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Salmon farmed on modern feeds contains less of the healthy, long-chain fatty acids (EPA and DHA) than before. Up until the turn of the millennium, farmed salmon were fed fish oil as a replacement for their omega-3 rich natural prey. However, fish oil is now a scarce resource, and more than half of the fat in modern feeds comes from plant oils that are inexpensive, but devoid of long-chain omega-3 fatty acids. How can we increase the omega-3 content of salmon on sustainable feeds?
One option is to breed salmon that are well adapted to the feeds of the future. There is heritable variation in salmon’s ability to build EPA and DHA from shorter omega-3 fatty acids. The DNA sequence of salmon is now well known, allowing rapid characterization of heritable differences in nutrient utilization. A salmon family that appears promising on one feed, may not be the best on another. Therefore, we need to understand the salmon’s body as a system: a functional whole made up of parts that mutually affect, but also depend on, each other. A systems understanding of the interplay between feed and genetic factors will allow a tailoring of fish to feed and vice versa, which is robust to fluctuations in feedstuff availability and pricing.
As a first step towards such a systems understanding, the GenoSysFat project involves two biological experiments. 1) A traditional feeding experiment using high- vs low-omega-3 diets and salmon families that differ in feed utilization. 2) A novel study with pieces of liver kept alive and “fed” in laboratory dishes, studying for each fish how different feeds affect metabolism and gene activity. This allows faster and more detailed exploration of the interplay between genetics and feeds. Results will be interpreted with the help of mathematical models for the biochemical reaction networks, which are well established for other species and will be adapted to salmon based on the newly sequenced salmon genome.
Programme: The Digital Salmon
SEEK ID: https://fairdomhub.org/projects/34
Public web page: http://tinyurl.com/genosysfat
Organisms: Danio rerio, Salmo salar, Oncorhynchus mykiss
FAIRDOM PALs: No PALs for this Project
Project created: 16th Oct 2015
Related items
- People (37)
- Institutions (7)
- Investigations (0+5)
- Studies (0+10)
- Assays (0+34)
- Data files (2+85)
- Models (0+2)
- SOPs (1+9)
- Publications (8)
- Presentations (0+6)
- Events (0+2)
- Documents (0+2)
- Samples (0+1)
Projects: GenoSysFat, DigiSal
Institutions: Norwegian University of Life Sciences

Projects: GenoSysFat, DigiSal
Institutions: Norwegian University of Life Sciences

Roles: PhD Student, Postdoc
Expertise: Bioinformatics
Projects: GenoSysFat, DigiSal
Institutions: Norwegian University of Life Sciences
Projects: GenoSysFat, DigiSal
Institutions: Norwegian University of Life Sciences

Projects: GenoSysFat, DigiSal
Institutions: Norwegian University of Life Sciences

Roles: Technician
Expertise: Molecular Biology, Microbiology, Genetics
Tools: Molecular Biology, Molecular biology techniques (RNA/DNA/Protein), Genetics, Microbiology
Projects: GenoSysFat, DigiSal
Institutions: Norwegian University of Life Sciences

Projects: DigiSal, GenoSysFat, SEEK tutorial for DigiSal, FAIRDOM Community Workers
Institutions: Norwegian University of Life Sciences

I am the data and model manager for the Digital Salmon
Projects: DigiSal, GenoSysFat
Institutions: Norwegian University of Life Sciences

Expertise: Transcriptomics, Comparative Genomics
Projects: GenoSysFat, DigiSal, SEEK tutorial for DigiSal
Institutions: Norwegian University of Life Sciences

Projects: DigiSal, GenoSysFat
Institutions: Norwegian University of Life Sciences

Expertise: Bioinformatics
Tools: Bioinformatics, Genetics, Transcriptomics, Molecular Biology
Projects: DigiSal, GenoSysFat, SAFE-Aqua, Unlock
Institutions: Wageningen University & Research

Roles: PhD Student
Expertise: semantics, Software Engineering, R, Python, Java, Data Management, Databases, Genetics, Genomics, Microbiology
Projects: DigiSal, GenoSysFat
Institutions: Cargill
Projects: PSYSMO, DigiSal, GenoSysFat, HUMET Startup, EmPowerPutida, MycoSynVac - Engineering Mycoplasma pneumoniae as a broad-spectrum animal vaccine, SAFE-Aqua, INDIE - Biotechnological production of sustainable indole
Institutions: Helmholtz Centre for Infection Research Braunschweig, Wageningen University & Research
Roles: Project Coordinator
Expertise: Microbiology, Mathematical modelling of biosystems and bioprocesses, Optimal experimental design, Systems Biology, Biotechnology
Tools: Bioinformatics, Genetic modification, Proteomics, Fermentation, Microarray analysis, Computational Systems Biology, Metabolic Engineering, microbiology techniques, reverse engineering, computational platform development, metabolic netwlrk visualization
My research activities has been to use mathematical models and Computational Biology to answer biological questions, intertwining in silico and experimental methods at all stages. I have a strong interest in exploring the interfaces between Fundamental Biology and bona fide Engineering, specifically in the realm of environmental and industrial problems. The research goals of my group are to contribute to the elucidation of mechanisms underlying basic cellular processes, evolution and ecological
...
Projects: DigiSal, GenoSysFat, SEEK tutorial for DigiSal
Institutions: Norwegian University of Life Sciences
Projects: DigiSal, GenoSysFat
Institutions: Norwegian University of Life Sciences

Projects: DigiSal, GenoSysFat, SEEK tutorial for DigiSal
Institutions: Norwegian University of Life Sciences
Projects: DigiSal, GenoSysFat
Institutions: Norwegian University of Life Sciences

Tools: Bioinformatics
Combined taxonomy table of abundance of OTUs (Operational Taxonomy Units) in both freshwater and saltwater samples from 16S V3-V4 Illumina sequencing of gut microbiota. Primers used for sequencing are given in https://fairdomhub.org/sops/270
The OTUs are presented in number of counts per sample (n=349). Each row represent one sample. Raw data are available in the Sequence Read Archive database under accession number SRP119730 (https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP119730).
Creators: Inga Leena Angell, Lars Snipen, Jon Olav Vik
Submitter: Inga Leena Angell
Investigations: 1 hidden item
Studies: 1 hidden item
Assays: 1 hidden item
Main page at NCBI for the salmon genome. Contains download links to annotation GFF, genome sequence FASTA, etc.
Creator: Jon Olav Vik
Submitter: Jon Olav Vik
Investigations: 1 hidden item
Studies: 1 hidden item
Assays: 1 hidden item
We have adapted the definitions of terms in [ISA best practice][1] and [programmes and projects][2]:
Programme = Overarching research theme (The Digital Salmon)
Project = Research grant (DigiSal, GenoSysFat)
Investigation = a particular biological process, phenomenon or thing
(typically corresponds to [plans for] one or more closely related papers)
Study = experiment whose design reflects a specific biological research question
Assay = standardized measurement or diagnostic experiment using a
...
Creators: Jon Olav Vik, Natalie Stanford
Submitter: Jon Olav Vik
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Abstract (Expand)
Authors: Y Jin, IL Angell, SR Sandve, LG Snipen, Y Olsen, K Rudi
Date Published: 24th Jan 2019
Publication Type: Not specified
DOI: 10.3354/aei00297
Citation: Aquacult. Environ. Interact. 11 : 31
Abstract (Expand)
Authors: Knut Rudi, Inga Leena Angell, Phillip B. Pope, Jon Olav Vik, Simen Rød Sandve, Lars-Gustav Snipen
Date Published: 15th Jan 2018
Publication Type: Not specified
DOI: 10.1128/AEM.01974-17
Citation: Appl Environ Microbiol 84(2) : e01974-17
Abstract (Expand)
Author: R. C. Edgar
Date Published: 18th Aug 2013
Publication Type: Not specified
PubMed ID: 23955772
Citation: Nat Methods. 2013 Oct;10(10):996-8. doi: 10.1038/nmeth.2604. Epub 2013 Aug 18.
Abstract (Expand)
Author: M. Bekaert
Date Published: 14th Nov 2012
Publication Type: Not specified
PubMed ID: 23166792
Citation: PLoS One. 2012;7(11):e49903. doi: 10.1371/journal.pone.0049903. Epub 2012 Nov 14.
Abstract (Expand)
Author: R. C. Edgar
Date Published: 12th Aug 2010
Publication Type: Not specified
PubMed ID: 20709691
Citation: Bioinformatics. 2010 Oct 1;26(19):2460-1. doi: 10.1093/bioinformatics/btq461. Epub 2010 Aug 12.
Abstract
Authors: J. G. Caporaso, J. Kuczynski, J. Stombaugh, K. Bittinger, F. D. Bushman, E. K. Costello, N. Fierer, A. G. Pena, J. K. Goodrich, J. I. Gordon, G. A. Huttley, S. T. Kelley, D. Knights, J. E. Koenig, R. E. Ley, C. A. Lozupone, D. McDonald, B. D. Muegge, M. Pirrung, J. Reeder, J. R. Sevinsky, P. J. Turnbaugh, W. A. Walters, J. Widmann, T. Yatsunenko, J. Zaneveld, R. Knight
Date Published: 11th Apr 2010
Publication Type: Not specified
PubMed ID: 20383131
Citation: Nat Methods. 2010 May;7(5):335-6. doi: 10.1038/nmeth.f.303. Epub 2010 Apr 11.
Abstract (Expand)
Authors: A. Brazma, P. Hingamp, J. Quackenbush, G. Sherlock, P. Spellman, C. Stoeckert, J. Aach, W. Ansorge, C. A. Ball, H. C. Causton, T. Gaasterland, P. Glenisson, F. C. Holstege, I. F. Kim, V. Markowitz, J. C. Matese, H. Parkinson, A. Robinson, U. Sarkans, S. Schulze-Kremer, J. Stewart, R. Taylor, J. Vilo, M. Vingron
Date Published: 1st Dec 2001
Publication Type: Not specified
PubMed ID: 11726920
Citation: Nat Genet. 2001 Dec;29(4):365-71.
Abstract (Expand)
Authors: G. Gillard, T. N. Harvey, A. Gjuvsland, Y. Jin, M. Thomassen, S. Lien, M. Leaver, J. S. Torgersen, T. R. Hvidsten, J. O. Vik, S. R. Sandve
Date Published: No date defined
Publication Type: Not specified
PubMed ID: 29431879
Citation: Mol Ecol. 2018 Feb 12. doi: 10.1111/mec.14533.