Wheat (Triticum aestivum L.) yield is directly proportional to physio-morphological traits. A high-density genetic map consisting of 2575 markers was used for mapping QTL controlling stay-green and agronomic traits in wheat grown under four diverse water regimes. A total of 108 additive QTL were identified in target traits. Among them, 28 QTL for chlorophyll content (CC) were detected on 11 chromosomes, 43 for normalized difference vegetation index (NDVI) on all chromosomes except 5B, 5D, and 7D, five for spikes per plant (NSP) on different chromosomes, nine for plant height (PH) on four chromosomes, and 23 for thousand-kernel weight (TKW) on 11 chromosomes. Considering all traits, the phenotypic variation explained (PVE) ranged from 3.61 to 41.62%. A major QTL, QNDVI.cgb-5A.7, for NDVI with a maximum PVE of 20.21%, was located on chromosome 5A. A stable and major PH QTL was observed on chromosome 4D with a PVE close to 40%. Most distances between QTL and corresponding flanking markers were less than 1 cM, and approximately one-third of the QTL coincided with markers. Each of 16 QTL clusters on 10 chromosomes controlled more than one trait and therefore could be regarded as pleiotropic regions in response to different water regimes. Forty-one epistatic QTL were identified for all traits having PVE of 6.00 to 25.07%. Validated QTL closely linked to flanking markers will be beneficial for marker-assisted selection in improving drought-tolerance in wheat.
Heat stress, a major abiotic stressor of wheat (Triticum aestivum L.), often results in reduced yield and decreased quality. In this study, a proteomic method, Tags for Relative and Absolute Quantitation Isobaric (iTRAQ), was adopted to analyze the protein expression profile changes among wheat cultivar Jing411 under heat stress. Results indicated that there were 256 different proteins expressed in Jing411 under heat stress. According to the result of gene annotation and functional classification, 239 proteins were annotated by 856 GO function entries, including growth and metabolism proteins, energy metabolism proteins, processing and storage proteins, defense-related proteins, signal transduction, unknown function proteins and hypothetical proteins. GO enrichment analysis suggested that the differentially expressed proteins in Jing411 under heat stress were mainly involved in stimulus response (67), abiotic stress response (26) and stress response (58), kinase activity (12), and transferase activity (12). Among the differentially expressed proteins in Jing411, 115 were attributed to 119 KEGG signaling/metabolic pathways. KEGG pathway enrichment analysis in Jing411 showed that heat stress mainly affected the starch and sucrose metabolism as well as protein synthesis pathway in the endoplasmic reticulum. The protein interaction network indicated that there were 8 differentially expressed proteins that could form an interaction network in Jing411.
5 November 2020 in Theoretical and Applied Genetics
Starch and prolamin composition and content are important indexes for determining the processing and nutritional quality of wheat (Triticum aestivum L.) grains. Several transcription factors (TFs) regulate gene expression during starch and protein biosynthesis in wheat. Storage protein activator (TaSPA), a member of the basic leucine zipper (bZIP) family, has been reported to activate glutenin genes and is correlated to starch synthesis related genes. In this study, we generated TaSPA-B overexpressing (OE) transgenic wheat lines. Compared with wild-type (WT) plants, the starch content was slightly reduced and starch granules exhibited a more polarized distribution in the TaSPA-B OE lines. Moreover, glutenin and ω- gliadin contents were significantly reduced, with lower expression levels of related genes (e.g., By15, Dx2, and ω-1,2 gliadin gene). RNA-seq analysis identified 2023 differentially expressed genes (DEGs). The low expression of some DEGs (e.g., SUSase, ADPase, Pho1, Waxy, SBE, SSI, and SS II a) might explain the reduction of starch contents. Some TFs involved in glutenin and starch synthesis might be regulated by TaSPA-B, for example, TaPBF was reduced in TaSPA-B OE-3 lines. In addition, dual-luciferase reporter assay indicated that both TaSPA-B and TaPBF could transactivate the promoter of ω-1,2 gliadin gene. These results suggest that TaSPA-B regulates a complex gene network and plays an important role in starch and protein biosynthesis in wheat.