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Transcriptome assembly of Modiolus modiolus and comparative analysis with Bathymodiolus platifrons
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Jie MENG1, 2, 3, 4, Mei YANG5, 6, Fei XU1, 3, 4, Xinzheng LI5, 6, 7, *, Li LI1, 2, 3, 4, *
Acta Oceanologica Sinica | 2018, 37(8) : 38 - 45
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Acta Oceanologica Sinica | 2018, 37(8): 38-45
• Marine Biology •
Transcriptome assembly of Modiolus modiolus and comparative analysis with Bathymodiolus platifrons
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Jie MENG1, 2, 3, 4, Mei YANG5, 6, Fei XU1, 3, 4, Xinzheng LI5, 6, 7, *, Li LI1, 2, 3, 4, *
Affiliations
  • 1 CAS Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences (CAS), Qingdao 266071, China
  • 2 Laboratory for Marine Fisheries and Aquaculture, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China
  • 3 National and Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
  • 4 Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China
  • 5 Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
  • 6 University of Chinese Academy of Sciences, Beijing 100039, China
  • 7 Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China
Published: 2018-08-25 doi: 10.1007/s13131-018-1232-2
Outline
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The genetic basis for bivalves’ adaptation and evolution is not well understood. Even few studies have focused on the mechanism of molluscan molecular evolution between the coastal intertidal zone and deep-sea environment. In our studies, we first conducted the transcritpome assembly of Modiolus modiolus mussels living in coastal intertidal zones. Also, we conducted transcriptome comparison analyses between M. modiolus and Bathymodiolus platifrons living in hydrothermal vents and cold methane/sulfide-hydrocarbon seeps. De novo assemblies of the clean reads yielded a total of 182 476 and 156 261 transcripts with N50 values of 1 769 and 1 545 in M. modiolus and B. platifrons. A total of 27 868 and 23 588 unigenes were identified, which also displayed the similar GO representation patterns. Among the 10 245 pairs of putative orthologs, we identified 26 protein-coding genes under strong positive selection (Ka/Ks>1) and 12 genes showing moderate positive selection (0.5<Ka/Ks<1). Most of those genes are predicted to be involved in stress resistance. Overall, our study first provides the transcriptomic database for M. modiolus. Transcriptome comparison illustrates the genome evolution between M. modiolus and B. platifrons, and provides an important foundation for future studies on these two species.

mollusc  /  transcriptome comparision  /  positive selection  /  stress adaptation
Jie MENG, Mei YANG, Fei XU, Xinzheng LI, Li LI. Transcriptome assembly of Modiolus modiolus and comparative analysis with Bathymodiolus platifrons[J]. Acta Oceanologica Sinica, 2018 , 37 (8) : 38 -45 . DOI: 10.1007/s13131-018-1232-2
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1 Introduction
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Bivalves, which were comprised of 30 000 extant species, are an important component of the ecosystem and biodiversity (Saavedra and Bachere, 2006). They were widely spread from the intertidal coastal areas to hydrothermal vents and cold seeps (Egas et al., 2012; Li et al., 2013). However, the genetic basis for their different adaptations is not well understood (Dame, 2011). Modiolus modiolus is a benthic marine organism, which filter feeds in near-shore habitats. As the important intertidal coastal habitat shellfish, its transcriptome sequence has not been conducted. Bathymodiolus platifrons are phylogenetically close to M. modiolus and belonged to the same family—Mytilidae. Bathymodiolus platifrons is a highly specialized animal inhabiting hydrothermal vent and cold seep ecosystems (Barry et al., 2002) and its genome sequences were also completed. These results have provided good data sets for the further genome comparision analysis. In our study, we first conduct the transcriptome analysis of M. modiolus which provided good data sources for further analysis. Also, we conducted the transcriptome comparision between M. modiolus and B. platifrons living in different environments, which provide valuable information to understand their different environmental adaptation mechanism.
In previous studies of marine invertebrate, the adaptive research has been conducted using single markers or candidate genes (Riesgo et al., 2012). Next-generation sequencing technology enabled analysis of large quantities of sequence data efficiently and cost-effectively (Schuster, 2008; Wang et al., 2009), which provided an efficient way to identify adaptive genes and explain the adaptive evolution process. Recently, marine bivalves’ genomic databases have been obtained, including Crassostrea gigas (Zhang et al., 2012), B. platifrons, M. philippinarum (Sun et al., 2017) and Patinopecten yessoensis (Wang et al., 2017), etc. Most of these publications mainly focused on the responses to multiple stressors including periodic hypoxia, hyposalinity, temperature fluctuations, and pollution. For evolutionary analysis, Zhao et al. (2014) conducted a comparative transcriptome analysis of two oysters, C. gigas and C. hongkongensis, and explained their adaptations and evolutionary mechanisms for dealing with hypo-osmotic conditions (Zhao et al., 2014). Wang et al. (2013) performed the first large-scale transcriptome comparison between the two scallop species, Chlamys farreri and P. yessoensis, and identified fast evolving genes, which played an important role in their speciation and local adaptation (Wang et al., 2013). For the evolutionary mechanisms of molluscans living in coastal intertidal zones and deep sea environments, there are also some studies. For example, Zheng et al. (2017) have conducted transcriptome comparision among B. platifrons, B. manusensis, M. kurilensis and Perna viridis. The results indicated that some immune responsive genes were positively selected and more highly expressed in the deep-sea mussels, which may be related with their endosymbiosis (Wang and Sun, 2017).
In this study, we first performed de novo transcriptome sequencing of M. modiolus using the Illumina sequence platform. Also, according to transcriptome comparison between M. modiolus and B. platifrons, 38 putative fast-evolving genes were identified, which may explain their different evolutionary mechanisms. This is the first time that the transcriptome of M. modiolus has been sequenced and will provide transcriptome resources for this mollusk. Additionally, in comparison with B. platifrons, we may use this transcriptome to find orthologous genes under potential positive selection between two species. This will help us to explain the different mechanisms for adaptation to hydrothermal vent and cold seep ecosystems versus coastal intertidal environments.
2 Materials and methods
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2.1 Sample collection and RNA isolation for Illumina sequencing
Liquid nitrogen-frozen samples B. platifrons were provided by Li Xinzheng from the Institute of Oceanology, Chinese Academy of Science. These were originally sampled from a cold seep located at a depth of 996.9 m (27°47.44′N, 126°53.802 9′E). Modiolus modiolus specimens were collected in Dalian, Liaoning Province, China. These samples were collected and immediately frozen in liquid nitrogen and then transferred and stored at –80°C. For these two species, various tissues (including gills, mantles and adductor muscle) were mixed equally and ground in liquid nitrogen. Total RNA was isolated using Trizol reagent (Invitrogen). RNA purity, concentration, and integrity were checked using a NanoPhotometer® spectrophotometer (IMPLEN, CA, USA), Qubit® RNA Assay Kit (Life Technologies, CA, USA), and Bioanalyzer 2100 system (Agilent Technologies, CA, USA).
2.2 Illumina sequencing
RNA (3 µg) per sample was used for RNA sample preparation. Sequencing libraries were generated using Illumina TruSeqTM RNA Sample Preparation Kit (Illumina, San Diego, USA) and index codes were added to each sample. The mRNA was purified from total RNA and the fragmentation was carried out using divalent cations under elevated temperature. First strand cDNA was synthesized using random oligonucleotides and the second strand cDNA synthesis was performed using DNA Polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities and enzymes were removed. After adenylation of the 3′ ends of DNA fragments, Illumina PE adapter oligonucleotides were ligated to prepare for hybridization. Illumina PCR Primer Cocktail in a 10-cycle PCR was conducted to obtain DNA fragments with ligated adaptor molecules. Products were purified and quantified on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed using TruSeq PE Cluster Kit v3-cBot-HS (Illumina) on a cBot Cluster Generation System. After cluster generation, the library preparations were sequenced.
2.3 Quality control and de novo assembly
Clean data were obtained by removing reads from raw data, containing adapter sequences, or with more than 10% known nucleotides, or with low quality reads (more than 50% base with quality Qphred≤5) using NGS QC toolkit package (Version 2.3). The Q20, Q30, GC-content and sequence duplication level of the clean data were calculated. Transcriptome assembly was accomplished using Trinity software (2.4.2669) and the parameters were set as “seqType=fq, min_contig_length=100, min_kmer_cov=2”, with the rest being default parameter (Grabherr et al., 2011). All the sequences from two transcriptomes were then taken into further process of redundancy removing using CD-HIT-EST v4.6 62 with a sequence identity threshold of 99% in every 1 000 bp.
2.4 Gene functional annotation
Gene function annotation was conducted based on these databases: Pfam (protein family); Nt (NCBI non-redundant nucleotide sequences); Swiss-Prot (amanually annotated and reviewed protein sequence database); KOG/COG (clusters of orthologous groups of proteins); KO (KEGG ortholog database); and GO (gene ontology). Gene expression levels were estimated by RSEM for each sample. Clean data were mapped back onto the assembled transcriptome, and the read count for each gene was obtained (Li and Dewey, 2011). We applied a sensitive HMM scanning method on known Pfam functional protein domains to classify the gene families (Sun et al., 2017). Heatmap analysis was conducted with R script.
2.5 GO and KEGG enrichment analysis
GO enrichment analysis DEGs was implemented by the GOseq R packages based Wallenius non-central hyper-geometric distribution (Young et al., 2010). KOBAS software 2.0 was used for KEGG enrichment analysis (Mao et al., 2005). KEGG is a database resource for understanding high-level functions produced by genome sequencing and other high-throughput experimental technologies (Kanehisa et al., 2008).
2.6 Ka/Ks analysis
We used the BLAST-base (OrthoMCL) method (Li et al., 2003) to identify putative orthologs between the two species. We retained only those ortholog pairs that matched the same proteins to avoid the inclusion of paralogs. The CDSs of orthologous were aligned for further analysis. The ratio of the number of nonsynonymous substitutions per nonsynonymous site (Ka) to the number of synonymous substitutions per synonymous site (Ks) was used to test for positive selection using PAML-CODEML method (Yang, 2007). The rates of Ka to Ks between putatively orthologous coding regions were calculated based on the maximum-likelihood method using KaKs_Calculator 2.0. The orthologs with a Ks rate less than 0.1 were excluded from further analysis.
3 Results and discussion
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3.1 Overall de novo assembly of the transcriptome for M. modiolus and B. platifrons
The cDNA libraries representing the different tissues (gills, mantles, and adductor) of M. modiolus and B. platifrons were constructed and then pooled for sequences. Sequencing of the tissue transcriptomes using the Illumina HiSeq 2000 platform in paired-end mode with a read length of 125 bp resulted in a total of 7.04 Gb and 5.97 Gb clean data in M. modiolus and B. platifrons (Table 1), respectively. After filtration, 46 904 896 and 39 817 358 clean reads were obtained and over 90% and 85% of them exceeded Q20 and Q30, indicating high quality of the sequencing data. De novo assemblies of the clean reads yielded a total of 182 476 and 156 261 transcripts with N50 values of 1 769 and 1 545 in M. modiolus and B. platifrons. ESTscan and BLAST search of the protein databases also resulted in the prediction of 137 763 and 119 880 coding transcripts (Table 1). The raw sequencing data have been submitted to NCBI under accession number SRR5043294. The statistics for the de novo assemblies and functional annotations are displayed in Table 1 and Fig. 1.
Modiolus modiolus has not been sequenced, which may be a bottleneck for further research into its ecology (Dinesen and Morton, 2014). In our study, we sequenced M. modiolus using transcriptome methods and more than two-thirds of the annotated unique sequences were matched to the known species. These results provided abundant sequence information for further studies of M. modiolus. Bathymodiolus platifrons transcriptome has already been published in previous studies (Wong et al., 2015). However, in our study, we obtained more than 1.6-fold numbers of transcripts for the mixture of different tissues used for sequencing, though we did not obtain more annotated transcripts. This may be because of the poor genomics database for marine bivalves. Finally, it should be noted that in hydrothermal vent and cold seep ecosystems, many bacteria are parasitic on B. platifrons (Nakamura-Kusakabe et al., 2016). In order to obtain clean sequences for B. platifrons, we also performed strict raw data quality control to remove contamination by pathogen genomes.
3.2 Functional analysis comparison of dominant transcripts in two species
We constructed functional dominant transcripts according to seven databases. Only 27.12% and 26.20% unique genes in M. modiolus and B. platifrons database were annotated in at least one database. A total of 27 868 and 23 588 transcripts were assigned with at least one GO term (Level 4) for 464 and 538 GO assignments in M. modiolus and B. platifrons (Figs S1 and S2). GO classification at Level 2 is shown in Figs S1 and S2. This wide distribution of GO terms further indicates that the transcripts represent a diverse range of functional classes. The top ten enriched GO terms are shown in Fig. 2a. From GO analysis, we can see that the most enriched GO terms in B. platifrons are related to the metabolism pathway, including the cellular macromolecule metabolic process, organic cyclic compound metabolic process, cellular nitrogen compound metabolic process, and cellular aromatic compound metabolic process. These enriched terms may be directly related with itsmethane/sulfide-hydrocarbon seeps and organic enrichment living environments. The same distribution was also observed in M. modiolus, which may be related with the increasingly polluted coastal environment.
Further, KEGG enrichment analysis was conducted with all annotated sequences. The analysis shows that 9 040 and 8 239 sequences are mapped to 32 metabolic pathways (Hierarchy2) in M. modiolus and B. platifrons (Figs S3 and S4). Among these, cellular processes (B. platifrons 27%, M. modiolus 29%) and metabolic processes (B. platifrons 28%, M. modiolus 28%), had the most unigenes (Fig. 2b). Moreover, in both two species, the “signal transduction pathway” (967 genes in B. platifrons, 1 084 genes in M. modiolus) was most significantly enriched. We propose that these pathways may be developed to deal with complicated environmental pressures (Fig. 2c). However, the “immune system” metabolic pathways varied between the two species, which may be related with their different living environments. Bathymodiolus platifrons is capable of acquiring chemo autotrophic bacteria as its major nutritional food source (Wong et al., 2015). It remains unclear how Bathymodiolus mussels distinguish pathogens from symbionts and how pathogens trigger immune responses (Bettencourt et al., 2007). However, M. modiolus living in coastal areas are exposed to constant challenge by invasive and pathogenic microbes. It has an open circulatory immune system with hemolymph serum containing diverse immune proteins, including soluble lectins, lysosomal enzymes and various antimicrobial peptides (Canesi et al., 2002). Overall, these annotations are useful to identify functional genes and specific biological processes in these two species.
3.3 Identification of putative orthologs and analysis of Ka/Ks
Aassessing the ratio of substitution rates at nonsynonymous and synonymous sites can help to identify genes under positive selection (Vitti et al., 2013). In our results, we searched for orthologs between these two species and found 10 245 putative orthologous genes according to OrthoMCL method (Li et al., 2003). Only 38 protein showed positive selection (dN/dS>0.5). A total of 26 genes (0.12%) had dN/dS>1 suggestive of signs of strong positive selection and 12 (0.079%) genes had 0.5<dN/dS<1 representing signatures of moderate positive selection (Kavembe et al., 2015) (Table 2). When Ka/Ks<0.1, the 8 661 orthologous genes are likely to be experiencing selection constraints.
3.4 Analysis of candidate genes under positive and conserved selection
The two species B. platifrons and M. modiolus have different inhabitations and possess specific adaptations to variable environmental factors between coastal intertidal area and deep sea, such as salinity, temperature, pH, heavy metals, and bacteria (Jones et al., 2006; Duperron et al., 2011). GO analysis was used to analyze the gene categories. The 38 genes were distributed among 15 different GO terms, most of which have physiological functions related to stress response (Fig. 3a). The enrichment GO terms included compound metabolic processes (nitrogen compound metabolic process, cellular aromatic compound metabolic process, and organic substance metabolic process), signal transduction processes (intracellular signal transduction and signal transduction process), and response-to-stimulus processes (pathogenesis and oxidation-reduction process). Bathymodiolus platifrons lives in the deep sea and experiences detrimental chemical pollutions, including heavy metal and methane. As a result, this species may have evolved abilities to adapt to the highly toxic chemical environment. Additionally, B. platifrons is capable of acquiring chemoautotrophic bacteria as its major nutritional food source and were involved in different immune responses (Fujiwara et al., 2000). The enriched GO terms may indicate that the different living environments have driven the evolution of these two species.
The orthologous genes with Ka/Ks<0.1 was considered to be conserved, and 8 661 orthologous pairs were identified between the two species in our results. GO enrichment analysis revealed that 11, 10 and 26 terms were enriched in biological processes, cellular components and molecular function processes, respectively (P-value≤0.05) (Fig. 3b). Among the biological processes, carbohydrate metabolism, catabolism, and biosynthetic processes were enriched. Among the molecular function process, nucleotide binding, ribonucleotide binding, and purine nucleotide binding processes were enriched. Among the cellular components, organelles and membrane bound-organelles were enriched. These metabolic pathways are primary processes in many species. For example, carbohydrate metabolism provides energy in nearly all known organisms, and the purine nucleotide binding process is related to nucleotide metabolism. These conserved metabolic pathways showed relative lower Ka/Ks values, indicating that they are subject to strong selection constraints.
3.5 Immune responsive genes analysis
One of the most extraordinary adaptation trait of Bathymodiolin mussels is their endosymbiosis (Jones et al., 2006). In previous studies, it has been revealed that B. platifrons has expanded and specie-specific immune responsive genes, which was the important genome basis for their adaptation under deep sea environment (Sun et al., 2017). However, for few species to be analyzed, it is still unknown whether this adaptation mechanism is species lineage-specific or is broadly conserved in other species. In our result, we conducted the transcriptome comparison analysis using four species, including two deep sea mussels, B. platifrons and B. manusensis, and two shallow-water mussels, M. kurilensis and M. modiolus. The transcriptome data of B. manusensis and M. kurilensis were obtained from previous studies (Zheng et al., 2017). We mainly focused on immune recognition receptors, which played important roles in initiation the immune responses (Toubiana et al., 2013). All these molecules were found in these four species, which were identified with previous studies (Fig. 4) (Zheng et al., 2017). Heatmap analysis of genes numbers revealed that two deep-sea bathymodiolin mussels and two shallow-water mussels clustered into two branches respectively. This further confirms the different immune systems between deep-sea and shallow water mussels may be related with their different living environments.
4 Conclusions
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Our study represents the first transcriptome profile in M. modiolus. According to comparative transcriptome analysis with B. platifrons, our results provide new insights into the molecular mechanisms underpinning unique adaptations to coastal intertidal environments or deep sea hydrothermal vent and cold seep environments. Selection analysis revealed that strong positive selection in genes is related to stress responses, indicating that the different living environments have driven the evolution of these two species. Our study provides transcriptomic resources for future genetic or genomic studies on M. modiolus and B. platifrons.
Acknowledgements
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The authors thank the scientists and crew of the R/V Kexue for their assistance in specimen collecting.
Data Accessibility
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The transcriptome data were submitted to NCBI database under SRR5043294 (PRJNA353979). All data underlying the findings are fully available without restriction.
Funding
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  • The Strategic Priority Research Program of the Chinese Academy of Sciences under contract No. XDB06010101; the Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology under contract No. 2015ASKJ02-03; Shandong Provincial Natural Science Foundation, China under contract No. ZR2016DQ13; the Earmarked Fund for Modern Agro-industry Technology Research System under contract No. CARS-48; the Taishan Scholars Climbing Program of Shandong; the project funded by China Postdoctoral Science Foundation.
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Appendix
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Year 2018 volume 37 Issue 8
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Article Info
doi: 10.1007/s13131-018-1232-2
  • Receive Date：2017-08-18
  • Online Date：2026-04-14
  • Published：2018-08-25
Article Data
Affiliations
History
  • Received：2017-08-18
  • Accepted：2018-03-13
Funding
The Strategic Priority Research Program of the Chinese Academy of Sciences under contract No. XDB06010101; the Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology under contract No. 2015ASKJ02-03; Shandong Provincial Natural Science Foundation, China under contract No. ZR2016DQ13; the Earmarked Fund for Modern Agro-industry Technology Research System under contract No. CARS-48; the Taishan Scholars Climbing Program of Shandong; the project funded by China Postdoctoral Science Foundation.
Affiliations
    1 CAS Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences (CAS), Qingdao 266071, China
    2 Laboratory for Marine Fisheries and Aquaculture, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China
    3 National and Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
    4 Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China
    5 Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
    6 University of Chinese Academy of Sciences, Beijing 100039, China
    7 Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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