Abstract
The carnivorous gastropod Rapana venosa (Valenciennes, 1846) is one of the most notorious ecological invaders worldwide. Here, we present the first high-quality chromosome-scale reference R. venosa genome obtained via PacBio sequencing, Illumina paired-end sequencing, and high-throughput chromosome conformation capture scaffolding. The assembled genome has a size of 2.30 Gb, with a scaffold N50 length of 64.63 Mb, and is anchored to 35 chromosomes. It contains 29,649 protein-coding genes, 77.22% of which were functionally annotated. Given its high heterozygosity (1.41%) and large proportion of repeat sequences (57.72%), it is one of the most complex genome assemblies. This chromosome-level genome assembly of R. venosa is an important resource for understanding molluscan evolutionary adaption and provides a genetic basis for its biological invasion control.
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Background & Summary
Caenogastropoda is an extraordinarily large and diverse group containing thousands of described species and comprising ~60% of extant gastropod species1. These snails are extremely diverse in morphology, diet, and habitat and inhabit marine, terrestrial, and freshwater environments in the wild2,3. To date, only two chromosome-level genomes of this clade have been published4,5, which limits our understanding of the internal phylogeny and evolutionary adaption of this important clade.
Rapana venosa (Valenciennes, 1846) is a common marine carnivorous snail in the Caenogastropoda. It is native to the coasts of the Bohai, East, and Yellow Seas in China, the northern Korean peninsula, the far east of Russia, and northern Japan6, and is an economically important species in China7. Via global transport, R. venosa has unintentionally been introduced into the Rio de la Plata between Argentina and Uruguay, Chesapeake Bay, Quiberon Bay in France, and the coastal waters of the Netherlands, as an invasive species8,9,10,11. Its successful establishment in these areas is based on its strong ecological fitness, involving high fecundity, easy dispersal as planktonic larvae, rapid growth rate, early sexual maturity, and broad tolerance to oxygen depletion, salinity, temperature, and water pollution12. In the Chesapeake Bay region, R. venosa has very different prey and predation strategies from the native gastropod, Urosalpinx cinerea, and therefore disrupts the local trophic structure and attenuation of native shellfish resources13. As R. venosa feeds on economically valuable bivalves, such as oysters, mussels, and clams, it has also caused severe economic losses in the Black Sea area14. The economic importance in Asian countries and global ecological invasiveness of this species has led to extensive studies on its developmental mechanism and the genetic basis of its environmental adaptation15,16,17. However, such studies are hampered by the lack of related genomic resources.
In this study, we used short reads generated by an Illumina platform, long reads generated by PacBio sequencing, and high-throughput chromosomal conformation capture (Hi-C) analysis to construct a high-quality R. venosa reference genome at the chromosomal level (Fig. 1). The genome sequences were assembled into 17,949 contigs, with a contig N50 length of 434.10 kb and a total length of 2.30 Gb. Chromosome scaffolding resulted in 5,242 sequences corresponding to 35 chromosomes. The largest 35 chromosome scale scaffolds are in total 2.25 Gb long, which corresponds to 97.88% of the total contig length. Using de novo and homolog-based strategies, 29,649 protein-coding genes were revealed by gene annotation, 77.22% of which were annotated in the publicly available NCBI RefSeq non-redundant protein, KEGG, TrEMBL, Swissprot, and InterPro databases. The R. venosa genome assembly has a high heterozygosity of 1.41% and a large proportion of repeat sequences (57.72%) and, therefore, is one of the most complex genome assemblies. Phylogenetic analysis indicated that R. venosa speciated from the common ancestor of Conus consors approximately 124.4 mya (78.3–177.5 mya).
Characterization of assembled R. venosa genome. From inner to outer layers: photograph of R. venosa, gene abundance, repeat element abundance, GC rate, and chromosome-level scaffolds at scale.
Methods
Sample collection and sequencing
Living specimens of R. venosa were collected from Laizhou Bay, China. We extracted genomic DNA from R. venosa muscle samples using a QIAGEN DNeasy Kit (QIAGEN, Shanghai, China) as per the product manual. We used electrophoresis on a 1% agarose gel to examine the quality of the isolated genomic DNA. To ensure the DNA samples met the sequencing requirements, we used a Qubit instrument to quantify the concentration and 23.2 ng/µL DNA was obtained. Then, the genomic DNA was purified and concentrated by AMpure PB magnetic beads. The processed genomic DNA were further applied to prepare a single-molecule real-time bell sequencing library using the SMRTbell Template Prep Kit 2.0 (Pacific Biosciences, Menlo Park, CA, USA)18. The library was sequenced using the Pacific Biosciences Sequel II in continuous long-read (CLR) mode following the manufacturer’s instructions. As a result, 3 SMRT cells were sequenced, and we obtained a total of 256.49 Gb PacBio reads. The N50 and N90 lengths of the reads were 434.10 kb and 58.92 kb, respectively. Based on the protocol, we constructed the Illumina short-insert (350 bp) library. Paired-end sequencing was performed on the Illumina Novaseq 6000 platform (Illumina, Inc., San Diego, CA, USA) and a total of 153.00 Gb reads were obtained. For the Hi-C sequencing, fresh muscle was fixed in 1% formaldehyde and the fixation was terminated with 0.2 M glycine. In accordance with the protocol19, we prepared the Hi-C library and then sequenced on an Illumina NovaSeq 6000 sequencing platform19.
Genome assembly
R. venosa genome assembly was challenging because of the extremely high percentages of sequence repeats (57.72%) and heterozygosity (1.41%). We tried different genome-assembly strategies and ultimately selected that with the highest continuity and accuracy (Table 1). In total, 256.49 Gb of PacBio long-read data was used for de novo genome assembly using wtdbg v 2.420, which resulted in 17,949 contigs and a contig N50 length of 434.10 Kb. We then used Pilon v 1.2321 to polish the assembled genome with the Illumina short reads from the same individual. Purge Haplotigs software was used to remove redundancy from the assembled genome, obtaining a 2,293.82 Mb long assembly (Table 2). The total gene space was 38.3 Mb and the mean exon number per mRNA was about six. In our previous genome survey analysis, the estimated genome size of R. venosa was 2.20 Gb with 67.04% sequence repeats using a k-mer analysis, quite near to the assembly in this study22. The genome assembly size of R. venosa is substantially larger than those of some closely related mollusc species, such as Crassostrea gigas (557.74 Mb)23, Biomphalaria glabrata (916.38 Mb)24, Pomacea canaliculata (440.07 Mb)25, and Achatina immaculata (1.65 Gb)26, similar to those of Octopus bimaculoides (2.40 Gb)27 and Conus consors (2.05 Gb)5, and smaller than that of Conus bullatus (3.43 Gb)4. Benchmarking Universal Single-Copy Orthologs (BUSCO) v 5.4.628 was used to evaluate the completeness and quality of the R. venosa genome assembly against the metazoa_odb10 database. Of the 978 BUSCO orthologous groups, 886 (90.6%) were identified as complete in the assembled genome (Table 3). This assembly was even better than the recently published genome of another Neogastropoda member, C. bullatus, with a contig N50 length of 171.48 kb and a BUSCO (v 5.4.6) value of 89.8%4. The GC content of the R. Rapana genome assembly is 42.38%.
Chromosomal-level genome scaffolding with Hi-C data
In total, 4991.96 million read pairs raw data were obtained from the Hi-C sequencing. We conducted quality control, sorting, and duplication removal using HiC-Pro v. 2.8.029. Using the Burrows-Wheeler Aligner (v. 0.7.10-r789)30, 63.86% of the clean data were aligned to the draft genome assembly. Here, after using Juicer v1.531,32 and 3D-DNA v17012333 to infer order and orientation, 97.88% of the contigs could be placed into 35 scaffolds (chromosomes), with their lengths ranging from 35.91 Mb to 129.26 Mb (Fig. 1, Table 4). After Hi-C scaffolding, the final Rapana genome assembly had a size of 2,251.40 Mb and a scaffold N50 of 64.63 Mb (Table 2). A chromatin contact matrix was manually curated in Juicebox v1.534 and the 35 scaffolds are clearly distinguishable in the heatmap in Fig. 2; the interaction signal around the diagonal is strongly apparent.
Hi-C assembly of chromosome interactive heat map. Abscissa and ordinate represent order of each bin on corresponding chromosome group. Color block illuminates intensity of interaction from white (low) to red (high).
Repeat sequences and genome annotation
We used ab initio prediction and homology comparison to annotate the repetitive R. venosa genomic elements. For the ab initio repeat annotation, we used RepeatModeler v. 1.0.935, LTR_FINDER v. 1.0.736, and RepeatScout v. 1.0.737 to build a de novo repetitive element database. We used RepeatMasker v. 4.0.738 to annotate the repeat elements in the database. We used RepeatMasker v. 4.0.7 and RepeatProteinMask v 4.0.7 to identify the known repeat element types via searching the Repbase v. 2018102639. In addition, Tandem Repeats Finder (TRF v. 4.09)40 was used to annotate tandem repeats, identifying 1327.65 Mb of repetitive sequences, representing 57.72% of the assembled genome. This proportion is substantially higher than in closely related species, such as Lottia gigantea (10.39%)41, Aplysia californica (21.80%)42, P. canaliculata (11.27%)25, and C. bullatus (38.56%)4. Among the repeat sequences, long interspersed nuclear elements were dominant (911.70 Mb, 39.636% of the assembled genome), and short interspersed nuclear elements were the rarest (6.09 Mb, 0.27%) (Table 5).
Candidate non-coding RNAs were annotated as follows. Ribosomal and transfer RNAs were predicted through BLASTN v. 2.2.2843 and tRNAscan-SE v. 1.444 (www.lowelab.ucsc.edu/tRNAscan-SE/), respectively. We thus annotated 165 rRNA and 3,241 tRNA genes (e-value: 1e–10). We searched against the Rfam database using Infernal v. 1.1.245 (http://infernal.janelia.org/) and identified 76 micro and 103 small nuclear RNAs.
We applied de novo, homolog-based, and transcriptomic strategies to annotate the protein coding genes in the R. venosa genome. For the de novo prediction, Augustus v. 3.2.346, pre-trained using the transcripts assembled from the RNA-seq of R. venosa, was employed to predict the coding regions on the repeat-masked assembly. The optimal parameters were obtained after the model training. For the homology-based prediction, we first downloaded the protein sequences of closely related molluscan species, including L. gigantea, C. consors, P. canaliculata, A. californica, A. immaculata, Elysia chlorotica, B. glabrata, C. gigas, Octopus vulgaris, and Haliotis rubra from the NCBI database. These protein sequences were aligned against the genome assembly using BLAT v. 3547 with an e-value threshold of 1e−5. Then, we used GeneWise v. 2.4.148 to align the matching proteins to the homologous genomic sequences to accurately splice the alignments. For the transcriptomic prediction, Hisat v. 2.0.449 and Stringtie v. 1.2.350 were used for assembly based on the reference transcripts, and TransDecoder v. 5.5.0 (https://i5k.nal.usda.gov/Tigriopus_californicus) was used for gene prediction. Finally, all results were merged to form a consensus gene set using GLEAN51, and 29,649 protein-coding genes were predicted. To functionally annotate the protein-coding genes, we searched public biological functional databases (SwissProt, InterPro, KEGG, and TrEMBL) for their sequences using BLASTX v. 2.2.2843 and BLASTN v. 2.2.2843 with an e-value threshold of 1e−5; 22,894 genes (77.22%) were annotated in at least one public database.
Data Records
The raw Illumina, PacBio, and Hi-C sequencing data are deposited in the NCBI SRA database under the accession numbers SRR2288921452, SRR2351797453, SRR2350145154, SRR2350145255, SRR2350145356, and SRR2350145457, respectively. The genome assembly has been deposited in the NCBI SRA database under the accession number JAQIHA00000000058. The genome annotations are available from the Figshare repository59.
Technical Validation
Evaluating genome assembly and annotation completeness
The assembled R. venosa genome size is 2.30 Gb with a scaffold N50 of 64.63 Mb (Fig. 1), close to the estimated size in previous studies22. Using blobtools v. 1.1.160, we created a blobplot to evaluate possible contamination of the contigs used for genome assembly (Fig. 3). As a result, we determined that 87.26% of the contigs had BLAST hits to mollusca. The remaining 12.74% of the contigs were categorized as follows: 8.03% as cnidaria, 2.49% as chordata, 0.17% as arthropoda, 0.07% as echinodermata, 0.04% as annelida, and 1.97% did not match any taxonomic group. These results suggest that the contigs used for R. venosa genome assembly were not contaminated with microorganisms. For the quality assessment of the genome assembly, an 90.6% completeness of BUSCO was obtained. The protein-coding sequence possessed an 89.1% completeness of BUSCO. These results suggest a high-quality R. venosa genome assembly considering its high heterozygosity and repeat content. The Illumina short reads were mapped to the assembled genome using BWA v. 0.7.10 to evaluate the completeness of the genome assembly30. As shown in the Tables 6, 99.30% of the reads could be mapped, covering 78.51% of the assembled genome (Table 6). The Hi-C heatmap shows a well-organized interaction pattern within the chromosomal region (Fig. 2), and assembly resulted in 35 chromosome-level scaffolds, in line with previously published karyotyping48. Taken together, these confidently confirm the accuracy of the chromosome scaffolding.
Taxon-annotated GC-coverage plot (BlobPlot) of the contigs used for R. venosa genome assembly. Each circle represents a contig sequence, plotted relative to its base coverage and GC proportion. Circle diameter is proportional the size of the contig it represents. Circles are colored according to their assigned taxon at the phylum level (see legend). Histograms show the distribution of the total assembly length along each axis.
Collinearity analysis and phylogenetic analysis
Collinearity analysis of chromosomes between R. venosa and another Caenogastropoda species Lautoconus ventricosus61 was conducted with LASTZ v. 1.02.0062. As shown in Fig. 4, almost 35 chromosome-level scaffolds of R. venosa displayed high homology with the corresponding chromosomes of L. ventricosus, which is suggestive of high quality sequencing and assembly and also make phylogenetic analysis more reliable. For phylogenetic analysis, we conducted pairwise sequence comparisons to predict orthologous genes. First, BLASTP v. 2.2.28 with an e-value cutoff of 1e–7 was used to compare the protein sequences of all species. Then, TreeFam v. 963 was applied to cluster all genes. The species used in the gene family clustering analysis were R. venosa, H. rubra, L. gigantea, C. consors, P. canaliculata, A. californica, A. immaculata, E. chlorotica, B. glabrata, C. gigas, and O. vulgaris.
Genomic synteny between R. venosa and L. ventricosus.
Phylogenetic trees were constructed based on single-copy orthologous gene families. Based on the alignment results of the orthologous protein sequences in MUSCLE v. 5.164, the corresponding coding regions of these protein sequences were selected. We extracted the fourfold degenerate synonymous sites of each alignment and concatenated them to form an individual supergene for each species. We used the supergene alignments to perform a maximum likelihood tree using PhyML v. 2.4.465, Mrbayes v. 3.2.6, and RAxML v. 8.2.1266, respectively. Finally, the tree was visualized using Figtree (Fig. 4a). The phylogenetic tree shows that R. venosa and C. consors cluster into one clade, and the positions of the other clades are consistent with previously findings26. MCMCtree67 in PAML v. 4.4b68, with a correlated molecular clock and HKY85 substitution model, was selected to estimate the divergence times between species. Five calibration nodes were used: C. gigas and O. vulgaris 532–582 mya, H. rubra and P. canaliculata 401–507 mya, L. gigantea and A. californica 401–507 mya, R. venosa and P. canaliculata 155–508 mya, and E. chlorotica and C. consors 334–489 mya. The divergence times of the calibrated nodes were retrieved from the TimeTree website (http://www.timetree.org/). As shown in the phylogenetic tree, the estimated split time between R. venosa and C. consors was approximately 124.4 mya (Fig. 5).
Phylogenetic analysis of R. venosa and 10 other species.
Code availability
No custom code was used in this study. The data analyses used standard bioinformatic tools specified in the methods.
References
Ponder, W. F. & Lindberg, D. R. Towards a phylogeny of gastropod molluscs: an analysis using morphological characters. Zool. J. Linn. Soc. 119, 83–265 (1997).
Colgan, D. J., Ponder, W. F., Beacham, E. & Macaranas, J. Molecular phylogenetics of Caenogastropoda (Gastropoda: Mollusca). Mol. Phylogenet. Evol. 42, 717–737 (2007).
Barco, A. et al. A molecular phylogenetic framework for the Muricidae, a diverse family of carnivorous gastropods. Mol. Phylogenet. Evol. 56, 1025–1039 (2010).
Peng, C. et al. The first Conus genome assembly reveals a primary genetic central dogma of conopeptides in C. betulinus. Cell Discov. 7, 11 (2021).
Brauer, A. et al. The mitochondrial genome of the venomous cone snail Conus consors. PLoS One 7, e51528 (2012).
Mann, R. & Harding, J. M. Salinity tolerance of larval Rapana venosa: implications for dispersal and establishment of an invading predatory gastropod on the North American Atlantic coast. Biol. Bull. 204, 96–103 (2003).
Yang, M.-J. et al. Expression and activity of critical digestive enzymes during early larval development of the veined rapa whelk, Rapana venosa (Valenciennes, 1846). Aquaculture 519, 734722 (2020).
Harding, J. M. & Mann, R. Observations on the biology of the Veined Rapa whelk, Rapana venosa (Valenciennes, 1846) in the Chesapeake Bay. J. Shellfish Res. 18, 9–17 (1999).
Pastorino, G., Penchaszadeh, P. E., Schejter, L. & Bremec, C. Rapana venosa (Valenciennes, 1846) (Mollusca: Muricidae): A new gastropod in South Atlantic waters. J. Shellfish Res. 19, 897–899 (2000).
Harding, J. M. & Mann, R. Veined rapa whelk (Rapana venosa) range extensions in the Virginia waters of Chesapeake Bay, USA. J. Shellfish Res. 24, 381–385 (2005).
Lanfranconi, A., Brugnoli, E. & Muniz, P. Preliminary estimates of consumption rates of Rapana venosa (Gastropoda, Muricidae); a new threat to mollusk biodiversity in the Rio de la Plata. Aquat. Invas. 8, 437–442 (2013).
Mann, R., Harding, J. M. & Westcott, E. Occurrence of imposex and seasonal patterns of gametogenesis in the invading veined rapa whelk Rapana venosa from Chesapeake Bay, USA. Mar. Ecol. Prog. Ser. 310, 129–138 (2006).
Harding, J. M., Kingsley-Smith, P., Savini, D. & Mann, R. Comparison of predation signatures left by Atlantic oyster drills (Urosalpinx cinerea Say, Muricidae) and veined rapa whelks (Rapana venosa Valenciennes, Muricidae) in bivalve prey. J. Exp. Mar. Biol. Ecol. 352, 1–11 (2007).
Savini, D., Castellazzi, M., Favruzzo, M. & Occhipinti-Ambrogi, A. The alien mollusc Rapana venosa (Valenciennes, 1846; Gastropoda, Muricidae) in the northern Adriatic Sea: population structure and shell morphology. Chem. Ecol. 20(sup1), 411–424 (2004).
Shi, P. et al. Molecular response and developmental speculations in metamorphosis of the veined rapa whelk, Rapana venosa. Integr. Zool. 18, 506–517 (2023).
Yang, M. J. et al. Symbiotic microbiome and metabolism profiles reveal the effects of induction by oysters on the metamorphosis of the carnivorous gastropod Rapana venosa. Comput. Struct. Biotechnol. J. 20, 1–14 (2022).
Yang, M. J. et al. Integrated mRNA and miRNA transcriptomic analysis reveals the response of Rapana venosa to the metamorphic inducer (juvenile oysters). Comput. Struct. Biotechnol. J. 21, 702–715 (2023).
Eid, J. et al. Real-time DNA sequencing from single polymerase molecules. Science 323, 133–138 (2009).
Rao, S. S. P. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).
Ruan, J. & Li, H. Fast and accurate long-read assembly with wtdbg2. Nat. Methods 17, 155–158 (2020).
Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9, e112963 (2014).
Song, H. et al. Genome survey on invasive veined rapa whelk (Rapana venosa) and development of microsatellite loci on large scale. J. Genet. 97, e79–e86 (2018).
Zhang, G. et al. The oyster genome reveals stress adaptation and complexity of shell formation. Nature 490, 49–54 (2012).
Bu, L. et al. Compatibility between snails and schistosomes: insights from new genetic resources, comparative genomics, and genetic mapping. Commun. Biol. 5, 940 (2022).
Liu, C. et al. The genome of the golden apple snail Pomacea canaliculata provides insight into stress tolerance and invasive adaptation. GigaScience 7, 9 (2018).
Liu, C. et al. Giant African snail genomes provide insights into molluscan whole-genome duplication and aquatic-terrestrial transition. Mol. Ecol. Resour. 21, 478–494 (2021).
Albertin, C. B. et al. Genome and transcriptome mechanisms driving cephalopod evolution. Nat. Commun. 13, 2427 (2022).
Waterhouse, R. M. et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 35, 543–548 (2018).
Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015).
Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).
Wingett, S. et al. HiCUP: pipeline for mapping and processing Hi-C data. F1000Res 4, 1310–1310 (2015).
Durand, N. C. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3, 95–98 (2016).
Dudchenko, O. et al. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356, 92–95 (2017).
Durand, N. C. et al. Juicebox provides a visualization system for Hi-C contact maps with unlimited zoom. Cell Syst. 3, 99–101 (2016).
Flynn, J. M. et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proc. Natl Acad. Sci. USA 117, 9451–9457 (2020).
Xu, Z. & Wang, H. LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons. Nucleic Acids Res. 35, W265–W268 (2007).
Price, A. L., Jones, N. C. & Pevzner, P. A. De novo identification of repeat families in large genomes. Bioinformatics 21(Supplement 1), i351–i358 (2005).
Chen, N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr. Protoc. Bioinformatics Chapter, Unit 4.10 (2004).
Bao, W., Kojima, K. K. & Kohany, O. Repbase Update, a database of repetitive elements in eukaryotic genomes. Mob. DNA 6, 11 (2015).
Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).
Simakov, O. et al. Insights into bilaterian evolution from three spiralian genomes. Nature 493, 526–531 (2013).
Knudsen, B., Kohn, A. B., Nahir, B., McFadden, C. S. & Moroz, L. L. Complete DNA sequence of the mitochondrial genome of the sea-slug, Aplysia californica: conservation of the gene order in Euthyneura. Mol. Phylogenet. Evol. 38, 459–469 (2006).
Chen, Y., Ye, W., Zhang, Y. & Xu, Y. High speed BLASTn: an accelerated MegaBLAST search tool. Nucleic Acids Res. 43, 7762–7768 (2015).
Lowe, T. M. & Chan, P. P. TRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res. 44, W54–W57 (2016).
Nawrocki, E. P. & Eddy, S. R. Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 29, 2933–2935 (2013).
Stanke, M. et al. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res. 34, W435–W439 (2006).
Kent, W. J. BLAT – The BLAST-like alignment tool. Genome Res. 12, 656–664 (2002).
Doerks, T., Copley, R. R., Schultz, J., Ponting, C. P. & Bork, P. Systematic identification of novel protein domain families associated with nuclear functions. Genome Res. 12, 47–56 (2002).
Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360-U121 (2015).
Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015).
Elsik, C. G. et al. Creating a honey bee consensus gene set. Genome Biol. 8, R13 (2007).
NCBI sequence read archive. https://identifiers.org/ncbi/insdc.sra:SRR22889214 (2022).
NCBI sequence read archive. https://identifiers.org/ncbi/insdc.sra:SRR23517974 (2022).
NCBI sequence read archive. https://identifiers.org/ncbi/insdc.sra:SRR23501451 (2022).
NCBI sequence read archive. https://identifiers.org/ncbi/insdc.sra:SRR23501452 (2022).
NCBI sequence read archive. https://identifiers.org/ncbi/insdc.sra:SRR23501453 (2022).
NCBI sequence read archive. https://identifiers.org/ncbi/insdc.sra:SRR23501454 (2022).
Yang, M., Song, H. & Zhang, T. Rapana venosa breed wild species isolate MY-2022, whole genome shotgun sequencing project. GenBank https://identifiers.org/ncbi/insdc:JAQIHA000000000 (2023).
Song, H. Annotations of Rapana venosa genome. Figshare. https://doi.org/10.6084/m9.figshare.22362598.v1 (2023).
Laetsch, D. R. & Blaxter, M. L. BlobTools: Interrogation of genome assemblies. F1000 Res. 6, 1287 (2017).
Pardos-Blas, J. R. et al. The genome of the venomous snail Lautoconus ventricosus sheds light on the origin of conotoxin diversity. GigaScience 10, giab037 (2021).
Harris, R. S. Improved Pairwise Alignment of Genomic DNA. Ph.D. dissertation, The Pennsylvania State University, Pennsylvania (2017).
Li, H. et al. TreeFam: a curated database of phylogenetic trees of animal gene families. Nucleic Acids Res. 34, D572–D580 (2006).
Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).
Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
Huelsenbeck, J. P. & Ronquist, F. MrBayes: bayesian inference of phylogenetic trees. Bioinformatics 17, 754–755 (2001).
Yang, Z. PAML 4: Phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).
Acknowledgements
This research was supported by the National Natural Science Foundation of China (Grant No. 32002409, 42206086, 31972814, and 32002374), the China Agriculture Research System of MOF and MARA, and the Creative Team Project of the Laboratory for Marine Ecology and Environmental Science, Qingdao National for Marine Science and Technology (Grant No. LMEESCTSP-2018). Hao Song was supported by the Young Elite Scientists Sponsorship Program by CAST (Grant No. 2021QNRC001) and Youth Innovation Promotion Association by CAS. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Oceanographic Data Center, IOCAS for support of data analysis.
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The authors’ contributions to specific working groups are indicated below. H. Song: steering committee, genome sequencing, genome assembly, genome annotation, data processing, statistical analysis, and manuscript writing. T. Zhang: steering committee. M. Yang: sampling, genome sequencing, genome assembly, genome annotation, data processing, statistical analysis, and manuscript writing. Z. Yu: sampling. Z. Hu: sampling. C. Zhou: sampling. P. Hu: sampling. P. Shi: genome sequencing, genome assembly, genome annotation, data processing, and statistical analysis. Z. Li: data processing and statistical analysis, manuscript writing. All authors have read and approved the final manuscript.
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Song, H., Li, Z., Yang, M. et al. Chromosome-level genome assembly of the caenogastropod snail Rapana venosa. Sci Data 10, 539 (2023). https://doi.org/10.1038/s41597-023-02459-7
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DOI: https://doi.org/10.1038/s41597-023-02459-7
