QTL analysis for yield components and kernel-related traits in maize across multi-environments

Huangzaosi, Qi319, and Ye478 are foundation inbred lines widely used in maize breeding in China. To elucidate genetic base of yield components and kernel-related traits in these elite lines, two F_2:3 populations derived from crosses Qi319?×?Huangzaosi (Q/H, 230 families) and Ye478?×?Huangzaosi (Y/H, 235 families), as well as their parents were evaluated in six environments including Henan, Beijing, and Xinjiang in 2007 and 2008. Correlation and hypergeometric probability function analyses showed the dependence of yield components on kernel-related traits. Three mapping procedures were used to identify quantitative trait loci (QTL) for each population: (1) analysis for each of the six environments, (2) joint analysis for each of the three locations across 2?years, and (3) joint analysis across all environments. For the eight traits measured, 90, 89, and 58 QTL for Q/H, and 72, 76, and 51 QTL for Y/H were detected by the three QTL mapping procedures, respectively. About 70% of the QTL from Q/H and 90% of the QTL from Y/H did not show significant QTL?×?environment interactions in the joint analysis across all environments. Most of the QTL for kernel traits exhibited high stability across 2?years at the same location, even across different locations. Seven major QTL detected under at least four environments were identified on chromosomes 1, 4, 6, 7, 9, and 10 in the populations. Moreover, QTL on chr. 1, chr. 4, and chr. 9 were detected in both populations. These chromosomal regions could be targets for marker-assisted selection, fine mapping, and map-based cloning in maize.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

QTL studies reveal little relevance of chilling-related seedling traits for yield in maize

Prolonged low temperature phases and short-term cold spells often occur in spring during the crucial stages of early maize (Zea mays L.) development. The effect of low temperature-induced growth retardation at the seedling stage on final yield is poorly studied. Therefore, the aim was to identify genomic regions associated with morpho-physiological traits at flowering and harvest stage and their relationship to previously identified quantitative trait loci (QTLs) for photosynthesis and morpho-physiological traits from the same plants at seedling stage. Flowering time, plant height and shoot biomass components at harvest were measured in a dent mapping population for cold tolerance studies, which was sown in the Swiss Midlands in early and late spring in two consecutive years. Early-sown plants exhibited chilling stress during seedling stage, whereas late-sown plants grew under favorable conditions. Significant QTLs, which were stable across environments, were found for plant height and for the time of flowering. The QTLs for flowering were frequently co-localized with QTLs for plant height or ear dry weight. The comparison with QTLs detected at seedling stage revealed only few common QTLs. A pleiotropic effect was found on chromosome 3 which revealed that a good photosynthetic performance of the seedling under warm conditions had a beneficial effect on plant height and partially on biomass at harvest. However, a high chilling tolerance of the seedling seemingly had an insignificant or small negative effect on the yield.     

QTL analysis of drought-related traits and grain yield in relation to genetic variation for leaf abscisic acid concentration in field-grown maize

Abscisic acid (ABA) concentration is a quantitatively inherited trait which plays a pivotal role in the response of plants to drought stress. A recent study identified 17 quantitative trait loci (QTLs) controlling bulk-leaf ABA concentration (L-ABA) in a maize (Zea mays L.) population of 80 F4 random families tested for two years under droughted field conditions. Sixteen of the QTL regions influencing L-ABA also harboured QTLs for one or more of the following traits: stomatal conductance, a drought sensitivity index, leaf temperature, leaf relative water content, anthesis-silking interval, and grain yield. The analysis of the effects of each QTL region on the investigated traits indicated that L-ABA mainly represented an indicator of the level of drought stress experienced by the plant at the time of sampling because an increase in L-ABA was most commonly associated with a decrease in both stomatal conductance and grain yield as well as an increase in leaf temperature. Opposite results were observed at one QTL region on chromosome 7 near the RFLP locus asg8. A model is presented to interpret these contrasting results in terms of pleiotropic effects.Key words: Abscisic acid, ABA, drought stress, quantitative trait locus (QTL), molecular markers, Zea mays.      

QTL detection for stover yield and quality traits using two connected populations in high-oil maize

Both yield and quality traits for stover portion were important for forage and biofuel production utility in maize. A high-oil maize inbred GY220 was crossed with two normal-oil dent maize inbred lines 8984 and 8622 to generate two connected F_2:3 populations with 284 and 265 F_2:3 families. Seven yield and quality traits were evaluated under two environments. The variance components of genotype (σ_g²), environment (σ_e²) and genotype × environment interactions (σ_ge²) were all significant for most traits in both populations. Different levels of correlations were observed for all traits. QTL mapping was conducted using composite interval mapping (CIM) for data under each environment and in combined analysis in both populations. Totally, 45 and 42 QTL were detected in the two populations. Only five common QTL across the two populations, and one and three common QTL across the two environments in the two populations were detected, reflecting substantial influence of genetic backgrounds and environments on the results of QTL detection for stover traits. Combined analysis across two environments failed to detect most QTL mapped using individual environmental data in both populations. Few of the detected QTL displayed digenic epistatic interactions. Common QTL among all traits were consistent with their correlations. Some QTL herein have been detected in previous researches, and linked with candidate genes for enzymes postulated to have direct and indirect roles in cell wall components biosynthesis.     

High congruency of QTL positions for heterosis of grain yield in three crosses of maize

The genetic basis of heterosis in maize has been investigated in a number of studies but results have not been conclusive. Here, we compare quantitative trait loci (QTL) mapping results for grain yield, grain moisture, and plant height from three populations derived from crosses of the heterotic pattern Iowa Stiff Stalk Synthetic × Lancaster Sure Crop, investigated with the Design III, and analyzed with advanced statistical methods specifically developed to examine the genetic basis of mid-parent heterosis (MPH). In two populations, QTL analyses were conducted with a joint fit of linear transformations Z ₁ (trait mean across pairs of backcross progenies) and Z ₂ (half the trait difference between pairs of backcross progenies) to estimate augmented additive and augmented dominance effects of each QTL, as well as their ratio. QTL results for the third population were obtained from the literature. For Z ₂ of grain yield, congruency of QTL positions was high across populations, and a large proportion of the genetic variance (~70%) was accounted for by QTL. This was not the case for Z ₁ or the other two traits. Further, almost all congruent grain yield QTL were located in the same or an adjacent bin encompassing the centromere. We conclude that different alleles have been fixed in each heterotic pool, which in combination with allele(s) from the opposite heterotic pool lead to high MPH for grain yield. Their positive interactions very likely form the base line for the superior performance of the heterotic pattern under study.     

Identification of large-effect QTL for kernel row number has potential for maize yield improvement

The kernel row number (KRN) per ear is an important component of maize (Zea mays L.) yield. In this study, a line with six kernel rows, MT-6, was used to investigate the genetic basis of KRN by quantitative trait locus (QTL) mapping. MT-6 was derived from a maize inbred line Mo17 and a teosinte entry X26-4 (Zea mays ssp. mexicana), with 23 % of its genome being homologous to X26-4. An MT-6/B73 F₂ segregating population consisting of 266 individuals was genotyped using 192 molecular markers spread evenly across the genome. The same F₂ population, together with its F_2:3 population, was phenotyped for KRN in three environments. Five individual QTL for KRN, including three substantially consistent major QTL detected in all environments, were identified on chromosomes 1, 2, 3, 4, and 5, respectively. These QTL accounted for 39.5–65.0 % of the KRN variation in these populations. Additionally, one pair of epistatic interaction between two loci with additive effects was detected and accounted for about 3 % of KRN variation. These results demonstrate that a few major QTL could substantially affect the evolution of maize KRNs and therefore provide valuable information for our understanding of the mechanism of KRN and the improvement in maize grain yield by molecular breeding.     

弱光胁迫对玉米产量及光合特性的影响

通过在玉米授粉前0～14d、授粉后1～14d、授粉后15～28d3个时期分别进行遮光处理,研究了弱光胁迫对两个玉米品种费玉3号和泰玉2号产量及光合特性的影响.结果表明:各时期弱光胁迫均使玉米产量降低,其中授粉前0～14d弱光处理的产量降幅最大,费玉3号对弱光胁迫的反应较泰玉2号敏感.弱光胁迫后籽粒灌浆高峰出现时间延迟、灌浆速率慢、积累量小;弱光胁迫开始的时间越早,籽粒达到最大灌浆速率的时间(Tmax)越晚.弱光胁迫期内,玉米Chl(a b)、Chla/b、光合速率(Pn)、光系统Ⅱ最大光化学效率(Fv/Fm)和光系统Ⅱ实际光化学效率(ФPSⅡ)显著下降,Chlb相对含量提高,胞间二氧化碳浓度(Ci)和非光化学淬灭系数(NPQ)则显著上升;胁迫结束后,玉米Chl(a b)、Chla/b、Pn、Fv/Fm、ФPSⅡ、Ci和NPQ逐渐恢复接近自然光照条件(CK)水平,而Chlb相对含量下降.表明非气孔因素是弱光胁迫下玉米光合速率降低的原因之一.     

Root-ABA1 QTL affects root lodging, grain yield, and other agronomic traits in maize grown under well-watered and water-stressed conditions

A major QTL affecting root traits and leaf ABA concentration was identified in maize (Zea mays L.) and named root-ABA1. For this QTL, back-cross-derived lines (BDLs) homozygous either for the (+) or for the (-) allele increasing or decreasing, respectively, root size and leaf ABA concentration, were developed. This study was conducted to evaluate the QTL effects in various genetic backgrounds and at different water regimes. The (+/+) and (-/-) BDLs were crossed with five or 13 inbred tester lines of different origin, thus producing two sets of test-crosses that were evaluated in Italy and China, respectively. Testing was conducted under both well-watered and water-stressed conditions. In Italy, the test-crosses derived from (+/+) BDLs, as compared with those derived from (-/-) BDLs, showed, across both water regimes, higher leaf ABA concentration (on average 384 versus 351 ng g(-1) DW) and lower root lodging (28.0 versus 52.5%), and lower grain yield under water-stressed conditions (4.88 versus 6.27 Mg ha(-1)). In China, where root lodging did not occur, the test-crosses derived from (+/+) BDLs were less productive at both water regimes (on average, 6.83 versus 7.49 Mg ha(-1)). The lower grain yield of the test-crosses derived from (+/+) BDLs was due to a lower number of ears per plant and to lower kernel weight. The results indicate that the (+) root-ABA1 allele confers not only a consistently lower susceptibility to root lodging but also a lower grain yield, especially when root lodging does not occur.     

Prediction of single-cross hybrid performance in maize using haplotype blocks associated with QTL for grain yield

Marker-based prediction of hybrid performance facilitates the identification of untested single-cross hybrids with superior yield performance. Our objectives were to (1) determine the haplotype block structure of experimental germplasm from a hybrid maize breeding program, (2) develop models for hybrid performance prediction based on haplotype blocks, and (3) compare hybrid performance prediction based on haplotype blocks with other approaches, based on single AFLP markers or general combining ability (GCA), under a validation scenario relevant for practical breeding. In total, 270 hybrids were evaluated for grain yield in four Dent × Flint factorial mating experiments. Their parental inbred lines were genotyped with 20 AFLP primer–enzyme combinations. Adjacent marker loci were combined into haplotype blocks. Hybrid performance was predicted on basis of single marker loci and haplotype blocks. Prediction based on variable haplotype block length resulted in an improved prediction of hybrid performance compared with the use of single AFLP markers. Estimates of prediction efficiency (R ² ) ranged from 0.305 to 0.889 for marker-based prediction and from 0.465 to 0.898 for GCA-based prediction. For inter-group hybrids with predominance of general over specific combining ability, the hybrid prediction from GCA effects was efficient in identifying promising hybrids. Considering the advantage of haplotype block approaches over single marker approaches for the prediction of inter-group hybrids, we see a high potential to substantially improve the efficiency of hybrid breeding programs. Tobias A. Schrag and Hans Peter Maurer contributed equally to this work.     

QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye

Key message

Genetic diversity in elite rye germplasm as well as F _2:3 testcross design enables fast QTL mapping to approach genes controlling grain yield, grain weight, tiller number and heading date in rye hybrids.

Abstract

Winter rye (Secale cereale L.) is a multipurpose cereal crop closely related to wheat, which offers the opportunity for a sustainable production of food and feed and which continues to emerge as a renewable energy source for the production of bioethanol and biomethane. Rye contributes to increase agricultural crop species diversity particularly in Central and Eastern Europe. In contrast to other small grain cereals, knowledge on the genetic architecture of complex inherited, agronomic important traits is yet limited for the outbreeding rye. We have performed a QTL analysis based on a F_2:3 design and testcross performance of 258 experimental hybrids in multi-environmental field trials. A genetic linkage map covering 964.9 cM based on SSR, conserved-orthologous set (COS), and mixed-phase dominant DArT markers allowed to describe 22 QTL with significant effects for grain yield, heading date, tiller number, and thousand grain weight across seven environments. Using rye COS markers, orthologous segments for these traits have been identified in the rice genome, which carry cloned and functionally characterized rice genes. The initial genome scan described here together with the existing knowledge on candidate genes provides the basis for subsequent analyses of the genetic and molecular mechanisms underlying agronomic important traits in rye.

     

Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia

Rice double-haploid (DH) lines of an indica and japonica cross were grown at nine different locations across four countries in Asia. Genotype-by-environment (G x E) interaction analysis for 11 growth- and grain yield-related traits in nine locations was estimated by AMMI analysis. Maximum G x E interaction was exhibited for fertility percentage number of spikelets and grain yield. Plant height was least affected by environment, and the AMMI model explained a total of 76.2% of the interaction effect. Mean environment was computed by averaging the nine environments and subsequently analyzed with other environments to map quantitative trait loci (QTL). QTL controlling the 11 traits were detected by interval analysis using mapmaker/qtl. A threshold LOD of >/=3.20 was used to identify significant QTL. A total of 126 QTL were identified for the 11 traits across nine locations. Thirty-four QTL common in more than one environment were identified on ten chromosomes. A maximum of 44 QTL were detected for panicle length, and the maximum number of common QTL were detected for days to heading detected. A single locus for plant height (RZ730-RG810) had QTL common in all ten environments, confirming AMMI results that QTL for plant height were affected the least by environment, indicating the stability of the trait. Two QTL were detected for grain yield and 19 for thousand-grain weight in all DH lines. The number of QTL per trait per location ranged from zero to four. Clustering of the QTL for different traits at the same marker intervals was observed for plant height, panicle number, panicle length and spikelet number suggesting that pleiotropism and or tight linkage of different traits could be the possible reason for the congruence of several QTL. The many QTL detected by the same marker interval across environments indicate that QTL for most traits are stable and not essentially affected by environmental factors.     

Molecular-marker-facilitated studies of morphological traits in maize. II: Determination of QTLs for grain yield and yield components

Genetic factors controlling quantitative inheritance of grain yield and its components have not previously been investigated by using replicated lines of an elite maize (Zea mays L.) population. The present study was conducted to identify quantitative trait loci (QTLs) associated with grain yield and grain-yield components by using restriction fragment length polymorphism (RFLP) markers. A population of 150 random F₂₃ lines was derived from the single cross of inbreds Mo17 and H99, which are considered to belong to the Lancaster heterotic group. Trait values were measured in a replicated trial near Ames, Iowa, in 1989. QTLs were located on a linkage map constructed with one morphological and 103 RFLP loci. QTLs were found for grain yield and all yield components. Partial dominance to overdominance was the primary mode of gene action. Only one QTL, accounting for 35% of the phenotypic variation, was identified for grain yield. Two to six QTLs were identified for the other traits. Several regions with pleiotropic or linked effects on several of the yield components were detected.     

Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL

Prediction methods to identify single-cross hybrids with superior yield performance have the potential to greatly improve the efficiency of commercial maize (Zea mays L.) hybrid breeding programs. Our objectives were to (1) identify marker loci associated with quantitative trait loci for hybrid performance or specific combining ability (SCA) in maize, (2) compare hybrid performance prediction by genotypic value estimates with that based on general combining ability (GCA) estimates, and (3) investigate a newly proposed combination of the GCA model with SCA predictions from genotypic value estimates. A total of 270 hybrids was evaluated for grain yield and grain dry matter content in four Dent × Flint factorial mating experiments, their parental inbred lines were genotyped with 20 AFLP primer-enzyme combinations. Markers associated significantly with hybrid performance and SCA were identified, genotypic values and SCA effects were estimated, and four hybrid performance prediction approaches were evaluated. For grain yield, between 38 and 98 significant markers were identified for hybrid performance and between zero and five for SCA. Estimates of prediction efficiency (R ²) ranged from 0.46 to 0.86 for grain yield and from 0.59 to 0.96 for grain dry matter content. Models enhancing the GCA approach with SCA estimates resulted in the highest prediction efficiency if the SCA to GCA ratio was high. We conclude that it is advantageous for prediction of single-cross hybrids to enhance a GCA-based model with SCA effects estimated from molecular marker data, if SCA variances are of similar or larger importance as GCA variances.     

Molecular mapping of quantitative trait loci for three kernel-related traits in maize using a double haploid population

Kernel size and kernel weight are important factors possibly involved in the determination of grain yield in maize, so identifying the genetic basis of kernel-related traits provides insights into the breeding of high-yield maize varieties. Kernel length (KL), kernel width (KW) and hundred kernel weight (HKW) were evaluated in three various planting conditions for the 240 field-grown double haploid (DH) lines derived from the single-cross hybrid Xianyu335. Variations in KL, KW and HKW were observed among DH lines, and all three traits showed a broad sense heritability of 76%. A total of 964 single nucleotide polymorphisms (SNPs) from the MaizeSNP3072 chip was utilised to create a high-density genetic map of 1546.4 cM and to identify quantitative trait loci (QTLs). Using composite interval mapping, a total of five, seven and five QTLs have been mapped for KL, KW and HKW, respectively. qkl1-2 and qkl4-1 explained 17.8% and 14.2% of the phenotypic variation in KL, respectively, and the other three QTLs contributed 3.2–4.0%. The phenotypic variation explained (PVE) of seven QTLs responsible for KW ranged from 3.3 to 9.5%. Three QTLs for HKW, qhkw1, qhkw5 and qhkw10 each explained more than 10% of the phenotypic variation, and qhkw4 and qhkw9 accounted for 3.0% and 6.0%, respectively. Due to their detection in multiple planting environments, the loci mapped here appear to be potential targets for the improvement of maize grain yield.     

Identification of QTL for production traits in chickens

If the poultry industry hopes to continue to flourish, the identification of potential quantitative trait loci (QTL) for production-related traits must be pursued This remains true despite the sequencing of the chicken genome. In view of this need, a scan of the chicken genome using 72 microsatellite markers was carried out on a meat-type x egg-type resource population measured for production and egg quality traits. Using a Bayesian analysis, potential QTL for a number of traits were identified on several chromosomes. Evidence of eight QTL regions associated with a total of eight traits (specific gravity, albumin height, Haugh score, shell shape, total number of eggs, final body weight, gain, and feed efficiency) was found. Two of these regions, one spanning the area of 263/287 cM on GAA01 and the other spanning the area of 23/28 cM on GAA02, were associated with multiple QTL.     

Identification of QTL for drought responses in maize and their use in testing causal relationships between traits

A difficulty in identifying traits that help crop plants maintaintheir yield under droughted conditions is distinguishing betweenthose traits that contribute to yield stability under droughtand traits that do not affect yield. With the development ofmolecular markers for many crops it is now possible to identifymajor quantitative trait loci (QTL) regulating specific droughtresponses. By comparing the coincidence of such QTL for specifictraits it is possible to test much more precisely than beforewhether a particular constitutive or adaptive response to droughtstress is likely to be of significance in improving droughtresistance. We have used this approach to identify QTL for ABAcontent and other traits likely to be important in determiningdrought response in maize. Eighty-four RFLP markers were mapped in an F2 population of81 plants from a cross between parents, Polj17 (drought resistant)and F-2 (drought sensitive), that differ markedly in many constitutiveand adaptive responses to drought stress. In a soil glasshouseexperiment, from which water was withheld for 3 weeks afteranthesis, flowering time, stomatal conductance, tissue ABA contents,leaf water relations parameters and fluorescence characteristics,root pulling force, and nodal root number were measured. Theminimum number and location of genes having major effects onthe traits were determined and possible causal relationshipsamongst them tested. Comparing the coincidence of QTL for ABAcontent and stomatal conductance showed that xylem ABA contentwas more likely to have had a regulatory effect on the stomatalconductance of those plants than the whole leaf ABA content.However, both xylem and leaf ABA contents were significantlyassociated with root characteristics, suggesting that the rootingbehaviour (either constitutive or adaptive) was important inregulating stress responses, particularly in determining xylemABA contents. We also found that Fm (a measure of the activityof photosynthetic reaction centres) was positively associatedwith chlorophyll concentration per unit area. Different methodsfor comparing QTL are presented and discussed. Key words: Quantitative trait loci (QTL), ABA content, rooting behaviour, fluorescence characteristics, drought responses, maize     

QTL analyses of heterosis for grain yield and yield-related traits in indica-japonica crosses of rice (Oryza sativa L.)

Two sets of rice materials, 166 RILs derived from a cross between Milyang 23 (Korean indica-type rice) and Tong 88-7 (japonica Rice), and BC₁F₁ hybrids derived from crosses between the RILs and the female parent, Milyang 23, were produced to identify QTLs for heterosis of yield and yield-related traits. The QTLs were detected from three different phenotype data sets including the RILs, BC1F1 hybrids, and mid-parental heterosis data set acquired from the definition of mid-parental heterosis. A total of 57 QTLs were identified for nine traits. Of eight QTLs detected for yield heterosis, five overlapped with other heterosis QTLs for yield-related traits such as spikelet number per panicle, days to heading, and spikelet fertility. Four QTLs for yield heterosis, gy1.1, py6, gy10, and py11, were newly identified in this study. We identified a total of 17 EpQTLs for yield heterosis that explain 21.4 ?? 59.0 % of total phenotypic variation, indicating that epistatic interactions may play an important role in heterosis.     

Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length

Deep-seeding tolerant seeds can emerge from deep soil where the moisture is suitable for seed germination. Breeding deep-seeding tolerant cultivars is becoming increasingly important in arid and semi-arid regions. To dissect the quantitative trait loci (QTL) controlling deep-seeding tolerance traits, we selected a tolerant maize inbred line 3681-4 and crossed it with the elite inbred line-X178 to generate an F₂ population and the derivative F_2:3 families. A molecular linkage map composed of 179 molecular markers was constructed, and 25 QTL were detected including 10 QTL for sowing at 10 cm depth and 15 QTL for sowing at 20 cm depth. The QTL analysis results confirmed that deep-seeding tolerance was mainly caused by mesocotyl elongation and also revealed considerable overlap among QTL for different traits. To confirm a major QTL on chromosome 10 for mesocotyl length measured at 20 cm depth, we selected and self-pollinated a BC₃F₂ plant that was heterozygous at the markers around the target QTL and homozygous at other QTL to generate a BC₃F₃ population. We found that this QTL explained more phenotypic variance in the BC₃F₃ population than that in the F₂ population, which laid the foundation for fine mapping and NIL (near-isogenic line) construction.