The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen) in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species, Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signaling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signaling in legumes. In this review, several studies on proteomics and metabolomics in model and crop legumes have been discussed. Additionally, applications of advanced proteomics and metabolomics approaches have also been included in this review for future applications in legume research. The integration of these "omics" approaches will greatly support the identification of accurate biomarkers in legume smart breeding programs.
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http://dx.doi.org/10.3389/fpls.2015.01116 | DOI Listing |
BMC Plant Biol
January 2025
Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, China.
Background: Space-induced plant mutagenesis, driven by cosmic radiation, offers a promising approach for the selective breeding of new plant varieties. By leveraging the unique environment of outer space, we successfully induced mutagenesis in 'Deqin' alfalfa and obtained a fast-growing mutant. However, the molecular mechanisms underlying its rapid growth remain poorly unexplored.
View Article and Find Full Text PDFFood Res Int
January 2025
Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055, Portici (Naples), Italy; Institute of Food Science & Technology, National Research Council, Via Roma 52, 83100, Avellino, Italy. Electronic address:
The winemaking process generates huge amounts of waste every year. Fermented grape pomace, the major by-waste product, holds significant value due to its chemical composition and technological properties. In this study a multi-omics approach was employed for the detailed molecular characterization of fermented grape pomace from Montepulciano grape, a widely used Italian red grape variety.
View Article and Find Full Text PDFCarbohydr Polym
March 2025
Glycomics and Glycan Bioengineering Research Center (GGBRC), College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China. Electronic address:
The major hurdle of xenotransplantation is the immune response triggered by human natural antibodies interacting with carbohydrate antigens on the transplanted animal organ. Specifically, terminal glycoprotein motifs such as galactose-α1,3-galactose (α-Gal) and N-glycolylneuraminic acid (Neu5Gc) are significant obstacles. Little is known about the abundance and compositions of asparagine-linked complex carbohydrates (N-glycans) carrying these motifs in mammalian organs.
View Article and Find Full Text PDFJ Proteomics
January 2025
State Key Laboratory of Tree Genetics and Breeding, Chinese Academy of Forestry, Beijing 100091, China; Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China. Electronic address:
The ability of axillary meristems to form axillary buds and subsequently develop into branches is influenced by phytohormones, environmental conditions, and genetic factors. The main trunk of Quercus fabri is prone to branching, which not only impacts the appearance and density of the wood and significantly reduces the yield rate. This study conducted transcriptomic, proteomic, and metabolomic analyses on three stages of axillary bud development in Q.
View Article and Find Full Text PDFCell Syst
December 2024
Center for Bioinformatics and Computational Medicine, Ann Arbor, MI 48109, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Program in Chemical Biology, University of Michigan, Ann Arbor, MI, USA; Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Electronic address:
While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning.
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