Search

The Myo-Inositol-1-phosphate synthase (MIPS) gene family is involved in the myo-inositol synthesis and plays a significant role in signal transduction, membrane biogenesis, oligosaccharides synthesis, auxin storage and transport, programmed cell death and abiotic stress tolerance in plants. This study comprehensively identified the MIPS genes in Rosaceae plant species, and 51 MIPS genes were identified from 26 Rosaceae species. The phylogenetic analysis divided the MIPSs into two clades (clade I; subfamily Amygdaloideae specific, and clade II; subfamily Rosoideae specific). MIPS genes of all 26 Rosaceae species consist of similar gene structure, motif and domain composition, which shows their conserved nature. The cis-regulatory elements (CREs) analysis revealed that most Rosaceae MIPS genes play a role in growth, development, and stress responses. Furthermore, the qRT-PCR analysis also revealed the involvement of RcMIPS gene in plant development and response to abiotic stresses, including drought and heat. The results of the present study contribute to the understanding of the biological function of Rosaceae MIPS genes, and that could be used in further functional validations. [ABSTRACT FROM AUTHOR]

Sugars are the major source of energy in living organisms and play important roles in osmotic regulation, cell signaling and energy storage. SWEETs (Sugars Will Eventually be Exported Transporters) are the most recent family of sugar transporters that function as uniporters, facilitating the diffusion of sugar molecules across cell membranes. In plants, SWEETs play roles in multiple physiological processes including phloem loading, senescence, pollen nutrition, grain filling, nectar secretion, abiotic (drought, heat, cold, and salinity) and biotic stress regulation. In this review, we summarized the role of SWEET transporters in plant development and abiotic stress. The gene expression dynamics of various SWEET transporters under various abiotic stresses in different plant species are also discussed. Finally, we discuss the utilization of genome editing tools (TALENs and CRISPR/Cas9) to engineer SWEET genes that can facilitate trait improvement. Overall, recent advancements on SWEETs are highlighted, which could be used for crop trait improvement and abiotic stress tolerance. [ABSTRACT FROM AUTHOR]

Key message: TFs involved in drought tolerance in plants may be utilized in future for developing drought tolerant cultivars of wheat and some other crops. Abstract: Plants have developed a fairly complex stress response system to deal with drought and other abiotic stresses. These response systems often make use of transcription factors (TFs); a gene encoding a specific TF together with -its target genes constitute a regulon, and take part in signal transduction to activate/silence genes involved in response to drought. Since, five specific families of TFs (out of >80 known families of TFs) have gained widespread attention on account of their significant role in drought tolerance in plants, TFs and regulons belonging to these five multi-gene families (AP2/EREBP, bZIP, MYB/MYC, NAC and WRKY) have been described and their role in improving drought tolerance discussed in this brief review. These TFs often undergo reversible phosphorylation to perform their function, and are also involved in complex networks. Therefore, some details about reversible phosphorylation of TFs by different protein kinases/phosphatases and the co-regulatory networks, which involve either only TFs or TFs with miRNAs, have also been discussed. Literature on transgenics involving genes encoding TFs and that on QTLs and markers associated with TF genes involved in drought tolerance has also been reviewed. Throughout the review, there is a major emphasis on wheat as an important crop, although examples from the model cereal rice (sometimes maize also), and the model plant Arabidopsis have also been used. This knowledge base may eventually allow the use of TF genes for development of drought tolerant cultivars, particularly in wheat. [ABSTRACT FROM AUTHOR]

Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic stresses. Therefore, it is crucial to identify TFs associated with abiotic stress response for breeding of abiotic stress tolerant crop cultivars. Based on a machine learning framework, a computational model was envisaged to predict TFs associated with abiotic stress response in plants. To numerically encode TF sequences, four distinct sequence derived features were generated. The prediction was performed using ten shallow learning and four deep learning algorithms. For prediction using more pertinent and informative features, feature selection techniques were also employed. Using the features chosen by the light-gradient boosting machine-variable importance measure (LGBM-VIM), the LGBM achieved the highest cross-validation performance metrics (accuracy: 86.81%, auROC: 92.98%, and auPRC: 94.03%). Further evaluation of the proposed model (LGBM prediction method + LGBM-VIM selected features) was also done using an independent test dataset, where the accuracy, auROC and auPRC were observed 81.98%, 90.65% and 91.30%, respectively. To facilitate the adoption of the proposed strategy by users, the approach was implemented as a prediction server called ASPTF, accessible at https://iasri-sg.icar.gov.in/asptf/. The developed approach and the corresponding web application are anticipated to supplement experimental methods in the identification of transcription factors (TFs) responsive to abiotic stress in plants. • Developed a computational method, "ASPTF" for identifying abiotic stress responsive transcription factors (TFs) in plants. • The ASPTF has been trained using data from 23 diverse plant species. • The overall results, confirmed the reliability and generalised predictive ability of the ASPTF. • The online prediction server ASPTF is freely accessible at https://iasri-sg.icar.gov.in/asptf/. [ABSTRACT FROM AUTHOR]