Transgenic creeping bentgrass overexpressing Osa‐miR393a exhibits altered plant development and improved multiple stress tolerance

MicroRNA393 (miR393) has been implicated in plant growth, development and multiple stress responses in annual species such as Arabidopsis and rice. However, the role of miR393 in perennial grasses remains unexplored. Creeping bentgrass (Agrostis stolonifera L.) is an environmentally and economically important C3 cool‐season perennial turfgrass. Understanding how miR393 functions in this representative turf species would allow the development of novel strategies in genetically engineering grass species for improved abiotic stress tolerance. We have generated and characterized transgenic creeping bentgrass plants overexpressing rice pri‐miR393a (Osa‐miR393a). We found that Osa‐miR393a transgenics had fewer, but longer tillers, enhanced drought stress tolerance associated with reduced stomata density and denser cuticles, improved salt stress tolerance associated with increased uptake of potassium and enhanced heat stress tolerance associated with induced expression of small heat‐shock protein in comparison with wild‐type controls. We also identified two targets of miR393, AsAFB2 and AsTIR1, whose expression is repressed in transgenics. Taken together, our results revealed the distinctive roles of miR393/target module in plant development and stress responses between creeping bentgrass and other annual species, suggesting that miR393 would be a promising candidate for generating superior crop cultivars with enhanced multiple stress tolerance, thus contributing to agricultural productivity.     

A metabolome‐based core hybridisation strategy for the prediction of rice grain weight across environments

Marker‐based prediction holds great promise for improving current plant and animal breeding efficiencies. However, the predictabilities of complex traits are always severely affected by negative factors, including distant relatedness, environmental discrepancies, unknown population structures, and indeterminate numbers of predictive variables. In this study, we utilised two independent F₁ hybrid populations in the years 2012 and 2015 to predict rice thousand grain weight (TGW) using parental untargeted metabolite profiles with a partial least squares regression method. A stable predictive model for TGW was built based on hybrids from the population in 2012 (r = 0.75) but failed to properly predict TGW for hybrids from the population in 2015 (r = 0.27). After integrating hybrids from both populations into the training set, the TGW of hybrids could be predicted but was largely dependent on population structures. Then, core hybrids from each population were determined by principal component analysis and the TGW of hybrids in both environments were successfully predicted (r > 0.60). Moreover, adjusting the population structures and numbers of predictive analytes increased TGW predictability for hybrids in 2015 (r = 0.72). Our study demonstrates that the TGW of F₁ hybrids across environments can be accurately predicted based on parental untargeted metabolite profiles with a core hybridisation strategy in rice. Metabolic biomarkers identified from early developmental stage tissues, which are grown under experimental conditions, may represent a workable approach towards the robust prediction of major agronomic traits for climate‐adaptive varieties.     

Rho‐associated coiled‐coil kinase 1 activation mediates amyloid precursor protein site‐specific Ser655 phosphorylation and triggers amyloid pathology

Rho‐associated coiled‐coil kinase 1 (ROCK1) is proposed to be implicated in Aβ suppression; however, the role for ROCK1 in amyloidogenic metabolism of amyloid precursor protein (APP) to produce Aβ was unknown. In the present study, we showed that ROCK1 kinase activity and its APP binding were enhanced in AD brain, resulting in increased β‐secretase cleavage of APP. Furthermore, we firstly confirmed that APP served as a substrate for ROCK1 and its major phosphorylation site was located at Ser655. The increased level of APP Ser655 phosphorylation was observed in the brain of APP/PS1 mice and AD patients compared to controls. Moreover, blockade of APP Ser655 phosphorylation, or inhibition of ROCK1 activity with either shRNA knockdown or Y‐27632, ameliorated amyloid pathology and improved learning and memory in APP/PS1 mice. These findings suggest that activated ROCK1 targets APP Ser655 phosphorylation, which promotes amyloid processing and pathology. Inhibition of ROCK1 could be a potential therapeutic approach for AD.     

A simple FRET system using two‐color CdTe quantum dots assisted by cetyltrimethylammonium bromide and its application to Hg(II) detection

In this study, we developed a novel simple fluorescence resonance‐energy transfer (FRET) system between two‐color CdTe quantum dots (QDs) assisted by cetyltrimethylammonium bromide (CTAB). Mercaptopropionic (MPA)‐capped CdTe QDs serving as both donors and acceptors were successfully synthesized by changing the refluxing time in aqueous solution. CTAB micelles formed in water and minimized the distance between the donors and acceptors significantly by electrostatic interactions, improving FRET efficiency. Several factors that affected the fluorescence spectra of the FRET system were investigated. The prepared FRET system was feasible as an effective fluorescent probe to detect Hg(II) in aqueous solution. At pH 7.0, a linear relationship between the quenched fluorescence intensity of orange‐emitting acceptors (QDs_(A)) and Hg(II) concentration was acquired in the range 5–250 nmol/L with a detection limit of 1.95 nmol/L. The developed method showed excellent analytical performance for Hg(II) with high sensitivity and acceptable selectivity, reproducibility and stability. This finding indicated that the method has a promising potential application for environmental monitoring. This study demonstrated the great promise of QDs for expedient, low‐cost and high‐sensitivity detection of Hg(II).     

Glutamine Metabolism Regulates Proliferation and Lineage Allocation in Skeletal Stem Cells

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