Genetic Variation for climate change resilience in growth of Atlantic salmon

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Genetic variation in growth in atlantic salmon when fed conventional and innovative diets

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Use of DNA pools of a reference population for genomic selection of a binary trait in Atlantic salmon

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Use of DNA pools of a reference population for genomic selection of a binary trait in Atlantic salmon

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Transcriptomic landscape of Atlantic salmon (Salmo salar L.) skin

In this study, we present the first spatial transcriptomic atlas of Atlantic salmon skin using the Visium Spatial Gene Expression protocol. We utilized frozen skin tissue from four distinct sites, namely the operculum, pectoral and caudal fins, and scaly skin at the flank of the fish close to the lateral line, obtained from two Atlantic salmon (150 g). High quality frozen tissue sections were obtained by embedding tissue in O.C.T media prior to freezing and sectioning. Further, we generated libraries and spatial transcriptomic maps, achieving a minimum of 80 million reads per sample with mapping efficiencies ranging from 79.3% to 89.4%. Our analysis revealed the detection of over 80.000 transcripts and nearly 30.000 genes in each sample. Among the tissue types observed in the skin, the epithelial tissues exhibited the highest number of transcripts (UMI-counts), followed by muscle tissue, loose and fibrous connective tissue, and bone. Notably, the widest nodes in the transcriptome network were shared among the epithelial clusters, while dermal tissues showed less consistency, which is likely attributable to the presence of multiple cell types at different body locations. Additionally, we identified collagen type 1 as the most prominent gene family in the skin, while keratins were found to be abundant in the epithelial tissue. Furthermore, we successfully identified gene markers specific to epithelial tissue, bone, and mesenchyme. To validate their expression patterns, we conducted a meta-analysis of the microarray database, which confirmed high expression levels of these markers in mucosal organs, skin, gills, and the olfactory rosette.publishedVersio

Applying genetic technologies to combat infectious diseases in aquaculture

Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies—sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/ parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.publishedVersio

Accuracy of within-family multi-trait genomic selection models in a sib-based aquaculture breeding scheme

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Accuracy of within-family multi-trait genomic selection models in a sib-based aquaculture breeding scheme

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An attempt at predicting blood beta-hydroxybutyrate from Fourier-transform mid-infrared spectra of milk using multivariate mixed models in Polish dairy cattle

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Prediction accuracy of direct and indirect approaches, and their relationships with prediction ability of calibration models

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