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.

Kreiss et al. Future Socio-Political Scenarios Aquaculture returns, and marketing options as opposed to the direct effect of climate-driven changes in the environment. These results can inform adaptation planning by the European aquaculture sector. Moreover, applying consistent scenarios including societal and economic dimensions, facilitates regional to global comparisons of adaptation advice both within and across Blue Growth sectors.

In order to improve fish health and reduce use of chemotherapeutants in aquaculture production, the immunomodulatory effect of various nutritional ingredients has been explored. In salmon, there is evidence that functional feeds can reduce the abundance of sea lice. This study aimed to determine if there were consistent changes in the skin mucus proteome that could serve as a biomarker for dietary yeast cell wall extract. The effect of dietary yeast cell wall extract on the skin mucus proteome of Atlantic salmon was examined using two-dimensional gel electrophoresis. Forty-nine spots showed a statistically significant change in their normalised volumes between the control and yeast cell wall diets. Thirteen spots were successfully identified by peptide fragment fingerprinting and LC-MS/MS and these belonged to a variety of functions and pathways. To assess the validity of the results from the proteome approach, the gene expression of a selection of these proteins was studied in skin mRNA from two different independent feeding trials using yeast cell wall extracts. A calreticulin-like protein increased in abundance at both the protein and transcript level in response to dietary yeast cell wall extract. The calreticulin-like protein was identified as a possible biomarker for yeast-derived functional feeds since it showed the most consistent change in expression in both the mucus proteome and skin transcriptome. The discovery of such a biomarker is expected to quicken the pace of research in the application of yeast cell wall extracts.

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Aquaculture, or the farmed production of fish and shellfish, has grown rapidly, from supplying just 7% of fish for human consumption in 1974 to more than half in 2016. This rapid expansion has led to the growth of Precision Aquaculture concept that aims to exploit data-driven management of fish production, thereby improving the farmer's ability to monitor, control, and document biological processes in farms. Fundamental to this paradigm is monitoring of environmental and animal processes within a cage, and processing those data toward farm insight using models and analytics. This paper presents an analysis of environmental and fish behaviour datasets collected at three salmon farms in Norway, Scotland, and Canada. Information on fish behaviour were collected using hydroacoustic sensors that sampled the vertical distribution of fish in a cage at high spatial and temporal resolution, while a network of environmental sensors characterised local site conditions. We present an analysis of the hydroacoustic datasets using AutoML (or automatic machine learning) tools that enables developers with limited data science expertise to train high-quality models specific to the data at hand. We demonstrate how AutoML pipelines can be readily applied to aquaculture datasets to interrogate the data and quantify the primary features that explains data variance. Results demonstrate that variables such as temperature, wind conditions, and hour-of-day were important drivers of fish motion at all sites. Further, there were distinct differences in factors that influenced in-cage variations driven by local variables such as water depth and ambient environmental conditions (particularly dissolved oxygen). The framework offers a transferable approach to interrogate fish behaviour within farm systems, and quantify differences between sites.

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In the present study, it was attempted to quantify sea lice grazing in lumpfish by using a recently published qPCR assay. This method utilizes a small aliquot (10 µL) of the stomach fluid of the lumpfish which can be collected using a sterile, 85 mm long pipette tip. We tested if repetitive sampling of stomach fluid influenced growth and survival in the sampled fish. The test lumpfish were sampled for stomach fluid at 6-16 days intervals for 95 days. No mortalities were recorded during the test period and there were no significant differences in growth compared to the control group. Quantification using the qPCR method was tested by two approaches; one with lumpfish that had grazed on sea lice ad libitum and the other with lumpfish that had been intubated with sea lice. The sea licespecific qPCR assay had an inversely related relationship with the number of eaten lice, especially from stomach samples of lumpfish that naturally fed on sea lice as opposed to intubated fish.