A multi-phenotype protocol for fine scale mapping of QTL in outbred heterogeneous stock mice

1. A multi-phenotype protocol for fine scale mapping of QTL in outbred heterogeneous stock mice LC Solberg, C Arboledas, P Burns, S Davidson, G Nunez, A Taylor, W Valdar, R Deacon, D Bannerman, W Cookson, D Gauguier, JNP Rawlins, R Mott, J Flint University of Oxford, Wellcome Trust Centre for Human Genetics

3. Heterogeneous Stock (HS) mice AJ AKR BALB C3H C57 DBA CBA LP HS Random Breeding >40 Generations Each chromosome is a random mosaic of the founders Northport HS founded by Robert Hitzemann (Demarest et al., 2001)

4. Power Calculation in HS: Percent Success for QTL Detection

5. 3-6000 molecular markers x 2000 mice = 6-12 million genotypes Multiple Phenotypes How can we make this project cost-effective?

6. Multiple Phenotypes • Behavioral Anxiety • Open Field Test • Elevated Plus Maze • Food Neophagia • Fear Potentiated Startle • Lung Function (Asthma) • Plethysmograph • Other • Corticosterone (post-stress) • Electrolyte measurements • Haematology • Immunology • Mandible shape • Wound Healing • Tissue Collection • Metabolic Function (Diabetes) • Glucose Tolerance • Insulin Sensitivity • Adiposity Index

7. Testing Order

8. For several of these phenotypes there are: • Known phenotypic differences between progenitor strains of HS mice • Previously identified QTL using HS progenitor inbred crosses

10. Inbred Differences Increased Variation in HS Time Spent in Open Arms of EPM

13. Inbred Differences Increased Variation in HS Response to Metacholine in Plethysmograph

14. Inbred Differences Increased Variation in HS Glucose Tolerance Test

15. 21 Phenotypes, 90 Phenotype Elements 200 Phenotype Elements and Covariates * 2000 mice = 400,000 Data Points 3-6,000 Molecular Markers * 2000 mice = 6-12 Million Genotypes

16. We Need a Database!

17. Integrated Genotyping System • Subjects (pedigrees) • Phenotypes (multivariate, covariates) • Markers (SNPs, microsatellites) • Genotypes (multiple observations, editing) (see poster)

18. IGS: Phenotypes

19. IGS: Phenotypes

20. Future Work • Genotyping • 3-6,000 SNPs and microsatellites • sub-centimorgan spacing across entire genome • Statistical Analysis • Dynamic programming using ancestral haplotypes (HAPPY) • Statistical modeling in R • Gene Identification

21. Conclusions • Genetic heterogeneity of HS mice make them ideal for fine mapping QTL • We are able to collect data accurately for multiple phenotypes from a large number of HS mice • We have developed a database to store all phenotypic and genotypic information • Data collected from this study will be used to search for genes involved in all phenotypes measured

24. The mouse is an ideal animal model • Genetically well-defined strains • Control of environmental factors • Validated mouse models of human quantitative traits • Inexpensive to test • Similarity with the human genome

25. How do we measure anxiety in mice? • Phenotypic correlation between open field activity and defecation defines emotionality Low Ambulation + High defecation = Anxious Mouse Open field arena • Emotionality in rodents is a good measure for susceptibility to human anxiety (Green and Hodges, 1991; Ramos and Mormede, 1998)

26. Fine-resolution mapping using HS Each chromosome is a random mosaic of the founders

27. Inbred Differences Increased Variation in HS Glucose Tolerance Test

28. Inbred Differences Increased Variation in HS Post-Stress Plasma Corticosterone

29. Phenotypes

31. Bioinformatics: Analysis • HAPPY (http://www.well.ox.ac.uk/happy) • for each mouse, calculates the probability of descent from each HS founder at each locus by dynamic programming • test for QTL = test for differences between HS founder effects • HAPPY now integrated into R: • dynamic-programming in C to compute probabilities • full range of R analyses available (multivariate,logistic regression etc)

32. Need for a Database In TOTAL: 21 Phenotypes, 87 Phenotype elements 174,000 Data Points