMark-ES v4.32 (Lomsadze et al., 2005) was used for ab initio gene prediction and Augustus (Keller et al., 2011) was trained using BUSCO. The gene models from the prediction sources “Augustus”, high-quality Augustus predictions (HiQ) with exon evidence, “pasa” (Haas et al., 2008)_, “snap” (Korf, 2004), “GlimmerHMM” (Majoros et al., 2004), and “GeneMark” were passed to Evidence Modeler (EVM Weights: {‘GeneMark’: 1, ‘HiQ’: 2, ‘pasa’: 6, ‘proteins’: 1, ‘Augustus’: 1, ‘GlimmerHMM’: 1, ‘snap’: 1, ‘transcripts’: 1}) to generate the final annotation files. Finally, followed by PASA to update the EVM consensus predictions, and add UTR annotations and models for alternatively spliced isoforms. Protein-coding genes were searched with BLASTP against the nr and SwissProt databases by diamond (v0.9.24) (Buchfink et al., 2015) with parameters “–more-sensitive –evalue 1e-3”, and mapped by HISAT2 (version 2.1.0) (Kim et al., 2019) with transcriptome reads. Gene models with no similarity to any known proteins and no mRNA support were removed from the final version. The gene models were screened by CGAT (Sims et al., 2014) and only the longest genes were retained.

Synteny analysis

Orthologues and orthogroups in C. jardinei and other 33 cnidarians proteomes were identified and inferred using OrthoFinder v2.5.2 (Emms and Kelly, 2019) with “-M msa” activated and default values to other parameters. To symbolise the gene families, the longest protein of each gene was taken as the representative in orthologues analysis. The species tree was constructed with fasttree using STAG algorithm and Hydra vulgaris was identified as the best outgroup species to construct the rooted tree using STRIDE method by OrthoFinder (Emms and Kelly, 2017; Emms and Kelly, 2018). Tree supporting value were the proportion of species tree derived from gene tree supporting each bipartition. The species tree was then converted into divergence tree using r8s (Sanderson, 2003). The tree structure and annotations were visualised using R package ‘ggtree’ (Wickham, 2016; Yu et al., 2017) in R v4.1.2 (R Core Team, 2022). Orthologues anchored by mutual best Diamond blastp hits (e-value cut-off 0.001) between C. jardinei and other 33 cnidarians as mentioned above were used in macrosynteny analyses. Oxford synteny plot were generated following previously described methods (So et al., 2022; Yichun, 2022). Detailed analytical scripts and materials were distributed at https://github.com/xieyichun50/coral_genome_Catalaphyllia_jardinei.

microRNA annotation

Adaptor sequences were trimmed from small RNA sequencing reads and Phred quality score less than 20 were removed. Processed reads of length within 18 bp and 27 bp were then mapped to the genomes using mapper.pl module of the mirDeep2 package (Friedländer et al., 2012). To identify known miRNA, the predicted coral microRNA hairpins were compared against metazoan microRNA precursor sequences from miRBase (Kozomara and Griffiths-Jones, 2014) using BLASTN (e-value <1e-2). For miRNAs with no significant sequence similarity to any of the miRNAs in miRBase were then checked manually. Novel microRNAs were defined when they fulfilled the criteria of microRNAs (Fromm et al., 2020). The expression levels of different arms of a miRNA were calculated based on the number of sequencing reads mapped to the respective arm region in the predicted miRNA hairpin by bowtie. In addition to the above, the precursor sequences of microRNAs from other corals in previous studies (Liew et al., 2014; Praher et al., 2021) were also used to carry out BLASTN searches for identification of any missed microRNA annotations.

Annotation of sesquiterpenoid pathway and neuropeptide genes

17 gene sequences involved in the sesquiterpenoid biosynthetic pathway retrieved from Nematostella vectensis and 4 gene sequences of neuropeptide (GLWamide, GRFamide, PRGamide and HIRamide) sequences from Hydra vulgaris were used for searching against the gene models and genome using BLASTP and TBLASTN, respectively. Putatively identified orthologues with a threshold of E-value equals to 10E-3 were tested by reciprocal searches in the NCBI nr database using BLASTP. For neuropeptide preprohormones, amino acid sequences were translated manually and aligned with MEGA 7.0 (Kumar et al., 2016), while the signaling sequences were analysed with SignalP 3.0 (Dyrløv Bendtsen et al., 2004). The cleavage sites were predicted by software ProP 1.0 (Duckert et al., 2004) and checked manually accordingly to the criteria suggested by Veenstra (2000). The potential mature neuropeptides were aligned using MEGA 7.0 (Kumar et al., 2016).

Results and discussion

High quality genome

Here, we presented a high-quality chromosome-level genome assembly of C. jardinei (2n = 28) (Heyward, 1985; Kenyon, 1997; Flot et al., 2006), the assembled genome size was 651 Mb, which is compatible with the kmer 21 estimate of a genome size of 685.5 Mb (Figure 1, Supplementary Information S3). 69.64% of the genomic sequences were contained on 14 pseudomolecules (Supplementary Information S1.3). The BUSCO score for complete genes is 88.05% (BUSCO version 5.1.3, metazoa_odb10), with complete and single-copy BUSCOs (S) being 84.28%, complete and duplicated BUSCOs (D) being 3.77%, fragmented BUSCOs (F) being 6.60% and Missing BUSCOs (M) being 5.35% (Figure 1C). Its scaffold N50 size (28.9Mb) represents the highest physical contiguity among the published coral genomes (Table 1). Using the transcriptomes, we predicted a total of 44,407 gene models including 37,003 protein coding genes and 7,404 tRNA genes, in the C. jardinei genome, which is within the range of 21,369 to 39,160 for other published coral genomes (Table 1).

Synteny analysis

To clarify the syntenic relationship and gene linkage blocks between C. jardinei and other cnidarians, we generated the Oxford synteny plots of species pairs using the orthologues anchored by mutual best BLAST hit (e-value 1e-3) (Figure 2, Supplementary Information S4). Global gene orthogroup inference identified 26,260 orthogroups. The phylogenetic tree was constructed using 1,029 single-copy orthogroups presented in 31 out of 34 species, where single-copy indicated only one gene was assigned to specific orthogroup for each species. The chromosomal organisations are conserved in most soft corals, and each pseudo-chromosome in C. jardinei was associated with a different chromosome in another soft coral Acropora millipora. Further comparisons of C. jardinei against the more distant species, such as the sea anemone (Nematostella vectensis) and the true jellyfish (Rhopilema esculentum), displayed the one-to-one relationship on most synteny blocks, and a few one-to-many blocks (Supplementary Figures 1–3). Evidence on breakage, fusion or large-scale duplication was rarely found in these investigated cnidarians, suggesting that the genomes of these cnidarians have not undergone massive evolutionary changes.

Figure 2

Homeobox genes

Homeobox genes are important developmental genes in animals and have been used as markers to understand genomic changes in animal evolution (e.g. Nong et al., 2020, Nong et al., 2021, Nong et al., 2022; Li et al., 2020; So et al., 2022; Qu et al., 2020; Shum et al., 2022). A total of 93 ANTP-class homeobox genes have been identified in the C. jardinei genome, including clusters of Hox-like and NK-like genes, and a ParaHox gene cluster (Figure 3; Supplementary Information S5). The data here further strengthens the idea that if distinct Hox and NK genes clusters are associated with ectodermal and mesodermal patterning, it could be a bilaterian-lineage specific event (Simakov et al., 2013; Nong et al., 2020), and the three gene ParaHox gene cluster could only be retained in the medusozoans than anthozoans among the extant cnidarians.

Figure 3

Heat shock protein family genes

Corals experiences abiotic stresses such as temperature, salinity, and oxygen concentration, and heat shock proteins (HSP) can assist and reconstruct the structure of damaged proteins under stresses (Collier and Benesch, 2020; Matambo et al., 2004; Whitley et al., 1999; Supplementary Figure 4). In general, HSP can be divided into six subfamilies, including HSPE (GroEL, cpn10), small heat shock proteins, HSP40, HSP70, HSP90, and HSP110, and HSP70 has been shown as chaperone proteins participated in response to heat stress in reef-building scleractinian corals (Franzellitti et al., 2018), (Haslbeck et al., 2016). In C. jardinei, we identified members of six HSP subfamilies, and their numbers were similar to those identified in the stony coral Acropora millepora chromosomal-level genome (Supplementary Figure 5, Supplementary Information S6). The identified heat shock protein gene families will be useful for future investigation of their roles in C. jardinei under different environmental conditions.

Neuropeptide genes

Neuropeptides play essential roles as endocrine factors and neurotransmitters, and are involved in the cellular differentiation and development of cnidarians (Takahashi, 2020). Here, Scleractinia conserved neuropeptides GLWamide, GRFamide, PRGamide, HIRamide, RWamide, RPamide and pQITRFamide were identified in C. jardinei (Figures 4A, B, Supplementary Information S7). A total of 6 mature peptides were identified from the preprohormone sequences of GLWamide in C. jardinei, and sequence alignment showed a conserved C-terminal GXW motif contained in these sequences (Figures 4C). Two of the GLWamides had “-GIW” replacement and such mutations were also identified in hard coral Euphyllia ancora (Shikina et al., 2020) (Figure 4C, Supplementary Information S8). For GRFamide preprohormones, 16 mature peptides were predicted. Among the identified PRGamide genes in C. jardinei, a single preprohormone gene was found to yield 46 different mature peptides (Figure 4B, Supplementary Information S8). For HIRamides, it was found that there was no glutamine residue identified from the predicted HIRamides in C. jardinei, where this phenomenon is also observable in other cnidarian HIRamides (Koch and Grimmelikhuijzen, 2019; Supplementary Information S8). For RWamide and RPamide, only 1 and 2 mature peptide(s) are yielding from the precursor respectively. Meanwhile, the precursor of pQITRFamide could be identified from the genome, but there was no expression shown in the sequenced transcriptomes, thus the number and form of mature peptides could not be identified (Figures 4B, C). The identified neuropeptides will be useful for future investigation of their developmental roles in C. jardinei.

Figure 4

Sesquiterpenoid biosynthetic pathway genes

Sesquiterpenoid hormones, such as juvenile hormone, regulate the development, metamorphosis, and reproduction in insects, and have long been thought to be confined to the arthropods (e.g. Qu et al., 2018; Tsang et al., 2020). A recent study has unexpectedly identified the sesquiterpenoid hormonal system in jellyfishes, suggesting that the sesquiterpenoid hormone system is established at the bilaterian-cnidarian ancestor (Nong et al., 2020). To test whether coral species contain a sesquiterpenoid hormone system, we searched the sesquiterpenoid biosynthetic pathway genes in C. jardinei genome (Figure 4D) and identified the mevalonate pathway, aldehyde dehydrogenase (ALDH), farnesyl transferase (FNT), Ste 24 endopeptidase (ZMPSTE24), prenyl protein peptidase (RCE1), isoprenylcysteine carboxymethyl transferase (ICMT) and prenylcysteine oxidase (PCYOXIL) in a similar manner as the jellyfishes (Figure 4D, Supplementary Information S9). This result suggests that coral also has the sesquiterpenoid hormone system, and the functional roles of these hormones remain to be seriously tested in different cnidarians.

microRNA gain and loss in corals

Unlike the situation in bilaterians which contain lots of conserved microRNAs across different lineages, the cnidarians and bilaterians are well known to share only one conserved microRNA miR-100 (Griffiths-Jones et al., 2011). Information of small RNA sequences among different cnidarians reveals limited number of conserved microRNAs among different cnidarian lineages (Nong et al., 2020; Praher et al., 2021). Here, we sequenced the small RNA from C. jardinei, and annotated a total of 35 microRNAs in this species (Figure 5, Supplementary Information S10). In comparison with other published cnidarian microRNAs, in congruent to previous studies (e.g. Nong et al., 2020), there were more lineage-specific microRNAs than conserved microRNAs among different cnidarian lineages. We also identified conserved microRNAs at different key nodes in the cnidarian phylogeny, including miR-2022 and miR-2030 that are conserved across all cnidarians, six other microRNAs (miR-2023, miR-2025, miR-2036, miR-2037, miR-2050, miR-9425) that are conserved across all anthozoans, and 4 and 1 other microRNAs that are conserved in the Actiniaria and Scleractinia, respectively (Figure 5). Our findings established the foundation for further investigation of the different roles of these conserved microRNAs in cnidarians.

Figure 5

Conclusion

In the present study, we provided a high-quality genome assembly and transcriptome resources of the elegance coral Catalaphyllia jardinei (Euphylliidae). Abiotic stress regulator, hormonal gene families, and microRNAs were annotated, which will serve as a foundation for further investigation into their roles in development and responses to climate change. Due to the easiness to culture C. jardinei in reef tanks and the established resources in this study, we propose this species to be adopted as a new laboratory model.

Funding

This work was supported by the TUYF Charitable Trust, Hong Kong Research Grant Council Collaborative Research Grant (C4015-20EF, C7013-19G), General Research Fund (14100919, 14100420), the Open Collaborative Research Fund and Operation Fund from the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (HKB L20200008), Center for Ocean Research in Hong Kong and Macau (CORE) (CORE is a joint research center for ocean research between QNLM and HKUST), and the Direct Grant of The Chinese University of Hong Kong (4053489, 4053547). YY was supported by the PhD studentship of The Chinese University of Hong Kong.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

• 1

  AkbarD.AsadiM. A. (2021). PERKEMBANGAN PENYAKIT KARANG HIAS KOLANG KALING KEMBANG (Catalaphyllia jardinei) OLEH CACING ACOEL FLATWORM (Waminoa sp.) DI PERAIRAN LAUT GILIMANUK, JEMBRANA BALI. J. Fish. Mar. Res.5, 270–275. doi: 10.21776/ub.jfmr.2021.005.02.12

  • CrossRef
  • Google Scholar
  • View reference in article

• 2

  AltschulS. F.GishW.MillerW.MyersE. W.LipmanD. J. (1990). Basic local alignment search tool. J. Mol. Biol.215, 403–410. doi: 10.1016/S0022-2836(05)80360-2

  • CrossRef
  • Google Scholar
  • View reference in article

• 3

  BellwoodD. R.HughesT. P.FolkeC.NyströmM. (2004). Confronting the coral reef crisis. Nature429, 827–833. doi: 10.1038/nature02691

  • CrossRef
  • Google Scholar
  • View reference in article

• 4

  BongaertsP.CookeI. R.YingH.WelsD.den HaanS.Hernandez-AgredaA.et al. (2021). Morphological stasis masks ecologically divergent coral species on tropical reefs. Curr. Biol.31, 2286–2298.e8. doi: 10.1016/j.cub.2021.03.028

  • CrossRef
  • Google Scholar
  • View reference in article

• 5

  BuchfinkB.XieC.HusonD. H. (2015). Fast and sensitive protein alignment using DIAMOND. Nat. Methods12, 59–60. doi: 10.1038/nmeth.3176

  • CrossRef
  • Google Scholar
  • View reference in article

• 6

  Buitrago-LópezC.MariappanK. G.CárdenasA.GegnerH. M.VoolstraC. R. (2020). The genome of the cauliflower coral pocillopora verrucosa. Genome Biol. Evol.12, 1911–1917. doi: 10.1093/gbe/evaa184

  • CrossRef
  • Google Scholar
  • View reference in article

• 7

  CatalaR. (1964). Carnival under the sea. EdSicardR. [ie Éditions R. Sicard. Available at: https://archive.org/details/carnivalundersea00cata

  • Google Scholar
  • View reference in article

• 8

  CollierM. P.BeneschJ. L. P. (2020). Small heat-shock proteins and their role in mechanical stress. Cell Stress Chaperones.25, 601–613. doi: 10.1007/s12192-020-01095-z

  • CrossRef
  • Google Scholar
  • View reference in article

• 9

  CunningR.BayR. A.GilletteP.BakerA. C.Traylor-KnowlesN. (2018). Comparative analysis of the Pocillopora damicornis genome highlights role of immune system in coral evolution. Sci. Rep.8, 16134. doi: 10.1038/s41598-018-34459-8

  • CrossRef
  • Google Scholar
  • View reference in article

• 10

  DelbeekJ. C. (2001). Coral farming: Past, present and future trends. Aquarium. Sci. Conserv.3, 171–181. doi: 10.1023/A:1011306125934

  • CrossRef
  • Google Scholar
  • View reference in article

• 11

  DuckertP.BrunakS.BlomN. (2004). Prediction of proprotein convertase cleavage sites. Protein Eng. Des. Sel.17, 107–112. doi: 10.1093/protein/gzh013

  • CrossRef
  • Google Scholar
  • View reference in article

• 12

  DulloW.-C. (2005). Coral growth and reef growth: a brief review. Facies51, 33–48. doi: 10.1007/s10347-005-0060-y

  • CrossRef
  • Google Scholar
  • View reference in article

• 13

  Dyrløv BendtsenJ.NielsenH.von HeijneG.BrunakS. (2004). Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol.340, 783–795. doi: 10.1016/j.jmb.2004.05.028

  • CrossRef
  • Google Scholar
  • View reference in article

• 14

  EmmsD. M.KellyS. (2017). STRIDE: Species tree root inference from gene duplication events. Mol. Biol. Evol.34, 3267–3278. doi: 10.1093/molbev/msx259

  • CrossRef
  • Google Scholar
  • View reference in article

• 15

  EmmsD. M.KellyS. (2018). STAG: Species tree inference from all genes267914. BioRxiv267914. doi: 10.1101/267914

  • CrossRef
  • Google Scholar
  • View reference in article

• 16

  EmmsD. M.KellyS. (2019). OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol.20, 238. doi: 10.1186/s13059-019-1832-y

  • CrossRef
  • Google Scholar
  • View reference in article

• 17

  FlotJ.-F.ozouF-cosTazC.TsuchiyaM.WoesikR. (2006). Comparative coral cytogenetics. In. Proc. 5th. Int. Coral. Reef. Symposium.1, 4–8. Available at: https://www.semanticscholar.org/paper/Comparative-coral-cytogenetics-Flot-ozouF-cosTaz/9c0679897fd7e6f84069b8e2600bcbed47715268 [Accessed May 31, 2022].

  • Google Scholar

• 18

  FranzellittiS.AiriV.CalbucciD.CaroselliE.PradaF.VoolstraC. R.et al. (2018). Transcriptional response of the heat shock gene hsp70 aligns with differences in stress susceptibility of shallow-water corals from the Mediterranean Sea. Mar. Environ. Res.140, 444–454. doi: 10.1016/j.marenvres.2018.07.006

  • CrossRef
  • Google Scholar
  • View reference in article

• 19

  FriedländerM. R.MackowiakS. D.LiN.ChenW.RajewskyN. (2012). miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res.40, 37–52. doi: 10.1093/nar/gkr688

  • CrossRef
  • Google Scholar
  • View reference in article

• 20

  FrommB.KellerA.YangX.FriedlanderM. R.PetersonK. J.Griffiths-JonesS. (2020). Quo vadis microRNAs? Trends Genet.36, 461–463. doi: 10.1016/j.tig.2020.03.007

  • CrossRef
  • Google Scholar
  • View reference in article

• 21

  FujiiT.KitanoY.TachikawaH. (2020). New distributional records of three species of euphylliidae (Cnidaria, anthozoa, hexacorallia, scleractinia) from the Ryukyu islands, Japan. Species. Diversity25, 275–282. doi: 10.12782/specdiv.25.275

  • CrossRef
  • Google Scholar
  • View reference in article

• 22

  FullerZ. L.MocellinV. J. L.MorrisL. A.CantinN.ShepherdJ.SarreL.et al. (2020). Population genetics of the coral Acropora millepora: Toward genomic prediction of bleaching. Science369, eaba4674. doi: 10.1126/science.aba4674

  • CrossRef
  • Google Scholar
  • View reference in article

• 23

  GardenerM. R.WhalleyR. D. B.SindelB. M. (2003). Ecology of nassella neesiana, Chilean needle grass, in pastures on the northern tablelands of new south wales. II. seedbank dynamics, seed germination, and seedling recruitment. Aust. J. Agric. Res.54, 621–626. doi: 10.1071/AR01076

  • CrossRef
  • Google Scholar
  • View reference in article

• 24

  Griffiths-JonesS.HuiJ. H. L.MarcoA.RonshaugenM. (2011). MicroRNA evolution by arm switching. EMBO Rep.12, 172–177. doi: 10.1038/embor.2010.191

  • CrossRef
  • Google Scholar
  • View reference in article

• 25

  HaasB. J.SalzbergS. L.ZhuW.PerteaM.AllenJ. E.OrvisJ.et al. (2008). Automated eukaryotic gene structure annotation using EVidenceModeler and the program to assemble spliced alignments. Genome Biol.9, R7. doi: 10.1186/gb-2008-9-1-r7

  • CrossRef
  • Google Scholar
  • View reference in article

• 26

  HarvellC. D.MitchellC. E.WardJ. R.AltizerS.DobsonA. P.OstfeldR. S.et al. (2002). Climate warming and disease risks for terrestrial and marine biota. Science296, 2158–2162. doi: 10.1126/science.1063699

  • CrossRef
  • Google Scholar
  • View reference in article

• 27

  HaslbeckM.PeschekJ.BuchnerJ.WeinkaufS. (2016). Structure and function of α-crystallins: Traversing from in vitro to in vivo. biochimica et biophysica acta (BBA) -. Gen. Subj.1860, 149–166. doi: 10.1016/j.bbagen.2015.06.008

  • CrossRef
  • Google Scholar
  • View reference in article

• 28

  HelmkampfM.BellingerM. R.GeibS. M.SimS. B.TakabayashiM. (2019). Draft genome of the rice coral montipora capitata obtained from linked-read sequencing. Genome Biol. Evol.11, 2045–2054. doi: 10.1093/gbe/evz135

  • CrossRef
  • Google Scholar
  • View reference in article

• 29

  HeywardA. J. (1985). Chromosomes of the coral goniopora lobata (Anthozoa: Scleractinia). Heredity55, 269–271. doi: 10.1038/hdy.1985.101

  • CrossRef
  • Google Scholar
  • View reference in article

• 30

  HughesT. P.BairdA. H.BellwoodD. R.CardM.ConnollyS. R.FolkeC.et al. (2003). Climate change, human impacts, and the resilience of coral reefs. Science301, 929–933. doi: 10.1126/science.1085046

  • CrossRef
  • Google Scholar
  • View reference in article

• 31

  IUCN (2020). IUCN 2019 International union for conservation of nature annual report 2019 (IUCN). #Available at: https://portals.iucn.org/library/node/49096.

  • Google Scholar
  • View reference in article

• 32

  JacksonJ. B. C.KirbyM. X.BergerW. H.BjorndalK. A.BotsfordL. W.BourqueB. J.et al. (2001). Historical overfishing and the recent collapse of coastal ecosystems. Science293, 629–637. doi: 10.1126/science.1059199

  • CrossRef
  • Google Scholar
  • View reference in article

• 33

  JeonY.ParkS. G.LeeN.WeberJ. A.KimH.-S.HwangS.-J.et al. (2019). The Draft Genome of an Octocoral, Dendronephthya gigantea. Genome Biol. Evol.11, 949–953. doi: 10.1093/gbe/evz043

  • CrossRef
  • Google Scholar
  • View reference in article

• 34

  KellerO.KollmarM.StankeM.WaackS. (2011). A novel hybrid gene prediction method employing protein multiple sequence alignments. Bioinformatics27, 757–763. doi: 10.1093/bioinformatics/btr010

  • CrossRef
  • Google Scholar
  • View reference in article

• 35

  KenyonJ. C. (1997). Models of reticulate evolution in the coral genus acropora based on chromosome numbers: Parallels with plants. Evolution51, 756–767. doi: 10.1111/j.1558-5646.1997.tb03659.x

  • CrossRef
  • Google Scholar
  • View reference in article

• 36

  KimD.PaggiJ. M.ParkC.BennettC.SalzbergS. L. (2019). Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol.37, 907–915. doi: 10.1038/s41587-019-0201-4

  • CrossRef
  • Google Scholar
  • View reference in article

• 37

  KochT. L.GrimmelikhuijzenC. J. P. (2019). Global neuropeptide annotations from the genomes and transcriptomes of cubozoa, scyphozoa, staurozoa (Cnidaria: Medusozoa), and octocorallia (Cnidaria: Anthozoa). Front. Endocrinol.10. doi: 10.3389/fendo.2019.00831

  • CrossRef
  • Google Scholar
  • View reference in article

• 38

  KorfI. (2004). Gene finding in novel genomes. BMC Bioinf.5, 59. doi: 10.1186/1471-2105-5-59

  • CrossRef
  • Google Scholar
  • View reference in article

• 39

  KozomaraA.Griffiths-JonesS. (2014). miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res.42, D68–D73. doi: 10.1093/nar/gkt1181

  • CrossRef
  • Google Scholar
  • View reference in article

• 40

  KumarS.StecherG.TamuraK. (2016). MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol.33, 1870–1874. doi: 10.1093/molbev/msw054

  • CrossRef
  • Google Scholar
  • View reference in article

• 41

  LiY.NongW.BarilT.YipH. Y.SwaleT.HaywardA.et al. (2020). Reconstruction of ancient homeobox gene linkages inferred from a new high-quality assembly of the Hong Kong oyster (Magallana hongkongensis) genome. BMC Genomics21, 713. doi: 10.1186/s12864-020-07027-6

  • CrossRef
  • Google Scholar
  • View reference in article

• 42

  LiewY. J.ArandaM.CarrA.BaumgartenS.ZoccolaD.TambuttéS.et al. (2014). Identification of MicroRNAs in the coral stylophora pistillata. PloS One9, e91101. doi: 10.1371/journal.pone.0091101

  • CrossRef
  • Google Scholar
  • View reference in article

• 43

  LomsadzeA.Ter-HovhannisyanV.ChernoffY. O.BorodovskyM. (2005). Gene identification in novel eukaryotic genomes by self-training algorithm. Nucleic Acids Res.33. 6494–6506. doi: 10.1093/nar/gki937

  • CrossRef
  • Google Scholar
  • View reference in article

• 44

  MajorosW. H.PerteaM.SalzbergS. L. (2004). TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics20, 2878–2879. doi: 10.1093/bioinformatics/bth315

  • CrossRef
  • Google Scholar
  • View reference in article

• 45

  MarçaisG.KingsfordC. (2011). A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics27, 764–770. doi: 10.1093/bioinformatics/btr011

  • CrossRef
  • Google Scholar
  • View reference in article

• 46

  MatamboT. S.OdunugaO. O.BoshoffA.BlatchG. L. (2004). Overproduction, purification, and characterization of the Plasmodium falciparum heat shock protein 70. Protein Expression Purification33, 214–222. doi: 10.1016/j.pep.2003.09.010

  • CrossRef
  • Google Scholar
  • View reference in article

• 47

  McCullochM.FallonS.WyndhamT.HendyE.LoughJ.BarnesD. (2003). Coral record of increased sediment flux to the inner great barrier reef since European settlement. Nature421, 727–730. doi: 10.1038/nature01361

  • CrossRef
  • Google Scholar
  • View reference in article

• 48

  NongW.CaoJ.LiY.QuZ.SunJ.SwaleT.et al. (2020). Jellyfish genomes reveal distinct homeobox gene clusters and conservation of small RNA processing. Nat. Commun.11, 3051. doi: 10.1038/s41467-020-16801-9

  • CrossRef
  • Google Scholar
  • View reference in article

• 49

  NongW.QuZ.LiY.Barton-OwenT.WongA. Y. P.YipH. Y.et al. (2021). Horseshoe crab genomes reveal the evolution of genes and microRNAs after three rounds of whole genome duplication. Commun. Biol.4, 1–11. doi: 10.1038/s42003-020-01637-2

  • CrossRef
  • Google Scholar
  • View reference in article

• 50

  NongW.YuY.Aase-RemediosM. E.XieY.SoW. L.LiY.et al. (2022). Genome of the ramshorn snail Biomphalaria straminea—an obligate intermediate host of schistosomiasis. GigaScience11, giac012. doi: 10.1093/gigascience/giac012

  • CrossRef
  • Google Scholar
  • View reference in article

• 51

  PalmerJ. M.StajichJ. (2020). Funannotate v1.8.1: Eukaryotic genome annotation (Zenodo). Avaialble at: https://github.com/nextgenusfs/funannotate.

  • Google Scholar
  • View reference in article

• 52

  PandolfiJ. M.BradburyR. H.SalaE.HughesT. P.BjorndalK. A.CookeR. G.et al. (2003). Global trajectories of the long-term decline of coral reef ecosystems. Science301, 955–958. doi: 10.1126/science.1085706

  • CrossRef
  • Google Scholar
  • View reference in article

• 53

  PradaC.HannaB.BuddA. F.WoodleyC. M.SchmutzJ.GrimwoodJ.et al. (2016). Empty niches after extinctions increase population sizes of modern corals. Curr. Biol.26, 3190–3194. doi: 10.1016/j.cub.2016.09.039

  • CrossRef
  • Google Scholar
  • View reference in article

• 54

  PraherD.ZimmermannB.DnyansagarR.DJM.MoyaA.ModepalliV.et al. (2021). Conservation and turnover of miRNAs and their highly complementary targets in early branching animals. Proc. R. Soc. B.: Biol. Sci.288, 20203169.

  • Google Scholar
  • View reference in article

• 55

  PutnamN. H.O’ConnellB. L.StitesJ. C.RiceB. J.BlanchetteM.CalefR.et al. (2016). Chromosome-scale shotgun assembly using an in vitro method for long-range linkage. Genome Res.26, 342–350. doi: 10.1101/gr.193474.115

  • CrossRef
  • Google Scholar
  • View reference in article

• 56

  QiuJ.-W.LauD. C. C.CheangC.ChowW. (2014). Community-level destruction of hard corals by the sea urchin Diadema setosum. Marine Pollution Bull.85, 783–788. doi: 10.1016/j.marpolbul.2013.12.012

  • CrossRef
  • Google Scholar
  • View reference in article

• 57

  QuZ.BendenaW. G.TobeS. S.HuJ. H. L. (2018). Juvenile hormone and sesquiterpenoids in arthropods: Biosynthesis, signaling, and role of MicroRNA. J. Steroid Biochem. Mol. Biol.184, 69–76. doi: 10.1016/j.jsbmb.2018.01.013

  • CrossRef
  • Google Scholar
  • View reference in article

• 58

  QuZ.NongW.YuY.BarilT.YipH. Y.HaywardA.et al. (2020). Genome of the four-finger threadfin Eleutheronema tetradactylum (Perciforms: Polynemidae). BMC Genomics21, 726. doi: 10.1186/s12864-020-07145-1

  • CrossRef
  • Google Scholar
  • View reference in article

• 59

  Ranallo-BenavidezT. R.JaronK. S.SchatzM. C. (2020). GenomeScope 2.0 and smudgeplot for reference-free profiling of polyploid genomes. Nat. Commun.11, 1432. doi: 10.1038/s41467-020-14998-3

  • CrossRef
  • Google Scholar
  • View reference in article

• 60

  R Core Team (2022). R: a language and environment for statistical computing.

  • Google Scholar
  • View reference in article

• 61

  RichardD. (2005). “Notes from the trenches: Asexual reproduction of catalaphyllia jardinei (Elegance coral),” in Reefkeeping magazine™ reef central, LLC-copyright © (2008).

  • Google Scholar
  • View reference in article

• 62

  RobbinsS. J.SingletonC. M.ChanC. X.MesserL. F.GeersA. U.YingH.et al. (2019). A genomic view of the reef-building coral Porites lutea and its microbial symbionts. Nat. Microbiol.4, 2090–2100. doi: 10.1038/s41564-019-0532-4

  • CrossRef
  • Google Scholar
  • View reference in article

• 63

  SandersonM. J. (2003). r8s: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock. Bioinformatics19, 301–302. doi: 10.1093/bioinformatics/19.2.301

  • CrossRef
  • Google Scholar
  • View reference in article

• 64

  Saville-KentW. (1893). The great barrier reef of Australia: Its products and Potentialities : Containing an account, with copious coloured and photographic illustrations (the latter here produced for the first time), of the corals and coral reefs, pearl and pearl-shell, beche-de-mer, other fishing industries, and the marine fauna of the Australian great barrier region. Allen.

  • Google Scholar
  • View reference in article

• 65

  SchlagerW. (1981). The paradox of drowned reefs and carbonate platforms. GSA. Bull.92, 197–211. doi: 10.1130/0016-7606(1981)92<197:TPODRA>2.0.CO;2

  • CrossRef
  • Google Scholar
  • View reference in article

• 66

  SchlagerW. (2003). Benthic carbonate factories of the phanerozoic. Int. J. Earth Sci. (Geologische. Rundschau).92, 445–464. doi: 10.1007/s00531-003-0327-x

  • CrossRef
  • Google Scholar
  • View reference in article

• 67

  ShikinaS.ChiuY.-L.ZhangY.YaoY.-C.LiuT.-Y.TsaiP.-H.et al. (2020). Involvement of GLWamide neuropeptides in polyp contraction of the adult stony coral euphyllia ancora. Sci. Rep.10, 9427. doi: 10.1038/s41598-020-66438-3

  • CrossRef
  • Google Scholar
  • View reference in article

• 68

  ShinzatoC.KhalturinK.InoueJ.ZayasuY.KandaM.KawamitsuM.et al. (2021). Eighteen coral genomes reveal the evolutionary origin of acropora strategies to accommodate environmental changes. Mol. Biol. Evol.38, 16–30. doi: 10.1093/molbev/msaa216

  • CrossRef
  • Google Scholar
  • View reference in article

• 69

  ShumC.NongW.SoW. L.LiY.QuZ.YipH. Y.et al. (2022). Genome of the sea anemone exaiptasia pallida and transcriptome profiles during tentacle regeneration. Front. Cell Dev. Biol.10, 1558. doi: 10.3389/fcell.2022.900321

  • CrossRef
  • Google Scholar
  • View reference in article

• 70

  SimakovO.MarletazF.ChoS.-J.Edsinger-GonzalesE.HavlakP.HellstenU.et al. (2013). Insights into bilaterian evolution from three spiralian genomes. Nature493, 526–531. doi: 10.1038/nature11696

  • CrossRef
  • Google Scholar
  • View reference in article

• 71

  SimsD.IlottN. E.SansomS. N.SudberyI. M.JohnsonJ. S.FawcettK. A.et al. (2014). CGAT: computational genomics analysis toolkit. Bioinformatics30, 1290–1291. doi: 10.1093/bioinformatics/btt756

  • CrossRef
  • Google Scholar
  • View reference in article

• 72

  SoW. L.NongW.XieY.BarilT.MaH.QuZ.et al. (2022). Myriapod genomes reveal ancestral horizontal gene transfer and hormonal gene loss in millipedes. Nat. Commun.13, 3010. doi: 10.1038/s41467-022-30690-0

  • CrossRef
  • Google Scholar
  • View reference in article

• 73

  TakahashiT. (2020). Comparative aspects of structure and function of cnidarian neuropeptides. Front. Endocrinol.11. doi: 10.3389/fendo.2020.00339

  • CrossRef
  • Google Scholar
  • View reference in article

• 74

  TsangS. S. K.LawS. T. S.LiC.QuZ.BendenaW. G.TobeS. S.et al. (2020) Diversity of Insect Sesquiterpenoid Regulation. . Available at: https://www.frontiersin.org/articles/10.3389/fgene.2020.01027 (Accessed September 11, 2022).

  • Google Scholar
  • View reference in article

• 75

  UNEP. (2005) World conservation monitoring centre:United Nations Environment Programme (2005). UNEP 2004 annual report.

  • Google Scholar
  • View reference in article

• 76

  VeenstraJ. A. (2000). Mono- and dibasic proteolytic cleavage sites in insect neuroendocrine peptide precursors. Arch. Insect Biochem. Physiol.43, 49–63. doi: 10.1002/(SICI)1520-6327(200002)43:2<49::AID-ARCH1>3.0.CO;2-M

  • CrossRef
  • Google Scholar
  • View reference in article

• 77

  VeronJ. E. N.Stafford-SmithM. (2000). Corals of the world (Townsville MC, Qld, Australia: Australian Institute of Marine Science).

  • Google Scholar
  • View reference in article

• 78

  VoolstraC. R.LiY.LiewY. J.BaumgartenS.ZoccolaD.FlotJ.-F.et al. (2017). Comparative analysis of the genomes of Stylophora pistillata and Acropora digitifera provides evidence for extensive differences between species of corals. Sci. Rep.7, 17583. doi: 10.1038/s41598-017-17484-x

  • CrossRef
  • Google Scholar
  • View reference in article

• 79

  WeisenfeldN.KumarV.ShahP.ChurchD.JaffeD. (2017). Direct determination of diploid genome sequences. Genome Res.27. doi: 10.1101/gr.214874.116

  • CrossRef
  • Google Scholar
  • View reference in article

• 80

  WellsJ. W. (1971). Notes on indo-pacific scleractinian corals. part 7 catalaphyllia, a new genus of reef corals.

  • Google Scholar
  • View reference in article

• 81

  WhitleyD.GoldbergS. P.JordanW. D. (1999). Heat shock proteins: A review of the molecular chaperones. J. Vasc. Surg.29, 748–751. doi: 10.1016/S0741-5214(99)70329-0

  • CrossRef
  • Google Scholar
  • View reference in article

• 82

  WickhamH. (2016). ggplot2: Elegant graphics for data analysis (Springer). Available at: https://link.springer.com/book/10.1007/978-0-387-98141-3.

  • Google Scholar
  • View reference in article

• 83

  WilkinsonC. R. (2002). Status of coral reefs of the world : 2002.

  • Google Scholar
  • View reference in article

• 84

  WilliamsB. K.NicholsJ. D.ConroyM. J. (2002). Analysis and management of animal populations (Academic Press).

  • Google Scholar
  • View reference in article

• 85

  WoodD. E.LuJ.LangmeadB. (2019). Improved metagenomic analysis with kraken 2. Genome Biol.20, 257. doi: 10.1186/s13059-019-1891-0

  • CrossRef
  • Google Scholar
  • View reference in article

• 86

  XieJ. Y.YeungY. H.KwokC. K.KeiK.AngP.ChanL. L.et al. (2020). Localized bleaching and quick recovery in Hong Kong's coral communities. Marine Pollution Bull.153, 110950. doi: 10.1016/j.marpolbul.2020.110950

  • CrossRef
  • Google Scholar
  • View reference in article

• 87

  YeungY. H.XieJ. Y.KwokC. K.KeiK.AngP.ChanL. L.et al. (2021). Hong Kong's subtropical scleractinian coral communities: Baseline, environmental drivers and management implications. Marine Pollution Bull.167, 112289. doi: 10.1016/j.marpolbul.2021.112289

  • CrossRef
  • Google Scholar
  • View reference in article

• 88

  Yichun. (2022). xieyichun50/Myriapod-genomes: Myriapod-genomes (v1.0.0). Zenodo10.5281/zenodo.6482625 xieyichun50/Genome-macrosynteny-gene-family-evolution: Genome-macrosynteny-gene-family-evolution-v1.0. Zenodo

  • Google Scholar
  • View reference in article

• 89

  YingH.CookeI.SprungalaS.WangW.HaywardD. C.TangY.et al. (2018). Comparative genomics reveals the distinct evolutionary trajectories of the robust and complex coral lineages. Genome Biol.19, 175. doi: 10.1186/s13059-018-1552-8

  • CrossRef
  • Google Scholar
  • View reference in article

• 90

  YongeC. M.NichollsA. G. (1931). “Studies on the physiology of corals: IV. The structure, distribution and physiology of THE ZOOXANTHELLAE,” in Scientific Reports/Great barrier reef expedition 1928-29, vol. 1. , 135–176.

  • Google Scholar
  • View reference in article

• 91

  YuG.SmithD. K.ZhuH.GuanY.LamT. T. Y. (2017). Ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol. Evol.8 (1), 28–36. doi: 10.1111/2041-210X.12628

  • CrossRef
  • Google Scholar
  • View reference in article