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Modeling carotenoid dynamics in salmon BMSW , Bangalore 2008

Modeling carotenoid dynamics in salmon BMSW , Bangalore 2008. Hannah Rajasingh Centre for Integrative Genetics (CIGENE) Norwegian University of Life Sciences Ås, Norway. Overview. Background to the pigmentation trait Research summary Model setup

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Modeling carotenoid dynamics in salmon BMSW , Bangalore 2008

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  1. Modeling carotenoid dynamics in salmonBMSW,Bangalore 2008 CIGENE Hannah Rajasingh Centre for Integrative Genetics (CIGENE) Norwegian University of Life Sciences Ås, Norway

  2. Overview • Background to the pigmentation trait • Research summary • Model setup • Experimental validation and sensitivity analysis • Model extensions • Conclusion CIGENE

  3. Salmonid pigmentation?? • Well-known feature of certain salmonid fish • Affected by both genetic and environmental factors • Genetic factors: intra- and inter-species variation, heritable trait • Environmental factors: diet, temperature etc. • Vital quality trait in aquaculture and thus of economic importance CIGENE

  4. Carotenoids • Naturally synthesized pigments present throughout the animal kingdom • Function as colouring agents, provitamin A compounds and antioxidants • Xanthophyll astaxanthin is the major carotenoid in aquatic species • High antioxidant activity CIGENE

  5. Salmonids • Salmonidae contain around 10 genera with well-known members being anadromous • Intricate life-history pattern with many variations • Carotenoid metabolism in pigmented salmonids closely linked with life-cycle changes CIGENE

  6. Muscle as carotenoid source CIGENE Muscle as carotenoid sink

  7. Sockeye (Oncorhynchus nerka) CIGENE Arctic char (Salvelinus alpinus)

  8. Problem: Clearer understanding of metabolic processes governing carotenoid muscle deposition required • Premises: • Carotenoid uptake and transport in the system based on fatty acids • Major features of the carotenoid pathway in salmonids are similar to that in mammals CIGENE

  9. CIGENE

  10. Mathematical model Flow and uptake of pigment through the system modeled as a function of feed input CIGENE Pigment concentration in blood, liver and muscle represented by 8 ODEs

  11. Parameters? • Rates of processes unknown • Constraints: • Optimal astaxanthin dietary content • Only 50% enters blood stream • Mean muscle concentration • Muscle uptake saturable with negligible degradation • Strong link with fatty acid transport CIGENE

  12. Short term feeding CIGENE Aas et al. 1999

  13. Long term feeding CIGENE March and MacMilan 1996

  14. Sensitivity analysis: QSS CIGENE Identify the processes/rates affecting muscle deposition to the greatest extent

  15. Sensitivity analysis: time-series CIGENE

  16. Pigment redistribution during maturation Claim: Not controlled by a specific regulatory system CIGENE

  17. Extension: Sites of genetic variations The model is extended to generate population of individuals by adding variances to the specific growth rates. CIGENE

  18. Extension: mGP representations • The dynamic model is combined with genome models to create mathematical genotype-phenotype representations • Genotypic and phenotypic variations linked within a single framework • Used to determine genetic model required to account for empirical salmon genetic data Genotype of a trait Phenotype of a trait CIGENE

  19. Conclusion • Early-phase, heuristic model is capable of incorporating available knowledge into a concerted whole • Muscle uptake process seems to have the highest influence on levels of pigment deposition –> potential site of genetic variation • Release of carotenoids from flesh of maturing salmonids does not require a specific control system regulating it CIGENE

  20. Acknowledgements • Stig W. Omholt • Leiv Øyehaug • Dag Inge Våge • Arne Gjuvsland • Lars Gidskehaug CIGENE

  21. Paper III: Sources of genetic variation CIGENE • Observed genetic variation not attributable to growth/intestinal uptake is predicted to be due to uptake processes in blood-muscle compartment • Mixed model estimated variances in filet colour (53%) and weight (30%) due to additive genetic effects • Path analysis split pigment variation into contributions from genetic, weight and other factors

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