Table 3.
Analysis of variance (ANOVA) results from a simple model in which each of the four detected QTL are represented by their peak markers
| Reaction Type (11-point scale) | Disease Severity (% leaf area) | |||
|---|---|---|---|---|
| Effecta | R2= 71.8% | R2= 64.5% | ||
| P | % Variation | P | % Variation | |
| 3B | < 0.0001 | 36.4% | < 0.0001 | 22.2% |
| 5A | < 0.0001 | 6.5% | < 0.0001 | 10.2% |
| 2B | < 0.0001 | 4.2% | < 0.0001 | 4.5% |
| 2A | < 0.0001 | 1.1% | < 0.0001 | 2.3% |
| 3B × 2B | < 0.0001 | 2.3% | < 0.0001 | 3.0% |
| 5A × 2B | < 0.0001 | 1.9% | < 0.0001 | 2.7% |
| 3B × 5A | < 0.0001 | 1.8% | < 0.0001 | 2.4% |
| 5A × 2A | 0.0137 | 0.1% | < 0.0001 | 0.7% |
| 3B × 2A | 0.0087 | 0.1% | 0.0049 | 0.3% |
| 2B × 2A | 0.1060 (NS) | 0.0% | 0.0647 (NS) | 0.1% |
a
The peak markers used to represent the four QTL in this model are gwm533.1 (3B), cfa2149 (5A), wmc474 (2B), and wPt-5839 (2A). Included in the model are the main effects of the four QTL, the first-order interactions among these QTL, years (not shown), and blocks within the field (nested within years, also not shown). P-values are presented for all main and first-order QTL effects. The overall model R2 values for the two phenotypic datasets are provided, and the percents of total phenotypic variation explained by each effect are also given.