As important yield-related traits, thousand-grain weight (TGW), grain number per spike (GNS) and grain weight per spike (GWS) are crucial components of wheat production.  To dissect their underlying genetic basis, a double haploid (DH) population comprised of 198 lines derived from 8762/Keyi 5214 was constructed.  We then used genechip to genotype the DH population and integrated the yield-related traits TGW, GNS and GWS for QTL mapping.  Finally, we obtained a total of 18 942 polymorphic SNP markers and identified 41 crucial QTLs for these traits.  Three stable QTLs for TGW were identified on chromosomes 2D (QTgw-2D.3 and QTgw-2D.4) and 6A (QTgw-6A.1), with additive alleles all from the parent 8762, explaining 4.81–18.67% of the phenotypic variations.  Five stable QTLs for GNS on chromosomes 3D, 5B, 5D and 6A were identified.  QGns-5D.1 was from parent 8762, while the other four QTLs were from parent Keyi 5214, explaining 5.89–7.08% of the GNS phenotypic variations.  In addition, a stable GWS genetic locus QGws-4A.3 was detected from the parent 8762, which explained 6.08–6.14% of the phenotypic variations.  To utilize the identified QTLs, we developed STARP markers for four important QTLs, Tgw2D.3-2, Tgw2D.4-1, Tgw6A.1 and Gns3D.1.  Our results provide important basic resources and references for the identification and cloning of genes related to TGW, GNS and GWS in wheat.

The construction of high density genetic linkage map provides a powerful tool to detect and map quantitative trait loci (QTLs) controlling agronomically important traits. In this study, simple sequence repeat (SSR) markers and Illumina 9K iSelect single nucleotide polymorphism (SNP) genechip were employed to construct one genetic linkage map of common wheat (Triticum aestivum L.) using 191 recombinant inbred lines (RILs) derived from cross Yu 8679×Jing 411. This map included 1 901 SNP loci and 178 SSR loci, covering 1 659.9 cM and 1 000 marker bins, with an average interval distance of 1.66 cM. A, B and D genomes covered 719.1, 703.5 and 237.3 cM, with an average interval distance of 1.66, 1.45 and 2.9 cM, respectively. Notably, the genetic linkage map covered 20 chromosomes, with the exception of chromosome 5D. Bioinformatics analysis revealed that 1 754 (92.27%) of 1 901 mapped SNP loci could be aligned to 1 215 distinct wheat unigenes, among which 1 184 (97.4%) were located on one single chromosome, and the rest 31 (2.6%) were located on 2 to 3 chromosomes. By performing in silico comparison, 214 chromosome deletion bin-mapped expressed sequence tags (ESTs), 1 043 Brachypodium genes and 1 033 rice genes were further added onto the genetic linkage map. This map not only integrated genetic and physical maps, SSR and SNP loci, respectively, but also provided the information of Brachypodium and rice genes corresponding to 1 754 SNP loci. Therefore, it will be a useful tool for comparative genomics analysis, fine mapping of QTL/gene controlling agronomically important traits and marker-assisted selection breeding in wheat.

14-3-3 proteins belong to a family of phosphoserine/threonine-binding modules and participate in a wide array of signal transduction and regulatory events. Our previous study demonstrated that Ta14-3-3 was significantly down-regulated in leaf and root tissues of hybrid wheat at the tillering stage. In this paper, three homoeologous Ta14-3-3 genes were cloned from common wheat (Triticum aestivum L., 2n=6x=42, AABBDD) and mapped on chromosomes 2A, 2B, and 2D, respectively. Transgenic Arabidopsis plants ectopically overexpressing Ta14-3-3 displayed shorter primary roots, delayed flowering and retarded growth rates, indicating that Ta14-3-3 acted as a growth inhibitor in Arabidopsis. In wheat, Ta14-3-3 was down-regulated in roots and leaves of hybrids as compared to their parental lines. We proposed that Ta14-3-3 proteins might regulate growth vigor in hybrid wheat.

Plant leaves respond to day/night cycling in a number of physiological ways. At the mRNA level, the expression of some genes changes during the 24 h period. To determine which proteins exhibited a rhythmic pattern of expression, proteomic profiles in maize seedling leaves were analyzed by high-throughput two-dimensional gel electrophoresis, combined with MALDI-TOF MS technology. Of the 464 proteins that were detected with silver staining in a pH range of 4-7, 17 (3.66%) showed clock rhythmicity in their abundance. These proteins belonged to diverse functional groups and proteins involved in photosynthesis and carbon metabolism were over-represented. These findings provide a new perspective on the relationship between the physiological functions of leaves and the clock rhythmic system.