SUMMARYMaize plant height is closely associated with biomass, lodging resistance and grain yield. Determining the genetic basis of plant height by characterizing and cloning plant height genes will guide the genetic improvement of crops. In this study, a quantitative trait locus (QTL) for plant height, qPH3.1, was identified on chromosome 3 using populations derived from a cross between Zong3 and its chromosome segment substitution line, SL15. The plant height of the two lines was obviously different, and application of exogenous gibberellin A 3 removed this difference. QTL mapping placed qPH3.1 within a 4.0 cM interval, explaining 32.3% of the phenotypic variance. Furthermore, eight homozygous segmental isolines (SILs) developed from two larger F 2 populations further narrowed down qPH3.1 to within a 12.6 kb interval. ZmGA3ox2, an ortholog of OsGA3ox2, which encodes a GA3 b-hydroxylase, was positionally cloned. Association mapping identified two polymorphisms in ZmGA3ox2 that were significantly associated with plant height across two experiments. Quantitative RT-PCR showed that SL15 had higher ZmGA3ox2 expression relative to Zong3. The resultant higher GA 1 accumulation led to longer internodes in SL15 because of increased cell lengths. Moreover, a large deletion in the coding region of ZmGA3ox2 is responsible for the dwarf mutant d1-6016. The successfully isolated qPH3.1 enriches our knowledge on the genetic basis of plant height in maize, and provides an opportunity for improvement of plant architecture in maize breeding.

Key messageMaize kernel row number might be dominated by a set of large additive or partially dominant loci and several small dominant loci and can be accurately predicted by fewer than 300 top KRN-associated SNPs.AbstractKernel row number (KRN) is an important yield component in maize and directly affects grain yield. In this study, we combined linkage and association mapping to uncover the genetic architecture of maize KRN and to evaluate the phenotypic predictability using these detected loci. A genome-wide association study revealed 31 associated single nucleotide polymorphisms (SNPs) representing 17 genomic loci with an effect in at least one of five individual environments and the best linear unbiased prediction (BLUP) over all environments. Linkage mapping in three F2:3 populations identified 33 KRN quantitative trait loci (QTLs) representing 21 QTLs common to several population/environments. The majority of these common QTLs that displayed a large effect were additive or partially dominant. We found 70 % KRN-associated genomic loci were mapped in KRN QTLs identified in this study, KRN-associated SNP hotspots detected in NAM population and/or previous identified KRN QTL hotspots. Furthermore, the KRN of inbred lines and hybrids could be predicted by the additive effect of the SNPs, which was estimated using inbred lines as a training set. The prediction accuracy using the top KRN-associated tag SNPs was obviously higher than that of the randomly selected SNPs, and approximately 300 top KRN-associated tag SNPs were sufficient for predicting the KRN of the inbred lines and hybrids. The results suggest that the KRN-associated loci and QTLs that were detected in this study show great potential for improving the KRN with genomic selection in maize breeding.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-015-2581-2) contains supplementary material, which is available to authorized users.

The kernel number is a grain yield component and an important maize breeding goal. Ear length, kernel number per row and ear row number are highly correlated with the kernel number per ear, which eventually determines the ear weight and grain yield. In this study, two sets of F2:3 families developed from two bi-parental crosses sharing one inbred line were used to identify quantitative trait loci (QTL) for four kernel number-related traits: ear length, kernel number per row, ear row number and ear weight. A total of 39 QTLs for the four traits were identified in the two populations. The phenotypic variance explained by a single QTL ranged from 0.4% to 29.5%. Additionally, 14 overlapping QTLs formed 5 QTL clusters on chromosomes 1, 4, 5, 7, and 10. Intriguingly, six QTLs for ear length and kernel number per row overlapped in a region on chromosome 1. This region was designated qEL1.10 and was validated as being simultaneously responsible for ear length, kernel number per row and ear weight in a near isogenic line-derived population, suggesting that qEL1.10 was a pleiotropic QTL with large effects. Furthermore, the performance of hybrids generated by crossing 6 elite inbred lines with two near isogenic lines at qEL1.10 showed the breeding value of qEL1.10 for the improvement of the kernel number and grain yield of maize hybrids. This study provides a basis for further fine mapping, molecular marker-aided breeding and functional studies of kernel number-related traits in maize.

IntroductionBuckwheat (Fagopyrum tataricum), an important food crop, also has medicinal uses. It is widely planted in Southwest China, overlapping with planting areas remarkably polluted by cadmium (Cd). Therefore, it is of great significance to study the response mechanism of buckwheat under Cd stress and further develop varieties with excellent Cd tolerance.MethodsIn this study, two critical periods of Cd stress treatment (days 7 and 14 after Cd treatment) of cultivated buckwheat (Pinku-1, named K33) and perennial species (F. tatari-cymosum Q.F. Chen) (duoku, named DK19) were analyzed using transcriptome and metabolomics.ResultsThe results showed that Cd stress led to changes in reactive oxygen species (ROS) and the chlorophyll system. Moreover, Cd-response genes related to stress response, amino acid metabolism, and ROS scavenging were enriched or activated in DK19. Transcriptome and metabolomic analyses highlighted the important role of galactose, lipid (glycerophosphatide metabolism and glycerophosphatide metabolism), and glutathione metabolism in response to Cd stress in buckwheat, which are significantly enriched at the gene and metabolic levels in DK19.DiscussionThe results of the present study provide valuable information for a better understanding of the molecular mechanisms underlying Cd tolerance in buckwheat and useful clues for the genetic improvement of drought tolerance in buckwheat.