Believing in MAGIC: Validation of a novel experimental breeding design

1. Believing in MAGIC: Validation of a novel experimental breeding design Emma Huang, Ph.D. Biometrics on the Lake December 2, 2009

2. Multiparent Advanced Generation Inter Cross

3. 2 parents BC F2 ... Experimental crosses A B B AB AB AB CSIRO Mathematical and Information Sciences

4. 4 Parents A C B D AB CD ABCD 6 generations of selfing Inbred individuals CSIRO Mathematical and Information Sciences

5. Final Result CSIRO Mathematical and Information Sciences

6. In theory... • No genotyping for users after setupis complete • Effective design forG x E • Resource for large community- many traits • Large population of RILs • Large genetic (allelic) and phenotypic diversity • Ability to map epistatic interactions • High recombination  high resolution RIL final lines Size Diversity CSIRO Mathematical and Information Sciences

7. Vital resource for linkage mapping • No physical map/sequence for wheat (yet) • Previous maps developed for specific population • Limited polymorphisms • Would have to join maps across populations • Possibly inconsistent estimates across maps • Many markers have not been mapped MAGIC map is potentially: • More complete due to greater genetic diversity • More accurate due to larger population size • More precise due to many generations of recombination CSIRO Mathematical and Information Sciences

8. But... nontrivial • Complex inheritance from founders • Limited genotyping • Population size/# markers – computational burden • Marker issues – dominant markers, polyploidy, etc. CSIRO Mathematical and Information Sciences

9. Theory vs. Reality CSIRO Mathematical and Information Sciences

10. Linkage Map Construction Basic Strategy • Filter and preprocess marker data • Estimate pairwise recombination • Group and order loci • Refinement CSIRO Mathematical and Information Sciences

11. Step 2: Estimating Recombination Distance • In standard designs, counting numbers of different genotypes • This doesn’t work for 4/8 way crosses • Many generations of recombination • No intermediate genotyping • Ambiguous inheritance of alleles Instead maximize the likelihood: CSIRO Mathematical and Information Sciences

12. A C B X X X X X X X X X X X X X X X X X Step 4: Refinement • Start with framework map • Position markers relative to fixed locations • Maximize likelihood over grid of positions Compared to initial ordering: • Iterative and time-consuming • Less sensitive to missing values • Additional information about marker relationships CSIRO Mathematical and Information Sciences

13. Simulations Real Data • 4-parent cross Input Variables: • Mixing structure • Inbreeding structure • Sample size • True linkage map • Marker quality Output Questions: • Precision of estimation • Reliability of grouping • Accuracy of ordering • Usefulness of 3-pt vs. 2-pt • Resolution of data MAGIC bag of tricks R package mpMap • Simulate data, filter/process, generate linkage map, visual quality checks CSIRO Mathematical and Information Sciences

14. In a perfect world “Nice” data – • Fully informative markers • No missing data • No genotyping errors Chr 6 Recombination fractions below diagonal; scaled LOD scores above Chr 5 Chr 4 Chr 3 Chr 2 Chr 1 CSIRO Mathematical and Information Sciences

15. Something closer to reality “Typical” data – • Biallelic markers • 10% missing data • 10% genotyping errors > datbad <- mp.sim(map, simped, seed=1, error.prob=.1, missing.prob=.1) ------------------------------------------------------- Summary of mpcross object ------------------------------------------------------- 0 markers were removed with missing values in founders 0 markers were removed with non-polymorphic founder genotypes ------------------------------------------------------- 195 markers were biallelic. 0 markers were multiallelic. ------------------------------------------------------- 195 markers had >5% missing data. 99 markers had >10% missing data. 0 markers had >20% missing data. ------------------------------------------------------- 49 markers had <1e-5 p-value for segregation distortion 2 markers had <1e-10 p-value for segregation distortion 0 markers had <1e-15 p-value for segregation distortion CSIRO Mathematical and Information Sciences

16. 4-parent MAGIC • DArT & SNP markers • Constructed map • 871 progeny • 1148 markers • 20/21 chromosomes • 2010: 5000 lines from 8-way cross CSIRO Mathematical and Information Sciences

17. Chromosome 6B Genetic Map Heat Map CSIRO Mathematical and Information Sciences

18. Looking to the future • Improve the current map • Starting from the least informative set of markers • Further genotyping to fill in gaps • QTL Mapping • Testing different approaches • Field trials • Association Mapping • Using constructed map for complex analysis CSIRO Mathematical and Information Sciences

19. CSIRO Mathematical and Information Sciences Emma Huang Research Scientist Phone: +61 7 3214 2953 Email: Emma.Huang@csiro.au Thanks to: Andrew George Colin Cavanagh Matthew Morell Thank you Contact UsPhone: 1300 363 400 or +61 3 9545 2176Email: Enquiries@csiro.au Web: www.csiro.au CSIRO Mathematical and Information Sciences