Effective Recombination in Plant Breeding and Linkage Mapping Populations: Testing Models and Mating Schemes

Transcription

1 Effective Recombination in Plant Breeding and Linkage Mapping Populations: Testing Models and Mating Schemes Raven et al., 1999 Seth C. Murray Assistant Professor of Quantitative Genetics and Maize Breeding Texas A&M University / Texas AgriLife Research

2 We Tend to Envision Recombination as Presented in Introductory Textbooks - Recombining the genetic material of two parents - Occurs in meiotic prophase I - Crossing over was described and modeled in: Muller H.J., 1916 The mechanism of crossing over, Am. Nat. 50: From: Raven, P.H., R.F. Evert and S.E. Eichhorn Biology of Plants; sixth ed., Freeman/Worth, New York From: Fairbanks, D. J., W. R. Andersen 1999 Genetics: the continuity of life. Brooks/Cole and Wadsworth, Pacific Grove, California, USA

3 Effective Recombination in an F 6 RIL Population Adding double crossovers Effective recombination can directly be observed through rearrangement of polymorphic marker genotypes and always less than the actual and expected number of recombination events

4 In Plant Breeding and Genetic Linkage Mapping Effective Recombination is Often the Limiting Factor INDIVIDUAL 1 INDIVIDUAL 2 INDIVIDUAL 3 INDIVIDUAL 4 INDIVIDUAL 5 INDIVIDUAL 6 INDIVIDUAL 7 INDIVIDUAL 8 INDIVIDUAL 9 Introgression of an exotic disease resistance gene we would still expect linkage drag. Potentially hundreds of genes within this linkage block, not near gene resolution for map based cloning - Few markers across a chromosome do not capture all events - With next generation sequencing technology we will soon capture all events - No perceived drawbacks with more recombination Agro 643 QTL Mapping Composite Interval Mapping

5 1) What are the minimum numbers of loci that must be simulated for sufficient likelihood of capturing all possible recombination? 2) Can textbook or alternative statistical distributions adequately model recombination in the high resolution Zea mays L. NAM dataset? 3) What proportion of effective recombination events in linkage populations might be missed due to insufficient and imperfect marker coverage? 4) What are the distributions of effective number of recombination events per chromosome that are expected to occur under common linkage population scenarios? 5) What is the relationship between heterozygosity and effective recombination?

6 How Do We Simulate Recombination and Linkage? Beads on a String Model : Locus 1 Locus 2 Locus 3 Locus 4 Locus 5 Locus 6 Locus 7 Locus 8 Parent 1 Parent 2 r r r r r r r F1 Locus Allele Allele C LCrossover<- ceiling(runif(1,0,loci/2)) RCrossover<- ceiling(runif(1,loci/2,loci)) 2 5 Example = Example =

7 Minimum Number of Markers Needed to Simulate Population Recombination Counting recombination events NOT distance (cm) Biparental cross selfed for 8 generations to RILs Dihybrid cross 3 generations of sibing 8 generations of selfing to RILs

8 Mean number of effective recombination events captured = β - (((log (loci+ β)) - (log (loci))) / χ ) Biparental cross selfed for 8 generations to RILs Dihybrid cross 3 generations of sibing 8 generations of selfing to RILs

9 - 25 F 6 Populations RILS SNPs - 136,000 recombination events

10 Parental (F 1 ) genotype before crossing over in prophase I A A A A A A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B B B B B B B B B B B A A A A A A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B B B B B B B B B B B A) Two strand double crossover model A A A A A A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B X B B B B B B B B B B B B B A A A A A A A A A A A A B B B B B B B B B B B B B A A A A A A A A A A A A X A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B B B B B B B B B B B B) Four strand quadruple crossover model Simulated Recombination events } 2 0 A A A A A B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B A A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B X B B B B B B B B B B B B B A A A A A A A A A A A A B B B B B B B B B B B B B A A A A A A A A A A A A X A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A B B B B B B B B B B C) Stochastic crossover model A A A A A A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B B B B B B B B B B B A A A A A A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B B B B B A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B X B B B B B B B B B B B B B A A A A A A A A A A A A B B B B B B B B B B B B B A A A A A A A A A A A A X A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B A A A A A A A A A A A A A A A A A A A A X A A A A A A A A A A A A A A A B B B A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B X B B B B B B B B B B B B B B B A A A B B B B B B B A A A A A A A A A A B B B B B B B B B B B B A A A X A A A A A A B B B B B B B B B B B B A A A A A A A B B B B B B B B B B A A A A A A A A A A A A B B B X B B B B B B A A A A A A A A A A A A B B B B B B B } 2 } 0 } 1 } 2 } 3 } 4 2

11 Fixed: four-strand quadruple crossover model Fixed: two-strand double crossover model Actual NAM data Stochastic: twostrand Poisson distributed (λ=3) model Stochastic: fourstrand geometric distributed (p =0.45) crossover model

12 Stochastic Poisson + Obligate Crossover Fit NAM Data Well MUST Develop Separate Rate for Each Chromosome Chromosome 1: NAM sample μ = 5.73 NAM sample σ = 8.73 Sim. Poisson λ = 2.24 Fit Chi-sq. = p > 0.001** Chromosome 9: NAM sample μ = 2.90 NAM sample σ = 3.87 Sim. Poisson λ = 0.90 Fit Chi-sq. = p > 0.78

13 Predicted Effect of Incomplete Marker Data in NAM With 84 polymorphic markers per chromosome we expect to detect 3.56 events (3.58 empirical) With 1004 polymorphic markers per chromosome we expect to detect 4.06 events (empirical: Stay Tuned)

14 Predicted Distributions of Effective Recombination Events Under Different Population Development Scenarios μ = 1.83 μ = 3.57 μ = 5.41 σ = 1.86 σ = 4.83 σ = 6.58 Event / gen. = 0.92 Event / gen. = 0.45 Event / gen. = 0.60 μ = 5.41 σ = 6.58 Event / gen. = 0.60 μ = 9.68 σ = E./ g. = 0.81 μ = 12.7 σ = E./ g. = 1.06

15 Direct Relationship Between Heterozygosity and the Effective Number of Events (Crossovers * Mean Genomewide Heterozygosity) + Previous Events

16 1) A minimum of 200 loci must be simulated to capture most effective recombination events in experimental populations (more are preferable). 2) Only a (stochastic Poisson + obligate) number of crossovers fits the high resolution Zea mays L. NAM dataset, not a textbook fixed number. 3) Insufficient and imperfect marker coverage is expected to miss 0.5 effective recombination events / chromosome / individual (~12%) in NAM. 4) The highest number of effective recombination events per generation is expected to be found in dihybrid populations > F 2 > doubled haploids F 1 > RILs. Intermating early always produces more recombination. 5) Average effective recombination per generation is equal to the recombination rate * average genomewide heterozygosity. - Thanks to SCSC 653 class of 2009 for asking good questions - Thanks to Jeffrey Glaubitz and Michael McMullen for updating a NAM file. - Conversations on an early work with: Mattieu Falque, Wojtek Pawlowski, Michael Gore, Jianming Yu, Mark Wright and Sean Miles, George Hodnett, Martha Hamblin and Randall Wisser. Funding for this project was provided by: