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      RNA-Seq Analysis Using De Novo Transcriptome Assembly as a Reference for the Salmon Louse Caligus rogercresseyi

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          Despite the economic and environmental impacts that sea lice infestations have on salmon farming worldwide, genomic data generated by high-throughput transcriptome sequencing for different developmental stages, sexes, and strains of sea lice is still limited or unknown. In this study, RNA-seq analysis was performed using de novo transcriptome assembly as a reference for evidenced transcriptional changes from six developmental stages of the salmon louse Caligus rogercresseyi. EST-datasets were generated from the nauplius I, nauplius II, copepodid and chalimus stages and from female and male adults using MiSeq Illumina sequencing. A total of 151,788,682 transcripts were yielded, which were assembled into 83,444 high quality contigs and subsequently annotated into roughly 24,000 genes based on known proteins. To identify differential transcription patterns among salmon louse stages, cluster analyses were performed using normalized gene expression values. Herein, four clusters were differentially expressed between nauplius I–II and copepodid stages (604 transcripts), five clusters between copepodid and chalimus stages (2,426 transcripts), and six clusters between female and male adults (2,478 transcripts). Gene ontology analysis revealed that the nauplius I–II, copepodid and chalimus stages are mainly annotated to aminoacid transfer/repair/breakdown, metabolism, molting cycle, and nervous system development. Additionally, genes showing differential transcription in female and male adults were highly related to cytoskeletal and contractile elements, reproduction, cell development, morphogenesis, and transcription-translation processes. The data presented in this study provides the most comprehensive transcriptome resource available for C. rogercresseyi, which should be used for future genomic studies linked to host-parasite interactions.

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          Rapid transcriptome characterization for a nonmodel organism using 454 pyrosequencing.

          We present a de novo assembly of a eukaryote transcriptome using 454 pyrosequencing data. The Glanville fritillary butterfly (Melitaea cinxia; Lepidoptera: Nymphalidae) is a prominent species in population biology but had no previous genomic data. Sequencing runs using two normalized complementary DNA collections from a genetically diverse pool of larvae, pupae, and adults yielded 608,053 expressed sequence tags (mean length = 110 nucleotides), which assembled into 48,354 contigs (sets of overlapping DNA segments) and 59,943 singletons. BLAST comparisons confirmed the accuracy of the sequencing and assembly, and indicated the presence of c. 9000 unique genes, along with > 6000 additional microarray-confirmed unannotated contigs. Average depth of coverage was 6.5-fold for the longest 4800 contigs (348-2849 bp in length), sufficient for detecting large numbers of single nucleotide polymorphisms. Oligonucleotide microarray probes designed from the assembled sequences showed highly repeatable hybridization intensity and revealed biological differences among individuals. We conclude that 454 sequencing, when performed to provide sufficient coverage depth, allows de novo transcriptome assembly and a fast, cost-effective, and reliable method for development of functional genomic tools for nonmodel species. This development narrows the gap between approaches based on model organisms with rich genetic resources vs. species that are most tractable for ecological and evolutionary studies.
            • Record: found
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            RNA-Seq-quantitative measurement of expression through massively parallel RNA-sequencing.

            The ability to quantitatively survey the global behavior of transcriptomes has been a key milestone in the field of systems biology, enabled by the advent of DNA microarrays. While this approach has literally transformed our vision and approach to cellular physiology, microarray technology has always been limited by the requirement to decide, a priori, what regions of the genome to examine. While very high density tiling arrays have reduced this limitation for simpler organisms, it remains an obstacle for larger, more complex, eukaryotic genomes. The recent development of "next-generation" massively parallel sequencing (MPS) technologies by companies such as Roche (454 GS FLX), Illumina (Genome Analyzer II), and ABI (AB SOLiD) has completely transformed the way in which quantitative transcriptomics can be done. These new technologies have reduced both the cost-per-reaction and time required by orders of magnitude, making the use of sequencing a cost-effective option for many experimental approaches. One such method that has recently been developed uses MPS technology to directly survey the RNA content of cells, without requiring any of the traditional cloning associated with EST sequencing. This approach, called "RNA-seq", can generate quantitative expression scores that are comparable to microarrays, with the added benefit that the entire transcriptome is surveyed without the requirement of a priori knowledge of transcribed regions. The important advantage of this technique is that not only can quantitative expression measures be made, but transcript structures including alternatively spliced transcript isoforms, can also be identified. This article discusses the experimental approach for both sample preparation and data analysis for the technique of RNA-seq.
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              RNA-seq: from technology to biology

              Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1 April 2014
                : 9
                : 4
                Laboratory of Biotechnology and Aquatic Genomics, Interdisciplinary Center for Aquaculture Research (INCAR), University of Concepción, Concepción, Chile
                University of North Carolina at Charlotte, United States of America
                Author notes

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

                Conceived and designed the experiments: CGE. Performed the experiments: CGE VVM GNA. Analyzed the data: CGE. Contributed reagents/materials/analysis tools: CGE. Wrote the paper: CGE VVM GNA.


                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.

                Page count
                Pages: 17
                This study was supported by the FONDAP (15110027) project granted by CONICYT-Chile. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Biology and Life Sciences
                Fish Farming
                Computational Biology
                Genome Analysis
                Genomic Databases
                Transcriptome Analysis
                Molecular Biology
                Molecular Biology Techniques
                Sequencing Techniques
                Sequence Analysis
                Sequence Databases
                Fish Biology



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