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Table 2  P  -values of associations between candidate genes and SHR incidence in sunflower

From: Association mapping in sunflower for sclerotinia head rot resistance

SUNFLOWER P MATRIX Q MATRIX
GENE ID (T = 0.2) (T = 0.8) (T = 0.2) (T = 0.8)
 HaMT  0.8400 0.8356 0.8237 0.8192
 HaPRP2  0.9493 0.9225 0.4897 0.9136
 HaCytP450C  0.7856 0.7820 0.4897 0.7488
 HaROPGEF2  0.9142 0.9486 0.9087 0.9454
 HaPP2C  0.7153 0.7256 0.6797 0.6918
 HaRIC_A  0.2094 0.2112 0.2015 0.2036
 HaRIC_B  0.0098** 0.0096** 0.0066** 0.0066**
 HaHP2  0.5818 0.5993 0.7514 0.5113
 HaZFHD  0.4526 0.4539 0.3443 0.3472
 HaGDPDI  0.9807 0.9811 0.9770 0.9775
 HaWP  0.4699 0.4645 0.4501 0.4449
 HaTRP  0.3764 0.3707 0.3501 0.9142
 HaPAL  0.1635 0.1646 0.1342 0.1359
 HaWRKY5  0.2255 0.2249 0.1398 0.1408
 HaWRKY7  0.1069 0.1019 0.0933 0.0892
 HaGLP4  0.3487 0.3567 0.3128 0.3219
  1. Kinship relationships were obtained as suggested by Bernardo [41]. The K matrix was calculated as K ij T = S ij 1 1 T + 1 , where T is the probability that two alleles are alike in state, given that they are not identical by descent. In practice, T is unknown, but different T values (0.2, 0.3, 0.7, 0.8, only showing data for 0.2 and 0.8) were evaluated to reach the maximum likelihood in model (1) explained in Methods Section. **P < 0.01.