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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.