C plants have the inherent capacity to concentrate atmospheric CO in the vicinity of RuBisCo, thereby increasing carboxylation, and inhibiting photorespiration. Carbonic anhydrase (CA), the first enzyme of C photosynthesis, converts atmospheric CO to HCO, which is utilized by PEPC to produce C acids. Bioengineering of C traits into C crops is an attractive strategy to increase photosynthesis and water use efficiency. In the present study, we isolated the PEPC gene from the C plant Setaria italica and transferred it to C rice. Overexpression of SiPEPC resulted in a 2-6-fold increment in PEPC enzyme activity in transgenic lines with respect to non-transformed control. Photosynthetic efficiency was enhanced in transformed plants, which was associated with increased ФPSII, ETR, lower NPQ, and higher chlorophyll accumulation. Water use efficiency was increased by 16-22% in PEPC transgenic rice lines. Increased PEPC activity enhanced quantum yield and carboxylation efficiency of PEPC transgenic lines. Transgenic plants exhibited higher light saturation photosynthesis rate and lower CO compensation point, as compared to non-transformed control. An increase in net photosynthesis increased the yield by (23-28.9%) and biomass by (24.1-29%) in transgenic PEPC lines. Altogether, our findings indicate that overexpression of Cspecific SiPEPC enzyme is able to enhance photosynthesis and related parameters in transgenic rice.
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http://dx.doi.org/10.1016/j.plaphy.2022.11.011 | DOI Listing |
J Exp Bot
January 2025
Noble Research Institute, Ardmore, OK 73401, USA.
Translating biological knowledge from Arabidopsis to crop species is important to advance agriculture and secure food production in the face of dwindling fertilizer resources and biotic and abiotic stresses. However, it is often not trivial to identify functional homologs (orthologs) of Arabidopsis genes in crops. Combining sequence and expression data can improve the correct prediction of orthologs.
View Article and Find Full Text PDFPlant Cell
January 2025
Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia.
Many C4 plants are used as food and fodder crops and often display improved resource use efficiency compared to C3 plants. However, the response of C4 plants to future extreme conditions such as heatwaves is less understood. Here, Setaria viridis, an emerging C4 model grass, was grown under long-term high temperature stress for two weeks (42°C, compared to 28°C).
View Article and Find Full Text PDFBMC Plant Biol
January 2025
Department of Crop, Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA.
Foxtail millet (Setaria italica L.) is nutritionally superior to other cereals of the family Poaceae, with the potential to perform better in marginal environments. In the present context of climate change, ecologically sound and low-input foxtail millet varieties can be chosen for agricultural sustainability.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
College of Agriculture, Shanxi Agricultural University, Taigu, 030801, China.
Backgrounds: Adapter proteins (APs) complex is a class of heterotetrameric complexes comprising of 4-subunits with important regulatory functions in eukaryotic cell membrane vesicle trafficking. Foxtail millet (Setaria italica L.) is a significant C model plant for monocotyledon studies, and vesicle trafficking may plays a crucial role in various life activities related to growth and development.
View Article and Find Full Text PDFInt J Biol Macromol
December 2024
Food Engineering and Bioprocess Technology Program, Department of Food, Agriculture, and Bioresources, School of Environment, Resources, and Development, Asian Institute of Technology, Khlong Luang, Pathumthani 12120, Thailand. Electronic address:
This research investigates the impact of microwave power, processing time, and solid-to-solvent ratio on protein recovery from foxtail millet (Setaria italica), using an artificial neural network (ANN) and genetic algorithm (GA). The extracted protein and subsequent hydrolysates were also evaluated for their techno-functional, structural, and digestibility properties. The ANN model, trained with the Levenberg-Marquardt algorithm and optimized by a GA, identified optimal extraction conditions (960 W, 66.
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