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      Sequencing, De Novo Assembly, and Annotation of the Transcriptome of the Endangered Freshwater Pearl Bivalve, Cristaria plicata, Provides Novel Insights into Functional Genes and Marker Discovery

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          Abstract

          Background

          The freshwater mussel Cristaria plicata (Bivalvia: Eulamellibranchia: Unionidae), is an economically important species in molluscan aquaculture due to its use in pearl farming. The species have been listed as endangered in South Korea due to the loss of natural habitats caused by anthropogenic activities. The decreasing population and a lack of genomic information on the species is concerning for environmentalists and conservationists. In this study, we conducted a de novo transcriptome sequencing and annotation analysis of C. plicata using Illumina HiSeq 2500 next-generation sequencing (NGS) technology, the Trinity assembler, and bioinformatics databases to prepare a sustainable resource for the identification of candidate genes involved in immunity, defense, and reproduction.

          Results

          The C. plicata transcriptome analysis included a total of 286,152,584 raw reads and 281,322,837 clean reads. The de novo assembly identified a total of 453,931 contigs and 374,794 non-redundant unigenes with average lengths of 731.2 and 737.1 bp, respectively. Furthermore, 100% coverage of C. plicata mitochondrial genes within two unigenes supported the quality of the assembler. In total, 84,274 unigenes showed homology to entries in at least one database, and 23,246 unigenes were allocated to one or more Gene Ontology (GO) terms. The most prominent GO biological process, cellular component, and molecular function categories (level 2) were cellular process, membrane, and binding, respectively. A total of 4,776 unigenes were mapped to 123 biological pathways in the KEGG database. Based on the GO terms and KEGG annotation, the unigenes were suggested to be involved in immunity, stress responses, sex-determination, and reproduction. A total of 17,251 cDNA simple sequence repeats (cSSRs) were identified from 61,141 unigenes (size of >1 kb) with the most abundant being dinucleotide repeats.

          Conclusions

          This dataset represents the first transcriptome analysis of the endangered mollusc, C. plicata. The transcriptome provides a comprehensive sequence resource for the conservation of genetic information in this species and enrichment of the genetic database. The development of molecular markers will assist in the genetic improvement of C. plicata.

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          Most cited references76

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          Heat-shock proteins, molecular chaperones, and the stress response: evolutionary and ecological physiology.

          Molecular chaperones, including the heat-shock proteins (Hsps), are a ubiquitous feature of cells in which these proteins cope with stress-induced denaturation of other proteins. Hsps have received the most attention in model organisms undergoing experimental stress in the laboratory, and the function of Hsps at the molecular and cellular level is becoming well understood in this context. A complementary focus is now emerging on the Hsps of both model and nonmodel organisms undergoing stress in nature, on the roles of Hsps in the stress physiology of whole multicellular eukaryotes and the tissues and organs they comprise, and on the ecological and evolutionary correlates of variation in Hsps and the genes that encode them. This focus discloses that (a) expression of Hsps can occur in nature, (b) all species have hsp genes but they vary in the patterns of their expression, (c) Hsp expression can be correlated with resistance to stress, and (d) species' thresholds for Hsp expression are correlated with levels of stress that they naturally undergo. These conclusions are now well established and may require little additional confirmation; many significant questions remain unanswered concerning both the mechanisms of Hsp-mediated stress tolerance at the organismal level and the evolutionary mechanisms that have diversified the hsp genes.
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            TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

            TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.
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              De novo assembly and analysis of RNA-seq data.

              We describe Trans-ABySS, a de novo short-read transcriptome assembly and analysis pipeline that addresses variation in local read densities by assembling read substrings with varying stringencies and then merging the resulting contigs before analysis. Analyzing 7.4 gigabases of 50-base-pair paired-end Illumina reads from an adult mouse liver poly(A) RNA library, we identified known, new and alternative structures in expressed transcripts, and achieved high sensitivity and specificity relative to reference-based assembly methods.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 February 2016
                2016
                : 11
                : 2
                : e0148622
                Affiliations
                [1 ]Department of Life Science and Biotechnology, College of Natural Sciences, Soonchunhyang University, 22 Soonchunhyangro, Shinchang-myeon, Asan, Chungchungnam-do, 336-745, Republic of Korea
                [2 ]National Institute of Biological Resources, Incheon, 404-170, Republic of Korea
                [3 ]Institute of Environmental Research, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon-si, Gangwon-do, 200-701, Republic of Korea
                [4 ]College of Agriculture and Life Science, Chonnam National University, 300 Yongbong-Dong, Buk-gu, Gwangju, 500-757, Republic of Korea
                [5 ]Research Institute, GnC BIO Co., LTD., 621-6 Banseok-dong, Yuseong-gu, Daejeon, 305-150, Republic of Korea
                [6 ]Trident School of Biotech Sciences, Trident Academy of Creative Technology (TACT), Bhubaneswar- 751024, Odisha, India
                CNRS UMR7622 & University Paris 6 Pierre-et-Marie-Curie, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: YSL BBP THW SK. Performed the experiments: SYP EBP JMC DKS. Analyzed the data: SWK HJH. Contributed reagents/materials/analysis tools: CK JSL YSH HSP. Wrote the paper: BBP THW SWK. Led and supervised the study: YSL.

                Article
                PONE-D-15-39795
                10.1371/journal.pone.0148622
                4752248
                26872384
                3285dcfc-cd98-4dc6-8453-7d439229dc73
                © 2016 Patnaik et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 September 2015
                : 20 January 2016
                Page count
                Figures: 9, Tables: 5, Pages: 28
                Funding
                This work was supported by the grant entitled "The Genetic and Genomic Evaluation of Indigenous Biological Resources" funded by the National Institute of Biological Resources (NIBR201503202).
                Categories
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                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Domains
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                Research and Analysis Methods
                Molecular Biology Techniques
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                Biology and Life Sciences
                Computational Biology
                Genome Analysis
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                Biology and Life Sciences
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                Molluscs
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                Biology and Life Sciences
                Cell Biology
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                All relevant data are within the paper and its Supporting Information files.

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