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Table 2 Main effect QTL (R2 > 10%) for plant architecture traits in the F2:3 population

From: Maize plant architecture trait QTL mapping and candidate gene identification based on multiple environments and double populations

Trait

Environment

QTL

Chr

Marker interval

Position(cM)

Position(bp)

LOD

Add

R2(%)

PH

2016 Changchun

qPH1-1

3

umc2269-bnlg1505

331.5- 336.5

156,958,516–162,111,302

11.28

23.27

21.96

2017 Changchun

qPH2-1

3

umc2265-umc1839

296.5–313.5

157,012,964–162,111,302

11.89

21.56

20.72

2018 Gongzhuling

qPH5-1

9

umc109-umc1170

309.5–336.5

2,940,677–12,687,973

4.1145

13.51

11.5094

EH

2017 Changchun

qEH2-1

1

umc1723a-bnlg1803

23.5–39.5

12,448,970–28,638,545

7.18

9.33

11.43

2017 Gongzhuling

qEH3-1

3

umc2265-umc1839

306.5–319.5

157,012,964–162,111,302

7.19

9.08

13.38

2018 Changchun

qEH4-1

10

umc1824c-umc1589

411.5- 426.5

95,315,410–110,657,182

8.24

-11.57

16.21

2018 Gongzhuling

qEH5-2

3

umc2265-umc1839

296.5–314.5

157,012,964–162,111,302

7.30

8.59

10.23

 

qEH5-3

4

umc2287-umc1371

32.5- 42.5

138,472,340–236,999,463

6.49

6.18

10.53

LA

2017 Changchun

qLA2-2

3

umc2268- umc1641

376.5–385.5

184,713,010–230,956,846

13.898

5.905

24.226

2018 Changchun

qLA4-1

3

umc2268-umc1641

376.5–385.5

184,713,010–230,956,846

5.097

4.583

10.413

IL

2018 Changchun

qIL4-2

10

phi054-umc2705

130.5–135.5

31,183,136–59,002,720

26.608

-2.812

30.748

 

qIL4-3

10

umc1824c-umc1589

418.5–432.5

95,315,410–110,657,182

13.989

-2.260

19.545

2018 Gongzhuling

qIL5-2

10

umc1824c-umc1589

420.5–428.5

95,315,410–110,657,182

12.401

-3.495

23.418