QTL Detection of Internode Length and its Component Index in Wheat Using Two Related RIL Populations

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1 DOI: /CRC QTL Detection of Internode Length and its Component Index in Wheat Using Two Related RIL Populations F. CUI 1,2 **, J. LI 1 **, A.M. DING 1 **, C.H. ZHAO 1 **, X.F. LI 1, D.S. FENG 1, X.Q. WANG 3, L. WANG 1,4 and H.G. WANG 1 * 1 State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Taian Subcenter of National Wheat Improvement Center, College of Agronomy, Shandong Agricultural University, Taian , China 2 Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, , Hebei, China 3 Municipal Academy of Agricultural Sciences, Zao zhuang , Shandong, China 4 Municipal Academy of Agricultural Sciences, Ji ning , Shandong, China (Received 9 May 2011; accepted 20 July 2011; Communicated by M. Molnár-Láng) To comprehensively understand the genetic basis of plant height (PH), quantitative trait locus (QTL) analysis for internode lengths, internode component indices and plant height component index (PHCI) were firstly conducted in the present study. Two related F 8:9 recombinant inbred line (RIL) populations comprising 485 and 229 lines were used. Two hundred and nine putative additive QTL for the eight traits were identified, 35 of which showed significance in at least three trials. Of these, at least 11 pairwise QTL were common to the two populations. PH components at the QTL level had different effects on PH, confirming our previous multivariate conditional analysis (Cui et al. 2011). Eleven major QTL that showed consistency in expression across environments should be of great value in the genetic improvement of PH in wheat. The results above will enhance the understanding of the genetic basis of PH in wheat. Keywords: wheat, internode length, internode component index, plant height component index, QTL Introduction Plant height (PH), an important agronomic trait in wheat, not only determines plant architecture but also contributes a lot to grain yield. Semi-dwarf plants possessed short, strong stalks and did not lodge. Since the introduction of dwarfing traits into plants, tremendous increases in wheat yields have been achieved (Peter 2003). Therefore, it is of great value to unravel the genetic basis of PH. Increasing numbers of QTL studies have now been conducted in an attempt to dissect the genetic basis of PH in wheat. However, most previous QTL detection were conducted based on phenotypic values of the final PH (Kato et al. 1999; Keller et al. 1999; Börner * Corresponding author; hgwang@sdau.edu.cn ** The first four authors contributed equally to this work Akadémiai Kiadó, Budapest

2 2 CUI et al.: QTL for Plant Height Components in Wheat et al. 2002; Huang et al. 2003; Sourdille et al. 2003; Huang et al. 2004; Liu et al. 2005; McCartney et al. 2005; Huang et al. 2006; Marza et al. 2006; Klahr et al. 2007; Zhang et al. 2008; Chu et al. 2008; Wang et al. 2009; Mao et al. 2010). By considering the developmental behavior, Wang et al. (2010) and Wu et al. (2010) have documented dynamic QTL for PH in wheat after Zhu (1995) introduced the new methodology for conditional genetic analysis to identify QTL expressed at certain stages of the life cycle. Using both unconditional mapping method and conditional mapping method for multivariable conditional analysis, we have dissected the relationships between PH and its components of wheat at an individual QTL level (Cui et al. 2011). Biologically, internode lengths and internode component indices play critical roles in determining the final PH in wheat. The internode characteristics have a great influence on the lodging resistance of crops (Pinthus 1973; Stanca et al. 1979; Dunn and Briggs 1989; Tavakoli et al. 2009). Therefore, understanding the genetic basis for internode lengths and internode component indices, especially for that of basal internodes, is of great importance when breeding wheat cultivars with satisfactory levels of lodging resistance. PH components, at the QTL level, had different effects on PH (Kato et al. 1999; Cui et al. 2011). In the present study, QTL mapping for the internode lengths, the internode indices, and the PH index were firstly conducted. The objectives of this study were to: (i) specify the genetic factors affecting PH in wheat comprehensively; and (ii) identify markers that can be used in marker-assisted selection (MAS) in wheat breeding programs. Materials and Methods Experimental populations and their evaluation Two related F 8:9 recombinant inbred line (RIL) populations were used in the present study. They were derived from two crosses by three Chinese common wheat varieties, i.e., between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY), comprising 485 and 229 lines, respectively. Relevant informations concerning the two populations and their parents are available from an earlier report (Cui et al. 2011). Details of the four trials (E1, E2, E3 and E4) and the trait evaluations are also given in Cui et al. (2011). Besides the plant height (PH), the internode lengths from the first to the fourth counted from the top, i.e., the first internode length, the second internode length, the third internode length and the forth internode length, were abbreviated as FIITL, SITL, TITL, and FOITL, respectively. The internode component indices from the first to the third from the top, i.e., the first internode component index, the second internode component index and the third internode component index, were abbreviated as FIITCI, SITCI and TITCI, respectively. They were calculated as follows: FIITCI=FIITL/(FIITL+SITL); SITCI= SITL/(SITL+TITL); and TITCI=TITL/(TITL+FOITL). The PH component index (PHCI) was calculated as PHCI=(FIITL+SITL)/PH.

3 CUI et al.: QTL for Plant Height Components in Wheat 3 Construction of the genetic linkage map, data analysis and QTL mapping Relevant information for the genetic linkage maps has been detailed in an earlier report (Cui et al. 2011). Phenotypic correlation coefficients between PH and its related traits were calculated from the trait means for the four environments. The correlation coefficients for the single traits between pairwise environments were calculated from the combined phenotypic values of the four environments. Basic statistical analysis was implemented by the software SPSS13.0 (SPSS, Chicago, USA). QTL screen were conducted using inclusive composite interval mapping by IciMapping 3.0 based on stepwise regression of simultaneous consideration of all marker information ( isbreeding.net/). The walking speed chosen for all QTL was 1.0 cm. The threshold LOD scores were calculated using 1,000 permutations. However, we ignored the QTL with a LOD value of <2.5 to make the QTL reported herein authentic and reliable. Individual as well as the pooled data collected from the average of the four environments above (P) were used for QTL mapping analysis. Results Phenotypic performance of the two RILs The final PH and the internode lengths for the two RIL populations and the parents in four environments are given in Cui et al. (2011). Among the four environments, significant differences of each internode length existed at the 0.05 level between Weimai 8 and Jimai 20, but did not exist between Weimai 8 and Yannong 19 (data not shown). No significant differences of internode component indices and PHCI existed either between Weimai 8 and Jimai 20 or between Weimai 8 and Yannong 19 (data not shown). However, all the eight traits varied widely among the individual lines in both populations, and showed strong transgressive segregations in all environments (Fig. 1). The correlation coefficients for the single traits between pairwise experiments were shown in Table 1. The corresponding correlation coefficients for SITCI and TITCI were lower in both WJ and WY populations, next to PHCI. Higher correlation coefficients for FIITL and SITL were observed in both WJ and WY populations. These correlation coefficients can serve as rough estimates of heritability in these experiments (Börner et al. 2002). QTL mapping in the WJ and WY population Up to 209 putative additive QTL for the eight traits were detected in the two populations, 11 pairwise of which, at least, were common to the two populations. They together covered all the 21 wheat chromosomes. Of these, 35 QTL showed significance in at least three trials, accounting for 16.75% of the total QTL (Table 2).

4 4 CUI et al.: QTL for Plant Height Components in Wheat Figure 1. Phenotypic distribution of wheat internode lengths and their component indices in progenies derived from the WJ and WY Table 1. Correlation coefficients between experiments Trait a Minimum Mean Maximum FIITL 0.506/ / /0.711 SITL 0.534/ / /0.813 TITL 0.409/ / /0.768 FOITL 0.335/ / /0.566 PHCI 0.187/ / /0.328 FIITCI 0.427/ / /0.700 SITCI 0.158/ / /0.280 TITCI 0.014/ / /0.351 For each entry, the first figure refers to WJ and the second to WY.

5 CUI et al.: QTL for Plant Height Components in Wheat 5 Traits Table 2. The number of QTL detected in the WJ and WY populations No. of QTL Contributions, % No. of trials <5% 5% 10% >10% FIITL 9/0 6/9 2/2 8/6 4/2 4/2 0/0 1/1 17/11 SITL 4/2 8/7 0/6 6/9 3/3 2/1 1/1 0/1 12/15 TITL 2/5 8/4 0/4 5/5 3/3 0/4 2/1 0/0 10/13 FOITL 7/0 4/5 0/5 7/5 4/4 0/1 0/0 0/0 11/10 PHCI 3/0 4/8 0/4 3/12 2/0 2/0 0/0 0/0 7/12 FIITCI 12/1 9/3 1/3 10/3 7/2 3/0 1/3 1/1 22/9 SITCI 9/1 6/7 0/2 10/9 4/1 1/0 0/0 0/0 15/10 TITCI 11/0 2/4 0/8 10/10 2/2 1/0 0/0 0/0 13/12 For each entry, the first numeral refers to WJ, and the second, to WY. Total The first internode length In all of the five trials, 17 putative additive QTL for FIITL in WJ were identified, individually explaining % of the phenotypic variation (Fig. 2). Of these, six QTL were reproducibly detected in no less than two environments of E1, E2, E3 and E4 (Table 3). Eleven putative additive QTL exhibiting from 5.96 to 15.67% of phenotypic variance of FIITL were revealed in WY (Fig. 2). Of these, five QTL could be detected reproducibly in at least two of the four different environments (Table 4). In WJ and WY, there were 11 and 4 QTL with length-enhancing alleles from the common parents Weimai 8, respectively. The second internode length A total of 12 and 15 putative additive QTL for SITL were detected in WJ and WY populations, respectively, individually exhibiting % and % of the phenotypic variance (Fig. 2). Three of the 12 QTL in WJ and four of the 15 in WY were verified in no less than two environments of E1, E2, E3 and E4 (Tables 3 and 4). Eight and ten QTL alleles increasing SITL were donated by the common parent Weimai 8 in WJ and WY, respectively. The third internode length For TITL, ten and 13 putative additive QTL were detected in WJ and WY, each accounting for % and % of the phenotypic variance, respectively (Fig. 2). In the WJ population, three QTL showed significance in at least two of the four environments (Table 3). In the WY population, six QTL were detected reproducibly in no less than two environments of E1, E2, E3 and E4 (Table 4). Totally, six QTL alleles increasing TITL each in WJ and WY, respectively, were originated from Weimai 8. The forth internode length In total, ten and 11 significant additive QTL for FOITL were identified in WJ and WY, individually exhibiting % and % phenotypic variance, respectively (Fig. 2). All the ten QTL in WJ could be detected only in one of the four environments.

6 6 CUI et al.: QTL for Plant Height Components in Wheat Figure 2. Location of putative QTL for internode lengths and their component indices based on 485 RILs derived from Weimai 8 Jimai 20 and 229 RILs from Weimai 8 Yannong 19, with the prefixes WJ and WY, respectively. A putative QTL with LOD > 2.5 is placed on its corresponding flanking markers. QTL symbols are described at the bottom right of Fig. 2, and E1, E2, E3, E4 or P under the corresponding QTL symbol indicates the trial where the QTL was detected. A horizontal arrow on the chromosome indicates an unconditional QTL for plant height that co-located with a QTL for plant height components, which has been reported by Cui et al. (2011)

7 CUI et al.: QTL for Plant Height Components in Wheat 7 Table 3. Putative additive QTL for internode-related traits showing consistency in no less than two of the four different environments in the WJ population Trait QTL a Environment LOD Contributions, % Additive effect b FIITL QFiitl-WJ-2A.5 E1/E2/E3/E4/P 5.32/8.45/ / /6.58/5.68/4.52/ /0.90/1.02/0.80/1.11 QFiitl-WJ-4D.3 E3/E4/P 3.49/5.29/ /10.57/ /1.24/0.87 QFiitl-WJ-5A-1.3 E1/E3/E4 4.04/3.42/ /4.11/ /1.04/1.15 QFiitl-WJ-7A.3 E2/E4/P 5.99/4.88/ /6.50/ / 0.92/ 0.76 QFiitl-WJ-7A.2 E2/E3 2.93/ / / 0.96 QFiitl-WJ-7B-2.3 E2/E4/P 6.91/2.96/ /2.54/ /0.73/0.82 SITL QSitl-WJ-2A.3 E1/E2/P 2.59/3.97/ /4.21/ /0.61/0.49 QSitl-WJ-2B.4 E1/E2/E3/P 4.11/5.08/4.52/ /4.29/5.32/ /0.53/0.53/0.51 QSitl-WJ-2B.3 E2/E4/P 4.64/3.96/ /6.02/ /0.81/0.66 TITL QTitl-WJ-2B.4 E2/E3/E4/P 3.30/3.76/3.60/ /6.76/6.02/ /0.68/0.83/0.38 QTitl-WJ-5D-2.2 E2/E3 2.67/ / / 0.53 QTitl-WJ-5D-1.4 E1/E2/E3/P 4.94/4.15/3.28/ /6.98/7.32/ /0.59/0.57/0.52 PHCI QPhci-WJ-1A.3 E2/E3/P 4.99/2.83/ /2.58/ /0.010/0.007 QPhci-WJ-2A.3 E3/E4/P 2.93/4.28/ /5.39/ /0.008/0.007 FIITCI QFiitci-WJ-2B.5 E1/E2/E3/E4/P 5.07/2.57/2.51/2.94/ /1.91/3.62/4.98/ / 0.004/ 0.009/ 0.007/ QFiitci-WJ-3A.2 E2/E3 6.24/ / / QFiitci-WJ-3B.3 E2/E4/P 4.56/4.58/ /5.32/ /0.006/0.004 QFiitci-WJ-5B.4 E2/E3/E4/P 6.00/3.71/5.83/ /3.16/4.28/ / 0.006/ 0.007/ QFiitci-WJ-5D-1.3 E1/E4/P 4.38/5.70/ /8.81/ / 0.010/ QFiitci-WJ-7D.3 E2/E4/P 4.31/3.06/ /3.67/ / 0.008/ SITCI QSitci-WJ-3B.3 E1/E2/P 3.39/4.04/ /3.71/ /0.005/0.005 QSitci-WJ-6A.2 E2/E4 4.78/ / / TITCI QTitci-WJ-4A.3 E2/E4/P 3.86/2.56/ /6.59/ /0.007/0.004 a The assignment of a QTL name is named according to the following rules: italic uppercase Q denotes QTL ; letters following it are the abbreviation ofthe corresponding trait; the next uppercase letters sandwiched the two dashes indicates the population in which the corresponding QTL was detected; next, a numeral plus an uppercase letter, A, B or D, indicates the wheat chromosome on which the corresponding QTL was detected; if a break occurred on a chromosome, a dash plus a numeral are placed as a suffix to distinguish different segments of the corresponding chromosome; the last numeral after a period denotes the number of environments in which the corresponding QTL was detected b Positive values indicate Weimai 8 alleles that increase the value of the corresponding trait, and conversely, negative values indicate Weimai 8 alleles decrease it

8 8 CUI et al.: QTL for Plant Height Components in Wheat Table 4. Putative additive QTL for internode-related traits showing consistency in no less than two of the four different environments in the WY population Trait QTL a Environment LOD Contributions, % Additive effect b FIITL QFiitl-WY-1D.5 E1/E2/E3/E4/P 4.26/4.37/5.07/4.16/ /7.48/9.02/15.67/ /1.09/1.21/1.46/1.19 QFiitl-WY-2D.2 E1/E3 5.76/ / / 1.43 QFiitl-WY-5D.2 E2/E4 4.19/ / /0.89 QFiitl-WY-7B.3 E3/E4/P 3.36/2.74/ /6.98/ / 0.94/ 0.75 QFiitl-WY-7D.3 E2/E3/P 3.43/3.50/ /7.29/ / 0.99/ 0.85 SITL QSitl-WY-1D.5 E1/E2/E3/E4/P 9.76/7.72/11.25/9.14/ /15.09/28.98/15.16/ /1.23/1.51/1.36/1.08 QSitl-WY-2D.4 E2/E3/E4/P 3.08/5.22/4.98/ /11.78/12.35/ /0.97/1.34/0.67 QSitl-WY-4D-2.3 E2/E4/P 5.46/4.52/ /6.16/ /0.90/0.73 QSitl-WY-5A-1.2 E4/P 2.77/ / /1.27 TITL QTitl-WY-1D.4 E1/E3/E4/P 4.20/7.27/4.96/ /20.11/9.56/ /1.09/0.86/0.64 QTitl-WY-2A.3 E1/E2/E3 3.41/6.06/ /14.56/ /0.78/1.18 QTitl-WY-4D-2.3 E1/E4/P 4.06/5.09/ /7.10/ /0.78//0.75 QTitl-WY-5A-1.2 E1/E2 3.86/ / / 0.40 QTitl-WY-5D.3 E3/E4/P 5.18/3.99/ /6.32/ / 0.79/ 0.74 QTitl-WY-6D.3 E2/E4/P 2.75/3.55/ /4.97/ /0.69/0.53 FOITL QFoitl-WY-2A.3 E2/E3/P 4.90/3.97/ /15.32/ /0.90/0.72 QFoitl-WY-7D.2 E1/E4 6.95/ / / 0.56 FIITCI QFiitci-WY-1D.5 E1/E2/E3/E4/P 6.63/3.51/10.25/5.94/ /5.78/19.32/11.51/ / 0.008/ 0.015/ 0.013/ QFiitci-WY-1D.4 E1/E2/E4/P 4.61/4.00/3.48/ /6.11/5.29/ / 0.013/ 0.014/ QFiitci-WY-2D.4 E1/E3/E4/P 6.27/9.00/6.24/ /17.59/11.16/ / 0.017/ 0.015/ QFiitci-WY-6A.4 E1/E2/E3/P 4.45/3.88/2.77/ /6.23/6.62/ / 0.008/ 0.009/ QFiitci-WY-6D.2 E2/E / / / For title description, see Table 3.

9 CUI et al.: QTL for Plant Height Components in Wheat 9 In the WY population, two QTL were identified reproducibly in two environments of E1, E2, E3 and E4 (Table 4). QTL alleles with length-increasing for FOITL presented in the two parents equally in both WJ and WY. Plant height component index Concerning PHCI, 19 QTL putative additive QTL were detected together in WJ and WY (Fig. 2). Only two QTL in WJ were identified reproducibly in two environments of E1, E2, E3 and E4 (Table 3). Totally, four and five QTL alleles increasing PHCI were donated by Weimai 8 in WJ and WY, respectively. The first internode component index Up to 22 putative additive QTL for FIITCI in WJ and nine in WY were detected (Fig. 2). Of these, six QTL in WJ and five in WY showed significance in at least two environments of E1, E2, E3 and E4 (Table 3 and 4). Nine and two QTL alleles from Weimai 8 increase the phenotypic value of FIITCI in WJ and WY, respectively. The second internode component index Fifteen and ten putative additive QTL for SITCI were identified in WJ and WY, respectively (Fig. 2). Of these, only two QTL in WJ could be detected in at least two of the four environments (Table 3). Totally, there were nine and four QTL alleles from Weimai 8 that increase the phenotypic value of SITCI in WJ and WY, respectively. The third internode component index Thirteen and 12 putative additive QTL for TITCI were identified in WJ and WY, individually explaining % and % of the phenotypic variance, respectively (Fig. 2). Of these, only QTitci-WJ-4A.3 were verified in at least two of the four environments (Table 3). In total, the additive effects for eight and nine QTL were positive with Weimai 8 increasing the QTL effects in WJ and WY populations, respectively. Common QTL resolved in both populations Based on common markers in two genetic maps, comparisons of congruent QTL were conducted. At least 11 pairwise QTL were common to the two populations. Alleles from the common parent Weimai 8 of all pairwise congruent QTL showed consistent additive effects, whether negative or positive simultaneously, with the exception of two pairwise congruent QTL for FIITCI and FOITL (Table 5). Though positions of most QTL identified in the two populations are of high congruency, it was hampered to predict and define a congruent QTL precisely by the limited number of common loci in the two genetic maps.

10 10 CUI et al.: QTL for Plant Height Components in Wheat Table 5. Congruent QTL resolved in both populations WJ a WY b Alleles c Common loci d QTitci-WJ-1A.2 QTitci-WY-1A.1a / BE470813/BE QSitl-WJ-2A.3 QSitl-WY-2A.1 +/+ Xbarc212/Xbarc212 QFiitl-WJ-2A.5 QFiitl-WY-2A.1 +/+ Xpsp3088/Xpsp3088 QPhci-WJ-2A.3 QPhci-WY-2A.1 +/+ Xpsp3088/Xpsp3088 QFiitci-WJ-2A.1 QFiitci-WY-2A.1 +/ Xpsp3088/Xpsp3088 QSitl-WJ-2D-2.2 QSitl-WY-2D.4 +/+ Xcfd168.1/Xcfd168.1 QTitci-WJ-5A-1.1 QTitci-WY-5A-1.1 +/+ Xcwm216/Xcwm216 QFoitl-WJ-5D-1.2 QFoitl-WY-5D.1 +/ Xbarc133/Xbarc133 QPhci-WJ-5D-1.2 QPhci-WY-5D.1a / Xbarc133/Xbarc133 QTitl-WJ-5D-2.2 QTitl-WY-5D.3 / Xwmc765/Xwmc765 QFoitl-WJ-5D-1.1 QFoitl-WY-5D.2 / Xwmc765/Xwmc765 a QTL detected in the WJ population b QTL detected in the WY population c, d For each entry, the first signal refers to WJ, and the second, to WY Discussion Disregarding the spike length, the internode lengths together determine PH in wheat. The genetic relationships between PH and PH components, including the spike length and the internode lengths, have been well characterized in one of our previous report, indicating that PH components, at the QTL level, had different effects on PH (Cui et al. 2011). In addition to the internode lengths, the present report firstly revealed the relationships between PH and the internode component indices and PHCI using unconditional QTL mapping method. Fig. 2 summarized the results of co-located QTL for PH and its component/related traits. Of the 25 unconditional QTL for PH in WJ and 34 in WY, 21 each shared common intervals with that of their corresponding component/related traits, respectively. In addition, 15 chromosomes in WJ and 13 in WY harbored QTL clusters for at least two different PH components. However, not all QTL for any pairwise traits always co-segregated, indicating that the components at the QTL level had different effects on PH, confirming previous reports (Kato et al. 1999; Cui et al. 2011). In addition, these results firstly unraveled the genetic relationships among the eight internode-related traits at the QTL level, thus contributing a lot to the understanding of the genetic basis of PH in wheat. PH in wheat has now been subjected to QTL analysis in many other reports (Kato et al. 1999; Keller et al. 1999; Börner et al. 2002; Huang et al. 2003; Sourdille et al. 2003; Huang et al. 2004; Liu et al. 2005; McCartney et al. 2005; Huang et al. 2006; Marza et al. 2006; Klahr et al. 2007; Zhang et al. 2008; Chu et al. 2008; Wang et al. 2009; Mao et al. 2010; Wang et al. 2010; Wu et al. 2010). However, no report, by now, has documented a QTL analysis on its component traits comprehensively. Previous reports have proven that cultivars with shorter basal internodes were prone to be lodging resistance (Dunn and Briggs 1989; Stanca et al. 1979; Pinthus 1973; Tavakoli et al. 2009). Therefore, understanding the genetic basis for FOITL and TITCI should be of great value for breeding programs designed to increase lodging resistance based on selecting desirable cultivars. Correlation coefficients for the single traits between pairwise experiments indicate that

11 CUI et al.: QTL for Plant Height Components in Wheat 11 FOITL have the lowest level heritability among the four internode lengths referred herein in both populations, as does TITCI among the three internode component indices referred herein in if SITCI was excepted in the WY population (Table 1). These findings implicate the instability of the QTL s expression for FOITL and TITCI across environments, which has been confirmed by the present QTL analysis (Fig. 2). QFoitl-WY-2A.3 and QTitci-WJ-4A.3, two QTL consistent over more than three environments, thus, should be of great value in selection for lodging resistance in breeding programs. Major QTL consistent over environments should be of great value for MAS. We defined an environment-independent QTL that were verified in at least three of the five trials. Together in WJ and WY populations, there were 35 environment-independent QTL (Tables 3 and 4). Of these, 11 were major QTL, each accounting for more than 10% of phenotypic variance; thus, they should be of great value in genetic improvement of wheat PH. Compared to Cui et al. (2011), the innovations and the new findings in the present report were as follows: (i) datas used in the present unconditional QTL mapping analysis was not the conditional phenotypic values of PH with respect to its given component/related traits but the investigative phenotypic values of PH component/related traits; (ii) the aims in the present unconditional QTL mapping analysis were not only to reveal the genetic relationships between PH and PH components but also to identify QTL for PH component/related traits, in turn dissecting the factors affecting PH comprehensively; (iii) the unconditional QTL for the internode lengths, the internode component indices and the plant height component index were firstly reported in this report; and (iv) the genetic relationships, at the QTL level, among the eight internode-related traits were firstly reported herein using the traditional QTL mapping method. In summary, we firstly dissected the factors affecting PH by partitioning it into its components. Thirty-five environment-independent QTL involving in all the eight traits were detected in the two populations and 11 of these were major QTL. The combination of two related populations makes the results of QTL detection more comprehensive. In addition, a large population size can enhance the authenticity and accuracy of the QTL detection. Acknowledgements This research was supported by the National Basic Research Program of China (973 Program, 2006CB101700). The author thanks Sishen Li, College of Agronomy, Shandong Agricultural University, Taian, China, for kindly providing EST-SSR markers. References Börner, A., Schumann, E., Fürste, A., Cöter, H., Leithold, B., Röder, M.S., Weber, W.E Mapping of quantitative trait locus determining agronomic important characters in hexaploid wheat (Triticum aestivum L.). Theor. Appl. Genet. 105: Chu, C.G., Xu, S.S., Friesen, T.L., Faris, J.D Whole genome mapping in a wheat doubled haploid population using SSRs and TRAPs and the identification of QTL for agronomic traits. Mol. Breed. 22: Cui, F., Li, J., Ding, A.M., Zhao, C.H., Wang, L., Wang, X.Q., Li, S.S., Bao, Y.G., Li, X.F., Feng, D.S., Kong, L.R., Wang, H.G Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat. Theor. Appl. Genet. 122:

12 12 CUI et al.: QTL for Plant Height Components in Wheat Dunn, G.J., Briggs, K.G Variation in culm anatomy among barley genotypes differing in lodging resistance. Can. J. Bot. 67: Huang, X.Q., Cloutier, S., Lycar, L., Radovanovic, N., Humphreys, D.G., Noll, J.S., Somers, D.J., Brown, P.D Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.). Theor. Appl. Genet. 113: Huang, X.Q., Cöster, H., Ganal, M.W., Röder, M.S Advanced backcross QTL analysis for the identification of quantitative trait loci alleles from wild relatives of wheat (Triticum aestivum L.). Theor. Appl. Genet. 106: Huang, X.Q., Kempf, H., Ganal, M.W., Röder, M.S Advanced backcross QTL analysis in progenies derived from a cross between a German elite winter wheat variety and a synthetic wheat (Triticum aestivum L). Theor. Appl. Genet. 109: Kato, K., Miura, H., Sawada, S QTL mapping of genes controlling ear emergence time and plant height on chromosome 5A of wheat. Theor. Appl. Genet. 98: Keller, M., Karutz, Ch., Schmid, J.E., Stamp, P., Winzeler, M., Keller, B., Messmer, M.M Quantitative trait loci for lodging resistance in a segregating wheat spelt population. Theor. Appl. Genet. 98: Klahr, A., Zimmermann, G., Wenzel, G., Mohler, V Effects of environment, disease progress, plant height and heading date on the detection of QTLs for resistance to Fusarium head blight in an European winter wheat cross. Euphytica 154: Kosambi, D.D The estimation of map distances from recombination values. Annu. Eugen. 12: Kumar, N., Kulwal, P.L., Balyan, H.S., Gupta, P.K QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat. Mol. Breed. 19: Liu, Z.H., Anderson, J.A., Hu, J., Friesen, T.L., Rasmussen, J.B., Faris, J.D A wheat intervarietal genetic linkage map based on microsatellite and target region amplified polymorphism markers and its utility for detecting quantitative trait loci. Theor. Appl. Genet. 111: Mao, S.L., Wei, Y.M., Cao, W.G., Lan, X.J., Yu, M., Chen, Z.M., Chen, G.Y., Zheng, Y.L Confirmation of the relationship between plant height and Fusarium head blight resistance in wheat (Triticum aestivum L.) by QTL meta-analysis. Euphytica 174: Marza, F., Bai, G.H., Carver, B.F., Zhou, W.C Quantitative trait loci for yield and related traits in the wheat population Ning7840 Clark. Theor. Appl. Genet. 112: McCartney, C.A., Somers, D.J., Humphreys, D.G., Lukow, O., Ames, N., Noll, J., Cloutier, S., McCallum, B.D Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 AC Domain. Genome 48: Peter, H The genes of the green revolution. Trends Genet. 19:5 9. Pinthus, M.J Lodging in wheat, barley and oats: The phenomenon, its causes and preventative measures. Adv. Agron. 25: Sourdille, P., Cadalen, T., Guyomarc h, H., Snape, J.W., Perretant, M.R., Charmet, G., Boeuf, C., Bernard, S., Bernard, M An update of the Courtot Chinese Spring intervarietal molecular marker linkage map for the QTL detection of agronomic traits in wheat. Theor. Appl. Genet. 106: Stanca, A.M., Jenkins, G., Hanson, P.R Varietal responses in spring barley to natural and artificial lodging and to a growth regulator. J. Agric. Sci. (Cambridge) 93: Tavakoli, H., Mohtasebi, S.S., Jafari, A Effects of moisture content, internode position and loading rate on the bending characteristics of barley straw. Res. Agric. Eng. 55: Wang, R.X., Hai, L., Zhang, X.Y., You, G.X., Yan, C.S., Xiao, S.H QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai Yu8679. Theor. Appl. Genet. 118: Wang, Z.H., Wu, X.S., Ren, Q., Chang, X.P., Li, R.Z., Jing, R.L QTL mapping for developmental behavior of plant height in wheat (Triticum aestivum L.). Euphytica 174: Wu, X.S., Wang, Z.H., Chang, X.P., Jing, R.L Genetic dissection of the developmental behaviours of plant height in wheat under diverse water regimes. J. Exp. Bot. 61: Zhang, K.P., Tian, J.C., Zhao, L., Wang, S.S Mapping QTLs with epistatic effects and QTL environment interactions for plant height using a doubled haploid population in cultivated wheat. J. Genet. Genomics 35: Zhu, J Analysis of conditional genetic effects and variance components in developmental genetics. Genetics 141: