Rice Science ›› 2015, Vol. 22 ›› Issue (6): 264-274.DOI: 10.1016/S1672-6308(14)60306-1
• Orginal Article • Previous Articles Next Articles
Chao Xiang1, Jie Ren1,2,3, Xiu-qin Zhao1, Zai-song Ding1, Jing Zhang1,2, Chao Wang1,2, Jun-wei Zhang1,2, Augustino Joseph Charles1, Qiang Zhang1, Yun-long Pang1, Yong-ming Gao1(), Ying-yao Shi2(
)
Received:
2015-04-06
Accepted:
2015-05-08
Online:
2015-06-06
Published:
2015-09-15
Chao Xiang, Jie Ren, Xiu-qin Zhao, Zai-song Ding, Jing Zhang, Chao Wang, Jun-wei Zhang, Augustino Joseph Charles, Qiang Zhang, Yun-long Pang, Yong-ming Gao, Ying-yao Shi. Genetic Dissection of Low Phosphorus Tolerance Related Traits Using Selected Introgression Lines in Rice[J]. Rice Science, 2015, 22(6): 264-274.
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.ricesci.org/EN/10.1016/S1672-6308(14)60306-1
Sampling stage | Treatment | Organic matter | Total N | Alkali-hydrolyzable | Olsen-P | Available K | pH |
---|---|---|---|---|---|---|---|
(g/kg) | (g/kg) | N (g/kg) | (g/kg) | (g/kg) | |||
Before sowing | A | 13.71 | 1.11 | 0.06 | 0.04 | 0.1 | 8.4 |
B | 7.85 | 0.57 | 0.04 | 0.01 | 0.07 | 8.6 | |
C | 8.2 | 0.62 | 0.04 | 0.01 | 0.07 | 8.6 | |
Elongation stage (7 d after the first fertilizer application) | A | - | 1.12 | 0.08 | 0.04 | - | - |
B | - | 0.55 | 0.04 | 0.01 | - | - | |
C | - | 0.56 | 0.04 | 0.01 | - | - | |
Before booting stage (before the second fertilizer application) | A | - | 0.96 | 0.07 | 0.03 | - | - |
B | - | 0.51 | 0.04 | 0.01 | - | - | |
C | - | 0.53 | 0.04 | 0.01 | - | - | |
Booting stage (7 d after the second fertilizer application) | A | - | 0.95 | 0.06 | 0.03 | - | - |
B | - | 0.55 | 0.05 | 0.01 | - | - | |
C | - | 0.48 | 0.04 | 0.01 | - | - | |
After harvest | A | 13.35 | 1.02 | 0.06 | 0.03 | 0.08 | 8.2 |
B | 7.42 | 0.53 | 0.03 | 0.01 | 0.06 | 8.2 | |
C | 7.05 | 0.54 | 0.03 | 0.01 | 0.06 | 8.2 |
Table 1 Soil organic matter and nitrogen (N), phosphorus (P) and potassium (K) contents of trial area for different treatments in Langfang, Hebei Province, China.
Sampling stage | Treatment | Organic matter | Total N | Alkali-hydrolyzable | Olsen-P | Available K | pH |
---|---|---|---|---|---|---|---|
(g/kg) | (g/kg) | N (g/kg) | (g/kg) | (g/kg) | |||
Before sowing | A | 13.71 | 1.11 | 0.06 | 0.04 | 0.1 | 8.4 |
B | 7.85 | 0.57 | 0.04 | 0.01 | 0.07 | 8.6 | |
C | 8.2 | 0.62 | 0.04 | 0.01 | 0.07 | 8.6 | |
Elongation stage (7 d after the first fertilizer application) | A | - | 1.12 | 0.08 | 0.04 | - | - |
B | - | 0.55 | 0.04 | 0.01 | - | - | |
C | - | 0.56 | 0.04 | 0.01 | - | - | |
Before booting stage (before the second fertilizer application) | A | - | 0.96 | 0.07 | 0.03 | - | - |
B | - | 0.51 | 0.04 | 0.01 | - | - | |
C | - | 0.53 | 0.04 | 0.01 | - | - | |
Booting stage (7 d after the second fertilizer application) | A | - | 0.95 | 0.06 | 0.03 | - | - |
B | - | 0.55 | 0.05 | 0.01 | - | - | |
C | - | 0.48 | 0.04 | 0.01 | - | - | |
After harvest | A | 13.35 | 1.02 | 0.06 | 0.03 | 0.08 | 8.2 |
B | 7.42 | 0.53 | 0.03 | 0.01 | 0.06 | 8.2 | |
C | 7.05 | 0.54 | 0.03 | 0.01 | 0.06 | 8.2 |
Material | Treatment | RRL (cm) | RRW (g) | RSW (g) | RWRSR | RTW (g) |
---|---|---|---|---|---|---|
Shuhui 527 | ||||||
Mean ± SD | E-D | 1.8 ± 2.6 a | 0.015 ± 0.003 b | 0.048 ± 0.018 a | 0.039 ± 0.027 b | 0.062 ± 0.021 a |
F-D | 4.0 ± 0.3 a | 0.026 ± 0.000 a | 0.030 ± 0.009 a | 0.207 ± 0.035 a | 0.056 ± 0.009 a | |
Minghui 86 | ||||||
Mean ± SD | E-D | 0.1 ± 1.0 a | 0.006 ± 0.008 a | 0.011 ± 0.015 a | 0.011 ± 0.067 b | -0.005 ± 0.062 a |
F-D | 0.6 ± 0.9 a | 0.008 ± 0.009 a | -0.005 ± 0.023 a | 0.160 ± 0.086 a | 0.003 ± 0.027 a | |
Yetuozai (1) | ||||||
Mean ± SD | E-D | 0.5 ± 1.8 a | 0.003 ± 0.012 a | 0.006 ± 0.038 a | 0.021 ± 0.082 a | 0.010 ± 0.049 a |
F-D | -0.1 ± 2.8 a | 0.009 ± 0.009 a | 0.001 ± 0.022 a | 0.107 ± 0.086 a | 0.009 ± 0.029 a | |
Yetuozai (2) | ||||||
Mean ± SD | E-D | 0.1 ± 1.1 b | 0.001 ± 0.007 a | -0.001 ± 0.008 a | 0.013 ± 0.071 a | -0.002 ± 0.015 a |
F-D | 1.8 ± 1.6 a | 0.001 ± 0.007 a | -0.021 ± 0.020 b | 0.135 ± 0.144 a | -0.020 ± 0.022 a | |
Shuhui 527/Yetuozai population (SY) | ||||||
Mean ± SD | E-D | 0.3 ± 0.9 a | 0.005 ± 0.017 a | 0.001 ± 0.033 a | 0.023 ± 0.042 a | 0.008 ± 0.045 a |
F-D | 0.6 ± 1.1 a | 0.007 ± 0.010 a | -0.015 ± 0.035 a | 0.102 ± 0.072 a | -0.007 ± 0.042 a | |
Range | E-D | -2.1-2.9 | -0.037-0.097 | -0.153-0.059 | -0.102-0.131 | -0.180-0.125 |
F-D | -2.8-3.1 | -0.015-0.040 | -0.116-0.073 | -0.084-0.406 | -0.131-0.093 | |
Minghui 86/Yetuozai population (MY) | ||||||
Mean ± SD | E-D | 0.2 ± 1.2 b | 0.001 ± 0.008 a | -0.007 ± 0.019 a | 0.026 ± 0.044 b | -0.006 ± 0.025 a |
F-D | 0.9 ± 1.0 a | 0.004 ± 0.009 a | -0.027 ± 0.019 b | 0.154 ± 0.112 a | -0.023 ± 0.026 b | |
Range | E-D | -2.4-1.6 | -0.014-0.014 | -0.043-0.044 | -0.070-0.127 | -0.057-0.057 |
F-D | -1.3-3.0 | -0.011-0.030 | -0.065-0.024 | 0.054-0.839 | -0.064-0.054 |
Table 3 Phenotypic performances of measured traits for introgression lines and their parents under nutrient solution culture conditions in Beijing, China.
Material | Treatment | RRL (cm) | RRW (g) | RSW (g) | RWRSR | RTW (g) |
---|---|---|---|---|---|---|
Shuhui 527 | ||||||
Mean ± SD | E-D | 1.8 ± 2.6 a | 0.015 ± 0.003 b | 0.048 ± 0.018 a | 0.039 ± 0.027 b | 0.062 ± 0.021 a |
F-D | 4.0 ± 0.3 a | 0.026 ± 0.000 a | 0.030 ± 0.009 a | 0.207 ± 0.035 a | 0.056 ± 0.009 a | |
Minghui 86 | ||||||
Mean ± SD | E-D | 0.1 ± 1.0 a | 0.006 ± 0.008 a | 0.011 ± 0.015 a | 0.011 ± 0.067 b | -0.005 ± 0.062 a |
F-D | 0.6 ± 0.9 a | 0.008 ± 0.009 a | -0.005 ± 0.023 a | 0.160 ± 0.086 a | 0.003 ± 0.027 a | |
Yetuozai (1) | ||||||
Mean ± SD | E-D | 0.5 ± 1.8 a | 0.003 ± 0.012 a | 0.006 ± 0.038 a | 0.021 ± 0.082 a | 0.010 ± 0.049 a |
F-D | -0.1 ± 2.8 a | 0.009 ± 0.009 a | 0.001 ± 0.022 a | 0.107 ± 0.086 a | 0.009 ± 0.029 a | |
Yetuozai (2) | ||||||
Mean ± SD | E-D | 0.1 ± 1.1 b | 0.001 ± 0.007 a | -0.001 ± 0.008 a | 0.013 ± 0.071 a | -0.002 ± 0.015 a |
F-D | 1.8 ± 1.6 a | 0.001 ± 0.007 a | -0.021 ± 0.020 b | 0.135 ± 0.144 a | -0.020 ± 0.022 a | |
Shuhui 527/Yetuozai population (SY) | ||||||
Mean ± SD | E-D | 0.3 ± 0.9 a | 0.005 ± 0.017 a | 0.001 ± 0.033 a | 0.023 ± 0.042 a | 0.008 ± 0.045 a |
F-D | 0.6 ± 1.1 a | 0.007 ± 0.010 a | -0.015 ± 0.035 a | 0.102 ± 0.072 a | -0.007 ± 0.042 a | |
Range | E-D | -2.1-2.9 | -0.037-0.097 | -0.153-0.059 | -0.102-0.131 | -0.180-0.125 |
F-D | -2.8-3.1 | -0.015-0.040 | -0.116-0.073 | -0.084-0.406 | -0.131-0.093 | |
Minghui 86/Yetuozai population (MY) | ||||||
Mean ± SD | E-D | 0.2 ± 1.2 b | 0.001 ± 0.008 a | -0.007 ± 0.019 a | 0.026 ± 0.044 b | -0.006 ± 0.025 a |
F-D | 0.9 ± 1.0 a | 0.004 ± 0.009 a | -0.027 ± 0.019 b | 0.154 ± 0.112 a | -0.023 ± 0.026 b | |
Range | E-D | -2.4-1.6 | -0.014-0.014 | -0.043-0.044 | -0.070-0.127 | -0.057-0.057 |
F-D | -1.3-3.0 | -0.011-0.030 | -0.065-0.024 | 0.054-0.839 | -0.064-0.054 |
Treatment | Population | Trait | QTL | Marker | Chromosome | Position (cM) | Bin | Probability | R2 (%) | Additive |
---|---|---|---|---|---|---|---|---|---|---|
A | SY | PN | qPN5.7 | RM26 | 5 | 118.8 | 5.7 | 0.017 | 10.2 | 0.47 |
A | SY | PN | qPN11.3 | RM536 | 11 | 55.1 | 11.3 | 0.005 | 13 | 0.29 |
A | MY | PN | qPN5.3 | RM169 | 5 | 58 | 5.3 | 0.032 | 8.5 | -0.3 |
A | SY | FGP | qFGP11.6 | RM254 | 11 | 110 | 11.6 | 0.017 | 9.7 | -8 |
A | SY | SNP | qSNP6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.016 | 9.8 | 10.48 |
A | SY | SNP | qSNP11.6 | RM254 | 11 | 110 | 11.6 | 0.018 | 9.5 | -9.11 |
A | SY | SF | qSF5.5 | RM164 | 5 | 78.7 | 5.5 | 0.015 | 10 | 1.52 |
A | MY | SF | qSF4.1 | RM335 | 4 | 22 | 4.1 | 0.014 | 11 | -2.53 |
A | MY | SF | qSF12.1 | RM20A | 12 | 3.2 | 12.1 | 0.006 | 13.8 | -4.51 |
A | SY | TGW | qTGW4.1 | RM335 | 4 | 22 | 4.1 | 0.025 | 8.6 | -1.05 |
A | SY | TGW | qTGW5.5 | RM164 | 5 | 78.7 | 5.5 | 0.04 | 7.2 | 0.63 |
A | SY | TGW | qTGW6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.008 | 11.9 | -1 |
A | SY | TGW | qTGW9.3 | RM219 | 9 | 11.7 | 9.3 | 0.017 | 9.5 | -0.83 |
A | MY | TGW | qTGW1.10 | RM200 | 1 | 143.2 | 1.1 | 0.031 | 8.7 | 0.55 |
A | MY | TGW | qTGW3.12 | RM514 | 3 | 216.4 | 3.12 | 0.01 | 12 | 0.64 |
A | SY | GY | qGY6.5 | RM541 | 6 | 76 | 6.5 | 0.009 | 11 | 1.15 |
A | SY | GY | qGY11.6 | RM254 | 11 | 110 | 11.6 | 0.018 | 9.5 | -1.06 |
B | SY | PN | qPN1.7 | RM9 | 1 | 92.4 | 1.7 | 0.047 | 6.8 | 0.32 |
B | SY | PN | qPN11.3 | RM536 | 11 | 55.1 | 11.3 | 0.003 | 14.4 | 0.33 |
B | SY | PN | qPN12.2 | RM155 | 12 | 20.9 | 12.2 | 0.004 | 14.4 | 0.25 |
B | SY | FGP | qFGP11.6 | RM254 | 11 | 110 | 11.6 | 0.007 | 12.2 | -8.56 |
B | MY | FGP | qFGP12.4 | RM511 | 12 | 59.8 | 12.4 | 0.007 | 13.3 | 14.57 |
B | SY | SNP | qSNP11.6 | RM254 | 11 | 110 | 11.6 | 0.006 | 12.7 | -9.26 |
B | MY | SNP | qSNP12.4 | RM511 | 12 | 59.8 | 12.4 | 0.003 | 16.1 | 18.81 |
B | SY | SF | qSF1.7 | RM9 | 1 | 92.4 | 1.7 | 0.022 | 8.9 | -2.3 |
B | SY | TGW | qTGW4.1 | RM335 | 4 | 22 | 4.1 | 0.005 | 12.8 | -1.32 |
B | SY | TGW | qTGW6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.002 | 15.1 | -1.17 |
B | SY | TGW | qTGW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.046 | 6.7 | 0.9 |
B | SY | TGW | qTGW9.3 | RM219 | 9 | 11.7 | 9.3 | 0.014 | 10 | -0.88 |
B | MY | TGW | qTGW1.10 | RM200 | 1 | 143.2 | 1.1 | 0.002 | 16.5 | 0.69 |
B | SY | GY | qGY6.5 | RM541 | 6 | 76 | 6.5 | 0.024 | 8.5 | 0.88 |
B | SY | GY | qGY11.6 | RM254 | 11 | 110 | 11.6 | 0.013 | 10.4 | -0.98 |
C | SY | PN | qPN1.2 | RM283 | 1 | 31.4 | 1.2 | 0.001 | 16.5 | -0.42 |
C | SY | PN | qPN1.7 | RM9 | 1 | 92.4 | 1.7 | 0.005 | 13 | 0.54 |
C | SY | PN | qPN5.7 | RM26 | 5 | 118.8 | 5.7 | 0.007 | 12.6 | 0.65 |
C | SY | PN | qPN6.1 | RM589 | 6 | 3.2 | 6.1 | 0.008 | 11.4 | 0.33 |
C | SY | PN | qPN11.3 | RM536 | 11 | 55.1 | 11.3 | 0.007 | 11.8 | 0.35 |
C | MY | PN | qPN5.3 | RM169 | 5 | 58 | 5.3 | 0.015 | 11 | -0.44 |
C | SY | SNP | qSNP6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.02 | 9.2 | 9.87 |
C | SY | SNP | qSNP11.6 | RM254 | 11 | 110 | 11.6 | 0.039 | 7.3 | -7.75 |
C | SY | SF | qSF1.7 | RM9 | 1 | 92.4 | 1.7 | 0.003 | 14.9 | -3.42 |
C | SY | SF | qSF5.5 | RM164 | 5 | 78.7 | 5.5 | 0.018 | 9.4 | 1.62 |
C | MY | SF | qSF4.1 | RM335 | 4 | 22 | 4.1 | 0.043 | 7.6 | -2.06 |
C | SY | TGW | qTGW4.1 | RM335 | 4 | 22 | 4.1 | 0.007 | 12.3 | -1.08 |
C | SY | TGW | qTGW5.5 | RM164 | 5 | 78.7 | 5.5 | 0.004 | 13.7 | 0.74 |
C | SY | TGW | qTGW6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.004 | 13.7 | -0.92 |
C | SY | TGW | qTGW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.032 | 7.7 | 0.8 |
C | SY | TGW | qTGW9.3 | RM219 | 9 | 11.7 | 9.3 | 0.013 | 10.1 | -0.74 |
C | MY | GY | qGY1.10 | RM200 | 1 | 143.2 | 1.1 | 0.003 | 15.8 | 1.42 |
Table 4 Identification of QTLs for yield traits in two populations under three treatments in Langfang, Hebei Province, China.
Treatment | Population | Trait | QTL | Marker | Chromosome | Position (cM) | Bin | Probability | R2 (%) | Additive |
---|---|---|---|---|---|---|---|---|---|---|
A | SY | PN | qPN5.7 | RM26 | 5 | 118.8 | 5.7 | 0.017 | 10.2 | 0.47 |
A | SY | PN | qPN11.3 | RM536 | 11 | 55.1 | 11.3 | 0.005 | 13 | 0.29 |
A | MY | PN | qPN5.3 | RM169 | 5 | 58 | 5.3 | 0.032 | 8.5 | -0.3 |
A | SY | FGP | qFGP11.6 | RM254 | 11 | 110 | 11.6 | 0.017 | 9.7 | -8 |
A | SY | SNP | qSNP6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.016 | 9.8 | 10.48 |
A | SY | SNP | qSNP11.6 | RM254 | 11 | 110 | 11.6 | 0.018 | 9.5 | -9.11 |
A | SY | SF | qSF5.5 | RM164 | 5 | 78.7 | 5.5 | 0.015 | 10 | 1.52 |
A | MY | SF | qSF4.1 | RM335 | 4 | 22 | 4.1 | 0.014 | 11 | -2.53 |
A | MY | SF | qSF12.1 | RM20A | 12 | 3.2 | 12.1 | 0.006 | 13.8 | -4.51 |
A | SY | TGW | qTGW4.1 | RM335 | 4 | 22 | 4.1 | 0.025 | 8.6 | -1.05 |
A | SY | TGW | qTGW5.5 | RM164 | 5 | 78.7 | 5.5 | 0.04 | 7.2 | 0.63 |
A | SY | TGW | qTGW6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.008 | 11.9 | -1 |
A | SY | TGW | qTGW9.3 | RM219 | 9 | 11.7 | 9.3 | 0.017 | 9.5 | -0.83 |
A | MY | TGW | qTGW1.10 | RM200 | 1 | 143.2 | 1.1 | 0.031 | 8.7 | 0.55 |
A | MY | TGW | qTGW3.12 | RM514 | 3 | 216.4 | 3.12 | 0.01 | 12 | 0.64 |
A | SY | GY | qGY6.5 | RM541 | 6 | 76 | 6.5 | 0.009 | 11 | 1.15 |
A | SY | GY | qGY11.6 | RM254 | 11 | 110 | 11.6 | 0.018 | 9.5 | -1.06 |
B | SY | PN | qPN1.7 | RM9 | 1 | 92.4 | 1.7 | 0.047 | 6.8 | 0.32 |
B | SY | PN | qPN11.3 | RM536 | 11 | 55.1 | 11.3 | 0.003 | 14.4 | 0.33 |
B | SY | PN | qPN12.2 | RM155 | 12 | 20.9 | 12.2 | 0.004 | 14.4 | 0.25 |
B | SY | FGP | qFGP11.6 | RM254 | 11 | 110 | 11.6 | 0.007 | 12.2 | -8.56 |
B | MY | FGP | qFGP12.4 | RM511 | 12 | 59.8 | 12.4 | 0.007 | 13.3 | 14.57 |
B | SY | SNP | qSNP11.6 | RM254 | 11 | 110 | 11.6 | 0.006 | 12.7 | -9.26 |
B | MY | SNP | qSNP12.4 | RM511 | 12 | 59.8 | 12.4 | 0.003 | 16.1 | 18.81 |
B | SY | SF | qSF1.7 | RM9 | 1 | 92.4 | 1.7 | 0.022 | 8.9 | -2.3 |
B | SY | TGW | qTGW4.1 | RM335 | 4 | 22 | 4.1 | 0.005 | 12.8 | -1.32 |
B | SY | TGW | qTGW6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.002 | 15.1 | -1.17 |
B | SY | TGW | qTGW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.046 | 6.7 | 0.9 |
B | SY | TGW | qTGW9.3 | RM219 | 9 | 11.7 | 9.3 | 0.014 | 10 | -0.88 |
B | MY | TGW | qTGW1.10 | RM200 | 1 | 143.2 | 1.1 | 0.002 | 16.5 | 0.69 |
B | SY | GY | qGY6.5 | RM541 | 6 | 76 | 6.5 | 0.024 | 8.5 | 0.88 |
B | SY | GY | qGY11.6 | RM254 | 11 | 110 | 11.6 | 0.013 | 10.4 | -0.98 |
C | SY | PN | qPN1.2 | RM283 | 1 | 31.4 | 1.2 | 0.001 | 16.5 | -0.42 |
C | SY | PN | qPN1.7 | RM9 | 1 | 92.4 | 1.7 | 0.005 | 13 | 0.54 |
C | SY | PN | qPN5.7 | RM26 | 5 | 118.8 | 5.7 | 0.007 | 12.6 | 0.65 |
C | SY | PN | qPN6.1 | RM589 | 6 | 3.2 | 6.1 | 0.008 | 11.4 | 0.33 |
C | SY | PN | qPN11.3 | RM536 | 11 | 55.1 | 11.3 | 0.007 | 11.8 | 0.35 |
C | MY | PN | qPN5.3 | RM169 | 5 | 58 | 5.3 | 0.015 | 11 | -0.44 |
C | SY | SNP | qSNP6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.02 | 9.2 | 9.87 |
C | SY | SNP | qSNP11.6 | RM254 | 11 | 110 | 11.6 | 0.039 | 7.3 | -7.75 |
C | SY | SF | qSF1.7 | RM9 | 1 | 92.4 | 1.7 | 0.003 | 14.9 | -3.42 |
C | SY | SF | qSF5.5 | RM164 | 5 | 78.7 | 5.5 | 0.018 | 9.4 | 1.62 |
C | MY | SF | qSF4.1 | RM335 | 4 | 22 | 4.1 | 0.043 | 7.6 | -2.06 |
C | SY | TGW | qTGW4.1 | RM335 | 4 | 22 | 4.1 | 0.007 | 12.3 | -1.08 |
C | SY | TGW | qTGW5.5 | RM164 | 5 | 78.7 | 5.5 | 0.004 | 13.7 | 0.74 |
C | SY | TGW | qTGW6.6 | RM5463 | 6 | 124.4 | 6.6 | 0.004 | 13.7 | -0.92 |
C | SY | TGW | qTGW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.032 | 7.7 | 0.8 |
C | SY | TGW | qTGW9.3 | RM219 | 9 | 11.7 | 9.3 | 0.013 | 10.1 | -0.74 |
C | MY | GY | qGY1.10 | RM200 | 1 | 143.2 | 1.1 | 0.003 | 15.8 | 1.42 |
Fig. 1. Identified QTLs for measured traits in two introgressed line populations under two environments.(A, Normal fertilization treatment in normal soil; B, Normal fertilization treatment in barren soil; C, Low-phosphorus stress in barren soil; PN, Panicle number per plant; FGP, Filled grain number per panicle; SNP, Spikelet number per panicle; SF, Spikelet fertility; TGW, 1000-grain weight; GY, Grain yield per plant; RRL, Relative root length; RRW, Relative root dry weight; RSW, Relative shoot dry weight; RTW, Relative total dry weight; RWRSR, Relative root-shoot ratio of dry weight; D, Control; E, Nutrient solution with 1/3 phosphorus of the control; F, Nutrient solution without phosphorus; Chr, Chromosome. * below the icon represents the QTL identified in Minghui 86/Yetuozai population, otherwise, in Shuhui 527/Yetuozai population.)
Treatment | Population | Trait | QTL | Marker | Chromosome | Position (cM) | Bin | Probability | R2 (%) | Additive |
---|---|---|---|---|---|---|---|---|---|---|
E-D | SY | RRL | qRRL9.3 | RM444 | 9 | 3.3 | 9.3 | 0.014 | 11.5 | 0.397 |
E-D | SY | RRL | qRRL12.4 | RM511 | 12 | 59.8 | 12.4 | 0.009 | 13 | 0.289 |
E-D | MY | RRL | qRRL6.6 | RM3307 | 6 | 113.4 | 6.6 | 0.007 | 14.4 | -0.403 |
E-D | MY | RRL | qRRL9.7 | RM108 | 9 | 73.3 | 9.7 | 0.034 | 11.4 | 0.353 |
E-D | SY | RRW | qRRW4.1 | RM335 | 4 | 21.5 | 4.1 | 0.019 | 10.9 | 0.009 |
E-D | SY | RRW | qRRW6.3 | RM510 | 6 | 20.8 | 6.3 | 0.035 | 8.8 | -0.007 |
E-D | SY | RRW | qRRW7.7 | RM47 | 7 | 90 | 7.7 | 0.036 | 8.8 | -0.009 |
E-D | SY | RRW | qRRW9.7 | RM160 | 9 | 82.4 | 9.7 | 0.03 | 9.9 | 0.006 |
E-D | MY | RRW | qRRW2.3 | RM145 | 2 | 49.8 | 2.3 | 0.028 | 9.6 | 0.002 |
E-D | MY | RRW | qRRW3.12 | RM514 | 3 | 216.4 | 3.12 | 0.049 | 7.9 | -0.002 |
E-D | MY | RRW | qRRW12.2 | RM155 | 12 | 20.9 | 12.2 | 0.016 | 11.5 | 0.003 |
E-D | SY | RSW | qRSW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.037 | 8.4 | -0.01 |
E-D | MY | RSW | qRSW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.032 | 9.2 | -0.004 |
E-D | MY | RSW | qRSW12.2 | RM155 | 12 | 20.9 | 12.2 | 0.04 | 8.5 | 0.007 |
E-D | SY | RTW | qRTW7.7 | RM47 | 7 | 90 | 7.7 | 0.039 | 8.7 | -0.024 |
E-D | SY | RTW | qRTW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.024 | 10.2 | -0.014 |
E-D | MY | RTW | qRTW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.038 | 8.7 | -0.006 |
E-D | MY | RTW | qRTW10.6 | RM590 | 10 | 117.2 | 10.6 | 0.046 | 8 | -0.01 |
E-D | MY | RTW | qRTW12.2 | RM155 | 12 | 20.9 | 12.2 | 0.035 | 9 | 0.01 |
E-D | SY | RWRSR | qRWRSR2.5 | RM3688 | 2 | 88.2 | 2.5 | 0.02 | 10.8 | -0.019 |
E-D | SY | RWRSR | qRWRSR6.1 | RM589 | 6 | 3.2 | 6.1 | 0.022 | 10.3 | -0.017 |
E-D | SY | RWRSR | qRWRSR10.5 | RM184 | 10 | 58 | 10.5 | 0.008 | 13.4 | 0.015 |
E-D | MY | RWRSR | qRWRSR3.12 | RM514 | 3 | 216.4 | 3.12 | 0.019 | 11 | -0.015 |
E-D | MY | RWRSR | qRWRSR5.8 | RM538 | 5 | 132.7 | 5.8 | 0.046 | 8 | 0.021 |
E-D | MY | RWRSR | qRWRSR11.4 | RM287 | 11 | 68.6 | 11.4 | 0.048 | 7.9 | 0.012 |
E-D | MY | RWRSR | qRWRSR12.2 | RM155 | 12 | 20.9 | 12.2 | 0.005 | 15 | 0.007 |
F-D | SY | RRL | qRRL2.4 | RM521 | 2 | 62.2 | 2.4 | 0.005 | 14.5 | 0.392 |
F-D | SY | RRL | qRRL5.6 | RM3295 | 5 | 91.2 | 5.6 | 0.003 | 16.6 | -0.489 |
F-D | MY | RRL | qRRL4.8 | RM349 | 4 | 146.8 | 4.8 | 0.006 | 15.1 | 0.835 |
F-D | MY | RRL | qRRL7.1 | RM481 | 7 | 3.2 | 7.1 | 0.015 | 12.1 | 0.166 |
F-D | SY | RRW | qRRW2.4 | RM290 | 2 | 66 | 2.4 | 0.047 | 8.5 | 0.004 |
F-D | SY | RRW | qRRW12.1 | RM20A | 12 | 3.2 | 12.1 | 0.049 | 7.7 | 0.003 |
F-D | SY | RRW | qRRW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.007 | 14.1 | -0.004 |
F-D | MY | RRW | qRRW1.3 | RM576 | 1 | 51 | 1.3 | 0.047 | 8.2 | 0.003 |
F-D | MY | RRW | qRRW4.4 | RM142 | 4 | 68.5 | 4.4 | 0.016 | 11.5 | -0.003 |
F-D | SY | RSW | qRSW1.2 | RM283 | 1 | 31.4 | 1.2 | 0.036 | 8.5 | 0.012 |
F-D | MY | RSW | qRSW3.8 | RM16 | 3 | 131.5 | 3.8 | 0.028 | 9.7 | -0.012 |
F-D | MY | RSW | qRSW5.7 | RM26 | 5 | 118.8 | 5.7 | 0.039 | 8.7 | 0.002 |
F-D | MY | RSW | qRSW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.006 | 14.6 | -0.009 |
F-D | SY | RTW | qRTW1.2 | RM283 | 1 | 31.4 | 1.2 | 0.039 | 8.4 | 0.015 |
F-D | SY | RTW | qRTW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.034 | 8.9 | -0.017 |
F-D | MY | RTW | qRTW3.8 | RM16 | 3 | 131.5 | 3.8 | 0.021 | 10.6 | -0.017 |
F-D | MY | RTW | qRTW3.12 | RM514 | 3 | 216.4 | 3.12 | 0.043 | 8.2 | -0.007 |
F-D | MY | RTW | qRTW5.7 | RM26 | 5 | 118.8 | 5.7 | 0.032 | 9.4 | 0.001 |
F-D | MY | RTW | qRTW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.005 | 15.4 | -0.01 |
F-D | SY | RWRSR | qRWRSR9.3 | RM219 | 9 | 11.7 | 9.3 | 0.044 | 8 | 0.024 |
F-D | MY | RWRSR | qRWRSR5.2 | RM574 | 5 | 41 | 5.2 | 0.006 | 14.7 | 0.056 |
F-D | MY | RWRSR | qRWRSR6.3 | RM510 | 6 | 20.8 | 6.3 | 0.012 | 12.6 | 0.043 |
Table 5 Identification of QTLs for measured traits in two populations in Beijing, China.
Treatment | Population | Trait | QTL | Marker | Chromosome | Position (cM) | Bin | Probability | R2 (%) | Additive |
---|---|---|---|---|---|---|---|---|---|---|
E-D | SY | RRL | qRRL9.3 | RM444 | 9 | 3.3 | 9.3 | 0.014 | 11.5 | 0.397 |
E-D | SY | RRL | qRRL12.4 | RM511 | 12 | 59.8 | 12.4 | 0.009 | 13 | 0.289 |
E-D | MY | RRL | qRRL6.6 | RM3307 | 6 | 113.4 | 6.6 | 0.007 | 14.4 | -0.403 |
E-D | MY | RRL | qRRL9.7 | RM108 | 9 | 73.3 | 9.7 | 0.034 | 11.4 | 0.353 |
E-D | SY | RRW | qRRW4.1 | RM335 | 4 | 21.5 | 4.1 | 0.019 | 10.9 | 0.009 |
E-D | SY | RRW | qRRW6.3 | RM510 | 6 | 20.8 | 6.3 | 0.035 | 8.8 | -0.007 |
E-D | SY | RRW | qRRW7.7 | RM47 | 7 | 90 | 7.7 | 0.036 | 8.8 | -0.009 |
E-D | SY | RRW | qRRW9.7 | RM160 | 9 | 82.4 | 9.7 | 0.03 | 9.9 | 0.006 |
E-D | MY | RRW | qRRW2.3 | RM145 | 2 | 49.8 | 2.3 | 0.028 | 9.6 | 0.002 |
E-D | MY | RRW | qRRW3.12 | RM514 | 3 | 216.4 | 3.12 | 0.049 | 7.9 | -0.002 |
E-D | MY | RRW | qRRW12.2 | RM155 | 12 | 20.9 | 12.2 | 0.016 | 11.5 | 0.003 |
E-D | SY | RSW | qRSW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.037 | 8.4 | -0.01 |
E-D | MY | RSW | qRSW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.032 | 9.2 | -0.004 |
E-D | MY | RSW | qRSW12.2 | RM155 | 12 | 20.9 | 12.2 | 0.04 | 8.5 | 0.007 |
E-D | SY | RTW | qRTW7.7 | RM47 | 7 | 90 | 7.7 | 0.039 | 8.7 | -0.024 |
E-D | SY | RTW | qRTW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.024 | 10.2 | -0.014 |
E-D | MY | RTW | qRTW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.038 | 8.7 | -0.006 |
E-D | MY | RTW | qRTW10.6 | RM590 | 10 | 117.2 | 10.6 | 0.046 | 8 | -0.01 |
E-D | MY | RTW | qRTW12.2 | RM155 | 12 | 20.9 | 12.2 | 0.035 | 9 | 0.01 |
E-D | SY | RWRSR | qRWRSR2.5 | RM3688 | 2 | 88.2 | 2.5 | 0.02 | 10.8 | -0.019 |
E-D | SY | RWRSR | qRWRSR6.1 | RM589 | 6 | 3.2 | 6.1 | 0.022 | 10.3 | -0.017 |
E-D | SY | RWRSR | qRWRSR10.5 | RM184 | 10 | 58 | 10.5 | 0.008 | 13.4 | 0.015 |
E-D | MY | RWRSR | qRWRSR3.12 | RM514 | 3 | 216.4 | 3.12 | 0.019 | 11 | -0.015 |
E-D | MY | RWRSR | qRWRSR5.8 | RM538 | 5 | 132.7 | 5.8 | 0.046 | 8 | 0.021 |
E-D | MY | RWRSR | qRWRSR11.4 | RM287 | 11 | 68.6 | 11.4 | 0.048 | 7.9 | 0.012 |
E-D | MY | RWRSR | qRWRSR12.2 | RM155 | 12 | 20.9 | 12.2 | 0.005 | 15 | 0.007 |
F-D | SY | RRL | qRRL2.4 | RM521 | 2 | 62.2 | 2.4 | 0.005 | 14.5 | 0.392 |
F-D | SY | RRL | qRRL5.6 | RM3295 | 5 | 91.2 | 5.6 | 0.003 | 16.6 | -0.489 |
F-D | MY | RRL | qRRL4.8 | RM349 | 4 | 146.8 | 4.8 | 0.006 | 15.1 | 0.835 |
F-D | MY | RRL | qRRL7.1 | RM481 | 7 | 3.2 | 7.1 | 0.015 | 12.1 | 0.166 |
F-D | SY | RRW | qRRW2.4 | RM290 | 2 | 66 | 2.4 | 0.047 | 8.5 | 0.004 |
F-D | SY | RRW | qRRW12.1 | RM20A | 12 | 3.2 | 12.1 | 0.049 | 7.7 | 0.003 |
F-D | SY | RRW | qRRW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.007 | 14.1 | -0.004 |
F-D | MY | RRW | qRRW1.3 | RM576 | 1 | 51 | 1.3 | 0.047 | 8.2 | 0.003 |
F-D | MY | RRW | qRRW4.4 | RM142 | 4 | 68.5 | 4.4 | 0.016 | 11.5 | -0.003 |
F-D | SY | RSW | qRSW1.2 | RM283 | 1 | 31.4 | 1.2 | 0.036 | 8.5 | 0.012 |
F-D | MY | RSW | qRSW3.8 | RM16 | 3 | 131.5 | 3.8 | 0.028 | 9.7 | -0.012 |
F-D | MY | RSW | qRSW5.7 | RM26 | 5 | 118.8 | 5.7 | 0.039 | 8.7 | 0.002 |
F-D | MY | RSW | qRSW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.006 | 14.6 | -0.009 |
F-D | SY | RTW | qRTW1.2 | RM283 | 1 | 31.4 | 1.2 | 0.039 | 8.4 | 0.015 |
F-D | SY | RTW | qRTW12.4 | RM511 | 12 | 59.8 | 12.4 | 0.034 | 8.9 | -0.017 |
F-D | MY | RTW | qRTW3.8 | RM16 | 3 | 131.5 | 3.8 | 0.021 | 10.6 | -0.017 |
F-D | MY | RTW | qRTW3.12 | RM514 | 3 | 216.4 | 3.12 | 0.043 | 8.2 | -0.007 |
F-D | MY | RTW | qRTW5.7 | RM26 | 5 | 118.8 | 5.7 | 0.032 | 9.4 | 0.001 |
F-D | MY | RTW | qRTW7.1 | RM481 | 7 | 3.2 | 7.1 | 0.005 | 15.4 | -0.01 |
F-D | SY | RWRSR | qRWRSR9.3 | RM219 | 9 | 11.7 | 9.3 | 0.044 | 8 | 0.024 |
F-D | MY | RWRSR | qRWRSR5.2 | RM574 | 5 | 41 | 5.2 | 0.006 | 14.7 | 0.056 |
F-D | MY | RWRSR | qRWRSR6.3 | RM510 | 6 | 20.8 | 6.3 | 0.012 | 12.6 | 0.043 |
Type | Population | Material | Environment | HD | PH | PN | PL | FGP | SNP | SF | TGW | GY | BI | HI |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(d) | (cm) | (cm) | (%) | (g) | (g) | (g) | ||||||||
Type 1 | MY | BL151 | Langfang, 2013 | 118.7 | 109.3 | 5.1 | 27.4 | 204.6 | 230.2 | 88.5 | 29 | 18.6 | 43 | 0.43 |
Hefei, 2012 | 94 | 119.4 | 6.9 | 26.8 | 109.7 | 160.6 | 68.3 | 29.1 | 21.7 | |||||
MY | BL158 | Langfang, 2013 | 115.7 | 105.8 | 6.2 | 27.5 | 175.7 | 235 | 74.6 | 29.3 | 23.8 | 51.6 | 0.46 | |
Hefei, 2012 | 93 | 106.4 | 7.7 | 23.6 | 107.6 | 135.4 | 79.7 | 31.6 | 25.8 | |||||
MY | BL165 | Langfang, 2013 | 119.3 | 100.6 | 6.7 | 25.5 | 170.4 | 234.6 | 73.1 | 20.6 | 19.5 | 46.7 | 0.42 | |
Hefei, 2012 | 90 | 115.4 | 8.3 | 24.9 | 92.3 | 126.9 | 72.5 | 30.1 | 22.8 | |||||
MY | BL167 | Langfang, 2013 | 115.3 | 101.2 | 6.3 | 25.2 | 143.6 | 203.8 | 70.5 | 28.5 | 20.9 | 41.1 | 0.51 | |
Hefei, 2012 | 94 | 107.7 | 8.3 | 24.2 | 105.2 | 140.6 | 74.9 | 25.9 | 22.7 | |||||
MY | BL170 | Langfang, 2013 | 116.7 | 108.1 | 4.7 | 27.6 | 239 | 272.6 | 87.7 | 26.9 | 18.7 | 37.3 | 0.5 | |
Hefei, 2012 | 93 | 120.4 | 6 | 23.7 | 97.7 | 125.2 | 78 | 27.6 | 16.2 | |||||
MY | BL197 | Langfang, 2013 | 117.7 | 93.2 | 4.5 | 27.2 | 170 | 214.8 | 79.1 | 25.3 | 18.5 | 37.1 | 0.5 | |
Hefei, 2012 | 92 | 108 | 7.7 | 25.9 | 92 | 150.1 | 61.4 | 30.3 | 21.4 | |||||
MY | BL198 | Langfang, 2013 | 117.3 | 100.4 | 5.8 | 27.4 | 202.8 | 256.5 | 77.9 | 28 | 22.4 | 45.7 | 0.49 | |
Hefei, 2012 | 92 | 111.9 | 5.3 | 24.3 | 82.5 | 142.3 | 58.9 | 28.5 | 12.5 | |||||
Type 2 | SY | BL66 | Langfang, 2013 | 116.7 | 105.9 | 6.7 | 24.9 | 180.5 | 221.2 | 81.6 | 29.2 | 29.2 | 60 | 0.49 |
Hefei, 2012 | 92 | 109.5 | 7.4 | 24.4 | 116.8 | 148.8 | 78.6 | 30.9 | 26.5 | |||||
MY | BL152 | Langfang, 2013 | 119 | 101.9 | 6.2 | 25.7 | 216.4 | 248.9 | 87 | 25.7 | 26.3 | 49.9 | 0.53 | |
Hefei, 2012 | 94 | 111.5 | 7.8 | 26.7 | 96.2 | 142.1 | 67.9 | 30 | 22.4 | |||||
MY | BL162 | Langfang, 2013 | 117.3 | 107.8 | 5.7 | 29 | 211.3 | 245.3 | 86.2 | 27 | 26.2 | 51 | 0.51 | |
Hefei, 2012 | 94 | 109.7 | 6.4 | 27.7 | 113.6 | 157.8 | 71.9 | 28.5 | 20.4 | |||||
MY | BL172 | Langfang, 2013 | 116.7 | 111 | 5.7 | 27.2 | 139.5 | 169.2 | 82.5 | 27.8 | 18.2 | 37 | 0.49 | |
Hefei, 2012 | 91 | 109.6 | 8.7 | 24.7 | 87.2 | 108.9 | 80 | 30 | 22.7 | |||||
MY | BL190 | Langfang, 2013 | 117.3 | 110.3 | 5.1 | 27.6 | 171.9 | 208.8 | 82.6 | 29.5 | 23 | 46.9 | 0.49 | |
Hefei, 2012 | 91 | 115.2 | 8.4 | 24.9 | 103.3 | 140.6 | 73.6 | 30.6 | 26.3 | |||||
MY | BL192 | Langfang, 2013 | 120.3 | 97.2 | 4.5 | 25.5 | 174.3 | 217.4 | 79.7 | 26.3 | 19.5 | 40.3 | 0.48 | |
Hefei, 2012 | 95 | 102.4 | 8 | 23 | 85.7 | 131.5 | 65.2 | 28.7 | 19.6 | |||||
MY | BL195 | Langfang, 2013 | 118 | 106.9 | 5.1 | 28.2 | 150.1 | 225.4 | 66.4 | 27.8 | 17.6 | 34.6 | 0.51 | |
Hefei, 2012 | 93 | 115.7 | 6.2 | 25.2 | 84 | 138.8 | 60.4 | 29.6 | 15.6 | |||||
Shuhui 527 | Langfang, 2013 | 116.3 | 98.1 | 4.6 | 25.6 | 130.3 | 162.1 | 80.6 | 27.6 | 16.2 | 34.1 | 0.48 | ||
Hefei, 2012 | 92.4 | 99.3 | 8 | 24.7 | 97.7 | 127.9 | 77.2 | 29.9 | 21.3 | |||||
Minghui 86 | Langfang, 2013 | 113.7 | 92.7 | 4.3 | 23.4 | 120.8 | 159.5 | 75.8 | 23.8 | 9.1 | 24.3 | 0.37 | ||
Hefei, 2012 | 93.8 | 106.5 | 8.1 | 26.3 | 82.8 | 143.7 | 61.3 | 27.8 | 16.3 |
Table 6 Trait performance of two IL populations with significant higher yield than the recurrent parents selected under low phosphorus stress conditions in Langfang, Hebei Province and Hefei, Anhui Province, China.
Type | Population | Material | Environment | HD | PH | PN | PL | FGP | SNP | SF | TGW | GY | BI | HI |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(d) | (cm) | (cm) | (%) | (g) | (g) | (g) | ||||||||
Type 1 | MY | BL151 | Langfang, 2013 | 118.7 | 109.3 | 5.1 | 27.4 | 204.6 | 230.2 | 88.5 | 29 | 18.6 | 43 | 0.43 |
Hefei, 2012 | 94 | 119.4 | 6.9 | 26.8 | 109.7 | 160.6 | 68.3 | 29.1 | 21.7 | |||||
MY | BL158 | Langfang, 2013 | 115.7 | 105.8 | 6.2 | 27.5 | 175.7 | 235 | 74.6 | 29.3 | 23.8 | 51.6 | 0.46 | |
Hefei, 2012 | 93 | 106.4 | 7.7 | 23.6 | 107.6 | 135.4 | 79.7 | 31.6 | 25.8 | |||||
MY | BL165 | Langfang, 2013 | 119.3 | 100.6 | 6.7 | 25.5 | 170.4 | 234.6 | 73.1 | 20.6 | 19.5 | 46.7 | 0.42 | |
Hefei, 2012 | 90 | 115.4 | 8.3 | 24.9 | 92.3 | 126.9 | 72.5 | 30.1 | 22.8 | |||||
MY | BL167 | Langfang, 2013 | 115.3 | 101.2 | 6.3 | 25.2 | 143.6 | 203.8 | 70.5 | 28.5 | 20.9 | 41.1 | 0.51 | |
Hefei, 2012 | 94 | 107.7 | 8.3 | 24.2 | 105.2 | 140.6 | 74.9 | 25.9 | 22.7 | |||||
MY | BL170 | Langfang, 2013 | 116.7 | 108.1 | 4.7 | 27.6 | 239 | 272.6 | 87.7 | 26.9 | 18.7 | 37.3 | 0.5 | |
Hefei, 2012 | 93 | 120.4 | 6 | 23.7 | 97.7 | 125.2 | 78 | 27.6 | 16.2 | |||||
MY | BL197 | Langfang, 2013 | 117.7 | 93.2 | 4.5 | 27.2 | 170 | 214.8 | 79.1 | 25.3 | 18.5 | 37.1 | 0.5 | |
Hefei, 2012 | 92 | 108 | 7.7 | 25.9 | 92 | 150.1 | 61.4 | 30.3 | 21.4 | |||||
MY | BL198 | Langfang, 2013 | 117.3 | 100.4 | 5.8 | 27.4 | 202.8 | 256.5 | 77.9 | 28 | 22.4 | 45.7 | 0.49 | |
Hefei, 2012 | 92 | 111.9 | 5.3 | 24.3 | 82.5 | 142.3 | 58.9 | 28.5 | 12.5 | |||||
Type 2 | SY | BL66 | Langfang, 2013 | 116.7 | 105.9 | 6.7 | 24.9 | 180.5 | 221.2 | 81.6 | 29.2 | 29.2 | 60 | 0.49 |
Hefei, 2012 | 92 | 109.5 | 7.4 | 24.4 | 116.8 | 148.8 | 78.6 | 30.9 | 26.5 | |||||
MY | BL152 | Langfang, 2013 | 119 | 101.9 | 6.2 | 25.7 | 216.4 | 248.9 | 87 | 25.7 | 26.3 | 49.9 | 0.53 | |
Hefei, 2012 | 94 | 111.5 | 7.8 | 26.7 | 96.2 | 142.1 | 67.9 | 30 | 22.4 | |||||
MY | BL162 | Langfang, 2013 | 117.3 | 107.8 | 5.7 | 29 | 211.3 | 245.3 | 86.2 | 27 | 26.2 | 51 | 0.51 | |
Hefei, 2012 | 94 | 109.7 | 6.4 | 27.7 | 113.6 | 157.8 | 71.9 | 28.5 | 20.4 | |||||
MY | BL172 | Langfang, 2013 | 116.7 | 111 | 5.7 | 27.2 | 139.5 | 169.2 | 82.5 | 27.8 | 18.2 | 37 | 0.49 | |
Hefei, 2012 | 91 | 109.6 | 8.7 | 24.7 | 87.2 | 108.9 | 80 | 30 | 22.7 | |||||
MY | BL190 | Langfang, 2013 | 117.3 | 110.3 | 5.1 | 27.6 | 171.9 | 208.8 | 82.6 | 29.5 | 23 | 46.9 | 0.49 | |
Hefei, 2012 | 91 | 115.2 | 8.4 | 24.9 | 103.3 | 140.6 | 73.6 | 30.6 | 26.3 | |||||
MY | BL192 | Langfang, 2013 | 120.3 | 97.2 | 4.5 | 25.5 | 174.3 | 217.4 | 79.7 | 26.3 | 19.5 | 40.3 | 0.48 | |
Hefei, 2012 | 95 | 102.4 | 8 | 23 | 85.7 | 131.5 | 65.2 | 28.7 | 19.6 | |||||
MY | BL195 | Langfang, 2013 | 118 | 106.9 | 5.1 | 28.2 | 150.1 | 225.4 | 66.4 | 27.8 | 17.6 | 34.6 | 0.51 | |
Hefei, 2012 | 93 | 115.7 | 6.2 | 25.2 | 84 | 138.8 | 60.4 | 29.6 | 15.6 | |||||
Shuhui 527 | Langfang, 2013 | 116.3 | 98.1 | 4.6 | 25.6 | 130.3 | 162.1 | 80.6 | 27.6 | 16.2 | 34.1 | 0.48 | ||
Hefei, 2012 | 92.4 | 99.3 | 8 | 24.7 | 97.7 | 127.9 | 77.2 | 29.9 | 21.3 | |||||
Minghui 86 | Langfang, 2013 | 113.7 | 92.7 | 4.3 | 23.4 | 120.8 | 159.5 | 75.8 | 23.8 | 9.1 | 24.3 | 0.37 | ||
Hefei, 2012 | 93.8 | 106.5 | 8.1 | 26.3 | 82.8 | 143.7 | 61.3 | 27.8 | 16.3 |
Trait | Marker | Chromosome | Position | Bin | QTL | Treatment | Langfang, Hebei Province | Hefei, Anhui Province | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(cM) | Probability | R2 (%) | Additive | Probability | R2 (%) | Additive | ||||||||||
TGW | RM335 | 4 | 22 | 4.1 | qTGW4.1 | A | 0.025 | 8.6 | -1.1 | 0.01 | 11 | -1.2 | ||||
C | 0.006 | 12.3 | -1.1 | 0.002 | 16 | -1.4 | ||||||||||
TGW | RM5463 | 6 | 124.4 | 6.6 | qTGW6.6 | A | 0.008 | 11.9 | -1 | 0.003 | 17 | -1.2 | ||||
C | 0.004 | 13.7 | -0.9 | 0.02 | 9 | -0.9 | ||||||||||
TGW | RM481 | 7 | 3.2 | 7.1 | qTGW7.1 | C | 0.032 | 7.7 | 0.8 | 0.05 | 6 | 0.8 | ||||
TGW | RM219 | 9 | 11.7 | 9.3 | qTGW9.3 | A | 0.017 | 9.5 | -0.8 | 0.01 | 12 | -0.9 | ||||
C | 0.013 | 10.1 | -0.7 | 0.002 | 15 | -1 | ||||||||||
GY | RM254 | 11 | 110 | 11.6 | qGY11.6 | A | 0.018 | 9.5 | -1.1 | 0.01 | 11 | -2.3 |
Table 7 Validation of five QTLs identified from Shuhui 527/Yetuozai population in Langfang (2013) and Hefei (2012) in China.
Trait | Marker | Chromosome | Position | Bin | QTL | Treatment | Langfang, Hebei Province | Hefei, Anhui Province | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(cM) | Probability | R2 (%) | Additive | Probability | R2 (%) | Additive | ||||||||||
TGW | RM335 | 4 | 22 | 4.1 | qTGW4.1 | A | 0.025 | 8.6 | -1.1 | 0.01 | 11 | -1.2 | ||||
C | 0.006 | 12.3 | -1.1 | 0.002 | 16 | -1.4 | ||||||||||
TGW | RM5463 | 6 | 124.4 | 6.6 | qTGW6.6 | A | 0.008 | 11.9 | -1 | 0.003 | 17 | -1.2 | ||||
C | 0.004 | 13.7 | -0.9 | 0.02 | 9 | -0.9 | ||||||||||
TGW | RM481 | 7 | 3.2 | 7.1 | qTGW7.1 | C | 0.032 | 7.7 | 0.8 | 0.05 | 6 | 0.8 | ||||
TGW | RM219 | 9 | 11.7 | 9.3 | qTGW9.3 | A | 0.017 | 9.5 | -0.8 | 0.01 | 12 | -0.9 | ||||
C | 0.013 | 10.1 | -0.7 | 0.002 | 15 | -1 | ||||||||||
GY | RM254 | 11 | 110 | 11.6 | qGY11.6 | A | 0.018 | 9.5 | -1.1 | 0.01 | 11 | -2.3 |
[1] | Carriger S, Vallee D.2007. More crop per drop.Rice Today, 6(2): 10-13. |
[2] | Chen M Y, Ali J, Fu B Y, Xu J L, Zhao M F, Jiang Y Z, Zhu L H, Shi Y Y, Yao D N, Gao Y M, Li Z K.2011. Detection of drought-related loci in rice at reproductive stage using selected introgressed lines.Agric Sci China, 10(1): 1-8. |
[3] | Dobermann A, Fairhurst T.2000. Rice: Nutrient Disorders & Nutrient Management. Los Banos: Potash & Phosphate Institute, Potash & Phosphate Institute of Canada and International Rice Research Institute: 1-191. |
[4] | Gao F Y, Lu X J, Kang H Q, Sun S X, Liu G C, Reng G J.2006. Screening and identification for rice tolerance to Pi deficency at seedling stage.Acta Agron Sin, 32(8): 1151-1155. (in Chinese with English abstract) |
[5] | Guo T R, Yao P C, Zhang Z D, Wang J J, Wang M.2013. Involvement of antioxidative defense system in rice seedlings exposed to aluminum toxicity and phosphorus deficiency.Chin J Rice Sci, 27(6): 653-657. (in Chinese with English abstract) |
[6] | He Y X, Zheng T Q, Hao X B, Wang L F, Gao Y M, Hua Z T, Zhai H Q, Xu J L, Xu Z J, Zhu L H, Li Z K.2010. Yield performances of japonica introgression lines selected for drought tolerance in a BC breeding programme.Plant Breeding, 129(2): 167-175. |
[7] | Huang L F, Tao X T, Gao W, Wang Y L, Zhuang H Y.2014. Effect of reduced phosphorus fertilizer application on yield formation and quality of japonica rice in Jiangsu coastal region.Chin J Rice Sci, 28(6): 632-638. (in Chinese with English abstract) |
[8] | Huang X H, Wei X H, Sang T, Zhao Q, Feng Q, Zhao Y, Li C Y, Zhu C R, Lu T T, Zhang Z W, Li M, Fan D L, Guo Y L, Wang A, Wang L, Deng L W, Li W J, Lu Y Q, Weng Q J, Liu K Y, Huang T, Zhou T Y, Jing Y F, Li W, Lin Z, Buckler E S, Qian Q, Zhang Q F, Li J Y, Han B.2010. Genome-wide association studies of 14 agronomic traits in rice landraces.Nat Genet, 42(11): 961-967. |
[9] | Ismail A M, Heuer S, Thomson M J, Wissuwa M.2007. Genetic and genomic approaches to develop rice germplasm for problem soils.Plant Mol Biol, 65(4): 547-570. |
[10] | Lea P J, Miflin B J.2011. Nitrogen assimilation and its relevance to crop improvement. In: Foyer C H, Zhang H. Annual Plant Reviews. West Sussex, UK: Blackwell Publishing Ltd: 42: 1-40. |
[11] | Li Z K.2005. Strategies for molecular rice breeding in China.Mol Plant Breeding, 3(5): 603-608. (in Chinese with English abstract) |
[12] | Loudet O, Chaillou S, Merigout P, Talbotec J, Daniel-Vedele F.2003. Quantitative trait loci analysis of nitrogen use efficiency in Arabidopsis.Plant Physiol, 131(1): 345-358. |
[13] | Luo L J.2005. Development of near isogenic introgression lines and molecular breeding on rice.Mol Plant Breeding, 3(5): 609-612. (in Chinese with English abstract) |
[14] | Lynch J P.2011. Root phenes for enhanced soil exploration and phosphorus acquisition: Tools for future crops.Plant Physiol, 156: 1041-1049. |
[15] | Ma G H, Yuan L P.2015. Hybrid rice achievements, development and prospect in China.Agric Sci China, 14(2): 197-205. |
[16] | Meng L J, Lin X Y, Wang J M, Chen K, Cui Y R, Xu J L, Li Z K.2013. Simultaneous improvement of cold tolerance and yield of temperate japonica rice (Oryza sativa L.) by introgression breeding.Plant Breeding, 132(6): 604-612. |
[17] | Moncada P, Martinez C P, Borrero J, Chatel M, Gauch Jr H, Guimaraes E, Tohme J, McCouch S R.2001. Quantitative trait loci for yield and yield components in an Oryza sativa-Oryza rufipogon BC2F2 population evaluated in an upland environment.Theor Appl Genet, 102(1): 41-52. |
[18] | Mu P, Huang C, Li J X, Liu L F, Liu U J, Li Z C.2008. QTL yield trait variation and QTL mapping in a DH population of rice under phosphorus deficiency.Acta Agron Sin, 34(7): 1137-1142. (in Chinese with English abstract) |
[19] | SAS Institute Inc.2008. SAS/STAT Software V9.2 User’s Guide. Cary, North Carolina, USA: SAS Institute Inc: 2430-2611. |
[20] | Tanksley S D, Nelson J C.1996. Advanced backcross QTL analysis: A method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines.Theor Appl Genet, 92(2): 191-203. |
[21] | Vinod K K, Heuer S.2012. Approaches towards nitrogen- and phosphorus-efficient rice.AoB Plants, doi: 10.1093/aobpla/pls028. |
[22] | Wu P.2013. The research on the molecular mechanism of absorption and utilization of high phosphorus in plant and its application.Chin Sci Technol Achiev, 9: 20. (in Chinese) |
[23] | Xu J L, Gao Y M, Fu B Y, Li Z K.2005. Identification and screening of favorable genes from rice germplasm in backcross introgression populations.Mol Plant Breeding, 3(5): 619-628. (in Chinese with English abstract) |
[24] | Zang J P, Sun Y, Wang Y, Yang J, Li F, Zhou Y L, Zhu L H, Jessica R, Mohammadhosein F, Xu J L, Li Z K.2008. Dissection of genetic overlap of salt tolerance QTL at the seedling and tillering stages using backcross introgression lines in rice.Sci China: Life Sci, 51(7): 583-591. |
[25] | Zhang F, Hao X B, Gao Y M, Hua Z T, Ma X F, Chen W F, Xu Z J, Zhu L H, Li Z K.2007. Improving seedling cold tolerance of japonica rice by using the ‘hidden diversity’ in indica rice germplasm in a backcross breeding program.Acta Agron Sin, 33(10): 1618-1624. (in Chinese with English abstract) |
[26] | Zheng T Q, Xu J L, Fu B Y, Gao Y M, Veruka S, Lafitte R, Zhai H Q, Wan J M, Zhu L H, Li Z K.2007. Application of genetic hitch-hiking and ANOVA in identification of loci for drought tolerance in populations of rice from directional selection.Acta Agron Sin, 33(5): 799-804. (in Chinese with English abstract) |
[1] | Prathap V, Suresh KUMAR, Nand Lal MEENA, Chirag MAHESHWARI, Monika DALAL, Aruna TYAGI. Phosphorus Starvation Tolerance in Rice Through a Combined Physiological, Biochemical and Proteome Analysis [J]. Rice Science, 2023, 30(6): 8-. |
[2] | Serena REGGI, Elisabetta ONELLI, Alessandra MOSCATELLI, Nadia STROPPA, Matteo Dell’ANNO, Kiril PERFANOV, Luciana ROSSI. Seed-Specific Expression of Apolipoprotein A-IMilano Dimer in Rice Engineered Lines [J]. Rice Science, 2023, 30(6): 6-. |
[3] | Sundus ZAFAR, XU Jianlong. Recent Advances to Enhance Nutritional Quality of Rice [J]. Rice Science, 2023, 30(6): 4-. |
[4] | Kankunlanach KHAMPUANG, Nanthana CHAIWONG, Atilla YAZICI, Baris DEMIRER, Ismail CAKMAK, Chanakan PROM-U-THAI. Effect of Sulfur Fertilization on Productivity and Grain Zinc Yield of Rice Grown under Low and Adequate Soil Zinc Applications [J]. Rice Science, 2023, 30(6): 9-. |
[5] | FAN Fengfeng, CAI Meng, LUO Xiong, LIU Manman, YUAN Huanran, CHENG Mingxing, Ayaz AHMAD, LI Nengwu, LI Shaoqing. Novel QTLs from Wild Rice Oryza longistaminata Confer Rice Strong Tolerance to High Temperature at Seedling Stage [J]. Rice Science, 2023, 30(6): 14-. |
[6] | LIN Shaodan, YAO Yue, LI Jiayi, LI Xiaobin, MA Jie, WENG Haiyong, CHENG Zuxin, YE Dapeng. Application of UAV-Based Imaging and Deep Learning in Assessment of Rice Blast Resistance [J]. Rice Science, 2023, 30(6): 10-. |
[7] | Md. Forshed DEWAN, Md. AHIDUZZAMAN, Md. Nahidul ISLAM, Habibul Bari SHOZIB. Potential Benefits of Bioactive Compounds of Traditional Rice Grown in South and South-East Asia: A Review [J]. Rice Science, 2023, 30(6): 5-. |
[8] | Raja CHAKRABORTY, Pratap KALITA, Saikat SEN. Phenolic Profile, Antioxidant, Antihyperlipidemic and Cardiac Risk Preventive Effect of Chakhao Poireiton (A Pigmented Black Rice) in High-Fat High-Sugar induced Rats [J]. Rice Science, 2023, 30(6): 11-. |
[9] | LI Qianlong, FENG Qi, WANG Heqin, KANG Yunhai, ZHANG Conghe, DU Ming, ZHANG Yunhu, WANG Hui, CHEN Jinjie, HAN Bin, FANG Yu, WANG Ahong. Genome-Wide Dissection of Quan 9311A Breeding Process and Application Advantages [J]. Rice Science, 2023, 30(6): 7-. |
[10] | JI Dongling, XIAO Wenhui, SUN Zhiwei, LIU Lijun, GU Junfei, ZHANG Hao, Tom Matthew HARRISON, LIU Ke, WANG Zhiqin, WANG Weilu, YANG Jianchang. Translocation and Distribution of Carbon-Nitrogen in Relation to Rice Yield and Grain Quality as Affected by High Temperature at Early Panicle Initiation Stage [J]. Rice Science, 2023, 30(6): 12-. |
[11] | Nazaratul Ashifa Abdullah Salim, Norlida Mat Daud, Julieta Griboff, Abdul Rahim Harun. Elemental Assessments in Paddy Soil for Geographical Traceability of Rice from Peninsular Malaysia [J]. Rice Science, 2023, 30(5): 486-498. |
[12] | Monica Ruffini Castiglione, Stefania Bottega, Carlo Sorce, Carmelina SpanÒ. Effects of Zinc Oxide Particles with Different Sizes on Root Development in Oryza sativa [J]. Rice Science, 2023, 30(5): 449-458. |
[13] | Tan Jingyi, Zhang Xiaobo, Shang Huihui, Li Panpan, Wang Zhonghao, Liao Xinwei, Xu Xia, Yang Shihua, Gong Junyi, Wu Jianli. ORYZA SATIVA SPOTTED-LEAF 41 (OsSPL41) Negatively Regulates Plant Immunity in Rice [J]. Rice Science, 2023, 30(5): 426-436. |
[14] | Ammara Latif, Sun Ying, Pu Cuixia, Noman Ali. Rice Curled Its Leaves Either Adaxially or Abaxially to Combat Drought Stress [J]. Rice Science, 2023, 30(5): 405-416. |
[15] | Liu Qiao, Qiu Linlin, Hua Yangguang, Li Jing, Pang Bo, Zhai Yufeng, Wang Dekai. LHD3 Encoding a J-Domain Protein Controls Heading Date in Rice [J]. Rice Science, 2023, 30(5): 437-448. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||