Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated genome-editing toolkit to enhance salt stress tolerance in rice and wheat.

The rice and wheat agricultural system is the primary source of food for billions across the world. However, the productivity and long-term sustainability of rice and wheat are threatened by a large number of abiotic stresses, especially salinity stress. Salinity has a significant impact on plant development and productivity and is one of the leading causes of crop yield losses in agricultural soils worldwide. Over the last few decades, several attempts have been undertaken to enhance salinity stress tolerance, most of which have relied on traditional or molecular breeding approaches. These approaches have so far been insufficient in addressing the issues of abiotic stress. However, due to the availability of genome sequences for cereal crops like rice and wheat and the development of genome editing techniques like clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein9 (Cas9), it is now possible to "edit" genes and influence key traits. Here, we review the application of the CRISPR/Cas9 system in both rice (Oryza sativa L.) and wheat (Triticum aestivum L.) to develop salinity tolerant cultivars. The CRISPR/Cas genome editing toolkit holds great promise of producing cereal crops tolerant to salt stress to increase agriculture resilience with a strong impact on the environment and public health.

Biotechnological strategies for the sustainable production of diosgenin from Dioscorea spp.

Diosgenin is a plant-derived secondary metabolite mainly present in the members of the plant family Dioscoreaceae. It is a pharmaceutically important compound because of its anti-cancerous, anti-diabetic, anticoagulant, anti-thrombosis, anti-inflammatory, anti-viral, anti-ageing and other properties. Biotechnology provides an opportunity to genetically manipulate cells, tissues, organs or the whole organisms by propagating them in vitro in order to harvest the bioactive compounds. Diosgenin production from botanical sources is being improved by in vitro techniques which include elicitation, genetic transformations and bioconversions. Various techniques have been developed to obtain compounds for drug detection including separation from plants and other natural sources, molecular modelling, synthetic chemistry and combinatorial chemistry. Development in molecular markers determines genetic relationship, genetic linkage map construction, genetic diversity and identification. For rapid clonal propagation and ex situ conservation, the in vitro tools involving plant cell, tissue and organ culture have been well documented for plant-derived diosgenin production. The present review encompasses the wide application of the biotechnological techniques for diosgenin production via elucidating its biosynthetic pathway, in vitro production and mass propagation and elicitation. In addition, molecular marker-mediated diversity assessment of diosgenin containing plant species is also discussed. The review also presents the recent literature to explore the limitations of the relevant studies and future direction of research on production of diosgenin from Dioscorea spp. KEY POINTS: • Critical and updated assessment on sustainable production of diosgenin from Dioscorea spp. • In vitro propagation of Dioscorea spp. and elicitation of diosgenin production. • Diversity assessment of Dioscorea spp. using molecular markers.

Biotechnological interventions of in vitro propagation and production of valuable secondary metabolites in Stevia rebaudiana.

Plant cell and tissue culture makes provision of a sustainable and nature-friendly strategy for the production of secondary metabolites, and modern progress in gene editing and genome engineering provides novel possibilities to improve both the qualitative and quantitative aspects of such phytochemicals. The ever-expanding quest for plant-based medicine to treat diabetes facilitates large-scale cultivation of Stevia rebaudiana to enhance the yield of its much-coveted low-calorie sweetener glycosides. The potential to process stevia as a "natural" product should enhance the acceptance of steviosides as a natural calorie-free sweetener especially suitable for use in diabetic and weight control drinks and foods. Besides sweetener agents, S. rebaudiana is a potent source of many antioxidant compounds and is used to cure immunodeficiencies, neurologic disorders, inflammation, diabetes mellitus, Parkinson's disease, and Alzheimer's disease. This comprehensive review presents the research outcomes of the many biotechnological interventions implicated to upscale the yield of steviol glycosides and its derivatives in in vitro cell, callus, tissue, and organ cultures with notes on the use of bioreactor and genetic engineering in relation to the production of these valuable compounds in S. rebaudiana. KEY POINTS: • Critical and updated assessment on sustainable production of steviol glycosides from Stevia rebaudiana. • In vitro propagation of S. rebaudiana and elicitation of steviol glycosides production. • Genetic fidelity and diversity assessment of S. rebaudiana using molecular markers.

Optimization of diosgenin extraction from Dioscorea deltoidea tubers using response surface methodology and artificial neural network modelling.

INTRODUCTION: Dioscorea deltoidea var. deltoidea (Dioscoreaceae) is a valuable endangered plant of great medicinal and economic importance due to the presence of the bioactive compound diosgenin. In the present study, response surface methodology (RSM) and artificial neural network (ANN) modelling have been implemented to evaluate the diosgenin content from D. deltoidea. In addition, different extraction parameters have been also optimized and developed. MATERIALS AND METHODS: Firstly, Plackett-Burman design (PBD) was applied for screening the significant variables among the selected extraction parameters i.e. solvent composition, solid: solvent ratio, particle size, time, temperature, pH and extraction cycles on diosgenin yield. Among seven tested parameters only four parameters (particle size, solid: solvent ratio, time and temperature) were found to exert significant effect on the diosgenin extraction. Moreover, Box-Behnken design (BBD) was employed to optimize the significant extraction parameters for maximum diosgenin yield. RESULTS: The most suitable condition for diosgenin extraction was found to be solid: solvent ratio (1:45), particle size (1.25 mm), time (45 min) and temperature (45°C). The maximum experimental yield of diosgenin (1.204% dry weight) was observed close to the predicted value (1.202% dry weight) on the basis of the chosen optimal extraction factors. The developed mathematical model fitted well with experimental data for diosgenin extraction. CONCLUSIONS: Experimental validation revealed that a well trained ANN model has superior performance compared to a RSM model.