1. Statistical association of genotype and phenotype

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

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

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

5. Association between genotype and phenotype Individual Marker 1Marker 2Marker 3Marker 4Marker 5Marker 6Phenotype A1111111111110.07 B1111111111110.35 C2222222222220.46 D2222222222220.67 E1212121212120.41 F1212121212120.30

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 Individual Marker 1Marker 2Marker 3Marker 4Marker 5Marker 6Phenotype A1111111111110.07 B1111111111110.35 C2222222222220.46 D2222222222220.67 E1212121212120.41 F1212121212120.30

10. Linear regression Association between genotype and phenotype

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

12. 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

13. 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

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