Www.umb.no NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 1 Modeling carotenoid dynamics in salmon BMSW, Bangalore 2008 Hannah Rajasingh Centre for Integrative.

Slides:



Advertisements
Similar presentations
Livestock Improvement through Selection
Advertisements

Copyright of for more videos,visit us.
Four Basic Types Of Measurement:
Incorporating biological functionality into crop models (QAAFI/UQ) Erik van Oosterom, Graeme Hammer.
Chinyere Ekine-Dzivenu (PhD Candidate) Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada. 1.
Animal Breeding & Genomics Centre Breeding a better pig in a changing global market Dr Jan ten Napel 18 th March, 2015.
Longfellow Middle School Meeting the needs of all learners Inspiring excellence and.
Lec 12: Rapid Bioassessment Protocols (RBP’s)
Discovery of a rare arboreal forest-dwelling flying reptile (Pterosauria, Pterodactyloidea) from China Wang et al. PNAS Feb. 11, 2008.
Four Basic Types Of Measurement: Categorizing –Nominal Ranking –Ordinal Determination of the size interval –Interval Determination of the size of ratios.
The Central Dogma & Data DNA mRNA Transcription Protei n Translation Metabolite Cellular processes Phenotype Embryology Organismal Biology Genetic Data.
Utilizing DNA testing in identifying multiple gene traits Prof Norman Maiwashe 1,2 (PhD, Pri Sci Nat) 1 ARC-Animal Production Institute 2 Dept. of Animal,
Introduction to Genetics
Regulated Flux-Balance Analysis (rFBA) Speack: Zhu YANG
Dynamic Energy Budgets i.r.t. population effects of toxicants Tjalling Jager Dept. Theoretical Biology.
Mechanistic modeling of zebrafish metabolism in relationship to food level and the presence of a toxicant (uranium) S. Augustine B.Gagnaire C. Adam-Guillermin.
Dynamic Energy Budget (DEB) theory by Elke, Svenja and Ben.
Tjalling Jager molecular genetics evolutionary ecology dynamic energy budgets Mechanisms behind life- history trade-offs.
Quantitative Genetics
NORM BASED APPROACHES FOR AUTOMATIC TUNING OF MODEL BASED PREDICTIVE CONTROL Pastora Vega, Mario Francisco, Eladio Sanz University of Salamanca – Spain.
DEB theory as framework for quantifying effects of noise on cetaceans Bas Kooijman Dept Theoretical Biology Washington, 2004/03/05.
Disentangling evolution and plasticity in adult sockeye migration date: a new method provides evidence of evolutionary change Lisa Crozier Mark Scheuerell.
Application of DEB theory to a particular organism in (hopefully somewhat) practical terms Laure Pecquerie University of California Santa Barbara.
Observing Patterns in Inherited Traits
國立陽明大學生資學程 陳虹瑋. Genetic Algorithm Background Fitness function ……. population selection Cross over mutation Fitness values Random cross over.
Quantitative Genetics
Review Session Monday, November 8 Shantz 242 E (the usual place) 5:00-7:00 PM I’ll answer questions on my material, then Chad will answer questions on.
Extension of Bayesian procedures to integrate and to blend multiple external information into genetic evaluations J. Vandenplas 1,2, N. Gengler 1 1 University.
Higher BMI (body mass index) is linked to greater brain atrophy in 700 MCI and AD patients, and in healthy elderly ADNI (N=587,critical P-value: 0.025)
Physiological Ecology How animals cope with environmental change, and what it means to their distribution and abundance in nature Steve McCormick USGS,
ConceptS and Connections
Tjalling Jager Dept. Theoretical Biology Assessing ecotoxicological effects on a mechanistic basis the central role of the individual.
Broad-Sense Heritability Index
Genetic Variation and Mutation. Definitions and Terminology Microevolution –Changes within populations or species in gene frequencies and distributions.
Animal Breeding & Genomics Centre Environmental and genetic regulation of prenatal events and its importance for postnatal growth performance and meat.
Chapter 5 Characterizing Genetic Diversity: Quantitative Variation Quantitative (metric or polygenic) characters of Most concern to conservation biology.
# 1 US Army Engineer Research and Development Center Multi-Criteria Decision Analysis and Environmental Risk Assessment for Nanomaterials Jeff Steevens.
O AK R IDGE N ATIONAL L ABORATORY U. S. D EPARTMENT OF E NERGY 1 Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Lessons Learned or How to Do.
GA-Based Feature Selection and Parameter Optimization for Support Vector Machine Cheng-Lung Huang, Chieh-Jen Wang Expert Systems with Applications, Volume.
1 Phenotypic Variation Variation of a trait can be separated into genetic and environmental components Genotypic variance  g 2 = variation in phenotype.
Animal Studies and Human Health Consequences Sorell L. Schwartz, Ph.D. Department of Pharmacology Georgetown University Medical Center.
Modelling aquaculture impacts
1 Departament of Bioengineering, University of California 2 Harvard Medical School Department of Genetics Metabolic Flux Balance Analysis and the in Silico.
2008 ADSA-ASAS Joint Annual Meeting Indianapolis, July 7-11 Genetic Parameters of Saturated and Monounsaturated Fatty Acids Estimated by Test-Day Model.
Development of a water temperature model to predict life- history expression and production of Oncorhynchus mykiss in the John Day River basin, Oregon.
QTL Mapping in Heterogeneous Stocks Talbot et al, Nature Genetics (1999) 21: Mott et at, PNAS (2000) 97:
Northwest Power and Conservation Council Sep 12-13, Science Policy Exchange Habitat Issues.
Discovery of a rare arboreal forest-dwelling flying reptile (Pterosauria, Pterodactyloidea) from China Wang et al. PNAS Feb. 11, 2008.
January 27, 2011 Examples of Recovery Evaluation Objectives in the Western U.S. Delta Stewardship Council Presentation by the Independent Consultant.
Interbull Meeting – Dublin 2007 Genetic Parameters of Butter Hardness Estimated by Test-Day Model Hélène Soyeurt 1,2, F. Dehareng 3, C. Bertozzi 4 & N.
Learning to Navigate Through Crowded Environments Peter Henry 1, Christian Vollmer 2, Brian Ferris 1, Dieter Fox 1 Tuesday, May 4, University of.
Population Dynamics Humans, Sickle-cell Disease, and Malaria How does a population of humans become resistant to malaria?
DNAmRNAProtein Small molecules Environment Regulatory RNA How a cell is wired The dynamics of such interactions emerge as cellular processes and functions.
Introduction to Physiological Principles
Yakima O. mykiss Modeling Workshop Ian Courter Casey Justice Steve Cramer.
Breeding Dynamics to Maternal Effects: the shape of populations to come Ian A. Fleming Ocean Sciences Centre Memorial University of Newfoundland.
Ichy Salmon: variation and adaptation Learning Goal: Students will understand the relationship between genetic variation and adaptation. Intended Learning.
Genetic influences “Which is more important, heredity or environment?” “Do the observed differences between people depend more on heredity or the environment?”
Endocrine Responses and Adaptations to Strength Training
NEW TOPIC: MOLECULAR EVOLUTION.
1.Stream A and Stream B are located on two isolated islands with similar characteristics. How do these two stream beds differ? 2.Suppose a fish that varies.
Nonlinear differential equation model for quantification of transcriptional regulation applied to microarray data of Saccharomyces cerevisiae Vu, T. T.,
The Heritability of happiness ‘Happiness depends, as Nature shows, less on exterior things than most suppose. ‘ - William Cowper.
Matrix Models for Population Management & Conservation March 2014 Lecture 10 Uncertainty, Process Variance, and Retrospective Perturbation Analysis.
Lecture 30. December 1, Evolution of Life-History Traits & Impacts on Fisheries Lab: Quiz tomorrow, practical in 1 week. Arthur has flash cards that.
7th Grade Cells Natural Selection
Evolution Standards Rachel Tumlin.
Presented by Christina Bullerwell
Evan G. Williams, Johan Auwerx  Cell 
X-chromosomal markers and FamLinkX
Presentation transcript:

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 1 Modeling carotenoid dynamics in salmon BMSW, Bangalore 2008 Hannah Rajasingh Centre for Integrative Genetics (CIGENE) Norwegian University of Life Sciences Ås, Norway

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 2 Overview  Background to the pigmentation trait  Research summary –Model setup –Experimental validation and sensitivity analysis –Model extensions  Conclusion

NORWEGIAN UNIVERSITY OF LIFE SCIENCES 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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES 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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES 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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 6 Muscle as carotenoid sink Muscle as carotenoid source

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 7 Sockeye (Oncorhynchus nerka) Arctic char (Salvelinus alpinus)

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 9

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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 12 Short term feeding Aas et al. 1999

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 13 Long term feeding March and MacMilan 1996

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 14 Sensitivity analysis: QSS Identify the processes/rates affecting muscle deposition to the greatest extent

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 15 Sensitivity analysis: time-series

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 16 Pigment redistribution during maturation Claim: Not controlled by a specific regulatory system

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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES 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 traitPhenotype of a trait

NORWEGIAN UNIVERSITY OF LIFE SCIENCES 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

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 20 Acknowledgements  Stig W. Omholt  Leiv Øyehaug  Dag Inge Våge  Arne Gjuvsland  Lars Gidskehaug

NORWEGIAN UNIVERSITY OF LIFE SCIENCES CIGENE 21 Paper III: Sources of genetic variation  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