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Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets

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Title Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
 
Creator Min Sun
Haidong Yan
Aling Zhang
Yarong Jin
Chuang Lin
Lin Luo
Bingchao Wu
Yuhang Fan
Shilin Tian
Xiaofang Cao
Zan Wang
Jinchan Luo
Yuchen Yang
Jiyuan Jia
Puding Zhou
Qianzi Tang
Jones, Christopher S.
Varshney, R.K.
Srivastava, R.K.
Min He
Zheni Xie
Xiaoshan Wang
Guangyan Feng
Gang Nie
Dejun Huang
Xinquan Zhang
Fangjie Zhu
Linkai Huang
 
Subject functional genomics
abiotic stress
millets
databases
plant breeding
biotechnology
 
Description 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.
 
Date 2023-08-02
2023-08-09T10:59:12Z
2023-08-09T10:59:12Z
 
Type Journal Article
 
Identifier Min Sun, Haidong Yan, Aling Zhang, Yarong Jin, Chuang Lin, Lin Luo, Bingchao Wu, Yuhang Fan,Shilin Tian, Xiaofang Cao, Zan Wang, Jinchan Luo, Yuchen Yang, Jiyuan Jia, Puding Zhou, Qianzi Tang, Jones, C.S., Varshney, R.K., Srivastava, R.K., Min He, Zheni Xie, Xiaoshan Wang, Guangyan Feng, Gang Nie, Dejun Huang, Xinquan Zhang, Fangjie Zhu and Linkai Huang. 2023. Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets. Plant Biotechnology Journal
1467-7652
https://hdl.handle.net/10568/131513
https://doi.org/10.1111/pbi.14136
 
Language en
 
Rights CC-BY-NC-ND-4.0
Open Access
 
Source Plant Biotechnology Journal