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Rice Stress-Resistant SNP Database.

Tareke Woldegiorgis, Samuel and Wang, Shaobo and He, Yiruo and Xu, Zhenhua and Chen, Lijuan and Tao, Huan and Zhang, Yu and Zou, Yang and Harrison, Andrew and Zhang, Lina and Ai, Yufang and Liu, Wei and He, Huaqin (2019) 'Rice Stress-Resistant SNP Database.' Rice, 12 (1). 97-. ISSN 1939-8425

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BACKGROUND:Rice (Oryza sativa L.) yield is limited inherently by environmental stresses, including biotic and abiotic stresses. Thus, it is of great importance to perform in-depth explorations on the genes that are closely associated with the stress-resistant traits in rice. The existing rice SNP databases have made considerable contributions to rice genomic variation information but none of them have a particular focus on integrating stress-resistant variation and related phenotype data into one web resource. RESULTS:Rice Stress-Resistant SNP database ( mainly focuses on SNPs specific to biotic and abiotic stress-resistant ability in rice, and presents them in a unified web resource platform. The Rice Stress-Resistant SNP (RSRS) database contains over 9.5 million stress-resistant SNPs and 797 stress-resistant candidate genes in rice, which were detected from more than 400 stress-resistant rice varieties. We incorporated the SNPs function, genome annotation and phenotype information into this database. Besides, the database has a user-friendly web interface for users to query, browse and visualize a specific SNP efficiently. RSRS database allows users to query the SNP information and their relevant annotations for individual variety or more varieties. The search results can be visualized graphically in a genome browser or displayed in formatted tables. Users can also align SNPs between two or more rice accessions. CONCLUSION:RSRS database shows great utility for scientists to further characterize the function of variants related to environmental stress-resistant ability in rice.

Item Type: Article
Uncontrolled Keywords: SNP; Biotic stress; Abiotic stress; Database
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 16 Jul 2021 13:14
Last Modified: 18 Aug 2022 13:26

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