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OsCSD2 and OsCSD3 Enhance Seed Storability by Modulating Antioxidant Enzymes and Abscisic Acid in Rice.

Plants (Basel, Switzerland) | 2024

Seed deterioration during storage poses a significant challenge to rice production, leading to a drastic decline in both edible quality and viability, thereby impacting overall crop yield. This study aimed to address this issue by further investigating candidate genes associated with two previously identified QTLs for seed storability through genome association analysis. Among the screened genes, two superoxide dismutase (SOD) genes, OsCSD2 (Copper/zinc Superoxide Dismutase 2) and OsCSD3, were selected for further study. The generation of overexpression and CRISPR/Cas9 mutant transgenic lines revealed that OsCSD2 and OsCSD3 play a positive regulatory role in enhancing rice seed storability. Subsequent exploration of the physiological mechanisms demonstrated that overexpression lines exhibited lower relative electrical conductivity, indicative of reduced cell membrane damage, while knockout lines displayed the opposite trend. Furthermore, the overexpression lines of OsCSD2 and OsCSD3 showed significant increases not only in SOD but also in CAT and POD activities, highlighting an augmented antioxidant system in the transgenic seeds. Additionally, hormone profiling indicated that ABA contributed to the improved seed storability observed in these lines. In summary, these findings provide valuable insights into the regulatory mechanisms of OsCSDs in rice storability, with potential applications for mitigating grain loss and enhancing global food security.

Pubmed ID: 38276765 RIS Download

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Associated grants

  • Agency: National Key Research and Development Program of China,
    Id: 2022YFD1200400
  • Agency: National Natural Science Foundation of China,
    Id: 31971864

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This is a list of tools and resources that we have found mentioned in this publication.


Rice Genome Annotation (tool)

RRID:SCR_006663

Database and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes

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KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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iTOL (tool)

RRID:SCR_018174

Web tool for display, annotation and management of phylogenetic trees. Accessible with any modern web browser.

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