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Quantitative proteomic data of chickpea leaves primed with nitric oxide donor for stress tolerance

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Title Quantitative proteomic data of chickpea leaves primed with nitric oxide donor for stress tolerance
 
Identifier https://doi.org/10.21421/D2/UY20HC
 
Creator Santisree Parankusam
Pooja B Mathur
Kiran K Sharma
 
Publisher ICRISAT Dataverse
 
Description Nitric oxide (NO) has emerged as a central regulator of various growth and developmental events in plants, such as seed germination, root growth, floral transition, senescence and stress defenses. However, the molecular mechanisms and targets of nitric oxide (NO) aren't fully known in plants. Our study reports the first large-scale quantitative proteomic analysis of NO donor responsive proteins in chickpea. To identify the molecular basis of NO treatment, the protein profiles in leaves of control and SNP treated 60 days old ICCV1882 line were compared using label-free quantitative proteomics based on nano LC-MS analysis. The separated peptides were used to identify protein matches from chickpea at the UniProt database and quantification using Protein Lynx Global Server from Waters. Proteome profiling revealed 172 down regulated and 76 up-regulated proteins, of which majority were involved in metabolic processes (118) by virtue of their catalytic (145) and binding (106) activity. Few crucial proteins such as S-adenosylmethionine synthase, dehydroascorbate reductase, pyruvate kinase fragment, 1-aminocyclopropane-1-carboxylic acid oxidase, 1-pyrroline-5-carboxylate synthetase were less abundant while bowman birk type protease inhibitor, non-specific lipid transfer protein, chalcone synthase, ribulose-1-5-bisphosphate carboxylase oxygenase large subunit, photosystem II D2 protein were highly abundant in SNP treated samples. This study highlights the protein networks for a better understanding of possible NO induced regulatory mechanisms in plants.
 
Subject Agricultural Sciences
Chickpea
Abiotic stress
Gel free proteomics
Nitric oxide
Mass spectroscopy
Sodium nitroprusside
 
Contributor Administrator
 
Type Quantitative proteomics