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

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Multiparent Advanced Generation Inter Cross

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

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

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CSIRO Mathematical and Information Sciences Final Result

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CSIRO Mathematical and Information Sciences In theory... No genotyping for users after setup is complete Effective design for G 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

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CSIRO Mathematical and Information Sciences 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

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

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CSIRO Mathematical and Information Sciences Theory vs. Reality

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CSIRO Mathematical and Information Sciences Linkage Map Construction Basic Strategy 1.Filter and preprocess marker data 2.Estimate pairwise recombination 3.Group and order loci 4.Refinement

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CSIRO Mathematical and Information Sciences 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:

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CSIRO Mathematical and Information Sciences 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 A C XXXXXXXXXXXXXXXXX B

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CSIRO Mathematical and Information Sciences MAGIC bag of tricks R package mpMap Simulate data, filter/process, generate linkage map, visual quality checks 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

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

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

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

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

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CSIRO Mathematical and Information Sciences 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

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CSIRO Mathematical and Information Sciences Emma Huang Research Scientist Phone: Thanks to: Andrew George Colin Cavanagh Matthew Morell Thank you Contact Us Phone: or Web:

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