Project description:Alkaline salts (e.g., NaHCO3 and Na2CO3) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na2SO4) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa (Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance.
Project description:Alfalfa (Medicago sativa L.) is a forage legume with significant agricultural value worldwide. MicroRNAs (miRNAs) are key components of post-transcriptional gene regulation and essentially control almost all aspect of plant growth and development. Although miRNAs have been reported from alfalfa but their expression profiles in different tissues and novel miRNAs as well as their targets have not been confirmed in this plant species. Therefore, we sequenced small RNAs in whole plantlets, shoots and roots of three different alfalfa genotypes (Altet-4, NECS-141 and NF08ALF06) to identify tissue-specific profiles. After comprehensive analysis using bioinformatics methods, we have identified 100 miRNA families, of which 21 belongs to the highly conserved families whereas the remaining 79 families are conserved between M. truncatula and M. sativa. The profiles of the six highly expressed conserved miRNA families (miR156, 159, 166, 319, 396, 398,) were relatively similar between the plantlets, roots and shoots of three genotypes. Contrastingly, the differenecs were robust between shoots and roots for miR160 and miR408 levels, which were low in roots compared to shoots. The study also has identified 17 novel miRNAs that also differed in their abundanecs between tissues of the alfalfa genotypes. Additionally, we have generated and analyzed the degradome libraries from three alfalfa genotypes that has confirmed 69 genes as targets for 31 miRNA families in alfalfa. The identification of conserved and novel miRNAs as well as their targets in different tissues of three genotypes not only enhanced our understanding of miRNA-mediated gene regulation in alfalfa but could also be useful for practical applications in alfalfa as well as related legume species.
Project description:We studied the application of transcriptome technology in alfalfa selenium treatment. After spraying sodium selenite on the leaves, the process of selenium absorption and assimilation of alfalfa is unknown. The time point of transcriptome determination was determined by measuring the change of selenium content. Our results showed that 12 h was the key point of the change of selenium content in alfalfa, that is, the selenium content increased continuously before 12 h, decreased gradually after 12 h, and remained stable after 48 h. Transcriptome sequencing showed that phosphorus transporter and endocytosis related genes may be involved in selenium absorption at 12 h compared with 0 H. 12-48 h, some thiometabolic pathways may be involved in selenium metabolism and ubiquitination pathway, which may be the detoxification pathway of selenoprotein.
Project description:In this study, proteomics was used to sequence the salt stress treatment group and the control group of Medicago sativa and Medicago truncatula. The aim was to discover the kegg pathway of the two alfalfa varieties under salt stress, which was of great significance to the exploration of the salt tolerance mechanism of alfalfa.
Project description:Two alfalfa varieties contrasting in heat tolerance, MS30 and MS37, were used for this experiment, and their seeds were provided by Sichuan Academy of Grassland Sciences. After two months of growth, both alfalfa varieties grow into adult-plants. Select 10-15 healthy plants with consistent growth to remain in each nutritional bowl. All materials are transferred to artificial climate boxes for high temperature stress treatment. The light cycle is still the day/night cycle:16/8h. According to the results of a prior experiment and based on the relevant report, the treatment temperature was set to 20℃, 25℃, 30℃, 35℃, 40℃ and 4℃, which is a gradient upward trend. Among them, alfalfa growing at 20°C were used as the control (non-HT stress). All alfalfa varieties were treated at each temperature gradient for 7 days and the leaves was collected for the determination of physiological indicators. Moreover, the physiological conditions of the plants and the humidity of the climate box were observed at any time. water the plants properly once a day, and the alfalfa special fertilizer was applied once in each cycle of temperature stress treatment to ensure the water and nutrition demand of the plant. Based on the results of the above experiment, some physiological responses demonstrated that most alfalfa varieties showed the most significant variation at 20℃, 35℃ and 43℃. Therefore, leaf samples collected from plants after exposure to the rising temperature 7 days were harvested for further TMT quantitative proteomic analysis.