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  • Title: Milletdb: a multi-omics database to accelerate the research of functional genomics and molecular breeding of millets.
    Author: Sun M, Yan H, Zhang A, Jin Y, Lin C, Luo L, Wu B, Fan Y, Tian S, Cao X, Wang Z, Luo J, Yang Y, Jia J, Zhou P, Tang Q, Jones CS, Varshney RK, Srivastava RK, He M, Xie Z, Wang X, Feng G, Nie G, Huang D, Zhang X, Zhu F, Huang L.
    Journal: Plant Biotechnol J; 2023 Nov; 21(11):2348-2357. PubMed ID: 37530223.
    Abstract:
    Millets are a class of nutrient-rich coarse cereals with high resistance to abiotic stress; thus, they guarantee food security for people living in areas with extreme climatic conditions and provide stress-related genetic resources for other crops. However, no platform is available to provide a comprehensive and systematic multi-omics analysis for millets, which seriously hinders the mining of stress-related genes and the molecular breeding of millets. Here, a free, web-accessible, user-friendly millets multi-omics database platform (Milletdb, http://milletdb.novogene.com) has been developed. The Milletdb contains six millets and their one related species genomes, graph-based pan-genomics of pearl millet, and stress-related multi-omics data, which enable Milletdb to be the most complete millets multi-omics database available. We stored GWAS (genome-wide association study) results of 20 yield-related trait data obtained under three environmental conditions [field (no stress), early drought and late drought] for 2 years in the database, allowing users to identify stress-related genes that support yield improvement. Milletdb can simplify the functional genomics analysis of millets by providing users with 20 different tools (e.g., 'Gene mapping', 'Co-expression', 'KEGG/GO Enrichment' analysis, etc.). On the Milletdb platform, a gene PMA1G03779.1 was identified through 'GWAS', which has the potential to modulate yield and respond to different environmental stresses. Using the tools provided by Milletdb, we found that the stress-related PLATZs TFs (transcription factors) family expands in 87.5% of millet accessions and contributes to vegetative growth and abiotic stress responses. Milletdb can effectively serve researchers in the mining of key genes, genome editing and molecular breeding of millets.
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