Phenotypic variation
The measured traits of the CM42×CM39 RILs as well as the two parents are listed in Table 1. CM42 had higher trait values for TGW, GW, GL, GNS, PH and SL than those of CM39 in each of environments and the best linear unbiased prediction (BLUP) datasets. In the RIL population, all traits showed wide and significant variations in all environments and the BLUP datasets (Table 1). Of them, the TGW ranges from 20.81 to 72.7 gram (g), the GW ranged from 2.6 to 4.21 millimeter (mm), the GL ranged from 5.88 to 8.81 mm, the PH ranged from 65.08 to 148.3 centimeter (cm), the GNS ranged from 24 to 81.2, the SL ranged from 6.65 to 18.17 cm, and the SNS ranged from 15.83 to 27 (Table 1), respectively. The BLUP datasets of all traits showed normal distributions in the RIL lines, which suggests polygenic inheritance of these traits (Fig. 1A). Additionally, the TGW, GL, PH, GNS and SL showed high broad-sense heritability of 0.54, 0.6, 0.91, 0.66 and 0.88, respectively (Table 1). Significant and positive correlations (P < 0.01) of the measured traits among all environments and the BLUP datasets were detected, which suggested that these traits were environmentally stable and mainly controlled by genetic factors (Table S2).
Table 1
Phenotypic variation of seven yield components, including thousand grain weight (TGW), grain number per spike (GNS), grain width (GW), grain length (GL), plant height (PH), spike length (SL) and spikelet number per spike (SNS), for the parents and the CM42×CM39 RIL lines in different environments.
Traits | Environments | Prarents | The CM42×CM39 RIL lines |
CM42 | CM39 | Range | Mean | SD | CV (%) | H2 |
TGW | 2017SHF | 54 | 52.94 | 38.34-70.88 | 58.57 | 5.84 | 9.98 | 0.54 |
| 2017SHL | 50.64 | 41.83 | 20.81-68.14 | 43.76 | 9.17 | 20.95 | |
| 2018SHF | 54.79 | 53.47 | 40.44-72.7 | 54.67 | 5.58 | 10.2 | |
| 2018SHL | 53.06 | 51.29 | 37.89-67.33 | 54.51 | 5.57 | 10.22 | |
| 2019SHF | 52.4 | 42.42 | 32.59-66.54 | 51.27 | 5.94 | 11.59 | |
| 2019SHL | 51.05 | 47.38 | 23.4-62.74 | 46.9 | 6.22 | 13.27 | |
| BLUP | 52.36 | 50.44 | 38.24-62.56 | 51.65 | 3.98 | 7.7 | |
GW | 2017SHF | 3.68 | 3.42 | 3.19-4.21 | 3.82 | 0.16 | 4.28 | 0.49 |
| 2017SHL | 3.54 | 3.31 | 2.6-4.01 | 3.38 | 0.29 | 8.57 | |
| 2018SHF | 3.58 | 3.53 | 3.19-4.04 | 3.69 | 0.16 | 4.35 | |
| 2018SHL | 3.63 | 3.61 | 3.15-3.96 | 3.65 | 0.15 | 4.14 | |
| 2019SHF | 3.6 | 3.16 | 3-3.9 | 3.5 | 0.18 | 5.21 | |
| 2019SHL | 3.56 | 3.49 | 2.84-3.99 | 3.49 | 0.19 | 5.37 | |
| BLUP | 3.59 | 3.51 | 3.21-3.87 | 3.59 | 0.11 | 3.06 | |
GL | 2017SHF | 7.73 | 7.17 | 6.78-8.81 | 7.76 | 0.41 | 5.26 | 0.6 |
| 2017SHL | 6.95 | 6.53 | 5.94-7.89 | 6.86 | 0.37 | 5.39 | |
| 2018SHF | 6.87 | 6.72 | 5.89-7.92 | 6.95 | 0.37 | 5.3 | |
| 2018SHL | 7.64 | 6.55 | 5.88-7.81 | 6.85 | 0.37 | 5.45 | |
| 2019SHF | 7.32 | 6.43 | 6-7.71 | 6.86 | 0.33 | 4.84 | |
| 2019SHL | 7.22 | 6.67 | 6.03-7.71 | 6.94 | 0.36 | 5.15 | |
| BLUP | 7.27 | 6.98 | 6.19-7.75 | 7.04 | 0.3 | 4.26 | |
PH | 2016SHF | 90.34 | 89.5 | 66.5-120.3 | 91.53 | 9.5 | 10.38 | 0.91 |
| 2016SHL | 89.8 | 87.2 | 76-148.3 | 95.97 | 10.49 | 10.93 | |
| 2017SHF | 97.67 | 96.33 | 81.33-143 | 103.3 | 10.65 | 10.31 | |
| 2017SHL | 99 | 98.8 | 66.63-121.2 | 91.39 | 9.73 | 10.65 | |
| 2018SHF | 91.7 | 87.08 | 65.08-131.9 | 93.9 | 11.82 | 12.59 | |
| 2018SHL | 94.61 | 90 | 70.8-135.4 | 95.57 | 11.32 | 11.84 | |
| 2019SHF | 90.05 | 85.9 | 69.45-126.8 | 98.74 | 9.89 | 10.02 | |
| 2019SHL | 93.33 | 89.3 | 78.5-127.4 | 97.58 | 8.98 | 9.21 | |
| BLUP | 93.24 | 91.91 | 74.65-127.5 | 96 | 9.14 | 9.52 | |
GNS | 2017SHF | 54 | 52 | 24-81.2 | 51.01 | 10.39 | 20.38 | 0.66 |
| 2017SHL | 44.5 | 43.6 | 26-77 | 41.94 | 8.08 | 19.27 | |
| 2018SHF | 54.6 | 49.9 | 31.6-70.8 | 45.62 | 6.11 | 13.4 | |
| 2018SHL | 54.5 | 54.1 | 35.3-70.8 | 52.07 | 7.18 | 13.78 | |
| 2019SHF | 55.7 | 53.7 | 35.2-84.6 | 53.66 | 8.18 | 15.24 | |
| 2019SHL | 56.5 | 56.2 | 35.5-75.8 | 53.77 | 7.07 | 13.15 | |
| BLUP | 53.17 | 52.44 | 37.76-66.18 | 49.85 | 4.62 | 9.26 | |
SL | 2016SHF | 12.18 | 9.96 | 8.67-18 | 13.09 | 1.75 | 13.37 | 0.88 |
| 2016SHL | 12.1 | 9 | 6.65-14 | 10.53 | 1.61 | 15.33 | |
| 2017SHF | 13.5 | 11.5 | 8.5-17.88 | 13.04 | 1.73 | 13.23 | |
| 2017SHL | 13 | 11.5 | 8.33-17.67 | 12.93 | 1.88 | 14.51 | |
| 2018SHF | 11.85 | 9.26 | 7.63-14.93 | 11.82 | 1.84 | 15.54 | |
| 2018SHL | 13.02 | 10.9 | 7.55-15.7 | 11.3 | 1.72 | 15.18 | |
| 2019SHF | 13.71 | 11.2 | 8.89-18.17 | 13.25 | 1.87 | 14.15 | |
| 2019SHL | 12.4 | 10.5 | 8.5-16.3 | 12.51 | 1.56 | 12.51 | |
| BLUP | 12.71 | 11.6 | 8.45-15.69 | 12.31 | 1.5 | 12.22 | |
SNS | 2017SHF | 18.6 | 19.6 | 16.2-25 | 19.58 | 1.39 | 7.08 | 0.4 |
| 2017SHL | 21.2 | 21.2 | 18-27 | 21.4 | 1.63 | 7.63 | |
| 2018SHF | 21.9 | 21.5 | 17.7-24.5 | 21.66 | 1.13 | 5.2 | |
| 2018SHL | 20.9 | 20.7 | 17.9-25.2 | 21.02 | 1.22 | 5.81 | |
| 2019SHF | 21.7 | 21.2 | 17.9-25 | 21.29 | 1.2 | 5.63 | |
| 2019SHL | 17.2 | 18.1 | 15.83-21.2 | 18.35 | 1.04 | 5.67 | |
| BLUP | 20.3 | 20.35 | 18.42-22.96 | 20.55 | 0.84 | 4.1 | |
SHF, Shifang; SHL, Shuangliu, BLUP, best linear unbiased prediction; CV, coefficient of variation; H2, broad-sense heritability |
Correlation analyses among different traits
The BLUP datasets of each trait was employed to assess their correlations in the CM42×CM39 RIL population. TGW had significantly positive correlation with GW, GL, PH and SL, and significantly negative correlation with GNS and SNS (P < 0.001) (Fig. 1). GW was significantly and positively correlated with GL (P < 0.001), weakly and positively correlated with SL (P < 0.05), significantly and negatively correlated with GNS and SNS (P < 0.001), and not correlated with PH, respectively (Fig. 1). GL had significantly positive correlation with PH and SL (P < 0.001), significantly negative correlation with GNS (P < 0.001), and weakly negative correlation with SNS (P < 0.05) (Fig. 1). Moreover, significantly positive correlations between PH and SL, GNS and SNS, and SL and SNS (P < 0.001), weakly positive correlations between PH and SNS (P < 0.05), significantly negative correlations between PH and GNS (P < 0.001), and no correlations between GNS and SL were detected, respectively (Fig. 1).
QTL detection
Phenotypic data of all traits evaluated in each environment and the BLUP datasets were used for QTL detection, in which the BLUP datasets were treated as an additional environment. A total of 30 QTLs were identified in multiple environments and located on all chromosomes excepting 3B, 3D, 4B, 4D, 5D and 6B (Table 2).
For TGW, two QTLs were detected on chromosomes 6A. QTgw.cib-6A.1 was detected in two environments and the BLUP datasets, explaining 9.89–16.38% of the phenotypic variance. QTgw.cib-6A.2 was a major QTL detected in four environments and the BLUP datases and explained 15.31–23.75% of the phenotypic variance. Alleles of CM42 for the two QTLs contributed to higher TGW (Table 2).
For GW, six QTLs were identified on chromosomes 2A, 2B, 5A, 6A and 7B. Of them, a major QTL QGw.cib-6A was identified in four environments and the BLUP datasets, explaining 8.6-23.31% of the GW variation. The allele of CM42 contributed positively to the GW. The rest five minor QTLs were identified in two environments and explained 5.2–9.89% of the GW variation. The favorable alleles of QGw.cib-2A and QGw.cib-5A were contributed by CM39, and that of QGw.cib-2B.1, QGw.cib-2B.2 and QGw.cib-7B were contributed by CM42 (Table 2).
Among the six QTLs for GL, two major QTL QGl.cib-3A and QGl.cib-6A were identified in five environments and the BLUP datasets, explaining 6.55–11.86% and 5.96–13.11% of the GL variation, respectively. The positive additive effects of the two QTLs on GL were contributed by CM42. The rest four minor QTLs were identified in two or three environments on chromosoems 5A, 6D and 7D, explaining 5.17–11.34% of the GL variation. The positive alleles of QGl.cib-5A.1, QGl.cib-5A.2 and QGl.cib-7D were derived from CM42, and that of QGl.cib-6D was from CM39 (Table 2).
Among the six QTLs for PH, QPh.cib-2D on chromosome 2D was a stable QTL and detected in five environments and the BLUP datasets, explaining 4.54–9.38% of the PH variation. The allele of CM39 contributed to higher PH. The rest five minor QTLs on chromosomes 1A, 4A, 5A, 5B and 6A were detected in two or three environments, explaining 3.8-11.37% of the PH variation. The positive alleles of QPh.cib-1A and QPh.cib-5B were from CM39, and that of QPh.cib-4A, QPh.cib-5A and QPh.cib-6A were from CM42 (Table 2).
Two minor QTLs for GNS on chromosomes 2D and 6A were detected in two environments and the BLUP datasets and explained 4.97–6.46% and 6.56–7.73% of the GNS variation, respectively. Alleles from CM42 and CM39 at QGns.cib-2D and QGns.cib-6A, respectively, contributed to positive effects on GNS (Table 2).
For SL, four QTLs were detected on chromosomes 2D, 5A, 5B and 6A. A major QTL QSl.cib-2D was detected in eight environments and the BLUP datasets, explaining 6.18–14.89% of the SL variation. QSl.cib-5B was a stable QTL and detected in three environments and the BLUP datasets, explaining 3.79–5.96% of the SL variation. Alleles of CM39 for the two QTLs contributed to increase of SL. Two minor QTLs QSl.cib-5A and QSl.cib-6A were detected in two or three environments, explaining 3.47–7.8% and 5.63–5.9% of the SL variation, respectively. The positive alleles of the two QTLs were contributed by CM42 (Table 2).
Four QTLs for SNS were identified on chromosomes 1B, 1D, 4A and 7A. Of them, QSns.cib-1B and QSns.cib-4A were detected in three environments and the BLUP datasets, explaining 7.47–16.18% and 2.34–10.46% of the SNS variation, respectively. QSns.cib-1D and QSns.cib-7A were detected in two environments, explaining 6.77–8.39% and 5.06–8.18% of the SNS variation, respectively. The favorable alleles of QSns.cib-1B and QSns.cib-7A were contributed by CM39, and that of QSns.cib-1D and QSns.cib-4A were contributed by CM42 (Table 2).
Table 2
Quantitative trait loci (QTLs) for thousand grain weight (TGW), grain number per spike (GNS), grain width (GW), grain length (GL), plant height (PH), spike length (SL) and spikelet number per spike (SNS) identified across multiple environments in the CM42×CM39 RIL population.
Trait | QTL | Environment | Chromosome | Interval (cM) | Flanking Markers | LOD | PVE(%) | Add |
TGW | QTgw.cib-6A.1 | 18SHF/18SHL/BLUP | 6A | 41.3-42.46 | Marker87546-Marker87736 | 6.17/8.03/4.44 | 13.49/16.38/9.89 | -1.89/-2/-1.04 |
| QTgw.cib-6A.2 | 17SHF/18SHL/19SHF/19SHL/BLUP | 6A | 52.98-59.52 | Marker90290-Marker91587 | 9.48/7.95/7.27/10.52/9.62 | 20.39/16.68/15.31/20.51/23.75 | -2.58/-2.06/-2.36/-2.88/-1.65 |
GW | QGw.cib-2A | 18SHF/19SHF | 2A | 14.86-17.08 | Marker26336-Marker26958 | 5.48/2.76 | 9.51/5.81 | 0.05/0.04 |
| QGw.cib-2B.1 | 19SHF/19SHL | 2B | 39.6-43.07 | Marker29502-Marker29525 | 2.66/4.09 | 5.46/6.62 | -0.04/-0.05 |
| QGw.cib-2B.2 | 17SHF/BLUP | 2B | 121.67-121.93 | Marker34419-Marker34417 | 3.83/3.7 | 5.2/5.2 | -0.04/-0.03 |
| QGw.cib-5A | 17SHF/BLUP | 5A | 27.76-27.97 | Marker70243-Marker70216 | 3.91/4.73 | 5.29/6.72 | 0.04/0.03 |
| QGw.cib-6A | 17SHF/17SHL/18SHL/19SHF/19SHL/BLUP | 6A | 49.98-58.87 | Marker90210-Marker91133 | 13.09/4.95/8.93/4.02/5.8/14.53 | 19.87/8.92/19.17/8.6/10.1/23.31 | -0.08/-0.09/-0.07/-0.05/-0.06/-0.06 |
| QGw.cib-7B | 18SHF/19SHL | 7B | 179.93-180.13 | Marker111000-Marker110965 | 5.36/5.98 | 9.07/9.89 | -0.05/-0.06 |
GL | QGl.cib-3A | 17SHF/17SHL/18SHL/19SHF/19SHL/BLUP | 3A | 64.7-66.41 | Marker40793-Marker40901 | 5.31/2.97/6.1/5.69/3.87/5.68 | 11.86/6.55/10.17/10.31/7.37/9.54 | -0.13/-0.08/-0.12/-0.1/-0.09/-0.09 |
| QGl.cib-5A.1 | 17SHL/BLUP | 5A | 3.46-7.55 | Marker69377-Marker69395 | 2.83/3.66 | 6.28/6.26 | -0.08/-0.07 |
| QGl.cib-5A.2 | 18SHL/19SHF | 5A | 86.87-87.49 | Marker71923-Marker71919 | 3.79/3.82 | 6.13/6.76 | -0.09/-0.08 |
| QGl.cib-6A | 17SHF/18SHF/18SHL/19SHF/19SHL/BLUP | 6A | 42.36-43.4 | Marker87807-Marker87738 | 5.32/4.62/7.72/3.39/5.37/7.41 | 11.85/10.15/13.11/5.96/10.37/12.7 | -0.13/-0.12/-0.13/-0.08/-0.11/-0.1 |
| QGl.cib-6D | 18SHL/19SHF/BLUP | 6D | 76.06-83.69 | Marker99119-Marker99140 | 4.17/5/3.17 | 6.95/8.98/5.17 | 0.1/0.1/0.06 |
| QGl.cib-7D | 17SHF/17SHL/BLUP | 7D | 32.68-38.76 | Marker111521-Marker111597 | 3/4.64/6.19 | 6.63/11.34/10.49 | -0.09/-0.11/-0.09 |
PH | QPh.cib-1A | 16SHF/17SHL/19SHF | 1A | 28.34-30.95 | Marker5758-Marker6328 | 5.58/6.07/3.64 | 7.62/7.53/5.87 | 2.96/3.03/2.65 |
| QPh.cib-2D | 16SHF/17SHL/18SHF/18SHL/19SHF/BLUP | 2D | 1.48-5.16 | Marker35344-Marker35422 | 3.42/4.31/3/4.7/3.14/2.56 | 4.54/5.23/6.73/9.38/5.03/6.2 | 2.29/2.53/3/3.72/2.46/2.31 |
| QPh.cib-4A | 16SHF/17SHL | 4A | 82.78-83.05 | Marker57956-Marker57959 | 4.76/5.71 | 6.43/7.05 | -2.73/-2.95 |
| QPh.cib-5A | 17SHF/19SHL/BLUP | 5A | 126.27-126.52 | Marker72631-Marker72950 | 3.02/2.91/2.52 | 7.18/7.03/5.62 | -2.8/-2.32/-2.2 |
| QPh.cib-5B | 16SHF/17SHL | 5B | 134.43-134.74 | Marker83905-Marker83879 | 3.07/3.18 | 4.07/3.8 | 2.17/2.16 |
| QPh.cib-6A | 16SHF/17SHL/19SHF | 6A | 54.61-54.76 | Marker90459-Marker90388 | 6.13/8.86/5.6 | 8.42/11.37/9.25 | -3.24/-3.88/-3.46 |
GNS | QGns.cib-2D | 18SHF/19SHF/BLUP | 2D | 0-5.16 | Marker35164-Marker35422 | 2.57/2.63/4.73 | 5.73/4.97/6.46 | -1.44/-1.93/-1.27 |
| QGns.cib-6A | 18SHL/19SHF/BLUP | 6A | 56.45-59.52 | Marker90628-Marker91587 | 3.35/3.83/4.91 | 7.73/7.46/6.56 | 2.07/2.46/1.33 |
SL | QSl.cib-2D | 16SHF/16SHL/17SHF/17SHL/18SHF/18SHL/19SHF/19SHL/BLUP | 2D | 1.48-5.16 | Marker35344-Marker35422 | 3.42/6.86/6.82/8.05/8.05/8.83/4.82/4.43/7.43 | 6.84/11.15/9.46/10.91/14.89/13.41/6.18/8.31/13.51 | 0.46/0.6/0.66/0.76/0.75/0.7/0.53/0.48/0.58 |
| QSl.cib-5A | 18SHL/19SHF/BLUP | 5A | 17.71-21.48 | Marker69427-Marker69525 | 2.59/6/2.61 | 3.47/7.8/4.22 | -0.36/-0.6/-0.32 |
| QSl.cib-5B | 16SHF/16SHL/17SHF/BLUP | 5B | 40.07-40.38 | Marker81580-Marker81513 | 2.99/3.06/2.87/2.51 | 5.96/4.76/3.79/4.04 | 0.43/0.39/0.42/0.32 |
| QSl.cib-6A | 19SHF/BLUP | 6A | 58.87-64.37 | Marker91133-Marker91933 | 4.62/3 | 5.9/5.63 | -0.54/-0.39 |
SNS | QSns.cib-1B | 17SHF/18SHL/19SHF/BLUP | 1B | 28.8-33.3 | Marker15740-Marker17413 | 16.86/4.13/6.11/5.4 | 16.18/7.47/9.85/8.21 | 0.82/0.35/0.4/0.25 |
| QSns.cib-1D | 17SHL/BLUP | 1D | 146.67-148.82 | Marker23471-Marker23475 | 5.65/4.49 | 8.39/6.77 | -0.5/-0.22 |
| QSns.cib-4A | 17SHF/18SHL/19SHF/BLUP | 4A | 72.98-81.71 | Marker57882-Marker57915 | 2.51/4.94/5.3/5.63 | 2.34/10.46/9.69/9.68 | -0.31/-0.41/-0.39/-0.27 |
| QSns.cib-7A | 19SHF/19SHL | 7A | 81.76-85.42 | Marker103527-Marker103903 | 3.25/4.47 | 5.06/8.18 | 0.28/0.3 |
PVE; mean of phenotypic variation explained; LOD, logarithm of the odd; Add, mean of additive effect (Positive values indicate that alleles from CM39 are increasing the trait scores, and negative values indicate that alleles from CM42 are increasing the trait scores); BLUP, best linear unbiased prediction. |
Effects of major QTL in mapping populations
Six major QTLs QSl.cib-2D, QGl.cib-3A, QTgw.cib-6A.1, QTgw.cib-6A.2, QGw.cib-6A, and QGl.cib-6A were stably identified in multiple environments and the BLUP datasets (Table 2). We further analyzed their effect on corresponding traits based on the flanking markers in the CM42×CM39 RIL population. As expected, lines possessing the positive alleles of the six loci showed significantly better performance on the corresponding traits compared with those have alleles showing negative effects in all environments and the BLUP datasets (Fig. 2). Additionally, three Kompetitive Allele Specific PCR (KASP) markers linked with QTgw.cib-6A.1, QTgw.cib-6A.2, QGw.cib-6A, QGl.cib-6A, and QSl.cib-2D were developed in the present study, which could be utilized in MAS for wheat yield improvement (Table S3, Figure S1).
QTL clusters on chromosome 2D and 6A
The QTL cluster on 2D, including three QTLs QSl.cib-2D, QPh.cib-2D and QGns.cib-2D, was co-located between Marker35164 and Marker35422 (Table 2). The CM39 alleles at the locus contributed to longer spike and higher plant, but less GNS. Two QTL clusters were identified on chromosome 6A (Table 2). One comprised two QTLs, QTgw.cib-6A.1 and QGl.cib-6A, was located between Marker87546 and Marker87738. The alleles of CM42 at the locus contributed to increased grain length and weight (Table 2). The other one contained five QTLs, QTgw.cib-6A.2, QGw.cib-6A, QPh.cib-6A, QGns.cib-6A and QSl.cib-6A, was located between Marker90210 and Marker91587. The allele of CM39 at the locus contributed to higher TGW, GW, PH and SL, but less GNS (Table 2).