Genomics Inform Search

CLOSE


Genomics Inform > Volume 19(3); 2021 > Article
Gim, Baek, Hah, Choo, Kim, and Yoo: Draft genome of Semisulcospira libertina, a species of freshwater snail

Abstract

Semisulcospira libertina, a species of freshwater snail, is widespread in East Asia. It is important as a food source. Additionally, it is a vector of clonorchiasis, paragonimiasis, metagonimiasis, and other parasites. Although S. libertina has ecological, commercial, and clinical importance, its whole-genome has not been reported yet. Here, we revealed the genome of S. libertina through de novo assembly. We assembled the whole-genome of S. libertina and determined its transcriptome for the first time using Illumina NovaSeq 6000 platform. According to the k-mer analysis, the genome size of S. libertina was estimated to be 3.04 Gb. Using RepeatMasker, a total of 53.68% of repeats were identified in the genome assembly. Genome data of S. libertina reported in this study will be useful for identification and conservation of S. libertina in East Asia.

Introduction

As a species of freshwater snail, Semisulcospira libertina is widespread in East Asia and it is an important food source. It is also a vector of clonorchiasis, paragonimiasis, metagonimiasis, and other parasites. It inhabits clean running waters or pools such as drainage ditches, slow flowing rivers, rice paddies, and streams. The phylogeography of S. libertina in Taiwan has been revealed in two studies [1,2] by its mitochondrial cytochrome c oxidase subunit I (COI) sequences. S. libertina belongs to genus Semisulcospira, a well-known group of freshwater snails. S. libertina can be readily identified by its nuclear seqeunce (28S ribosomal RNA) and mitochondrial sequence (16S ribosomal RNA) [3]. In genus Semisulcospira, mitochondrial genomes of S. libertina [4], S. coreana [5], and S. gottsei [6] have been reported. In Gastropoda, mitochondrial genome studies have been performed to classify species until now, as well as genomes were revealed in some species. The genome of Biomphalaria glabrata, a freshwater snail, has been reported [7]. Genomes of owl limpet (Lottia gigantea) [8] and abalones (Haliotis discus hannai) [9] have also been revealed. However, no study has reported whole-genome of Semisulcospira genus. A draft genome of Radix auricularia (big-ear Radix) [10] and a genome of Conus tribblei [11] are cases of genome sequencing in Gastropoda.
S. libertina has ecological, commercial, and clinical importance [12,13], thus whole-genome data of S. libertina could be of great help in many ways. In this study, we sequenced the whole-genome and transcriptome of S. libertina for the first time using Illumina NovaSeq 6000 platform. To enhance the accuracy of gene prediction, we integrated S. libertina transcriptome data with gene set annotation for the assembled genome. Our genomic data could provide basic knowledge for understanding genomic features of S. libertina. They could be used for further comparative, systemic, and functional genomic studies of freshwater snails.

Methods

Sample collection and nucleic acid extraction

Specimens of healthy S. libertina were collected from the upstream of Bukhan River basin, South Korea (37°47'32.3"N, 127°31'49.8"E) in June 2019. Morphometric characteristics such as shell length (20‒30 mm) and weight (5‒6 g) of collected S. libertina samples were determined. The samples were stored in a ‒80°C freezer. Freshest individuals (five for DNA and five for RNA) with the best DNA or RNA quality were studied. Genomic DNAs were extracted from muscle tissues using DNeasy Blood & Tissue Kits (Qiagen, Hilden, Germany). RNAs were extracted using Trizol reagent (Invitrogen, Carlsbad, CA, USA). The quality of RNA was comfirmed based on 28S/18S ratio. RNA integrity number (RIN) of the extracted RNA was determiend using a Tecan F-200 and an Agilent Bioanalyzer 2100 system (Agilent, Santa Clara, CA, USA). All RNAs extracted from samples had RIN values of 6.5‒7.0. One sample with the highest quality among five DNA or RNA samples was used for sequencing.

Sequencing library construction

To construct sequencing library, high molecular weight genomic DNAs were sheared to ~500 bp using a Covaris S2 Ultrasonicator system. All DNA libraries for sequencing were constructed following Illumina’s instruction. To check the quality of the library constructed, the size of the library was detemrined with a 2200 TapeStation (Agilent). Normalized libraries were diluted with hybridization buffer. Clusters of each library were then made with a cBot system and a HiSeq Rapid Duo cBot Sample Loading Kit (Illumina, San Diego, CA, USA). Pair-end libraries were prepared following the manufacturer’s guideline (Illumina). Final library products were sequenced on an Illumina NovaSeq 6000 platform using HiSeq Rapid Paired End Cluster Kit v2 and SBS Kit V2 for 100 PE sequencing (Illumina). Raw fastq sequences are available under BioProject ID PRJNA659426.

Filtering raw sequences for de novo assembly

To maintain quality of sequences, raw reads were filtered to remove the following: (1) reads presented with letter N (ambiguous bases) or poly-A motif; (2) reads with low-quality bases (below base quality 7) from the 549 bp insert size library; (3) reads with adapter contamination; (4) reads with small sizes of inserts in which read 1 and read 2 overlapped for more than 10 bp (only 10% mismatch allowed); (5) PCR duplicates (reads were considered duplicates when read 1 and read 2 of two pair-end reads were identical).

De novo assembly of the S. libertina genome

K-mer size of 17-bp was estimated using SOAPec v2.01, and the best k was 77. The genome size was calculated using the following formula: genome size = total number of k-mer/k-mer depth. The size of the S. libertina genome was estimated to be 3.04 Gb. The genome was then assembled using qualified reads from the pair-end libraries. De novo assembly invovled contig construction followed by scaffolding and gap closure. In the step of contig construction, a short insert library (429 bp) was used to construct a de Brujin graph using SOAPdenovo v2.04 with default parameters [14]. All erroneous data derived from clip tips, bubbles, and connection with low coverage were eliminated. All qualified reads were then realigned with contig sequences. Reads were mapped with bowtie2 v2.2.5 using end-to-end mode and default options. Mapping was perforemd with samtools v1.2.1 and bedtools v2.26. We used benchmarking universal single-copy orthologs software (BUSCO; v2.0) to assess the genome completeness [15].

Identification of repeat sequences

To identify repeat sequences in the genome of S. libertina, the follwoing two approaches were applied: (1) a homology-based approach; and (2) a de novo-based approach. Identification of homology-based repeat sequences was performed with RepeatMasker (v4.0.9) using Repbase libraries (2019, volume 19, issue 1) containing identified repeat sequences [16].
Identification of de novo-based repeat sequences was then finished with RepeatModeler v1.0.8 [16]. Simple sequence repeats (SSRs) were identified using perl script of SSR identification tool (SSRIT; ftp://ftp.gramene.org/pub/gramene/archives/software/scripts/ssr.pl). SSR target primer pairs were designed with flanking sequences of SSR using Primer 3 program (v0.4.0) [17]. These primers met the following criteria: having GC content > 50%, annealing temperature range at 55‒62°C, and primer length of 18‒26 bp in size.

Prediction of noncoding RNAs

From de novo assembled S. libertina genome, four types of noncoding RNA (ncRNA; miRNAs, tRNAs, rRNAs, and snRNAs) were identified by searching databases as follows, tRNAscan-SE with default setting was applied to search for definite tRNA positions [18]. To detect snRNAs and miRNAs, INFERNAL v1.1.1 was used to search for putative sequences with Rfam database (release 9.1) [19]. For rRNA predictions in the S. libertina genome, BLAST (v2.2.29+) homology search was performed [20].

Transcriptome sequencing

For RNA sequencing, cDNA libraries were constructed. mRNA was enriched with oligo-dT attached magnetic beads from total RNA (2 mg). Purified mRNAs were sheared into short fragments and synthesized into double-stranded cDNAs by reverse-transcription immediately. Synthesized cDNAs were subjected to end-repair, poly-A addition, and ligations with adaptors provided by a TruSeqRNA sample prep Kit (Illumina). Modified mRNA fragments were separated on bluepippin 2% agarose gel cassette. Suitable fragments were automatically purified and used as templates for PCR amplification. Final products were 400-500 bp in length and evaluated with an Agilent High Sensitivity DNA Kit (Agilent) on an Agilent Bioanalyzer 2100 system. Subsequently, the constructed libraries were sequenced using an Illumina HiSeq 2500 sequencer (Illumina). All processes were conducted by TheragenETEX Bio Institute (Suwon, Korea).

Gene prediction and annotation

For the annotation of S. libertina genome, a combination of evidence-based gene prediction (RNA-sequencing [RNA-seq] and proteins) and ab initio gene prediction was used. First, transcript alignment was performed with STAR v2.7.0a using a set of gene model annotations [21]. From RNA-seq data, clean reads with average quality scores of higher than Q30 were aligned from all libraries and used for gene prediction using GeneMark-ET v4.29 [22]. Next, homologous proteins of other species were aligned to the genome using TBlastN v2.2.29+ with an E-value cutoff of 1E-5. Aligned protein sequences were used for the prediction of gene regions using Exonerate v2.2.0 with default parameters [20]. A final gene set of S. libertina was produced with AUGUSTUS v3.2.1 using default settings [23]. Gene functions were assigned according to the best alignment attained using BLASTP against UniProt database (Last modified in January 17, 2019), NCBI nr (accecced in June 28, 2019; E-value cutoff of 1E-5), and InterProScan v5.17 [24,25].

Visualization and phylogenetic analysis

For visualization, we used R v3.6.1 and RStudio v1.2.5019 (https://cran.r-project.org/). For heatmap drawing, we used “pheatmap v1.0.10” and “heatmap3 v1.1.6” packages. From whole-mitochondrial genome and COI regions of mitochondrial DNA, the maximum likelihood tree was obtained with a Tamura-Nei model using MEGA-X v10.1.4 [26,27]. Mitochondrial DNA sequences of related species were retrieved from GenBank. Accession numbers were indicated in dendrograms.

Results

De novo assambly of S. libertina

A genomic DNA sample of S. libertina was used to construct short-insert paired end libraries. Paired end sequencing of 429 bp insert libraries generated a total of 60.99 Gb sequence data with an Illumina NovaSeq 6000 platform. Based on k-mer analysis, the genome size of S. libertina was estimated to be 3.04 Gb (3,037,193,258 bp) at a k-mer size of 17. The k-mer frequency distribution had two peaks. This is because the heterozygosity of the S. libertina genome is relatively high [28]. Sequence reads from paired end and mate were assembled, and gaps in scaffolds were subsequently filled with Illumina reads using GapCloser v1.12 [14]. Characteristics of the assembled genome are listed in Supplementary Table 1. The N50 size was 2,788. The total number of contigs was 748,492. Raw sequence data were deposited to NCBI SRA (PRJNA659426). Benchmarking was performed by universal single-copy orthologs software (BUSCO; v2.0) to assess the genome completeness [15]. Our assembly covered 23.0% of core genes, with 225 genes being complete genes (Supplementary Table 2).

Gene prediction and annotation

Gene prediction and structural-annotation were carried out using homology-based search. Determination of gene set was performed using transcriptome data. First, we sought to comprehensively describe ncRNA to build better coding gene models. By homology-based Blast search, a total of 935 rRNA copies were matched with 105,942 bp, accounting for 0.01% of the genome. In addition, 572 tRNA copies were estimated using tRNAscan-SEtool [18]. Using INFERNAL [19], miRNAs with 109,716 copies (9,270,754 bp) and snRNAs with 3,797 copies (426,539 bp) were found.
A total of 61,610 gene models were then predicted. The average length of genes was calculated to be 424 bp. Gene annotation databases were used to annotate gene models, find protein sequence, and search for biological functions of annotated genes. Among 61,610 gene models, 39,949 were annotated genes. A total of 10,065, 19,659, and 37,333 genes were producted hits with UniProt, NCBI nonredundant, and InterProScan databases, respectively (Table 1). Each analysis was performed under default options.

Repeat sequences

Repeat composition of the S. libertina genome was then investigated. We used homology and de novo-based approaches first. We then combined these two approaches. Using RepeatMasker, a total of 53.68% of repeats were identified in the genome. More than half of total repeat length was filled with unclassified repeats, accounting for 34.68% of the genome. DNA transposons accounted for 7.48% of the genome. Most sequences of retrotransposons consisted of long interspersed nuclear elements (9.54%) and long terminal repeat elements (5.58%), whereas short interspersed nuclear elements (0.97%) were present at low proportions (Table 2).
We also discovered features of SSRs to provide clues for polymorphic information of other species of the genus Semisulcospira and molecular markers. In the genome, a total of 35,610 copies of dinucleotide repeats were detected whereas the copy number of each hexa to deca-nucoeotide repeat was <70 (Table 3). On average, a total of 512,774 dinucleotide repeats were detected and 364.97 dinucleotide repeats were detected per million basepairs. Among dinucleotide repeats, CA had the highest frequency (6,494 copies) whereas CG had the lowest frequency (656 copies). Based on these SSR data, we predicted a total of 750,057 primer sets for SSR targets that could be used for polymorphism screening across congener species of S. libertina.

Comparative analysis with related species

Four genomes of similar species, owl limpet, air-breathing freshwater snail, and oyster (owl limpet, Lottia gigantea; air-breathing freshwater snail, Biomphalaria glabrata; oyster, Crassostrea gigas) were compared. Based on PFAM database, we compared the copy number of shell formation related genes in each genome [29,30]. In the heatmap, the number of orthologous genes in each genome was depicted for 25 genes (Table 4, Fig. 1). Shell formation-related genes were retrived from previous studies [29,30]. In these four genomes, the mostly detected gene was indicated by a ‘Top’ row bar. A total of 25 genes used to depict heatmap and phylogenetic tree from four class (MT, metabolic transcripts; PI, protease inhibitors; SF, shell formation; SM, small matrix proteins; and TP, transmembrane proteins) were indicated by a second row bar.
We also provided a table and heatmap presenting the copy number of orthologous genes in each genome (Supplementary Table 3). Fig. 2 provides enriched PFAM domains identified as copy number. In the genome of C. gigas, PFAM domains were overrepresented. In the genome of S. libertina, domain signals from PFAM had weaker patterns than in genomes of other species. Therefore, the genome of S. libertina was distinctively divided into genomes of other three species.
We also provided a maximum likelihood tree for whole-mitochondrial genome (Fig. 3A) and COI regions of mitochondrial DNA (Fig. 3B). The phylogenetic tree shown in Fig. 3 reflects the relationshp of PFAM domains (Fig. 2). Dendrograms were derived from mitochondrial genome sequences obtained from GenBank database. In the phylogenetic tree of the whole-mitochondrial genome, S. coreana and Turritella bacillum were grouped (Fig. 3A). However, for COI regions, S. libertina and S. coreana were grouped as expected (Fig. 3B). As expected, C. gigas and B. glabrata were outgrouped with S. libertina in both analyses (Fig. 3).

Discussion

The genome of S. libertina could provide insights into freshwater shellfish biology such as extraction of useful components and shell body plan. Next-generation sequencing technologies have greatly reduced the cost of whole-genome sequencing. A huge amount of sequencing data have been accumulated and utilized to study substances such as venom and druggable tartgets. However, in comparison with vertebrate genome studies, freshwater snail genome study is still at its infancy. We tried to provide a source for genomics of freshwater snails. Because of its large genome size, we provided a draft genome in this study. Our draft genome has relatively lower sequencing depth (<20×). Therefore, validation steps by other methods such as PCR or targeted sequencing is needed in the future to obtain accurate genetic information. This draft genome could be used for further studies so that biological mechanisms could be elucidated.
Previous studies have shown that genomes of invertebrates have relatively high heterozygosity, and the genome of S. libertina might also show high heterozygosity, like genomes of Dendronephthya gigantea [31] and Ruditapes philippinarum [32]. The genome size of C. tribblei was 2.76 Gb [11], and the genome size R. philippinarum was 2.56 Gb [32]. The genome size of S. libertina was relatively larger than that of other species such as Gastropada class or R. philippinarum. R. auricularia has a relatively small genome size of 910 Mb [10]. Oyster, Crassostrea gigas, has a smaller genome size of 637 Mb [30]. Freshwater snail B. glabrata has a genome size of approximately 916 Mb [7]. The genome size of S. libertina is very large compared to other similar species, and it is similar to that of humans (3.10 Gb). Evolutionary and phylogenetic approaches to large genome sizes will be needed as future studies.
We calculated the copy number of orthologous genes based on PFAM dataset (Supplementary Table 3). The genome of C. gigas had the highest copy number for shell formation related genes. Similar copy number patterns were detected for genomes of S. libertina and B. glabrata. The genome of B. glabrata has different patterns of shell formation proteomes compared to the genome of C. gigas [7]. In the genome of C. gigas, PIs are highly abundant in shells. The copy number of PIs in four genomes had similar patterns in our analysis. In the genome of C. gigas, lectin C-type domain, EF-hand domain pair, and thrombospondin type 1 domain have dramatically higher copy numbers. Lectin C-type‒containing proteins are highly expressed in the digestive gland of C. gigas [30]. The copy number was also highly detected in our genome. Two genes (alkaline phosphatase and tyrosinase) related to shell formation showed the highest copy number in S. libertina among the four species. It means that freshwater snails could have slightly different copy numbers for shellfish metabolism.
Mitochondrial DNA sequences and COI sequences are useful for species identification. This is because each species has specific patterns in their sequences. We obtained two phylogenetic trees from whole mitochondrial and COI sequences. These trees showed slightly different patterns. COI seqeucnes tended to be more accurate evolutionarily and taxonomically than whole mitochondrial sequence. Thus, COI sequences are used to confirm species identification and geological distribution of Semisulcospira genus.
One of the limitations of this study was our assembly with a total length of 1.4 Gb, but the total genome size was 3 Gb. About 46.7% of the assembled sequences are available. If the complete genome is provided through additional sequencing to the sequence provided by us, it is expected to be of great help in genomics studies on Gastropoda species [33]. The sequence information in this study is incomplete, and it will not be easy to profile the genome charasteristics. Based on our study, evolutionary or phylogenetic studies in similar species could be performed by comparing gene family diversity of complete genes.
Here, we identified gene sets of S. libertina predicted with de novo genome assembly data for the first time. These results may provide clues for ecological studies of freshwater environments and immunological studies of secreted materials of S. libertina. Our study may also provide useful information for better understanding of the evolutionary relationship among Gastropoda species.

Notes

Authors’ Contribution

Conceptualization: JIY, HJC, JSK. Data curation: JAG, YSH. Formal analysis: JAG, JSK, KWB. Funding acquisition: JIY, HJC. Methodology: JAG, YSH, JIY. Writing - original draft: JAG, KWB, JIY. Writing - review & editing: JAG, KWB, YSH, HJC, JSK, JIY.

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Acknowledgments

This research was supported by the Ministry of SMEs and Startups' 2018 technology development project to foster regional key industries (grant number: P0002726).

Supplementary Materials

Supplementary data can be found with this article online at http://www.genominfo.org.
Supplementary Table 1.
Summary of genome assembly (k = 77 selected)
gi-21039suppl1.pdf
Supplementary Table 2.
Summary of benchmarking universal single-copy orthologs (BUSCO) analysis (lineage dataset was used as metazoa_odb9; and number of BUSCOs was 978)
gi-21039suppl2.pdf
Supplementary Table 3.
Enriched PFAM domains identified as copy number in four genomes
gi-21039suppl3.pdf

Fig. 1.
Copy number of orthologous shell formation related genes calculated with PFAM in four genomes (air-breathing freshwater snail, Biomphalaria glabrata; oyster, Crassostrea gigas; owl limpet, Lottia gigantea; freshwater snail, Semisulcospira libertina). In these four genomes, genes detected with the highest frequency were indicated with ‘MAX’ row bar. A total of 25 genes were used to depict heatmap and construct phylogenetic tree from five class (MT, metabolic transcripts; PI, protease inhibitors; SF, shell formation; SM, small matrix proteins; TP, transmembrane proteins). They are indicated as the second row bar. Full description of each gene name is shown in Supplementary Table 3.
gi-21039f1.jpg
Fig. 2.
Heatmap presenting copy numbers of orthologous genes in each genome. Each unit was selected if five or more copy numbers were present in the genome (air-breathing freshwater snail, Biomphalaria glabrata; oyster, Crassostrea gigas; owl limpet, Lottia gigantea; freshwater snail, Semisulcospira libertina). In the dendrogram, B. glabrata and L. gigantea were grouped whereas S. libertina was outgrouped.
gi-21039f2.jpg
Fig. 3.
Maximum likelihood tree for whole-mitochondrial genome (A) and cytochrome c oxidase subunit I regions of mitochondrial DNA (B). These dendrograms were derived from mitochondrial genome sequences identified in the GenBank database and sequences obtained from the present study. Values at nodes indicate branch lengths. Branch length is proportional to the distance between taxa.
gi-21039f3.jpg
Table 1.
Results of gene prediction for the genome of Semisulcospira libertina
Parameter Value
Total No. of gene models predicted 61,610
 Annotated gene 39,949
 Uniprot 10,065
 NCBI nonredundant 19,659
 InterProScan 37,333
Average gene length (bp) 424
Average of GC content (%) 53.68
Table 2.
Number, length, and proportion of repetitive elements in the genome of Semisulcospira libertina
Type No. of Elements Length (bp) % in genome
Retrotransposons 1,190,727 224,533,654 15.98
 SINEs 102,400 13,600,944 0.97
 LINEs 784,492 134,091,004 9.54
 LTR elements 303,708 78,375,018 5.58
 Retroposon 127 5,771 0.00
DNA transposons 596,425 105,094,630 7.48
 DNA 507,157 80,734,772 5.75
 RC 89,191 24,777,502 1.76
 Other 77 7,150 0.00
Inserted sequence 9 437 0.00
Segmental duplication 3 134 0.00
Unclassified 3,711,311 487,237,955 34.68
Small RNA 3505 444,780 0.03
Satellites 6767 901,035 0.06
Simple repeats 847777 43,050,705 3.06
Low complexity 79335 4,196,255 0.30
Total 832,215,362 59.23
Table 3.
Summary of simple sequence repeats distribution in the genome of Semisulcospira libertina
Repeat type Frequency Frequency per million
2 512,774 364.97
3 132,734 94.47
4 86,955 61.89
5 14,883 10.59
6 1,590 1.13
7 241 0.17
8 374 0.27
9 259 0.18
10 247 0.18
Table 4.
Shell formation related genes (ID and description were obtained from PFAM; species with the highest copy number in four genomes is indicated the in top column)
ID Description Highest copy number
Shell formation proteins [30]
 PF00245 Alkaline phosphatase S_libertina
 PF00262 Calreticulin B_glabrata and C_gigas
 PF03142 Chitin synthase C_gigas
 PF14704 Dermatopontin C_gigas
 PF00264 Tyrosinase S_libertina
Metabolic transcripts [29]
 PF00067 Cytochrome P450 C_gigas
 PF00151 Lipase L_gigantea
 PF13469 Sulfotransferase family C_gigas
Protease inhibitors [29]
 PF00050 Kazal-type serine protease inhibitor domain C_gigas
 PF07648 Kazal-type serine protease inhibitor domain C_gigas
Small matrix proteins [29]
 PF00057 Low-density lipoprotein receptor domain class A C_gigas
 PF00058 Low-density lipoprotein receptor repeat class B C_gigas
 PF00059 Lectin C-type domain C_gigas
 PF00090 Thrombospondin type 1 domain C_gigas
 PF01607 Chitin binding Peritrophin-A domain C_gigas
 PF02412 Thrombospondin type 3 repeat C_gigas
 PF03067 Chitin binding domain C_gigas
 PF07645 Calcium-binding EGF domain B_glabrata
 PF08976 EF-hand domain C_gigas
 PF13405 EF-hand domain C_gigas
 PF13499 EF-hand domain pair C_gigas
 PF13833 EF-hand domain pair C_gigas
Transmembrane proteins [29]
 PF01146 Caveolin C_gigas
 PF05478 Prominin C_gigas
 PF14878 Death-like domain of SPT6 B_glabrata

References

1. Chiu YW, Bor H, Kuo PH, Hsu KC, Tan MS, Wang WK, et al. Origins of Semisulcospira libertina (gastropoda: semisulcospiridae) in Taiwan. Mitochondrial DNA A DNA Mapp Seq Anal 2017;28:518-525.

2. Hsu KC, Bor H, Lin HD, Kuo PH, Tan MS, Chiu YW. Mitochondrial DNA phylogeography of Semisulcospira libertina (Gastropoda: Cerithioidea: Pleuroceridae): implications the history of landform changes in Taiwan. Mol Biol Rep 2014;41:3733-3743.

3. Lee T, Hong HC, Kim JJ, D OF. Phylogenetic and taxonomic incongruence involving nuclear and mitochondrial markers in Korean populations of the freshwater snail genus Semisulcospira (Cerithioidea: Pleuroceridae). Mol Phylogenet Evol 2007;43:386-397.

4. Zeng T, Yin W, Xia R, Fu C, Jin B. Complete mitochondrial genome of a freshwater snail, Semisulcospira libertina (Cerithioidea: Semisulcospiridae). Mitochondrial DNA 2015;26:897-898.

5. Kim YK, Lee SM. The complete mitochondrial genome of freshwater snail, Semisulcospira coreana (Pleuroceridae: Semisulcospiridae). Mitochondrial DNA B Resour 2018;3:259-260.
crossref pmid
6. Lee SY, Lee HJ, Kim YK. Comparative analysis of complete mitochondrial genomes with Cerithioidea and molecular phylogeny of the freshwater snail, Semisulcospira gottschei (Caenogastropoda, Cerithioidea). Int J Biol Macromol 2019;135:1193-1201.
crossref pmid
7. Adema CM, Hillier LW, Jones CS, Loker ES, Knight M, Minx P, et al. Whole genome analysis of a schistosomiasis-transmitting freshwater snail. Nat Commun 2017;8:15451.
crossref pmid
8. Simakov O, Marletaz F, Cho SJ, Edsinger-Gonzales E, Havlak P, Hellsten U, et al. Insights into bilaterian evolution from three spiralian genomes. Nature 2013;493:526-531.
crossref pmid
9. Nam BH, Kwak W, Kim YO, Kim DG, Kong HJ, Kim WJ, et al. Genome sequence of pacific abalone (Haliotis discus hannai): the first draft genome in family Haliotidae. Gigascience 2017;6:1-8.
crossref pmid pmc
10. Schell T, Feldmeyer B, Schmidt H, Greshake B, Tills O, Truebano M, et al. An annotated draft genome for Radix auricularia (Gastropoda, Mollusca). Genome Biol Evol 2017;9:585-592.
crossref pmid
11. Barghi N, Concepcion GP, Olivera BM, Lluisma AO. Structural features of conopeptide genes inferred from partial sequences of the Conus tribblei genome. Mol Genet Genomics 2016;291:411-422.
pmid pmc
12. Jeon T, Lee YS, Kim HJ. Hepatoprotection by Semisulcospira libertina against acetaminophen-induced hepatic injury in mice. Prev Nurt Food Sci 2003;8:239-244.
crossref pmid
13. Park YJ, Lee MN, Kim EM, Park JY, Noh JK, Choi TJ, et al. Development and characterization of novel polymorphic microsatellite markers for the Korean freshwater snail Semisulcospira coreana and cross-species amplification using next-generation sequencing. J Ocean Limnol 2020;3:503-508.

14. Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 2012;1:18.

15. Simao FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 2015;31:3210-3212.
crossref pmid
16. Smit AF, Hubley R, Green P. RepeatModeler Open-1.0. 2008-2015. Seattle: Institute for Systems Biology, 2015.
pmid pmc
17. Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, et al. Primer3—new capabilities and interfaces. Nucleic Acids Res 2012;40:e115.
crossref pmid
18. Lowe TM, Chan PP. tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res 2016;44:W54-W57.

19. Nawrocki EP, Eddy SR. Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 2013;29:2933-2935.
crossref pmid pmc
20. Altschul SF. BLAST algorithm. In: Encyclopedia of Lifre Sciences Chichester: John Wiley & Sons, Ltd., 2014.
crossref
21. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013;29:15-21.

22. Hoff KJ, Lange S, Lomsadze A, Borodovsky M, Stanke M. BRAKER1: unsupervised RNA-seq-based genome annotation with GeneMark-ET and AUGUSTUS. Bioinformatics 2016;32:767-769.
crossref pmid
23. Stanke M, Morgenstern B. AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res 2005;33:W465-W467.
crossref pmid
24. Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 2014;30:1236-1240.
crossref pmid pmc
25. Mulder NJ, Apweiler R. The InterPro database and tools for protein domain analysis. Curr Protoc Bioinformatics 2008;Chapter 2:Unit 2 7.
crossref
26. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 2018;35:1547-1549.
crossref pmid pmc
27. Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol 1993;10:512-526.
pmid
28. Kajitani R, Toshimoto K, Noguchi H, Toyoda A, Ogura Y, Okuno M, et al. Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads. Genome Res 2014;24:1384-1395.
crossref pmid pmc
29. De Wit P, Durland E, Ventura A, Langdon CJ. Gene expression correlated with delay in shell formation in larval Pacific oysters (Crassostrea gigas) exposed to experimental ocean acidification provides insights into shell formation mechanisms. BMC Genomics 2018;19:160.
pmid pmc
30. Zhang G, Fang X, Guo X, Li L, Luo R, Xu F, et al. The oyster genome reveals stress adaptation and complexity of shell formation. Nature 2012;490:49-54.
crossref pmid
31. Jeon Y, Park SG, Lee N, Weber JA, Kim HS, Hwang SJ, et al. The draft genome of an octocoral, Dendronephthya gigantea. Genome Biol Evol 2019;11:949-953.
pmid pmc
32. Mun S, Kim YJ, Markkandan K, Shin W, Oh S, Woo J, et al. The whole-genome and transcriptome of the Manila clam (Ruditapes philippinarum). Genome Biol Evol 2017;9:1487-1498.
crossref pmid pmc
33. Adachi K, Yoshizumi A, Kuramochi T, Kado R, Okumura SI. Novel insights into the evolution of genome size and AT content in mollusks. Mar Biol 2021;168:25.
crossref
TOOLS
Share :
Facebook Twitter Linked In Google+
METRICS Graph View
  • 0 Crossref
  • 0 Scopus
  • 430 View
  • 11 Download
Related articles in GNI


ABOUT
ARTICLE CATEGORY

Browse all articles >

BROWSE ARTICLES
FOR CONTRIBUTORS
Editorial Office
Room No. 806, 193 Mallijae-ro, Jung-gu, Seoul 04501, Korea
Tel: +82-2-558-9394    Fax: +82-2-558-9434    E-mail: kogo3@kogo.or.kr                

Copyright © 2021 by Korea Genome Organization.

Developed in M2PI

Close layer
prev next