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MAGIC :Multiparent advanced generation intercross and QTL discovery


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MAGIC or multiparent advanced generation inter-crosses is an experimental method that increases the precision with which genetic markers are linked to quantitative trait loci (QTL). This method was first introduced by (Mott et al., 2000) in animals as an extension of the advanced intercrossing (AIC) approach suggested by (Darvasi and Soller , 1995)for fine mapping multiple QTLs for multiple traits. Advanced Intercrossed Lines (AILs) are generated by randomly and sequentially intercrossing a population initially originating from a cross between two inbred lines.
MAGIC involves multiple parents, called founder lines, rather than bi-parental control. AILs increase the recombination events in small chromosomal regions for the purpose of fine mapping. These lines are then cycled through multiple generations of outcrossing. Each generation of random mating reduces the extent of linkage disequilibrium (LD), allowing the QTL to be mapped more accurately.

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MAGIC :Multiparent advanced generation intercross and QTL discovery

  1. 1. MAGIC, Multiparent advanced generation intercross anew genetic resource for multiple trait improvement andQTL discovery in crops G.Kalidasan
  2. 2.  Quantitative traits  Phenotype expression  Natural variation Experimental System  Selection or Natural Population  Experimental Population Multiparent Advanced Generation Intercross Population Case Studies
  3. 3. Selection and Natural populationsSelection experimentsMarker allele frequency – Unrelated individualsMany generationsDifference in phenotypeLD between QTL and markerLD around a QTL
  4. 4. DomesticationComparison of allele frequencyWithout phenotypic informationLoci subject to selection
  5. 5.  Exploits LD in diverse population Human Crops MaizeAdvantage Cheaper and high density markersDisadvantage Spurious associations Greater precision but low power
  6. 6. Mutant population  Spontaneous mutation  Induced mutation  Mutagenesis  Large resources  Poly ploidyTILLING  Phenotyping screen  Knowledge on genes controlling trait
  7. 7. F2 and backcross (BC) populations  Additive effects  Few meiosesRecombinant inbred lines  RILs are advanced homozygous lines  Increased recombination events and improved map resolution  Epistatic interactions
  8. 8. Near isogenic lines(NIL) Target trait is required for the generation of NILs. High-resolution mappingDouble haploids 100% purity and genetic uniformity.  Genetic studies
  9. 9. Randomly and sequentially intercrossed population.Phenotypic selection to further reduce the frequency of deleterious alleles from the donor. Detect QTLs with epistatic effects Useful meiotic recombination
  10. 10. Linkage map  DNA Markers  Position and relative genetic distance  For identifying chromosomal regions that contain genes controlling simple or complex traits using QTL analysis QTL mapping Advantage  High detection power  Few markers are required Disadvantage  Large confidence interval of upto 5 to 30cM  Limited resolution  Only two alleles tested
  11. 11. Multiparent advanced generation intercross Animals. (Mott et al., 2000) and (Yalchin et al., 2005) Fine-mapping of multiple QTLs for multiple traits in the same population. Advanced intercrossed lines (AILs) Each generation reduces the extent of linkage disequilibrium (LD), thus allowing QTL to be mapped more accurately. Lines derived from early generations can be used for QTL detection and coarse mapping While those derived from later generations will only detect marker-trait associations if markers are located very close to the QTL.
  12. 12.  Extended to plants (Cavanagh et al., 2008) Diverse founder lines n/2 generations RILs Increased intercrossing cycles
  13. 13. Short generation period- ArabidopsisEight founder linesG1G2G3G4G10-12SNP genotyping platformsSSR Markers
  14. 14.  Statistics tools Linear mixed effect model and Hierarchical Bayes QTL mapping - study the interrelationship between individuals MLs and founder lines and increases the precision to detect QTL HAPPY- a software package for Multipoint QTL Mapping in Genetically Heterogeneous Animals R/mp Map- A computational platform for the genetic analysis of multi-parent recombinant inbred lines
  15. 15. Advantages Shuffling the genes across different parents enable accurately ordering the genes Increased recombination - novel rearrangements of alleles and greater genetic diversity. Best combinations of genes for important traits development 1000 Magic individuals Seeds retained - fine mapping Epistatic and G X E interactions Facilitate the discovery, identification and manipulation of new forms of allelic variability
  16. 16. Disadvantages Extensive segregation More time Large scale phenotyping
  17. 17. (Rakshit et al., 2012)
  18. 18.  In Arabidopsis fine mapping of QTL for germination and bolting time (Kover et al. 2009) Studies in flowering time candidate genes (Ehrenreich et al. 2009) Developed computational platform R/mp Map for Genetic analysis (Huang and George, 2011)
  19. 19.  19 ‘‘founder’’ accessions Wide geographical distribution Staggered planting scheme Replanted families – randomly assigned crosses 342 F4 outcrossed families Each F4 family derived up to 3 MLs followed by selfing 6 generations 527 lines taken out of 1026
  20. 20.  Developmental quantitative traits Measured the heritability (h2) h2 L is the proportion of variation that is due to genetic differences between lines, using the phenotypic average of the replicates within each line h2 P is an estimate of the genetic variance if only one replicate per line were phenotyped h2L ≥ h2P h2L increases with the number of replicates Mean of each line is used for QTL mapping
  21. 21. Phenotypic varianceDiallelic population - 0.5 Magic – 0.052Average minor allele frequency in founder lines is 0.2270% of SNP shared between any pair of foundersIncreasing replication within line reduces non- genetic varianceImproves power of QTL
  22. 22.  A hidden Markov model (HMM) is used to make a multipoint probabilistic reconstruction of the genome of each ML as a mosaic of the founder haplotypes. Diallelic SNPs cannot distinguish between all founders so information from neighboring SNPs is used to compute the posterior probability Pis(L) is that at a given locus L, the ML i is descended from founder s. Locus is defined to be the interval between two adjacent genotyped SNPs, labeled by the name of the left-hand SNP.
  23. 23.  Used fixed-effects QTL models but to accommodate population structure, in different ways used multiple-QTL modeling or random effects to explain the correlations introduced in population structure Checked with hierarchical Bayesian random effects model All approaches model the mosaic structure of the MAGIC genomes as described in and implemented in the R package HAPPY Detected two QTLs on chromosomes 3 and 4 for the number of days to germination and bolting time.
  24. 24.  Constructed a linkage map from a four parent MAGIC population and validate it against a comprehensive DArT consensus map drawing together maps from over 100 biparental populations Incorporated the alien introgressions in to the linkage map Level of LD across the genome and compare it with previous estimates for LD from previous studies The power and precision of MAGIC for QTL mapping for plant height , an important trait for yield potential
  25. 25.  Selected four elite wheat cultivar , A- Yitpi , B- Baxter, C- Chara, D- WestoniaGenetic diversity based on genetic survey of international wheat samplesDiverse geographical distributionPhenotypic diversity for a range of traits
  26. 26. Genotyping Used 1285 DArT markers, 57 SSR markers and 1536 SNPs 384 SNPs observed to be polymorphic among the parental lines were selected for genome wide coveragePhenotyping 1100 RILs – Plant height was recorded
  27. 27.  R package mpMap Filtered with monomorphic markers Estimated the recombination fraction all pairs of loci with function ‘mpestrf’ Grouped the markers based on estimated recombination fractions and LOD scores with the function ‘mpgroup’ For map resolution computed recombination events for all lines using the function ‘mpprob’ Which calculates the multipoint probablity at each locus that the observed genotype is inherited from each of the four founder
  28. 28.  Both internal and external comparisons was done Examined a series of diagnostic plots to propose changes to ordering which were then tested through ‘ compare orders’ function in R/mpMap Used heatmaps based on both recombination fractions and LD using R/Ldheatmap The tool provided visualization of the relationships between all pairs of markers
  29. 29. External comparison Diagnostic checks are compared it to an external DArT consensus wheat map Each individual consensus map was based on genotyping involving the analyis of between 206 and 1525markers, with an average density of 582 markers
  30. 30.  Test the introgression in magic population Sr36 is an introgression from Triticum timopheevii for stem rust resistance – carried in variety Baxter on chromosome 2B cause segregation distortion Aimed to identify markers associated with it and identify lines containing it Computed the degree of segregation distortion for which i) the Baxter allele differed from all other founder alleles ii) mutual recombination of < 0.05 was observed were tagged as potential markers in the introgression Estimated the probablity of a line having inherited an allele from the founder Baxter for the identified markers(‘mpprob’)
  31. 31. Linkage disequilbrium Multipoint probablities were computed using the function ‘mpprob’ in R/mpMap and LD was computed using the function ‘mpcalcld’QTL Mapping For all analyses used the ‘mplMmm’ function in the R package mpMap, which performs the interval mapping in the context of a linear mixed model Three QTL for plant height were detected near known genes on chromosomes 2D, 4B, 4D.
  32. 32.  (MAGIC) populations combine the advantages of linkage analysis and association studies. The increased recombination in MAGIC populations leads to novel rearrangements of alleles and greater genetic diversity Can facilitate the discovery, identification and manipulation of new forms of allelic variability They require longer time and more resource to be generated and they are likely to show extensive segregation for developmental traits. MAGIC populations are likely to bring paradigm shift towards QTL analysis in plant species
  33. 33.  The experimental method was underway since it has to be studied in many crops The tools used for QTL mapping are very complex, so simplified models has to be developed in near future for understanding. In near future the method will bring success in finding our economic interest of traits in plants.