2012
DOI: 10.1016/j.gene.2012.03.053
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Characterization of rainbow trout gonad, brain and gill deep cDNA repertoires using a Roche 454-Titanium sequencing approach

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Cited by 9 publications
(2 citation statements)
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“…With the advent of the next generation sequencing technologies, the gathering of large amounts of sequence data for a given organism at affordable costs is more feasible [12], and high-throughput 454 pyrosequencing has been used to explore the transcriptome of rainbow trout ( Oncorhynchus mykiss ) [13,14], Atlantic cod ( Gadus morhua ) [15] and turbot [16]. In the case of gilthead sea bream, two deep sequencing studies have been reported from whole larval tissues [17] and skeletal muscle [18], yielding 68,289 and 43,461 assembled sequences, respectively.…”
Section: Introductionmentioning
confidence: 99%
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“…With the advent of the next generation sequencing technologies, the gathering of large amounts of sequence data for a given organism at affordable costs is more feasible [12], and high-throughput 454 pyrosequencing has been used to explore the transcriptome of rainbow trout ( Oncorhynchus mykiss ) [13,14], Atlantic cod ( Gadus morhua ) [15] and turbot [16]. In the case of gilthead sea bream, two deep sequencing studies have been reported from whole larval tissues [17] and skeletal muscle [18], yielding 68,289 and 43,461 assembled sequences, respectively.…”
Section: Introductionmentioning
confidence: 99%
“…As the annotation success of a sequencing project is highly dependent on the size of the assembled sequences, approaches conducted to obtain longer sequences become desirable. At this respect, it has been proved in some animal models, including rainbow trout [13,14], that the use of two or more tissues for sequencing and assembly increases the number of annotated genes. On this basis, the primary goal of the present study was to generate a large amount of gilthead sea bream transcriptomic reads from metabolically and immunologically relevant tissues by means of the construction of five 454 pyrosequencing libraries, combining them with Sanger sequences from public repositories and our own published data.…”
Section: Introductionmentioning
confidence: 99%