Unconditional and Conditional QTL Mapping for Tiller Numbers at Various Stages with Single Segment Substitution Lines in Rice(Oryza sativa L.)

Tiller is one of the most important agronomic traits which influences quantity and quality of effective panicles and finally influences yield in rice. It is important to understand ＂static＂ and ＂dynamic＂ information of the QTLs for tillers in rice. This work was the first time to simultaneously map unconditional and conditional QTLs for tiller numbers at various stages by using single segment substitution lines in rice. Fourteen QTLs for tiller number, distributing on the corresponding substitution segments of chromosomes 1, 2, 3, 4, 6, 7 and 8 were detected. Both the number and the effect of the QTLs for tiller number were various at different stages, from 6 to 9 in the number and from 1.49 to 3.49 in the effect, respectively. Tiller number QTLs expressed in a time order, mainly detected at three stages of 0-7 d, 14-21 d and 35-42 d after transplanting with 6 positive, 9 random and 6 negative expressing QTLs, respectively. Each of the QTLs expressed one time at least during the whole duration of rice. The tiller number at a specific stage was determined by sum of QTL effects estimated by the unconditional method, while the increasing or decreasing number in a given time interval was controlled by the total of QTL effects estimated by the conditional method. These results demonstrated that it is highly effective and accurate for mapping of the QTLs by using single segment substitution lines and the conditional analysis methodology.

Conditional and unconditional QTLs mapping of gluten strength in common wheat (Triticum aestivum L.)

Dissecting the genetic relationships among gluten-related traits is important for high quality wheat breeding. Quantita- tive trait loci （QTLs） analysis for gluten strength, as measured by sedimentation volume （SV） and gluten index （GI）, was performed using the QTLNetwork 2.0 software. Recombinant inbred lines （RILs） derived from the winter wheat varieties Shannong 01-35xGaocheng 9411 were used for the study. A total of seven additive QTLs for gluten strength were identi- fied using an unconditional analysis. QGi1D-13 and QSv1D-14 were detected through unconditional and conditional QTLs mapping, which explained 9.15-45.08% of the phenotypic variation. QTLs only identified under conditional QTL mapping were located in three marker intervals： WPT-3743-GLU-D1 （1D）, WPT-7001-WMC258 （1B）, and WPT-8682-WPT-5562 （1B）. Six pairs of epistatic QTLs distributed nine chromosomes were identified. Of these, two main effect QTLs （QGi1D-13 and QSvlD-14） and 12 pairs of epistatic QTLs were involved in interactions with the environment. The results indicated that chromosomes 1B and 1D are important for the improvement of gluten strength in common wheat. The combination of conditional and unconditional QTLs mapping could be useful for a better understanding of the interdependence of different traits at the QTL molecular level.

Conditional QTL Mapping of Sedimentation Volume on Seven Quality Traits in Common Wheat

To evaluate the possible genetic interrelationships between flour components and the sedimentation volume（SD）,a doubled haploid（DH） population comprising 168 lines were used to identify the conditional quantitative trait loci（QTLs） for SD in three environments.Ten additive QTLs and 15 pairs of epistatic QTLs were detected for SD through unconditional and conditional QTL mapping.Three major additive QTLs were detected for SD conditioned on the seven quality traits.Two additive QTLs were found to be independent of these traits.Three additive QTLs were suppressed by three of the seven traits because of non-detection in unconditional mapping.Three pairs of epistatic QTLs were completely affected by the seven traits because of detection in unconditional mapping but no-detection in conditional mapping.Twelve pairs of epistatic QTLs were detected in conditional mapping.Our results indicated that conditional mapping could contribute to a better understanding of the interdependence of different and closely correlated traits at the QTL molecular level,especially some minor QTLs were found.The conditional mapping approach provides new insights that will make it possible to avoid the disadvantages of different traits by breeding through molecular design.

Dynamics and genetic regulation of macronutrient concentrations during grain development in maize

Nitrogen(N), phosphorus(P), and potassium(K) are essential macronutrients that are crucial not only for maize growth and development, but also for crop yield and quality. The genetic basis of macronutrient dynamics and accumulation during grain filling in maize remains largely unknown. In this study, we evaluated grain N, P, and K concentrations in 206 recombinant inbred lines generated from a cross of DH1M and T877 at six time points after pollination. We then calculated conditional phenotypic values at different time intervals to explore the dynamic characteristics of the N, P, and K concentrations. Abundant phenotypic variations were observed in the concentrations and net changes of these nutrients. Unconditional quantitative trait locus(QTL) mapping revealed 41 non-redundant QTLs, including 17, 16, and 14 for the N, P, and K concentrations, respectively. Conditional QTL mapping uncovered 39 non-redundant QTLs related to net changes in the N, P, and K concentrations. By combining QTL, gene expression, co-expression analysis, and comparative genomic data, we identified 44, 36, and 44 candidate genes for the N, P, and K concentrations, respectively, including GRMZM2G371058 encoding a Doftype zinc finger DNA-binding family protein, which was associated with the N concentration, and GRMZM2G113967encoding a CBL-interacting protein kinase, which was related to the K concentration. The results deepen our understanding of the genetic factors controlling N, P, and K accumulation during maize grain development and provide valuable genes for the genetic improvement of nutrient concentrations in maize.

Identification of genomic regions determining flower and pod numbers development in soybean (Glycine max L.)

Flower and pod numbers per plant are important agronomic traits underlying soybean yield. So far quantitative trait loci （QTL） de- tected for flower and pod-related traits have mainly focused on the final stage, and might therefore have ignored genetic effects expressed during a specific developmental stage. Here, dynamic expressions of QTL for flower and pod numbers were identified using 152 recom- binant inbred lines （RILs） and a linkage map of 306 markers. Wide genetic variation was found among RILs; 17 unconditional and 18 conditional QTL were detected for the two traits at different developmental stages over two years. Some QTL were detected only at one stage and others across two or more stages, indicating that soybean flower and pod numbers development may be governed by time-dependent gene expression. Three main QTL （qfn-Chrl8-2, qfn-Chr20-1, and qfn-Chr19） were detected for flower number, and two main QTL （qpn-Chrll and qpn-Chr20） were detected for pod number. The phenotypic variation explained by them ranged from 6.1% to 34.7%. The markers linked to these QTL could be used in marker-assisted selection for increasing soybean flower and pod numbers, with the ultimate aim of increasing soybean yield. Comparison of the QTL regions for flower and pod numbers traits with the related genes reported previously showed that seven and four related genes were located in the QTL regions of qfn-Chr11 and qfn-Chr19, respectively. These results provide a basis for free mapping and cloning of flower and pod development-related genes.