Plant height (PH) in wheat is a complex trait; its components include spike length (SL) and internode lengths. To precisely analyze the factors affecting PH, two F(8:9) recombinant inbred line (RIL) populations comprising 485 and 229 lines were generated. Crosses were performed between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY). Possible genetic relationships between PH and PH components (PHC) were evaluated at the quantitative trait locus (QTL) level. PH and PHC (including SL and internode lengths from the first to the fourth counted from the top, abbreviated as FIITL, SITL, TITL, and FOITL, respectively) were measured in four environments. Individual and the pooled values from four trials were used in the present analysis. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using IciMapping V2.2. All 21 chromosomes in wheat were shown to harbor factors affecting PH in two populations, by both conditional and unconditional QTL mapping methods. At least 11 pairwise congruent QTL were identified in the two populations. In total, ten unconditional QTL and five conditional QTL that could be detected in the conditional analysis only have been verified in no less than three trials in WJ and WY. In addition, three QTL on the short arms of chromosomes 4B, 4D, and 7B were mapped to positions similar to those of the semi-dwarfing genes Rht-B1, Rht-D1 and Rht13, respectively. Conditional QTL mapping analysis in WJ and WY proved that, at the QTL level, SL contributed the least to PH, followed by FIITL; TITL had the strongest influence on PH, followed by SITL and FOITL. The results above indicated that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and it can efficiently and precisely reveal counteracting QTL, which will enhance the understanding of the genetic basis of PH in wheat. The combination of two related populations with a large/moderate population size made the results authentic and accurate.

Grain protein content (GPC) and gluten quality are the most important factors determining the end-use quality of wheat for pasta-making. Both GPC and gluten quality are considered to be polygenic traits influenced by environmental factors and other agricultural practices. Two related F 8:9 recombinant inbred line (RIL) populations were generated to localise genetic factors controlling seven quality traits: GPC, wet gluten content (WGC), flour whiteness (FW), kernel hardness (KH), water absorption (Abs), dough development time (DDT) and dough stability time (DST). These lines were derived by crossing Weimai 8 and Jimai 20 (WJ) and by crossing Weimai 8 and Yannong 19 (WY). In total, WJ comprised 485 lines, while WY comprised 229 lines. Data on these seven quality traits were collected from each line in five different environments. Up to 85 putative QTLs for the seven traits were detected in WJ and 65 putative QTLs were detected in WY. Of these QTLs, 31 QTLs (36.47%) were detected in at least two trials in WJ, while 24 QTLs (36.92%) were detected in at least two trials in WY. Three QTLs from WJ and 25 from WY accounted for more than 10% of the phenotypic variance. The total 150 QTLs were spread throughout all 21 wheat chromosomes. Of these, at least thirteen pairwise were common to both populations, accounting for 20.00 and 15.29% of the total QTLs in WJ and WY, respectively. A major QTL for GPC, accounting for 53.04% of the phenotypic variation, was detected on chromosome 5A. A major QTL for WGC also shared this interval, explained more than 36% of the phenotypic variation, and was significant in two environments. Though colocated QTLs were common, every trait had its unique control mechanism, even for two closely related traits. Due to the different sizes of the two line populations, we also assessed the effects of population size on the efficiency and precision of QTL detection. In sum, this study will enhance our understanding of the genetic basis of these seven pivotal quality traits and facilitate the breeding of improved wheat varieties.

Arabidopsis cryptochrome 2 (CRY2) is a blue-light receptor mediating blue-light inhibition of hypocotyl elongation and photoperiodic promotion of floral initiation. CRY2 is a constitutive nuclear protein that undergoes blue-light-dependent phosphorylation, ubiquitination, photobody formation, and degradation in the nucleus, but the relationship between these blue-light-dependent events remains unclear. It has been proposed that CRY2 phosphorylation triggers a conformational change responsible for the subsequent ubiquitination and photobody formation, leading to CRY2 function and/or degradation. We tested this hypothesis by a structure-function study, using mutant CRY2-GFP fusion proteins expressed in transgenic Arabidopsis. We show that changes of lysine residues of the NLS (Nuclear Localization Signal) sequence of CRY2 to arginine residues partially impair the nuclear importation of the CRY2K541R and CRY2K554/5R mutant proteins, resulting in reduced phosphorylation, physiological activities, and degradation in response to blue light. In contrast to the wild-type CRY2 protein that forms photobodies exclusively in the nucleus, the CRY2K541R and CRY2K554/5R mutant proteins form protein bodies in both the nucleus and cytosol in response to blue light. These results suggest that photoexcited CRY2 molecules can aggregate to form photobody-like structure without the nucleus-dependent protein modifications or the association with the nuclear CRY2-interacting proteins. Taken together, the observation that CRY2 forms photobodies markedly faster than CRY2 phosphorylation in response to blue light, we hypothesize that the photoexcited cryptochromes form oligomers, preceding other biochemical changes of CRY2, to facilitate photobody formation, signal amplification, and propagation, as well as desensitization by degradation.

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