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Exploring the Transcriptome of Atlantic Salmon (Salmo salar) Skin, a Major Defense Organ

Overview of attention for article published in Marine Biotechnology, April 2012
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Title
Exploring the Transcriptome of Atlantic Salmon (Salmo salar) Skin, a Major Defense Organ
Published in
Marine Biotechnology, April 2012
DOI 10.1007/s10126-012-9447-2
Pubmed ID
Authors

Giulia Micallef, Ralph Bickerdike, Caroline Reiff, Jorge M. O. Fernandes, Alan S. Bowman, Samuel A. M. Martin

Abstract

The skin of fish is the first line of defense against pathogens and parasites. The skin transcriptome of the Atlantic salmon is poorly characterized, and currently only 2,089 expressed sequence tags (ESTs) out of a total of half a million sequences are generated from skin-derived cDNA libraries. The primary aim of this study was to enhance the transcriptomic knowledge of salmon skin by using next-generation sequencing (NGS) technology, namely the Roche-454 platform. An equimolar mixture of high-quality RNA from skin and epidermal samples of salmon reared in either freshwater or seawater was used for 454-sequencing. This technique yielded over 600,000 reads, which were assembled into 34,696 isotigs using Newbler. Of these isotigs, 12 % had not been sequenced in Atlantic salmon, hence representing previously unreported salmon mRNAs that can potentially be skin-specific. Many full-length genes have been acquired, representing numerous biological processes. Mucin proteins are the main structural component of mucus and we examined in greater detail the sequences we obtained for these genes. Several isotigs exhibited homology to mammalian mucins (MUC2, MUC5AC and MUC5B). Mucin mRNAs are generally >10 kbp and contain large repetitive units, which pose a challenge towards full-length sequence discovery. To date, we have not unearthed any full-length salmon mucin genes with this dataset, but have both N- and C-terminal regions of a mucin type 5. This highlights the fact that, while NGS is indeed a formidable tool for sequence data mining of non-model species, it must be complemented with additional experimental and bioinformatic work to characterize some mRNA sequences with complex features.

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Geographical breakdown

Country Count As %
United States 1 <1%
France 1 <1%
Unknown 119 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 26%
Student > Ph. D. Student 28 23%
Student > Master 13 11%
Student > Doctoral Student 8 7%
Student > Postgraduate 6 5%
Other 22 18%
Unknown 13 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 64 53%
Biochemistry, Genetics and Molecular Biology 19 16%
Environmental Science 5 4%
Engineering 3 2%
Immunology and Microbiology 3 2%
Other 5 4%
Unknown 22 18%