PMC:3820681 / 15373-34077 JSONTXT

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and Discussion\n\nIllumina sequencing and assembly\nWe performed Illumina GAIIx platform sequencing of a normalized cDNA library prepared from different tissues of multiple C. fluminea individuals to develop a comprehensive understanding of the molecular mechanisms governing C. flumineas genome biology and to obtain as many gene transcripts as possible. Sequencing generated 67,087,130 transcriptomic reads consisting of 6,708,713,000 bp of raw data. From the reads, 62,250,336 high-quality reads and 5,898,595,168 bp (5.9G) of high-quality data (87.92% of raw data) were generated based on the raw data under the standard of Q20 (Q20 is the quality scores of the Illumina sequencing, sequencing error rate \u003c1%). The high-quality data were aligned and de novo assembled using Velvet and Oases into 134,684 unigenes consisting of 106,542,508 bp. Unigenes ranged in size from 100 to 12,367 bp with an average length of 791 bp and N50 length of 1,264 bp (Table 2). Among these unigenes, 65,979 (49.0%) were longer than 500 bp, and 34,248 (25.4%) of this subset were longer than 1,000 bp (Figure 1). The reads were submitted to the Sequence Read Archive (SRA) at NCBI under the accession number SRA062349.\n10.1371/journal.pone.0079516.t002 Table 2 Summary of sequence assembly.\n10.1371/journal.pone.0079516.g001 Figure 1 Assembly length statistic.\nAmong these unigenes, 65,979 (49.0%) were longer than 500 bp, and 34,248 (25.4%) of this subset were longer than 1,000 bp. The Illumina GAIIx method has been successfully used for the de novo assembly of transcriptomes in many species [50-54]. As compared with other recent studies, our results indicated that the Illumina GAIIx platform can provide much more data than the traditional Sanger sequencing method. The average size of the unigenes in our present study were 791 bp larger than those produced in previous studies using Illumina and 454 technologies (e.g., 618 [30], 546 [31], 367 [50], 396 [51], 223 [52] and 474 [53]).\n\nAnnotation of unigenes\nTo provide putative annotations for the assembly, all of the assembled unigenes were evaluated using BLASTx and BLASTn similarity searches against the Nt, Nr, Swiss-Prot, COG and KEGG databases (Table 3 and Table S1). A total of 24,767 unigenes (18.4% of the total) were matched in the Nt databases, and 38,985 unigenes (28.9% of the total) matched in the Nr databases with an E value \u003c1e-5. Additionally, 27,849 unigenes (20.7% of the total) can be matched to the Swiss-Prot databases with an E value \u003c1e-10 (Table 3).\n10.1371/journal.pone.0079516.t003 Table 3 Unigene annotation statistics of the C. fluminea transcriptome. Annotation information could not be assigned for a large percentage of the sequences obtained in this study. The poor annotation efficiency could have been due to the lack of sequences in public databases for species that are phylogenetically closely related to C. fluminea [30]. Only 40 (0.03%) unigenes were matched to C. fluminea. For matches to the Bivalve class in the Nr database, the greatest number of the matched unigenes (0.4%) showed similarities with Ruditapes philippinarum followed by M. galloprovincialis (0.39%), Crassostrea gigas (0.35%), Chlamys farreri (0.21%) and Haliotis discus discus (0.17%). The low number of matches indicates a lack of bivalve data in public databases.\n\nCOG, CO and KEGG classification\nThe Clusters of Orthologous Groups (COGs) of proteins were generated by comparing the protein sequences of complete genomes. Each cluster contains proteins or groups of paralogs from at least three lineages [38]. The current COG database contains both prokaryotic clusters and eukaryotic clusters [39]. We aligned the unigenes to the COG databases to find homologous genes and classify possible functions of the unigenes (Figure 2). A total of 14,035 unigenes (10.4% of the total) had a match in COG database with an E value \u003c1e-10 (Table 3). The possible functions of 11,771 (83.87% of COG matched) unigenes were classified and subdivided into 24 COG categories (Table S2). The largest group was ‘General function prediction only’ (2241, 19.04%), followed by ‘Post-translational modification, protein turnover, chaperones’ (1527, 12.97%) and ‘Translation, ribosomal structure and biogenesis’ (908, 7.71%).\n10.1371/journal.pone.0079516.g002 Figure 2 COG classification of the unigenes.\nPossible functions of 11,771 unigenes were classified and subdivided into 24 COG categories. GO is an international standardized gene functional classification system and covers three domains: cellular component, molecular function and biological process. The InterPro domains were annotated by InterProScan Release 27.0, and functional assignments were mapped onto the GO structures. In total, 20,686 unigenes were matched to a GO annotation (Table 3). We used WEGO to perform the GO classifications and draw the GO tree to facilitate the classification of the C. fluminea transcripts into putative functional groups. In total, 20,286 unigenes were assigned GO terms in 46 functional groups and three categories (Table S3), including 19,167 unigenes at the cellular component level, 25,414 unigenes at the molecular function level and 26,279 unigenes at the biological process level (Figure 3). Within the cellular component category, cell (6,447) and cell part (6,447) were the most highly represented groups. Binding (13,252) and catalytic activity (9,019) were most abundant groups within the molecular function category. A total of 22 GO functional groups were assigned into the biological process category, among which metabolic process (9,021) and cellular process (7,726) were the most highly represented.\n10.1371/journal.pone.0079516.g003 Figure 3 Classification of C. fluminea sequences based on predicted Gene Ontology (GO) terms.\nIn total, 20,286 unigenes were assigned GO terms in 46 functional groups and three categories, including 19,167 unigenes at the cellular component level, 25,414 unigenes at the molecular function level and 26,279 unigenes at the biological process level. Based on comparative analyses using the KEGG database, 32,042 unigenes (23.8% of the total) were found to have a match with an E value \u003c1e-10 using BLASTx (Table 3). We used a Perl script to retrieve KO information from the BLAST result, establish pathway associations between unigenes and the database and then match these 32,042 sequences to 253 different KEGG pathways (Table S4). Of these 32,042 sequences with KEGG annotation, 10,389 were classified into metabolism groups, with most of them involved in amino acid metabolism, carbohydrate metabolism, lipid metabolism and energy metabolism. The greatest number of sequences were classified into the genetic information processing pathways (9,373), followed by human diseases (6,036), cellular processes (4,862) and environmental information processing (3,199).\nOver all, the possible functions of the assembled unigenes were assessed by similarity matches with the COG, CO and KEGG databases. The results of these databases searches help us better understand the biological features of C. fluminea. The patterns of the C. fluminea found in this study were common and similar to other organisms [23,30,31,50].\n\nORF identification and SSR discovery\nThe “getorf” function of EMBOSS software was used to identify the ORFs of the assembled sequences. Of the 134,684 assembled C. fluminea unigene sequences, 105,737 (78.50%) had an ORF longer than 100 bp, with an average length of 445 bp (min length = 102, max length = 11,592, Figure 4).\n10.1371/journal.pone.0079516.g004 Figure 4 ORF lengths of the C. fluminea transriptome. The application of marker-assisted selection (MAS) or genome-wide marker-assisted selection (G-MAS) can be employed in the C. fluminea breeding program. Currently, a limited collection of genetic markers is available for C. fluminea. In this study, simple sequence repeats (SSRs) were identified. The putative and filtered SSRs C. fluminea are shown in Table S5. In total, 2,151 SSRs were identified from the assembled sequences (Table 4). Of 1,547 SSR-containing sequences, 340 SSRs were present in compound form, and 452 sequences contained more than one SSR. The most frequent repeat motifs were tri-nucleotides, which accounted for 57.83% of all SSRs, followed by di-nucleotides (31.38%), tetra-nucleotides (7.53%), penta-nucleotides (3.11%) and hexa-nucleotides (0.14%). These SSRs would be top candidates for marker development and very helpful for further research involving population genetic structuring, relatedness, genetic or genomic studies on this species.\n10.1371/journal.pone.0079516.t004 Table 4 Summary of simple sequence repeat (SSR) types in the C. fluminea transcriptome.\n\nIdentification and validation of putative biomarker transcriptomic sequences\nTo verify the assembly and annotation results and to identify potential environmental pollution biomarkers, 15 related assembled unigenes, including five antioxidase genes (Cu/Zn superoxide dismutase, Cu/Zn SOD), glutathione peroxidase A (GPx-A) and mu glutathione S-transferase (GST-mu), thioredoxin peroxidase 1(TPX1) and thioredoxin peroxidase 2 (TPX2), two cytochrome P450 genes (CYP4 and CYP30), three GABA receptor-related genes (GABA neurotransmitter transporter 1, GABAT1; GABAA receptor-associated protein, GABARAP; and GABAA receptor-associated protein-like 2, GABARAPL2) and five HSP genes (Hsp22, Hsp40, Hsp60, Hsp70 and Hsp90), were selected and subjected to RT-PCR and real-time PCR analyses (Table S6).\nThe antioxidant defense system (including SOD, GPx, GST and TPX) is very effective at reducing damage when oxidative stress has occurred. SOD catalyzes the transformation of superoxide radicals to H2O2 and O2 and represents the initial response to oxyradicals. GPx then catalyzes the reduction of H2O2. GST belongs to a multifunctional family of cytosolic enzymes involved in phase II biotransformation, which plays an important role in protecting tissues from oxidative stress. Eight classes of GST isoenzymes can be distinguished based on their substrate specificity, immunological properties and protein sequences homology [55]. Thioredoxin peroxidase (TPX) is a member of proteins that are conserved from yeast to mammals and to which natural killer enhancing factor belongs. These proteins are antioxidants that function as peroxidases only when coupled to a sulfhydryl reducing system.  Previous studies have suggested that SOD, CAT, Se-GPx and GST-pi transcript levels in Corbicula fluminea could be used as biomarkers of Cu and Cd exposure in aquatic environments [55,56]. The identification of Cu/Zn SOD, GPx-A, GST-mu, TPX1 and TPX2 genes in the present study would allow for the use of C. fluminea antioxidant defense system assays in pollutant monitoring.\nThe cytochrome P450s (CYPs) comprise one of the largest and most versatile protein families in living organisms and are involved in a variety of detoxification and endogenous functions [57,58]. In bivalve mollusks, the CYPs are poorly studied, as there only a few CYP genes with known regulatory mechanisms that have been identified in mussel and oyster, including CYP1-like and CYP3-like genes. The study of CYP1A in C. fluminea showed that this gene was a useful biomarker for exposure to PCBs [59]. The CfCYP4 and CfCYP30 genes were identified based on transcript sequences obtained using specific primers in this present work. The identification of these genes will facilitate an improved understanding of CYPs in bivalves.\nGABARAP, an important protein in the autophagy process, is evolutionarily conserved and is involved in innate immunity in eukaryotic cells. In invertebrates, GABARAP is the major inhibitory neurotransmitter in synapses of both the central and peripheral nervous systems [60]. The GABARAP subfamily consists of GABARAP, GABARAPL1, GABARAPL2 and GABARAPL3. Recently, the GABARAP and related genes have been isolated from several mollusks, such as Lymnaea stagnalis and Haliotis diversicolor [61,62]. However, the actual biological functions of GABARAP remain elusive [62]. In this study, we identified three C. fluminea GABARAPs: GABAT1, GABARAP and GABARAPL2. These results will help us gain a better understanding of the molecular and physiological processes involving GABARAPs in mollusks.\nHSPs are commonly used as biomarkers of exposure to various stressors (such as temperature, metal toxicity, toxic exposure and infection) [63]. These proteins comprise a group of highly conserved, yet highly diversified, proteins that primarily function as molecular chaperones, stabilizing protein folding and preventing indiscriminate protein interactions by sequestering unfolded proteins, which can be found in diverse organisms from bacteria to mammals [64]. The major HSP families are Hsp60, Hsp70, Hsp90 and the small HSPs family (sHsp) [65]. The sHsp family is a heterogeneous group of proteins of intermediate molecular weight (12-43kDa), such as Hsp22 and Hsp40.The Hsp70 protein family is considered to be the major HSP family and has been the most extensively studied. Under adverse environmental conditions, Hsp70 can improve expression levels and takes part in the defense, repair or detoxification machinery of the cell by tightly binding denatured proteins. In bivalve species, many studies have shown that the transcription of Hsp70 is simultaneously and differentially modulated upon exposure to environmental stressors [66,67]. Recent studies reported that Hsp90 can be regulated by a range of stressors such as food deprivation, heavy metal exposure and thermal shock [68-70]. In this study, we sought to identify sequences in the C. fluminea transcriptome that encode Hsp22, Hsp40, Hsp60, Hsp70 and Hsp90. Based on the results of unigenes annotation (BLASTx with the E \u003c1e-5), we identified five putative HSP (22, 40, 60, 70 and 90) sequences corresponding to unigenes loci.\nPartial sequences for all 15 of the aforementioned potential biomarker genes were cloned from adult female C. fluminea digestive gland cDNAs and compared with the assembled sequences using RT-PCR. The products of RT-PCR were analyzed using agarose gel electrophoresis (Figure 5), RT-PCR primers and Sanger sequencing data are shown in Table S6. The consensus sequence data for the selected genes have been deposited with GenBank under the accession numbers shown in Table 1. The sequence variation was minimal (\u003e99% nucleotide identity) and was associated with either the heterogeneity of the C. fluminea colony, which was annually outbred with local conspecifics, or with sequencing errors introduced during Sanger sequencing of the RT-PCR products.\n10.1371/journal.pone.0079516.g005 Figure 5 RT-PCR analyses of the 15 potential C. fluminea genes.\nPCR was performed using the cDNA prepared from adult clams. 1: Cf(Cu/Zn)SOD,234bp;2: CfGPx-A,372bp;3:CfGST-mu,369bp;4:CfTPX1,393bp;5:CfTPX2,273bp;6:CfCYP4,459bp;7:CfCYP30,612bp;8: CfGABAT1,510bp;9:CfGABARAP,276bp;10:CfGABARAPL2,264bp;11:CfHsp22,282bp;12: CfHsp40,672bp;13:CfHsp60,477bp;14:CfHsp70,467bp;15:CfHsp90,570bp.\n\nReal-time Quantitative PCR (RT-qPCR) verification\nAmplification products for the 15 aforementioned potential biomarker genes in the digestive gland of the C. fluminea following 30 days exposure to 0.05, 0.5 and 5 μg/L fluoxetine exposure are shown in Figure 6.\n10.1371/journal.pone.0079516.g006 Figure 6 Real-time qPCR analyses of expression profiles of the 15 functional genes after 30 days fluoxetine exposure.\nExperiments were performed in triplicate and repeated three times with similar results. Bars display mean±S.D. One-way ANOVA (p\u003c0.05) was performed using OriginPro® to test the differences of gene expressions between control and fluoxetine treated clams. For antioxidase genes, the mRNA expression levels of (Cu/Zn) SOD and GPx-A were significantly up-regulated in the 0.5 and 5 μg/L (p\u003c0.05) fluoxetine groups. GST-mu was significantly increased (p\u003c0.05) at 5 μg/L, while TPX1 was only up-regulated (p\u003c0.05) at the 5 μg/L. No significant change was observed in TPX2 (Figure 6), indicating that TPX2 gene is not sensitive to fluoxetine. Previous studies have reported that low concentration of fluoxetine (0.075 μg/L) exposure can affect antioxidant system in M. galloprovincialis [46]. In the present study, 0.5 and 5 μg/L fluoxetine exposure led to significant upregulation of the antioxidase genes (except TPX2) suggesting that the antioxidase genes will be useful biomarkers for exposure to environmental stress. \nCYP4 expression peaked following 5 μg/L fluoxetine exposure with a 4.81-fold increase in transcript levels. CYP30 was significantly (p\u003c0.05) up-regulated at the 0.5 and 5 μg/L by 4.76-fold and 9.24-fold, respectively (Figure 6). As was previously reported, the CYP3-like-2 gene was up-regulated in the digestive gland of M. edulis by PCB126 [58]. Our study found that the gene expressions of CYP4 and CYP30 were up regulated in digestive after fluoxetine exposure. Therefore, further studies are needed to discover the function of CYPs in the C. fluminea.\nIn this study, the C. fluminea GABARAPs genes were significantly up-regulated (p\u003c0.05) with 5 μg/L fluoxetine exposure, while GABARAPL2 was significantly decreased (p\u003c0.05) (Figure 6). Although the actual biological functions of GABARAPs remain elusive [62], the results of our study showed the putative function of GABARAPs in C. fluminea.\nOur present study found that the mRNA transcript for Hsp22, Hsp40, Hsp60 and Hsp90 were significantly increased by 0.5 and 5 μg/L with increases of 2.47-fold and 3.45-fold, 33.93-fold and 67.01-fold, 2.34-fold and 5.83-fold, 4.61-fold and 5.14-fold, respectively. The gene expression of Hsp90 was significantly increased in the 0.05 μg/L (p\u003c0.05) and 5 μg/L (p\u003c0.05) fluoxetine exposure groups. No significant differences were observed in the most of the genes (except Hsp90) at the 0.05 μg/L fluoxetine exposure group (Figure 6). Many previous studies reported that various stressors (such as temperature, metal toxicity and infection) can affect the expression of Hsp70 and Hsp90 [66-70], However, the small Hsps (Hsp22, Hsp40) and Hsp60 have been poorly studied. The present study showed that small Hsps, and Hsp60 were also useful biomarkers when exposure to fluoxetine in C. fluminea.\nOver all, the RT-qPCR results of the 15 selected genes after fluoxetine exposure confirmed that the 15 functional genes are linked to environmental stress. We can use the 15 genes as environmental biomarkers to monitor the environmental pollutants in the future. However, further research is needed to better understand the molecular mechanisms of C. fluminea following the contamination exposure.\n"}

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and Discussion\n\nIllumina sequencing and assembly\nWe performed Illumina GAIIx platform sequencing of a normalized cDNA library prepared from different tissues of multiple C. fluminea individuals to develop a comprehensive understanding of the molecular mechanisms governing C. flumineas genome biology and to obtain as many gene transcripts as possible. Sequencing generated 67,087,130 transcriptomic reads consisting of 6,708,713,000 bp of raw data. From the reads, 62,250,336 high-quality reads and 5,898,595,168 bp (5.9G) of high-quality data (87.92% of raw data) were generated based on the raw data under the standard of Q20 (Q20 is the quality scores of the Illumina sequencing, sequencing error rate \u003c1%). The high-quality data were aligned and de novo assembled using Velvet and Oases into 134,684 unigenes consisting of 106,542,508 bp. Unigenes ranged in size from 100 to 12,367 bp with an average length of 791 bp and N50 length of 1,264 bp (Table 2). Among these unigenes, 65,979 (49.0%) were longer than 500 bp, and 34,248 (25.4%) of this subset were longer than 1,000 bp (Figure 1). The reads were submitted to the Sequence Read Archive (SRA) at NCBI under the accession number SRA062349.\n10.1371/journal.pone.0079516.t002 Table 2 Summary of sequence assembly.\n10.1371/journal.pone.0079516.g001 Figure 1 Assembly length statistic.\nAmong these unigenes, 65,979 (49.0%) were longer than 500 bp, and 34,248 (25.4%) of this subset were longer than 1,000 bp. The Illumina GAIIx method has been successfully used for the de novo assembly of transcriptomes in many species [50-54]. As compared with other recent studies, our results indicated that the Illumina GAIIx platform can provide much more data than the traditional Sanger sequencing method. The average size of the unigenes in our present study were 791 bp larger than those produced in previous studies using Illumina and 454 technologies (e.g., 618 [30], 546 [31], 367 [50], 396 [51], 223 [52] and 474 [53]).\n\nAnnotation of unigenes\nTo provide putative annotations for the assembly, all of the assembled unigenes were evaluated using BLASTx and BLASTn similarity searches against the Nt, Nr, Swiss-Prot, COG and KEGG databases (Table 3 and Table S1). A total of 24,767 unigenes (18.4% of the total) were matched in the Nt databases, and 38,985 unigenes (28.9% of the total) matched in the Nr databases with an E value \u003c1e-5. Additionally, 27,849 unigenes (20.7% of the total) can be matched to the Swiss-Prot databases with an E value \u003c1e-10 (Table 3).\n10.1371/journal.pone.0079516.t003 Table 3 Unigene annotation statistics of the C. fluminea transcriptome. Annotation information could not be assigned for a large percentage of the sequences obtained in this study. The poor annotation efficiency could have been due to the lack of sequences in public databases for species that are phylogenetically closely related to C. fluminea [30]. Only 40 (0.03%) unigenes were matched to C. fluminea. For matches to the Bivalve class in the Nr database, the greatest number of the matched unigenes (0.4%) showed similarities with Ruditapes philippinarum followed by M. galloprovincialis (0.39%), Crassostrea gigas (0.35%), Chlamys farreri (0.21%) and Haliotis discus discus (0.17%). The low number of matches indicates a lack of bivalve data in public databases.\n\nCOG, CO and KEGG classification\nThe Clusters of Orthologous Groups (COGs) of proteins were generated by comparing the protein sequences of complete genomes. Each cluster contains proteins or groups of paralogs from at least three lineages [38]. The current COG database contains both prokaryotic clusters and eukaryotic clusters [39]. We aligned the unigenes to the COG databases to find homologous genes and classify possible functions of the unigenes (Figure 2). A total of 14,035 unigenes (10.4% of the total) had a match in COG database with an E value \u003c1e-10 (Table 3). The possible functions of 11,771 (83.87% of COG matched) unigenes were classified and subdivided into 24 COG categories (Table S2). The largest group was ‘General function prediction only’ (2241, 19.04%), followed by ‘Post-translational modification, protein turnover, chaperones’ (1527, 12.97%) and ‘Translation, ribosomal structure and biogenesis’ (908, 7.71%).\n10.1371/journal.pone.0079516.g002 Figure 2 COG classification of the unigenes.\nPossible functions of 11,771 unigenes were classified and subdivided into 24 COG categories. GO is an international standardized gene functional classification system and covers three domains: cellular component, molecular function and biological process. The InterPro domains were annotated by InterProScan Release 27.0, and functional assignments were mapped onto the GO structures. In total, 20,686 unigenes were matched to a GO annotation (Table 3). We used WEGO to perform the GO classifications and draw the GO tree to facilitate the classification of the C. fluminea transcripts into putative functional groups. In total, 20,286 unigenes were assigned GO terms in 46 functional groups and three categories (Table S3), including 19,167 unigenes at the cellular component level, 25,414 unigenes at the molecular function level and 26,279 unigenes at the biological process level (Figure 3). Within the cellular component category, cell (6,447) and cell part (6,447) were the most highly represented groups. Binding (13,252) and catalytic activity (9,019) were most abundant groups within the molecular function category. A total of 22 GO functional groups were assigned into the biological process category, among which metabolic process (9,021) and cellular process (7,726) were the most highly represented.\n10.1371/journal.pone.0079516.g003 Figure 3 Classification of C. fluminea sequences based on predicted Gene Ontology (GO) terms.\nIn total, 20,286 unigenes were assigned GO terms in 46 functional groups and three categories, including 19,167 unigenes at the cellular component level, 25,414 unigenes at the molecular function level and 26,279 unigenes at the biological process level. Based on comparative analyses using the KEGG database, 32,042 unigenes (23.8% of the total) were found to have a match with an E value \u003c1e-10 using BLASTx (Table 3). We used a Perl script to retrieve KO information from the BLAST result, establish pathway associations between unigenes and the database and then match these 32,042 sequences to 253 different KEGG pathways (Table S4). Of these 32,042 sequences with KEGG annotation, 10,389 were classified into metabolism groups, with most of them involved in amino acid metabolism, carbohydrate metabolism, lipid metabolism and energy metabolism. The greatest number of sequences were classified into the genetic information processing pathways (9,373), followed by human diseases (6,036), cellular processes (4,862) and environmental information processing (3,199).\nOver all, the possible functions of the assembled unigenes were assessed by similarity matches with the COG, CO and KEGG databases. The results of these databases searches help us better understand the biological features of C. fluminea. The patterns of the C. fluminea found in this study were common and similar to other organisms [23,30,31,50].\n\nORF identification and SSR discovery\nThe “getorf” function of EMBOSS software was used to identify the ORFs of the assembled sequences. Of the 134,684 assembled C. fluminea unigene sequences, 105,737 (78.50%) had an ORF longer than 100 bp, with an average length of 445 bp (min length = 102, max length = 11,592, Figure 4).\n10.1371/journal.pone.0079516.g004 Figure 4 ORF lengths of the C. fluminea transriptome. The application of marker-assisted selection (MAS) or genome-wide marker-assisted selection (G-MAS) can be employed in the C. fluminea breeding program. Currently, a limited collection of genetic markers is available for C. fluminea. In this study, simple sequence repeats (SSRs) were identified. The putative and filtered SSRs C. fluminea are shown in Table S5. In total, 2,151 SSRs were identified from the assembled sequences (Table 4). Of 1,547 SSR-containing sequences, 340 SSRs were present in compound form, and 452 sequences contained more than one SSR. The most frequent repeat motifs were tri-nucleotides, which accounted for 57.83% of all SSRs, followed by di-nucleotides (31.38%), tetra-nucleotides (7.53%), penta-nucleotides (3.11%) and hexa-nucleotides (0.14%). These SSRs would be top candidates for marker development and very helpful for further research involving population genetic structuring, relatedness, genetic or genomic studies on this species.\n10.1371/journal.pone.0079516.t004 Table 4 Summary of simple sequence repeat (SSR) types in the C. fluminea transcriptome.\n\nIdentification and validation of putative biomarker transcriptomic sequences\nTo verify the assembly and annotation results and to identify potential environmental pollution biomarkers, 15 related assembled unigenes, including five antioxidase genes (Cu/Zn superoxide dismutase, Cu/Zn SOD), glutathione peroxidase A (GPx-A) and mu glutathione S-transferase (GST-mu), thioredoxin peroxidase 1(TPX1) and thioredoxin peroxidase 2 (TPX2), two cytochrome P450 genes (CYP4 and CYP30), three GABA receptor-related genes (GABA neurotransmitter transporter 1, GABAT1; GABAA receptor-associated protein, GABARAP; and GABAA receptor-associated protein-like 2, GABARAPL2) and five HSP genes (Hsp22, Hsp40, Hsp60, Hsp70 and Hsp90), were selected and subjected to RT-PCR and real-time PCR analyses (Table S6).\nThe antioxidant defense system (including SOD, GPx, GST and TPX) is very effective at reducing damage when oxidative stress has occurred. SOD catalyzes the transformation of superoxide radicals to H2O2 and O2 and represents the initial response to oxyradicals. GPx then catalyzes the reduction of H2O2. GST belongs to a multifunctional family of cytosolic enzymes involved in phase II biotransformation, which plays an important role in protecting tissues from oxidative stress. Eight classes of GST isoenzymes can be distinguished based on their substrate specificity, immunological properties and protein sequences homology [55]. Thioredoxin peroxidase (TPX) is a member of proteins that are conserved from yeast to mammals and to which natural killer enhancing factor belongs. These proteins are antioxidants that function as peroxidases only when coupled to a sulfhydryl reducing system.  Previous studies have suggested that SOD, CAT, Se-GPx and GST-pi transcript levels in Corbicula fluminea could be used as biomarkers of Cu and Cd exposure in aquatic environments [55,56]. The identification of Cu/Zn SOD, GPx-A, GST-mu, TPX1 and TPX2 genes in the present study would allow for the use of C. fluminea antioxidant defense system assays in pollutant monitoring.\nThe cytochrome P450s (CYPs) comprise one of the largest and most versatile protein families in living organisms and are involved in a variety of detoxification and endogenous functions [57,58]. In bivalve mollusks, the CYPs are poorly studied, as there only a few CYP genes with known regulatory mechanisms that have been identified in mussel and oyster, including CYP1-like and CYP3-like genes. The study of CYP1A in C. fluminea showed that this gene was a useful biomarker for exposure to PCBs [59]. The CfCYP4 and CfCYP30 genes were identified based on transcript sequences obtained using specific primers in this present work. The identification of these genes will facilitate an improved understanding of CYPs in bivalves.\nGABARAP, an important protein in the autophagy process, is evolutionarily conserved and is involved in innate immunity in eukaryotic cells. In invertebrates, GABARAP is the major inhibitory neurotransmitter in synapses of both the central and peripheral nervous systems [60]. The GABARAP subfamily consists of GABARAP, GABARAPL1, GABARAPL2 and GABARAPL3. Recently, the GABARAP and related genes have been isolated from several mollusks, such as Lymnaea stagnalis and Haliotis diversicolor [61,62]. However, the actual biological functions of GABARAP remain elusive [62]. In this study, we identified three C. fluminea GABARAPs: GABAT1, GABARAP and GABARAPL2. These results will help us gain a better understanding of the molecular and physiological processes involving GABARAPs in mollusks.\nHSPs are commonly used as biomarkers of exposure to various stressors (such as temperature, metal toxicity, toxic exposure and infection) [63]. These proteins comprise a group of highly conserved, yet highly diversified, proteins that primarily function as molecular chaperones, stabilizing protein folding and preventing indiscriminate protein interactions by sequestering unfolded proteins, which can be found in diverse organisms from bacteria to mammals [64]. The major HSP families are Hsp60, Hsp70, Hsp90 and the small HSPs family (sHsp) [65]. The sHsp family is a heterogeneous group of proteins of intermediate molecular weight (12-43kDa), such as Hsp22 and Hsp40.The Hsp70 protein family is considered to be the major HSP family and has been the most extensively studied. Under adverse environmental conditions, Hsp70 can improve expression levels and takes part in the defense, repair or detoxification machinery of the cell by tightly binding denatured proteins. In bivalve species, many studies have shown that the transcription of Hsp70 is simultaneously and differentially modulated upon exposure to environmental stressors [66,67]. Recent studies reported that Hsp90 can be regulated by a range of stressors such as food deprivation, heavy metal exposure and thermal shock [68-70]. In this study, we sought to identify sequences in the C. fluminea transcriptome that encode Hsp22, Hsp40, Hsp60, Hsp70 and Hsp90. Based on the results of unigenes annotation (BLASTx with the E \u003c1e-5), we identified five putative HSP (22, 40, 60, 70 and 90) sequences corresponding to unigenes loci.\nPartial sequences for all 15 of the aforementioned potential biomarker genes were cloned from adult female C. fluminea digestive gland cDNAs and compared with the assembled sequences using RT-PCR. The products of RT-PCR were analyzed using agarose gel electrophoresis (Figure 5), RT-PCR primers and Sanger sequencing data are shown in Table S6. The consensus sequence data for the selected genes have been deposited with GenBank under the accession numbers shown in Table 1. The sequence variation was minimal (\u003e99% nucleotide identity) and was associated with either the heterogeneity of the C. fluminea colony, which was annually outbred with local conspecifics, or with sequencing errors introduced during Sanger sequencing of the RT-PCR products.\n10.1371/journal.pone.0079516.g005 Figure 5 RT-PCR analyses of the 15 potential C. fluminea genes.\nPCR was performed using the cDNA prepared from adult clams. 1: Cf(Cu/Zn)SOD,234bp;2: CfGPx-A,372bp;3:CfGST-mu,369bp;4:CfTPX1,393bp;5:CfTPX2,273bp;6:CfCYP4,459bp;7:CfCYP30,612bp;8: CfGABAT1,510bp;9:CfGABARAP,276bp;10:CfGABARAPL2,264bp;11:CfHsp22,282bp;12: CfHsp40,672bp;13:CfHsp60,477bp;14:CfHsp70,467bp;15:CfHsp90,570bp.\n\nReal-time Quantitative PCR (RT-qPCR) verification\nAmplification products for the 15 aforementioned potential biomarker genes in the digestive gland of the C. fluminea following 30 days exposure to 0.05, 0.5 and 5 μg/L fluoxetine exposure are shown in Figure 6.\n10.1371/journal.pone.0079516.g006 Figure 6 Real-time qPCR analyses of expression profiles of the 15 functional genes after 30 days fluoxetine exposure.\nExperiments were performed in triplicate and repeated three times with similar results. Bars display mean±S.D. One-way ANOVA (p\u003c0.05) was performed using OriginPro® to test the differences of gene expressions between control and fluoxetine treated clams. For antioxidase genes, the mRNA expression levels of (Cu/Zn) SOD and GPx-A were significantly up-regulated in the 0.5 and 5 μg/L (p\u003c0.05) fluoxetine groups. GST-mu was significantly increased (p\u003c0.05) at 5 μg/L, while TPX1 was only up-regulated (p\u003c0.05) at the 5 μg/L. No significant change was observed in TPX2 (Figure 6), indicating that TPX2 gene is not sensitive to fluoxetine. Previous studies have reported that low concentration of fluoxetine (0.075 μg/L) exposure can affect antioxidant system in M. galloprovincialis [46]. In the present study, 0.5 and 5 μg/L fluoxetine exposure led to significant upregulation of the antioxidase genes (except TPX2) suggesting that the antioxidase genes will be useful biomarkers for exposure to environmental stress. \nCYP4 expression peaked following 5 μg/L fluoxetine exposure with a 4.81-fold increase in transcript levels. CYP30 was significantly (p\u003c0.05) up-regulated at the 0.5 and 5 μg/L by 4.76-fold and 9.24-fold, respectively (Figure 6). As was previously reported, the CYP3-like-2 gene was up-regulated in the digestive gland of M. edulis by PCB126 [58]. Our study found that the gene expressions of CYP4 and CYP30 were up regulated in digestive after fluoxetine exposure. Therefore, further studies are needed to discover the function of CYPs in the C. fluminea.\nIn this study, the C. fluminea GABARAPs genes were significantly up-regulated (p\u003c0.05) with 5 μg/L fluoxetine exposure, while GABARAPL2 was significantly decreased (p\u003c0.05) (Figure 6). Although the actual biological functions of GABARAPs remain elusive [62], the results of our study showed the putative function of GABARAPs in C. fluminea.\nOur present study found that the mRNA transcript for Hsp22, Hsp40, Hsp60 and Hsp90 were significantly increased by 0.5 and 5 μg/L with increases of 2.47-fold and 3.45-fold, 33.93-fold and 67.01-fold, 2.34-fold and 5.83-fold, 4.61-fold and 5.14-fold, respectively. The gene expression of Hsp90 was significantly increased in the 0.05 μg/L (p\u003c0.05) and 5 μg/L (p\u003c0.05) fluoxetine exposure groups. No significant differences were observed in the most of the genes (except Hsp90) at the 0.05 μg/L fluoxetine exposure group (Figure 6). Many previous studies reported that various stressors (such as temperature, metal toxicity and infection) can affect the expression of Hsp70 and Hsp90 [66-70], However, the small Hsps (Hsp22, Hsp40) and Hsp60 have been poorly studied. The present study showed that small Hsps, and Hsp60 were also useful biomarkers when exposure to fluoxetine in C. fluminea.\nOver all, the RT-qPCR results of the 15 selected genes after fluoxetine exposure confirmed that the 15 functional genes are linked to environmental stress. We can use the 15 genes as environmental biomarkers to monitor the environmental pollutants in the future. However, further research is needed to better understand the molecular mechanisms of C. fluminea following the contamination exposure.\n"}