4.7 Article

Characterization of the rainbow trout transcriptome using Sanger and 454-pyrosequencing approaches

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BMC GENOMICS
卷 11, 期 -, 页码 -

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BMC
DOI: 10.1186/1471-2164-11-564

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  1. USDA [2007-35205-17914]
  2. USDA-ARS [58-1930-5-537]

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Background: Rainbow trout are important fish for aquaculture and recreational fisheries and serves as a model species for research investigations associated with carcinogenesis, comparative immunology, toxicology and evolutionary biology. However, to date there is no genome reference sequence to facilitate the development of molecular technologies that utilize high throughput characterizations of gene expression and genetic variation. Alternatively, transcriptome sequencing is a rapid and efficient means for gene discovery and genetic marker development. Although a large number (258,973) of EST sequences are publicly available, the nature of rainbow trout duplicated genome hinders assembly and complicates annotation. Results: High-throughput deep sequencing of the Swanson rainbow trout doubled-haploid transcriptome using 454-pyrosequencing technology yielded similar to 1.3 million reads with an average length of 344 bp, a total of 447 million bases. De novo assembly of the sequences yielded 151,847 Tentative Consensus (TC) sequences (average length of 662 bp) and 224,391 singletons. A combination assembly of both the 454-pyrosequencing ESTs and the preexisting sequences resulted in 161,818 TCs (average length of 758 bp) and 261,071 singletons. Gene Ontology analysis of the combination assembly showed high similarities to transcriptomes of other fish species with known genome sequences. Conclusion: The 454 library significantly increased the suite of ESTs available for rainbow trout, allowing improved assembly and annotation of the transcriptome. Furthermore, the 454 sequencing enables functional genome research in rainbow trout, providing a wealth of sequence data to serve as a reference transcriptome for future studies including identification of paralogous sequences and/or allelic variation, digital gene expression and proteomic research.

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