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Association mapping
 

Association mapping

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Association mapping methodology

Association mapping methodology

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    Association mapping Association mapping Presentation Transcript

    • ASSOCIATION MAPPINGWITH TASSEL VG SHOBHANA
    • Genomics Effective tools Identify genes in pathwaysAlleles of agronomic traits Quite challenging ASSOCIATION MAPPING - high resolution - to evaluate wide range of alelles rapidly
    • Genetic Linkage occurs when particular genetic loci or alleles for genes are inherited jointly seen on the same chromosome are physically connected first discovered - British geneticists William Bateson and Reginald Punnett Sturtvent - possiblility to obtain a measure for the distance between the genes - linkage map A recombinant frequency (RF) of 1% is equivalent to 1 m.u.
    • Quantitative trait loci Inheritance of a phenotypic characteristic - varies in degree - attributed to the interactions between two or more genes and their environment. Stretches of DNA that are closely linked to the genes that underlie the trait. QTLs can be molecularly identified (for example, with PCR or AFLP) to help map regions of the genome. This can be an early step in identifying and sequencing these genes. Their phenotypes typically vary along a continuous gradient depicted by a bell curve.
    • Differences: Linkage and AssociationLinkage analysis Association mapping  Recombination is the main Co- inheritance of force of elimination of neighbouring DNA variants linkage. (in both).  Recombination events occur Only few chances for over many generations. recombination to occur.  Eliminated linkage between Low resolution of map. a mutated gene.  Only very close markers are in LD with the mutated gene.
    • QTL mapping is the statistical study of the allelesthat occur in a locus and the phenotypes (physical forms or traits) that they produce.Limitations of using natural populations: It requires the growth of three generations beforelinkage analysis is possible. Very large segregating populations are needed toachieve a high resolution map. The molecular markers may be specific (polymorphic) to only one particular crossing family.
    • A complementary approach - to analyse Linkage Disequilibrium in natural populations.Successfully in humans - no large mapping families.LD between two loci in natural populations - affected by all the recombination events.Have happened since the two alleles appeared in some individuals of the population.LD declines as the number of generations increases, so that in old populations.LD is limited to small distances.This is desirable!!Since a marker very close to a mutation responsible for a disease makes it easier to reach the mutated gene.
    •  Linkage disequilibrium is the correlation between pairs of polymorphisms. One simple way to estimate linkage disequilibrium between pairs of sites is to calculate r2. The average distance between polymorphisms, at which r2 drops below 0.1 - a rough estimate of the resolution. The rate of LD decay may also be locus specific as differences in recombination rate, mutation rate, and selection history can affect LD patterns.
    • -- LD measures the closeness of the genetic associationbetween markers and a particular trait.-- May be used to identify markers in close proximity tothe gene(s) responsible for the trait.
    • Association mapping is good for, 5000 times higher resolution than using F2 populations Surveys tens of alleles – while in standard methods – only a maximum of two alleles Linkage disequilibrium and selection – keys to association analysis Rely on – the extensive history of mutation – recombination to dissect a trait
    • Materials Genotypic data  100 genotypes from each cluster – no closely related lines.  One line from one taxon only.  Has to be as diverse it could be – Extensive recombination history.  50 - 150 markers in a non random mated population – Good statistical power!! – Modest number of SSRs – large numbers of SNPs, – AFLP may provide a good compromise Phenotypic data? – Across 2-3 seasons in replications
    • A standard procedure for association analysis on candidate genes: 1. Select positional candidate genes using existing QTL and positional cloning studies 2. Choose germplasm that will capture the bulk of diversity present. (When possible, use inbred lines) 3. Score phenotypic traits in replicated trials 4. Amplify and sequence candidate genes 5. Manipulate sequence into valid alignments and identify polymorphisms 6. Obtain diversity estimates and evaluate patterns of selection 7. Statistically evaluate associations between genotypes and phenotypes taking population structure into account
    • Sequence Manipulation Softwares Phred and Phrap (http://www.codoncode.com/) - to assess sequence quality and contig (join) sequences Biolign (http://www.mbio.ncsu.edu/BioEdit/bioedit.html) - to edit multiple alignments of contigs and evaluate SNPs (custom software package) MegAlign from DNASTAR Sequencher from GeneCodes (http://www.genecodes.com) offer similar features
    • Association Analysis SoftwarePopulation Structure: STRUCTURE (http://pritch.bsd.uchicago.edu)Linkage Disequilibrium: – Arlequin (http://lgb.unige.ch/arlequin) – TASSEL (http://www.maizegenetics.net) (ANOVA and regression analysis) – PowerMarker (http://www.statgen.ncsu.edu) – DnaSP (http://www.bio.ub.es/~julio/DnaSP.html)STRAT - (http://pritch.bsd.uchicago.edu) - for testing association of binary traits across structured populationsSAS (http://www.sas.com) carries out a wide range of statistics useful for association analysis.
    • TASSEL Trait Analysis byaSSociation, Evolution and Linkage
    • Analysis Mode Result Mode
    • ONLINE TOOL IN TASSEL
    • DATA MODELS IN EXCEL
    • LD Plot
    • DIVERSITY & CLUSTERS
    • Conclusions1. Mapping with F2 or derived populations is powerful for evaluating two alleles with low resolution.2. Association analysis can evaluate numerous alleles at high resolution.3. These two approaches are complementary.4. The successful integration - will allow the rapid dissection of almost any trait within a few years time.5. The key to association analysis is the choice of germplasm, quality of phenotypic data, and use of statistical analyses to control for population structure.6. The combination of association mapping and QTL mapping could make it routine to dissect complex traits.