- Research article
- Open Access
The genome of the giant Nomura’s jellyfish sheds light on the early evolution of active predation
- Hak-Min Kim†1, 2,
- Jessica A. Weber†3, 4,
- Nayoung Lee†5,
- Seung Gu Park1,
- Yun Sung Cho1, 2, 6,
- Youngjune Bhak1, 2,
- Nayun Lee5,
- Yeonsu Jeon1, 2,
- Sungwon Jeon1, 2,
- Victor Luria7,
- Amir Karger8,
- Marc W. Kirschner7,
- Ye Jin Jo5,
- Seonock Woo9, 10,
- Kyoungsoon Shin11,
- Oksung Chung6, 12,
- Jae-Chun Ryu13,
- Hyung-Soon Yim10,
- Jung-Hyun Lee10,
- Jeremy S. Edwards14,
- Andrea Manica15,
- Jong Bhak1, 2, 6, 12Email author and
- Seungshic Yum5, 9Email author
© The Author(s). 2019
- Received: 8 January 2019
- Accepted: 28 February 2019
- Published: 29 March 2019
Unique among cnidarians, jellyfish have remarkable morphological and biochemical innovations that allow them to actively hunt in the water column and were some of the first animals to become free-swimming. The class Scyphozoa, or true jellyfish, are characterized by a predominant medusa life-stage consisting of a bell and venomous tentacles used for hunting and defense, as well as using pulsed jet propulsion for mobility. Here, we present the genome of the giant Nomura’s jellyfish (Nemopilema nomurai) to understand the genetic basis of these key innovations.
We sequenced the genome and transcriptomes of the bell and tentacles of the giant Nomura’s jellyfish as well as transcriptomes across tissues and developmental stages of the Sanderia malayensis jellyfish. Analyses of the Nemopilema and other cnidarian genomes revealed adaptations associated with swimming, marked by codon bias in muscle contraction and expansion of neurotransmitter genes, along with expanded Myosin type II family and venom domains, possibly contributing to jellyfish mobility and active predation. We also identified gene family expansions of Wnt and posterior Hox genes and discovered the important role of retinoic acid signaling in this ancient lineage of metazoans, which together may be related to the unique jellyfish body plan (medusa formation).
Taken together, the Nemopilema jellyfish genome and transcriptomes genetically confirm their unique morphological and physiological traits, which may have contributed to the success of jellyfish as early multi-cellular predators.
- Jellyfish mobility
- Medusa structure formation
- de novo genome assembly
Jellyfish genome assembly and annotation
Here, we present the first de novo genome assembly of the Nomura’s jellyfish (Nemopilema nomurai; Fig. 1b). It resulted in a 213-Mb genome comprised of 255 scaffolds and an N50 length of 2.71 Mb, containing only 1.48% gaps (Additional file 1: Tables S2 and S3). The Nemopilema hybrid assembly was created using a combination of short and long read sequencing technologies, consisting of 38.2 Gb Pacific Biosciences (PacBio) single-molecule real-time sequencing (SMRT) reads, along with 98.6 Gb of Illumina short-insert, mate-pair, and TruSeq synthetic long reads (Additional file 1: Figures S3–S5; Tables S4–S7). The resulting assembly shows the longest continuity among cnidarian genomes (Additional file 1: Table S9). We predicted 18,962 protein-coding jellyfish genes by combining de novo (using medusa bell and tentacle tissue transcriptomes) and homologous gene prediction methods (Additional file 1: Tables S10 and S11, Additional files 2 and 3). This process recovered the highest number of single-copy orthologous genes  among all published non-bilaterian metazoan genome assemblies to date (Additional file 1: Table S12). A total of 21.07% of the jellyfish genome was found to be made up of transposable elements, compared to those of Acropora digitifera (9.45%), Nematostella vectensis (33.63%), and Hydra vulgaris (42.87%) (Additional file 1: Table S13).
We compared the Nemopilema genome to other cnidarian genomes, including the recently published Aurelia aurita  and Clytia hemisphaerica genomes , all of which are from predominantly sessile taxa, to detect unique Scyphozoa function (active mobility), physical structure (medusa bell), and chemistry (venom). We also performed transcriptome analyses of both Nemopilema nomurai and the Sanderia malayensis jellyfish across three medusa tissue types and four developmental stages.
Evolutionary analysis of the jellyfish
Genomic context and muscle-associated genes
Jellyfish have two primary muscle types: the epitheliomuscular cells, which are the predominant muscle cells found in sessile cnidarians, and the striated muscle cells located in the medusa bell that are essential for swimming. To understand the evolution of active-swimming in jellyfish, we examined their codon bias compared to other metazoans by calculating the guanine and cytosine content at the third codon position (GC3) [14, 15] (Additional file 1: Figure S13). It has been suggested that genes with high level of GC3 are more adaptable to external stresses (e.g., environmental changes) . Among the high-scoring top 100 GC3 biased genes, the regulation of muscle contraction, and neuropeptide signaling pathways, GO terms were specific to Nemopilema (Additional file 4: Tables S25 and S26). Calcium plays a key role in the striated muscle contraction in jellyfish, and the calcium signaling pathway (GO:0004020, P = 5.60E− 10) showed a high level of GC3 biases specific to Nemopilema. Nemopilema and Aurelia top 500 GC3 genes were enriched in GO terms associated with homeostasis (e.g., cellular chemical homeostasis and sodium ion transport), which we speculate is essential for the activation of muscle contractions that power the jellyfish’s mobile predation (Additional file 1: Section 5.1; Additional file 4: Tables S27 and S28).
Since cnidarians have been reported to lack titin and troponin complexes, which are critical components of bilaterian striated muscles, it has been suggested that the two clades independently evolved striated muscles . A survey of genes that encode muscle structural and regulatory proteins in cnidarians showed a conserved eumetazoan core actin-myosin contractile machinery shared with bilaterians (Additional file 1: Table S32). However, like other cnidarians, Nemopilema lacks titin and troponin complexes, which are key components of bilaterian striated muscles. Also, γ-syntrophin, a component of the dystroglycan complex, was absent in Nemopilema, Aurelia, and Hydra. However, Nemopilema and Aurelia do possess α/β-Dystrobrevin and α/ε-Sarcoglycan dystroglycan-associated costamere proteins, indicating that several components of the dystroglycan complex were lost after the Scyphozoa-Hydrozoa split. It was suggested that Hydra undergone secondary simplifications relative to Nematostella, which has a greater degree of muscle-cell-type specialization . Compared to Hydra and Nematostella, Nemopilema and Aurelia show intermediate complexity of muscle structural and regulatory proteins between Hydra and Nematostella.
Medusa bell and tentacle transcriptome profiling
Conversely, gene expression analyses of the tentacles revealed high RNA expression levels of neurotransmitter-associated functional categories (ion channel complex, postsynapse, and neurotransmitter receptor activity; Fig. 3b; Additional file 5: Tables S34–S37); consistent with the anatomy of jellyfish tentacles, which contain the sensory cells and a loose plexus of the neuronal subpopulation at the base of the ectoderm .
Body patterning in the jellyfish
There has been much debate surrounding the early evolution of body patterning in the metazoan common ancestor, particularly concerning the origin and expansion of Hox and Wnt gene families [22–24]. In total, 83 homeodomains were found in Nemopilema, while 82, 41, 120, and 148 of homeodomains were found from Aurelia, Hydra, Acropora, and Nematostella, respectively (Additional file 1: Table S41). Five of the eight Hox genes in Nemopilema are of the posterior type that are associated with aboral axis development  and clustered with Nematostella’s posterior Hox genes, HOXE and HOXF (Additional file 1: Figures S18–S20). Aurelia has six posterior type Hox genes, but does not have the HOXB, C, and D type (HOX2 in humans). Though absent in Hydra and Acropora, synteny analyses of ParaHox genes in Nemopilema show that the XLOX/CDX gene is located immediately downstream of GSX in the same tandem orientation as those in Nematostella, suggesting that XLOX/CDX was present in the cnidarian common ancestor and subsequently lost in some lineages (Additional file 1: Figure S21). Hox-related genes, EVX and EMX, are also present in Nemopilema and Aurelia, although they are absent in Hydra. Given the large amount of ancestral diversity in the Wnt genes, it has been proposed that Wnt signaling controlled body plan development in the early metazoans . Nemopilema possesses 13 Wnt orthologs representing 10 Wnt subfamilies (Additional file1: Figure S22; Table S42). Wnt9 is absent from all cnidarians, likely representing losses in the cnidarian common ancestor. Cnidarians have undergone dynamic lineage-specific Wnt subfamily duplications, such as Wnt8 (Nematostella, Acropora, and Aurelia), Wnt10 (Hydra), and Wnt11, and Wnt16 (Nemopilema and Aurelia). It has been proposed that a common cluster of Wnt genes (Wnt1–Wnt6–Wnt10) existed in the last common ancestor of arthropods and deuterostomes . Our analyses of cnidarian and bilaterian genomes revealed that Acropora also possess this cluster, while Nemopilema, Aurelia, and Hydra are missing Wnt6, suggesting loss of the Wnt6 gene in the Medusozoa common ancestor (Additional file 1: Figure S23). Taken together, the jellyfish have comparable number of Hox and Wnt genes to other cnidarians, but the dynamic repertoire of these gene families suggests that cnidarians have evolved independently to adapt their physiological characteristics and life cycle.
Polyp to medusa transition in jellyfish
The polyp-to-medusa transition is prominent in jellyfish compared to the other sessile cnidarians. To understand the genetic basis of the medusa structure formation in the jellyfish, we compared transcriptional regulation between cnidarians and across jellyfish developmental stages (see Additional file 1: Sections 7.1 and 7.2). We assembled the Sanderia transcripts using six pooled samples of transcriptomes (Additional file 1: Table S43). The assembled transcripts had a total length of 61 Mb and resulted in 58,290 transcript isoforms and 43,541 unique transcripts, with a N50 of 2325 bp. On average, 87% of the RNA reads were aligned to into the assembled transcripts (Additional file 1: Table S44), indicating that the transcript assembly represented the majority of sequenced reads. Furthermore, the composition of the protein domains contained in the top 20 ranks was quite similar between Nemopilema and Sanderia (Additional file 1: Table S45). To obtain differentially expressed genes for each stage, we compared each stage with the previous or next stage in the life cycle of the jellyfish. The polyp stage, which represents a sessile stage in the jellyfish life cycle, showed enriched terms related to ion channel activity and energy metabolism (regulation of metabolic process, and amino sugar metabolic process; Additional file 1: Table S46). Active feeding in the polyp stimulates asexual proliferation either into more polyps or metamorphosis to strobila . Since anthozoans do not form a medusa, the strobila asexual reproductive stage is an important stage in which to study the metamorphosis from polyp to medusa. In this stage, GO terms related to amide biosynthetic and metabolic process were highly expressed compared to the polyp stage (Additional file 1: Table S47). It has been reported that RF-amide and LW-amide neuropeptides were associated with metamorphosis in cnidarians [28–30]. However, we could not confirm this finding in our strobila and ephyra stage comparisons. In our system, the gene expression patterns of the two stages are quite similar. In the ephyra, the released mobile stage, GO terms involving amide biosynthetic and metabolic process were also highly expressed compared to the merged medusa stage (Additional file 1: Table S48). In the medusa, extracellular matrix, metallopeptidase activity, and immune system process terms were enriched (Additional file 1: Table S49), consistent with the physiology of their bell, tentacles, and oral arm tissue types.
Identification of toxin-related domains in jellyfish
An interesting branch on the tree of life, jellyfish have evolved remarkable morphological and biochemical innovations that allow them to actively hunt using pulsed jet propulsion and venomous tentacles. While the expansion and contraction of distinct families reflect the adaptation to salinity and predation and the convergent evolution of muscle elements, the Nemopilema genome strikes a balance between the conservation of many ancient genes and an innovative potential reflected in significant number of new genes that appeared since Rhizostomeae emerged. The Nemopilema nomurai genome has provided clues to the genetic basis of the innovative structure, function, and chemistry that have allowed this distinctive early group of predators to colonize the waters of the globe.
A medusa Nemopilema nomurai was collected at the Tongyeong Marine Science Station, KIOST (34.7699 N, 128.3828 E) on Sept. 12, 2013. The Sanderia malayensis samples were obtained from Aqua Planet Jeju Hanwha (Seogwipo, Korea) for transcriptome analyses of developmental stages since Nemopilema cannot be easily grown in the laboratory. The DNA and RNA preparation of Nemopilema and Sanderia are described in Additional file 1: Section 1.1. Species identification of Nemopilema was confirmed by comparing the MT-COI gene of five species of jellyfish. We aligned Nemopilema Illumina short reads (~ 400 bp insert-size) to the MT-COI gene of Chrysaora quinquecirrha (NC_020459.1), Cassiopea frondosa (NC_016466.1), Craspedacusta sowerbyi (NC_018537.1), and Aurelia aurita (NC_008446.1) jellyfish with BWA-MEM aligner . Consensus sequences for each jellyfish were generated using SAMtools . The consensus sequence from C. sowerbyi was excluded due to low coverage. We conducted multiple sequence alignment using MUSCLE  and ran the MEGA v7  neighbor joining phylogenetic tree (gamma distribution) with 1000 bootstrap replicates. Mitochondrial DNA phylogenetic analyses confirmed the identification of the Nemopilema sample as Nemopilema nomurai.
Genome sequencing and scaffold assembly
For the de novo assembly of Nemopilema, PacBio SMRT and five Illumina DNA libraries with various insert sizes (400 bp, 5 Kb, 10 Kb, 15 Kb, and 20 Kb) were constructed according to the manufacturers’ protocols. The Illumina libraries were sequenced using a HiSeq2500 with a read length of 100 bp (400 bp, 15 Kb, and 20 Kb) and a HiSeq2000 with a read length of 101 bp (5 Kb and 10 Kb). Quality filtered PacBio subreads were assembled into distinct contigs using the FALCON assembler  with various read length cutoffs. To extend contigs to scaffolds, we aligned the Illumina long mate-pair libraries (5 Kb, 10 Kb, 15 Kb, and 20 Kb) to contig sets and extended the contigs using SSPACE . Gaps generated by SSPACE were filled by aligning the Illumina short-insert paired-end sequences using GapCloser . We also generated TSLRs using an Illumina HiSeq2000, which were aligned to scaffolds to correct erroneous sequences and to close gaps using an in-house script. Detailed genome sequencing and assembly process are provided in Additional file 1: Section 2.2.
The jellyfish genome was annotated for protein-coding genes and repetitive elements. We predicted protein-coding genes using a two-step process, with both homology- and evidence-based prediction. Protein sequences of the sea anemone, hydra, sponge, human, mouse, and fruit fly from the NCBI database and Cnidaria protein sequences from the NCBI Entrez protein database were used for homology-based gene prediction. Two tissue transcriptomes from Nemopilema were used for evidence-based gene prediction via AUGUSTUS . Final Nemopilema protein-coding genes were determined using AUGUSTUS with exon (from the homology-based gene prediction) and intron (from the evidence-based gene prediction) hints. Repetitive elements were also predicted using Tandem Repeats Finder  and RepeatMasker . Details of the annotation process are provided in Additional file 1: Sections 3.1 and 3.2.
Gene age estimation
Phylostratigraphy employs BLASTP-scored sequence similarity to estimate the minimal age of every protein-coding gene. The protein sequence is used to query the NCBI non-redundant database and detect the most distant species in which a sufficiently similar sequence is present inferring that the gene is at least as old as the age of the common ancestor . For every species, we use the NCBI taxonomy. The timing of most divergence events is estimated using TimeTree  and the Encyclopedia of Life . To facilitate detection of sequence similarity, we use the e value threshold of 10−3. We evaluate the age of all proteins whose length is equal or greater than 40 amino acids. We count the number of genes in each phylostratum, from the most ancient (PS 1) to the newest (PS 11). To see broad evolutionary patterns, we aggregate the counts from several phylostrata into three broad evolutionary eras: ancient (PS 1–5, cellular organisms to Eumetazoa, 4204 Mya to 741 Mya), middle (PS 6–7, Cnidaria to Scyphozoa, 741 Mya to 239 Mya), and young (PS 8–11, Rhizostomeae to Nemopilema nomurai, 239 Mya to present).
Comparative evolutionary analyses
Orthologous gene clusters were constructed to examine the conservation of gene repertoires among the genomes of the Nemopilema nomurai, Aurelia aurita, Hydra vulgaris, Clytia hemisphaerica, Acropora digitifera, Nematostella vectensis, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Homo sapiens, Trichoplax adhaerens, Amphimedon queenslandica, Mnemiopsis leidyi, and Monosiga brevicollis using OrthoMCL . To infer a phylogeny and divergence times, we used RAxML  and MEGA7 program , respectively. A gene family expansion and contraction analysis was conducted using the Café program . Domain regions were predicted by InterProScan  with domain databases. Details of the comparative analysis are provided in Additional file 1: Sections 4.1–4.3.
Transcriptome sequencing and expression profiling
Illumina RNA libraries from Nemopilema nomurai and Sanderia malayensis were sequenced using a HiSeq2500 with 100-bp read lengths. Since there is not a reference genome for S. malayensis, we de novo assembled a pooled six RNA-seq read set using the Trinity assembler . Quality filtered RNA reads from Nemopilema and Sanderia were aligned to the Nemopilema genome assembly and the assembled transcripts, respectively, using the TopHat  program. Expression values were calculated by the Fragments Per Kilobase Of Exon Per Million Fragments Mapped (FPKM) method using Cufflinks , and differentially expressed genes were identified by DEGseq . Details of the transcriptome analysis are presented in Additional file 1: Sections 5.2 and 7.1.
Hox and ParaHox analyses
We examined the homeodomain regions in Nemopilema using the InterProScan program. Hox and ParaHox genes were identified in Nemopilema by aligning the homeodomain sequences of human and fruit fly to the identified Nemopilema homeodomains. We considered only domains that were aligned to both the human and fruit fly. We also used this process for Acropora, Hydra, and Nematostella for comparison. Additionally, we added one Hox gene for Acropora and two Hox genes for Hydra, which are absent in the NCBI gene set, though they were present in previous studies [23, 60]. Hox and ParaHox genes of Clytia hemisphaerica, a hydrozoan species with a medusa stage, were also added based on a previous study . Finally, a multiple sequence alignment of these domains was conducted using MUSCLE, and a FastTree  maximum likelihood phylogeny was generated using the Jones–Taylor–Thornton (JTT) model with gamma option.
Wnt gene subfamily analyses
Wnt genes of Nematostella and Hydra were downloaded from previous studies [25, 63], and those of Acropora were downloaded from the NCBI database. Wnt genes in Nemopilema and Aurelia were identified using the Pfam database by searching for “wnt family” domains. A multiple sequence alignment of Wnt genes was conducted using MUSCLE, and aligned sequences were trimmed using the trimAl program  with “gappyout” option. A phylogenetic tree was generated using RAxML with the PROTGAMMAJTT model and 100 bootstraps.
Korea Institute of Science and Technology Information (KISTI) provided us with the Korea Research Environment Open NETwork (KREONET), which is the internet connection service for efficient information and data transfer.
This work was supported by the Genome Korea Project in Ulsan Research Funds (1.180024.01 and 1.180017.01) of Ulsan National Institute of Science & Technology (UNIST). This work was also supported by a grant from the Marine Biotechnology Program (20170305, Development of Biomedical materials based on marine proteins) and the Collaborative Genome Program (20180430) funded by the Ministry of Oceans and Fisheries, Korea. This work was also supported by the Collaborative Genome Program for Fostering New Post-Genome Industry of the National Research Foundation (NRF) funded by the Ministry of Science and ICT (MSIT) (NRF-2017M3C9A6047623 and NRF-2017R1A2B2012541). V.L. and M.W.K. gratefully acknowledge funding support from the National Institutes of Health of USA (R01 HD073104 and R01 HD091846 to M.W.K.).
Availability of data and materials
The jellyfish genome project has been deposited at DDBJ/ENA/GenBank under the accession PEDN00000000 . The version described in this paper is version PEDN01000000. Raw DNA and RNA sequence reads for Nemopilema nomurai and Sanderia malayensis have been submitted to the NCBI Sequence Read Archive database (SRA627560) . All other data can be obtained from the authors upon reasonable request.
JB and SY supervised the project. YSC, JB, and SY planned and coordinated the project. HMK, JAW, YSC, SY, and JB wrote the manuscript. NayoungL, NayunL, YJJ, SW, KS, JCR, HSY, JHL, and SY prepared the samples, performed the experiments, and provided toxinological considerations. VL, AK, and MWK performed the gene evolutionary age analysis. HMK, SGP, YSC, YB, YJ, SJ, OC, JSE, and AM performed the in-depth bioinformatics data analyses. All authors read and approved the final manuscript.
Ethics approval and consent to participate
This is not applicable.
YSC and OC are employees, and JB is on the scientific advisory board of Clinomics Inc. HMK, YSC and JB have an equity interest in the company. All other coauthors declare that they have no competing interests.
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- Park E, Hwang DS, Lee JS, Song JI, Seo TK, Won YJ. Estimation of divergence times in cnidarian evolution based on mitochondrial protein-coding genes and the fossil record. Mol Phylogenet Evol. 2012;62(1):329–45.PubMedView ArticleGoogle Scholar
- Arai MN. A functional biology of Scyphozoa: Springer Science & Business Media; 2012.Google Scholar
- Hale G. The classification and distribution of the class Scyphozoa. Eugene: University of Oregon; 1999.Google Scholar
- Anderson PA, Schwab WE. The organization and structure of nerve and muscle in the jellyfish Cyanea capillata (Coelenterata; Scyphozoa). J Morphol. 1981;170(3):383–99.PubMedView ArticleGoogle Scholar
- Gemmell BJ, Costello JH, Colin SP, Stewart CJ, Dabiri JO, Tafti D, Priya S. Passive energy recapture in jellyfish contributes to propulsive advantage over other metazoans. Proc Natl Acad Sci U S A. 2013;110(44):17904–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Dong Z, Liu D, Keesing JK. Jellyfish blooms in China: dominant species, causes and consequences. Mar Pollut Bull. 2010;60(7):954–63.PubMedView ArticleGoogle Scholar
- Simao FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31(19):3210–2.PubMedView ArticleGoogle Scholar
- Gold DA, Katsuki T, Li Y, Yan X, Regulski M, Ibberson D, Holstein T, Steele RE, Jacobs DK, Greenspan RJ. The genome of the jellyfish Aurelia and the evolution of animal complexity. Nat Ecol Evol. 2019;3(1):96–104.PubMedView ArticleGoogle Scholar
- Leclère L, Horin C, Chevalier S, Lapébie P, Dru P, Peron S, Jager M, Condamine T, Pottin K, Romano S, et al. The genome of the jellyfish Clytia hemisphaerica and the evolution of the cnidarian life-cycle. bioRxiv. 2018. https://doi.org/10.1101/369959.
- Chapman JA, Kirkness EF, Simakov O, Hampson SE, Mitros T, Weinmaier T, Rattei T, Balasubramanian PG, Borman J, Busam D, et al. The dynamic genome of Hydra. Nature. 2010;464(7288):592–6.PubMedPubMed CentralView ArticleGoogle Scholar
- Shinzato C, Shoguchi E, Kawashima T, Hamada M, Hisata K, Tanaka M, Fujie M, Fujiwara M, Koyanagi R, Ikuta T. Using the Acropora digitifera genome to understand coral responses to environmental change. Nature. 2011;476(7360):320.PubMedView ArticleGoogle Scholar
- Putnam NH, Srivastava M, Hellsten U, Dirks B, Chapman J, Salamov A, Terry A, Shapiro H, Lindquist E, Kapitonov VV, et al. Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organization. Science. 2007;317(5834):86–94.PubMedView ArticleGoogle Scholar
- Galliot B, Quiquand M, Ghila L, de Rosa R, Miljkovic-Licina M, Chera S. Origins of neurogenesis, a cnidarian view. Dev Biol. 2009;332(1):2–24.PubMedView ArticleGoogle Scholar
- Shen W, Wang D, Ye B, Shi M, Ma L, Zhang Y, Zhao Z. GC3-biased gene domains in mammalian genomes. Bioinformatics. 2015;31(19):3081–4.PubMedPubMed CentralView ArticleGoogle Scholar
- Wan X-F, Xu D, Kleinhofs A, Zhou J. Quantitative relationship between synonymous codon usage bias and GC composition across unicellular genomes. BMC Evol Biol. 2004;4(1):19.PubMedPubMed CentralView ArticleGoogle Scholar
- Tatarinova TV, Alexandrov NN, Bouck JB, Feldmann KA. GC3 biology in corn, rice, sorghum and other grasses. BMC Genomics. 2010;11:308.PubMedPubMed CentralView ArticleGoogle Scholar
- Steinmetz PR, Kraus JE, Larroux C, Hammel JU, Amon-Hassenzahl A, Houliston E, Worheide G, Nickel M, Degnan BM, Technau U. Independent evolution of striated muscles in cnidarians and bilaterians. Nature. 2012;487(7406):231–4.PubMedPubMed CentralView ArticleGoogle Scholar
- Seipel K, Schmid V. Evolution of striated muscle: jellyfish and the origin of triploblasty. Dev Biol. 2005;282(1):14–26.PubMedView ArticleGoogle Scholar
- Cegolon L, Heymann WC, Lange JH, Mastrangelo G. Jellyfish stings and their management: a review. Mar Drugs. 2013;11(2):523–50.PubMedPubMed CentralView ArticleGoogle Scholar
- Leclere L, Rottinger E. Diversity of cnidarian muscles: function, anatomy, development and Regeneration. Front Cell Dev Biol. 2016;4:157.PubMedGoogle Scholar
- Watanabe H, Fujisawa T, Holstein TW. Cnidarians and the evolutionary origin of the nervous system. Develop Growth Differ. 2009;51(3):167–83.View ArticleGoogle Scholar
- Kamm K, Schierwater B, Jakob W, Dellaporta SL, Miller DJ. Axial patterning and diversification in the cnidaria predate the Hox system. Curr Biol. 2006;16(9):920–6.PubMedView ArticleGoogle Scholar
- Chourrout D, Delsuc F, Chourrout P, Edvardsen RB, Rentzsch F, Renfer E, Jensen MF, Zhu B, de Jong P, Steele RE, et al. Minimal ProtoHox cluster inferred from bilaterian and cnidarian Hox complements. Nature. 2006;442(7103):684–7.PubMedView ArticleGoogle Scholar
- Finnerty JR, Pang K, Burton P, Paulson D, Martindale MQ. Origins of bilateral symmetry: Hox and dpp expression in a sea anemone. Science. 2004;304(5675):1335–7.PubMedView ArticleGoogle Scholar
- Kusserow A, Pang K, Sturm C, Hrouda M, Lentfer J, Schmidt HA, Technau U, von Haeseler A, Hobmayer B, Martindale MQ, et al. Unexpected complexity of the Wnt gene family in a sea anemone. Nature. 2005;433(7022):156–60.PubMedView ArticleGoogle Scholar
- Nusse R. An ancient cluster of Wnt paralogues. Trends Genet. 2001;17(8):443.PubMedView ArticleGoogle Scholar
- Han C-H, Uye SI. Combined effects of food supply and temperature on asexual reproduction and somatic growth of polyps of the common jellyfish Aurelia aurita sl. Plankton Benthos Res. 2010;5(3):98–105.View ArticleGoogle Scholar
- Maiorova TD, Kosevich IA, Melekhova OP. On some features of embryonic development and metamorphosis of Aurelia aurita (Cindaria, Scyphozoa). Ontogenez. 2012;43(5):333–49.PubMedGoogle Scholar
- Müller WA, Leitz T. Metamorphosis in the Cnidaria. Can J Zool. 2002;80(10):1755–71.View ArticleGoogle Scholar
- Schmich J, Trepel S, Leitz T. The role of GLWamides in metamorphosis of Hydractinia echinata. Dev Genes Evol. 1998;208(5):267–73.PubMedView ArticleGoogle Scholar
- Fuchs B, Wang W, Graspeuntner S, Li Y, Insua S, Herbst EM, Dirksen P, Bohm AM, Hemmrich G, Sommer F, et al. Regulation of polyp-to-jellyfish transition in Aurelia aurita. Curr Biol. 2014;24(3):263–73.PubMedView ArticleGoogle Scholar
- Cunningham TJ, Duester G. Mechanisms of retinoic acid signalling and its roles in organ and limb development. Nat Rev Mol Cell Biol. 2015;16(2):110–23.PubMedPubMed CentralView ArticleGoogle Scholar
- So EN, Crowe DL. Characterization of a retinoic acid responsive element in the human ets-1 promoter. IUBMB Life. 2000;50(6):365–70.PubMedView ArticleGoogle Scholar
- Lassen S, Helmholz H, Ruhnau C, Prange A. A novel proteinaceous cytotoxin from the northern Scyphozoa Cyanea capillata (L.) with structural homology to cubozoan haemolysins. Toxicon. 2011;57(5):721–9.PubMedView ArticleGoogle Scholar
- Jungo F, Bougueleret L, Xenarios I, Poux S. The UniProtKB/Swiss-Prot Tox-Prot program: a central hub of integrated venom protein data. Toxicon. 2012;60(4):551–7.PubMedPubMed CentralView ArticleGoogle Scholar
- Rawlings ND, Barrett AJ. Evolutionary families of metallopeptidases. Methods Enzymol. 1995;248:183–228.PubMedView ArticleGoogle Scholar
- Li R, Yu H, Xue W, Yue Y, Liu S, Xing R, Li P. Jellyfish venomics and venom gland transcriptomics analysis of Stomolophus meleagris to reveal the toxins associated with sting. J Proteome. 2014;106:17–29.View ArticleGoogle Scholar
- Brinkman DL, Jia X, Potriquet J, Kumar D, Dash D, Kvaskoff D, Mulvenna J. Transcriptome and venom proteome of the box jellyfish Chironex fleckeri. BMC Genomics. 2015;16:407.PubMedPubMed CentralView ArticleGoogle Scholar
- Jouiaei M, Yanagihara AA, Madio B, Nevalainen TJ, Alewood PF, Fry BG. Ancient venom systems: a review on Cnidaria toxins. Toxins (Basel). 2015;7(6):2251–71.View ArticleGoogle Scholar
- Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv. 2013. https://arxiv.org/abs/1303.3997.
- Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.PubMedPubMed CentralView ArticleGoogle Scholar
- Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33(7):1870–4.View ArticleGoogle Scholar
- Chin CS, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, Clum A, Copeland A, Huddleston J, Eichler EE, et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods. 2013;10(6):563–9.PubMedView ArticleGoogle Scholar
- Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano W. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics. 2010;27(4):578–9.PubMedView ArticleGoogle Scholar
- Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, Liu Y, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1(1):18.PubMedPubMed CentralView ArticleGoogle Scholar
- Stanke M, Keller O, Gunduz I, Hayes A, Waack S, Morgenstern B. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res. 2006;34(Web Server issue):W435–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27(2):573.PubMedPubMed CentralView ArticleGoogle Scholar
- Tarailo-Graovac M, Chen N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinformatics. 2009;4:10. 11–14.10. 14PubMedGoogle Scholar
- Domazet-Loso T, Brajkovic J, Tautz D. A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. Trends Genet. 2007;23(11):533–9.PubMedView ArticleGoogle Scholar
- Kumar S, Stecher G, Suleski M, Hedges SB. TimeTree: a resource for timelines, timetrees, and divergence times. Mol Biol Evol. 2017;34(7):1812–9.PubMedView ArticleGoogle Scholar
- Parr CS, Wilson N, Leary P, Schulz KS, Lans K, Walley L, Hammock JA, Goddard A, Rice J, Studer M, et al. The encyclopedia of life v2: providing global access to knowledge about life on earth. Biodivers Data J. 2014;2:e1079.View ArticleGoogle Scholar
- Li L, Stoeckert CJ Jr, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 2003;13(9):2178–89.PubMedPubMed CentralView ArticleGoogle Scholar
- Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics. 2006;22(21):2688–90.PubMedPubMed CentralView ArticleGoogle Scholar
- Han MV, Thomas GW, Lugo-Martinez J, Hahn MW. Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3. Mol Biol Evol. 2013;30(8):1987–97.PubMedView ArticleGoogle Scholar
- Zdobnov EM, Apweiler R. InterProScan--an integration platform for the signature-recognition methods in InterPro. Bioinformatics. 2001;17(9):847–8.PubMedView ArticleGoogle Scholar
- Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8(8):1494–512.PubMedView ArticleGoogle Scholar
- Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012;7(3):562–78.PubMedPubMed CentralView ArticleGoogle Scholar
- Wang L, Feng Z, Wang X, Wang X, Zhang X. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010;26(1):136–8.PubMedView ArticleGoogle Scholar
- DuBuc TQ, Ryan JF, Shinzato C, Satoh N, Martindale MQ. Coral comparative genomics reveal expanded Hox cluster in the cnidarian-bilaterian ancestor. Integr Comp Biol. 2012;52(6):835–41.PubMedPubMed CentralView ArticleGoogle Scholar
- Chiori R, Jager M, Denker E, Wincker P, Da Silva C, Le Guyader H, Manuel M, Queinnec E. Are Hox genes ancestrally involved in axial patterning? Evidence from the hydrozoan Clytia hemisphaerica (Cnidaria). PLoS One. 2009;4(1):e4231.PubMedPubMed CentralView ArticleGoogle Scholar
- Price MN, Dehal PS, Arkin AP. FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5(3):e9490.PubMedPubMed CentralView ArticleGoogle Scholar
- Lengfeld T, Watanabe H, Simakov O, Lindgens D, Gee L, Law L, Schmidt HA, Ozbek S, Bode H, Holstein TW. Multiple Wnts are involved in Hydra organizer formation and regeneration. Dev Biol. 2009;330(1):186–99.PubMedView ArticleGoogle Scholar
- Capella-Gutierrez S, Silla-Martinez JM, Gabaldon T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009;25(15):1972–3.PubMedPubMed CentralView ArticleGoogle Scholar
- Ellegren H, Galtier N. Determinants of genetic diversity. Nat Rev Genet. 2016;17(7):422–33.PubMedView ArticleGoogle Scholar
- Marçais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics. 2011;27(6):764–70.PubMedPubMed CentralView ArticleGoogle Scholar
- Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano W. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics. 2011;27(4):578–9.PubMedView ArticleGoogle Scholar
- Salmela L, Walve R, Rivals E, Ukkonen E. Accurate self-correction of errors in long reads using de Bruijn graphs. Bioinformatics. 2017;33(6):799–806.PubMedGoogle Scholar
- McCoy RC, Taylor RW, Blauwkamp TA, Kelley JL, Kertesz M, Pushkarev D, Petrov DA, Fiston-Lavier AS. Illumina TruSeq synthetic long-reads empower de novo assembly and resolve complex, highly-repetitive transposable elements. PLoS One. 2014;9(9):e106689.PubMedPubMed CentralView ArticleGoogle Scholar
- Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421.PubMedPubMed CentralView ArticleGoogle Scholar
- She R, Chu JS, Wang K, Pei J, Chen N. GenBlastA: enabling BLAST to identify homologous gene sequences. Genome Res. 2009;19(1):143–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Slater GS, Birney E. Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics. 2005;6:31.PubMedPubMed CentralView ArticleGoogle Scholar
- Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–11.PubMedPubMed CentralView ArticleGoogle Scholar
- Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J. Repbase update, a database of eukaryotic repetitive elements. Cytogenet Genome Res. 2005;110(1–4):462–7.PubMedView ArticleGoogle Scholar
- Price AL, Jones NC, Pevzner PA. De novo identification of repeat families in large genomes. Bioinformatics. 2005;21(Suppl 1):i351–8.PubMedView ArticleGoogle Scholar
- Hedges SB, Dudley J, Kumar S. TimeTree: a public knowledge-base of divergence times among organisms. Bioinformatics. 2006;22(23):2971–2.PubMedView ArticleGoogle Scholar
- Demuth JP, De Bie T, Stajich JE, Cristianini N, Hahn MW. The evolution of mammalian gene families. PLoS One. 2006;1:e85.PubMedPubMed CentralView ArticleGoogle Scholar
- Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.PubMedView ArticleGoogle Scholar
- Bond JS, Beynon RJ. The astacin family of metalloendopeptidases. Protein Sci. 1995;4(7):1247–61.PubMedPubMed CentralView ArticleGoogle Scholar
- Bork P, Beckmann G. The CUB domain. A widespread module in developmentally regulated proteins. J Mol Biol. 1993;231(2):539–45.PubMedView ArticleGoogle Scholar
- Rachamim T, Morgenstern D, Aharonovich D, Brekhman V, Lotan T, Sher D. The dynamically evolving nematocyst content of an anthozoan, a scyphozoan, and a hydrozoan. Mol Biol Evol. 2015;32(3):740–53.PubMedView ArticleGoogle Scholar
- Brekhman V, Malik A, Haas B, Sher N, Lotan T. Transcriptome profiling of the dynamic life cycle of the scypohozoan jellyfish Aurelia aurita. BMC Genomics. 2015;16:74.PubMedPubMed CentralView ArticleGoogle Scholar
- Tavaré S. Some probabilistic and statistical problems in the analysis of DNA sequences. Lect Math Life Sci. 1986;17(2):57–86.Google Scholar
- Herbert A, Rich A. RNA processing and the evolution of eukaryotes. Nat Genet. 1999;21(3):265–9.PubMedView ArticleGoogle Scholar
- Seidel U, Bober E, Winter B, Lenz S, Lohse P, Goedde HW, Grzeschik KH, Arnold H. Alkali myosin light chains in man are encoded by a multigene family that includes the adult skeletal muscle, the embryonic or atrial, and nonsarcomeric isoforms. Gene. 1988;66(1):135–46.PubMedView ArticleGoogle Scholar
- Satterlie RA. Do jellyfish have central nervous systems? J Exp Biol. 2011;214(8):1215–23.PubMedView ArticleGoogle Scholar
- Lesh-Laurie GE, Suchy PE. Cnidaria: scyphozoa and cubozoa. Microsc Anat Invertebrates. 1991;2:185–266.Google Scholar
- Nakanishi N, Yuan D, Hartenstein V, Jacobs DK. Evolutionary origin of rhopalia: insights from cellular-level analyses of Otx and POU expression patterns in the developing rhopalial nervous system. Evol Dev. 2010;12(4):404–15.PubMedView ArticleGoogle Scholar
- Mazza ME, Pang K, Martindale MQ, Finnerty JR. Genomic organization, gene structure, and developmental expression of three clustered otx genes in the sea anemone Nematostella vectensis. J Exp Zool B Mol Dev Evol. 2007;308(4):494–506.PubMedView ArticleGoogle Scholar
- Epstein RJ, Lin K, Tan TW. A functional significance for codon third bases. Gene. 2000;245(2):291–8.PubMedView ArticleGoogle Scholar
- Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, Fridman W-H, Pagès F, Trajanoski Z, Galon J. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009;25(8):1091–3.PubMedPubMed CentralView ArticleGoogle Scholar
- Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.PubMedPubMed CentralView ArticleGoogle Scholar
- Campbell NA, Reece JB, Taylor MR, Simon EJ, Dickey J. Biology: concepts & connections, vol. 3: Pearson/Benjamin Cummings; 2009.Google Scholar
- Dillies M-A, Rau A, Aubert J, Hennequet-Antier C, Jeanmougin M, Servant N, Keime C, Marot G, Castel D, Estelle J. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Brief Bioinform. 2013;14(6):671–83.PubMedView ArticleGoogle Scholar
- Holland PW. Evolution of homeobox genes. Wiley Interdiscip Rev Dev Biol. 2013;2(1):31–45.PubMedView ArticleGoogle Scholar
- Park TY, Woo J, Lee DJ, Lee DC, Lee SB, Han Z, Chough SK, Choi DK. A stem-group cnidarian described from the mid-Cambrian of China and its significance for cnidarian evolution. Nat Commun. 2011;2:442.PubMedPubMed CentralView ArticleGoogle Scholar
- Collins AG, Schuchert P, Marques AC, Jankowski T, Medina M, Schierwater B. Medusozoan phylogeny and character evolution clarified by new large and small subunit rDNA data and an assessment of the utility of phylogenetic mixture models. Syst Biol. 2006;55(1):97–115.Google Scholar
- Alonso CR. Hox proteins: sculpting body parts by activating localized cell death. Curr Biol. 2002;12(22):R776–8.PubMedView ArticleGoogle Scholar
- Kuhn K, Streit B, Schierwater B. Isolation of Hox genes from the scyphozoan Cassiopeia xamachana: implications for the early evolution of Hox genes. J Exp Zool. 1999;285(1):63–75.PubMedView ArticleGoogle Scholar
- Komiya Y, Habas R. Wnt signal transduction pathways. Organogenesis. 2008;4(2):68–75.PubMedPubMed CentralView ArticleGoogle Scholar
- Haas B, Papanicolaou A. TransDecoder (find coding regions within transcripts); 2016.Google Scholar
- Duong V, Rochette-Egly C. The molecular physiology of nuclear retinoic acid receptors. From health to disease. Biochim Biophys Acta. 2011;1812(8):1023–31.PubMedView ArticleGoogle Scholar
- Gutierrez-Mazariegos J, Schubert M, Laudet V. Evolution of retinoic acid receptors and retinoic acid signaling. In: The biochemistry of retinoic acid receptors I: Structure, activation, and function at the molecular level. Dordrecht: Springer; 2014. p. 55–73.Google Scholar
- Kostrouch Z, Kostrouchova M, Love W, Jannini E, Piatigorsky J, Rall JE. Retinoic acid X receptor in the diploblast, Tripedalia cystophora. Proc Natl Acad Sci U S A. 1998;95(23):13442–7.PubMedPubMed CentralView ArticleGoogle Scholar
- Chambon P. The nuclear receptor superfamily: a personal retrospect on the first two decades. Mol Endocrinol. 2005;19(6):1418–28.PubMedView ArticleGoogle Scholar
- Rhinn M, Dolle P. Retinoic acid signalling during development. Development. 2012;139(5):843–58.PubMedView ArticleGoogle Scholar
- Lalevee S, Anno YN, Chatagnon A, Samarut E, Poch O, Laudet V, Benoit G, Lecompte O, Rochette-Egly C. Genome-wide in silico identification of new conserved and functional retinoic acid receptor response elements (direct repeats separated by 5 bp). J Biol Chem. 2011;286(38):33322–34.PubMedPubMed CentralView ArticleGoogle Scholar
- Mariottini GL, Pane L. Cytotoxic and cytolytic cnidarian venoms. A review on health implications and possible therapeutic applications. Toxins (Basel). 2013;6(1):108–51.View ArticleGoogle Scholar
- Frazao B, Vasconcelos V, Antunes A. Sea anemone (Cnidaria, Anthozoa, Actiniaria) toxins: an overview. Mar Drugs. 2012;10(8):1812–51.PubMedPubMed CentralView ArticleGoogle Scholar
- Nevalainen TJ, Peuravuori HJ, Quinn RJ, Llewellyn LE, Benzie JA, Fenner PJ, Winkel KD. Phospholipase A2 in cnidaria. Comp Biochem Physiol B Biochem Mol Biol. 2004;139(4):731–5.PubMedView ArticleGoogle Scholar
- Talvinen KA, Nevalainen TJ. Cloning of a novel phospholipase A2 from the cnidarian Adamsia carciniopados. Comp Biochem Physiol B Biochem Mol Biol. 2002;132(3):571–8.PubMedView ArticleGoogle Scholar
- Johnson LS, Eddy SR, Portugaly E. Hidden Markov model speed heuristic and iterative HMM search procedure. BMC Bioinformatics. 2010;11:431.PubMedPubMed CentralView ArticleGoogle Scholar
- Kim H-K, Weber JA, Lee N, Park SG, Cho YS, Bhak Y et al. The genome of the giant Nomura’s jellyfish sheds light on the early evolution of active predation. 2019.. BioProject datasets. Available from: https://www.ncbi.nlm.nih.gov/nuccore/PEDN00000000 Google Scholar
- Kim H-K, Weber JA, Lee N, Park SG, Cho YS, Bhak Y et al. The genome of the giant Nomura’s jellyfish sheds light on the early evolution of active predation. 2019. SRA datasets. Available from: https://www.ncbi.nlm.nih.gov/sra/?term=SRA627560 Google Scholar