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
AJ AKRBALBC3H C57 DBA CBA LP HS Random Breeding >40 Generations Each chromosome is a random mosaic of the founders Heterogeneous Stock (HS) mice Northport HS founded by Robert Hitzemann (Demarest et al., 2001)
Power Calculation in HS: Percent Success for QTL Detection Percent variance explained by QTL Significance level5%1%0.1%5%1%0.1% Population Size Population Size Population Size
Multiple Phenotypes molecular markers x 2000 mice = 6-12 million genotypes How can we make this project cost-effective?
Multiple Phenotypes Behavioral Anxiety Open Field Test Elevated Plus Maze Food Neophagia Fear Potentiated Startle Lung Function (Asthma) Plethysmograph Metabolic Function (Diabetes) Glucose Tolerance Insulin Sensitivity Adiposity Index Other Corticosterone (post-stress) Electrolyte measurements Haematology Immunology Mandible shape Wound Healing Tissue Collection
WeekDayTest(s) 5MMicrochip, Ear Punch, Imm. Sample 6MOpen Field Test TElevated Plus Maze WFood Neophagia Th, FHome Cage Activity, Burrowing 7M-WFear Potentiated Startle ThContext Freezing FCue Conditioning, Plasma for CORT 8FPlethysmograph 9T, WGlucose Tolerance Test Th, FTissue Harvest Testing Order
For several of these phenotypes there are: Known phenotypic differences between progenitor strains of HS mice Previously identified QTL using HS progenitor inbred crosses
Time Spent in Open Arms of EPM Increased Variation in HS Inbred Differences
Response to Metacholine in Plethysmograph Inbred Differences Increased Variation in HS
Glucose Tolerance Test Inbred Differences Increased Variation in HS
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
We Need a Database!
Integrated Genotyping System Subjects (pedigrees) Phenotypes (multivariate, covariates) Markers (SNPs, microsatellites) Genotypes (multiple observations, editing) (see poster)
IGS: Phenotypes
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
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
The mouse is an ideal animal model Genetically well-defined strains Control of environmental factors Similarity with the human genome Inexpensive to test Validated mouse models of human quantitative traits
How do we measure anxiety in mice? Open field arena Emotionality in rodents is a good measure for susceptibility to human anxiety (Green and Hodges, 1991; Ramos and Mormede, 1998) Low Ambulation + High defecation = Anxious Mouse Phenotypic correlation between open field activity and defecation defines emotionality
Fine-resolution mapping using HS Each chromosome is a random mosaic of the founders
Glucose Tolerance Test Inbred Differences Increased Variation in HS
Post-Stress Plasma Corticosterone Inbred Differences Increased Variation in HS
Phenotypes
Bioinformatics: Analysis 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)
Need for a Database TestNumber of Phenotype Elements Number of Mice Total Data Points EPM ,000 PG ,000 Glucose420008,000 In TOTAL: 21 Phenotypes, 87 Phenotype elements 174,000 Data Points