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Statistical association of genotype and phenotype

Statistical association of genotype and phenotype. Linkage map. Fig. 3 in Collard et al. Euphytica (2005) 142: 169–196. Linkage map. Fig. 7 in Collard et al. Euphytica (2005) 142: 169–196. Association between genotype and phenotype. Fig. 9 in Collard et al. Euphytica (2005) 142: 169–196.

michael-crosby
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Statistical association of genotype and phenotype

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  1. Statistical association of genotype and phenotype

  2. Linkage map Fig. 3 in Collard et al. Euphytica (2005) 142: 169–196

  3. Linkage map Fig. 7 in Collard et al. Euphytica (2005) 142: 169–196

  4. Association between genotype and phenotype Fig. 9 in Collard et al. Euphytica (2005) 142: 169–196

  5. Association between genotype and phenotype

  6. Single marker analysis • Using e.g., ANOVA, regression • However, can’t distinguish between effect size and distance between marker and QTL

  7. Interval mapping • Uses multiple markers at a time • Uses flanking marker genotypess to infer probability of genotype at intervals between the markers • Associates probability of genotype with phenotype

  8. Association between genotype and phenotype

  9. Association between genotype and phenotype • Linear regression

  10. Association between genotype and phenotype • Maximum likelihood LOD score = log(maximum likelihood with a QTL) maximum likelihood without a QTL

  11. Selective genotyping • Genotyping is expensive and time consuming • May be more efficient to genotype only the most phenotypically extreme individuals Darvasi and Soller 1992, Theor Appl Genet 85: 353-359

  12. Selective genotyping • Genotyping is expensive and time consuming • May be more efficient to genotype only the most phenotypically extreme individuals • Selective genotyping may reduce power to resolve linked QTL • Selective genotyping may affect estimates of QTL effect size

  13. Beavis effect • Small sample sizes may lead to overestimation of QTL effect sizes

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