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

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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Main Authors: 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
Format: Journal Article biblioteca
Language:English
Published: Wiley 2023-08-02
Subjects:functional genomics, abiotic stress, millets, databases, plant breeding, biotechnology,
Online Access:https://hdl.handle.net/10568/131513
https://doi.org/10.1111/pbi.14136
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spelling dig-cgspace-10568-1315132023-10-18T07:00:12Z Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets 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 functional genomics abiotic stress millets databases plant breeding biotechnology 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. 2023-08-02 2023-08-09T10:59:12Z 2023-08-09T10:59:12Z Journal Article 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 en CC-BY-NC-ND-4.0 Open Access Wiley Plant Biotechnology Journal
institution CGIAR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cgspace
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CGIAR
language English
topic functional genomics
abiotic stress
millets
databases
plant breeding
biotechnology
functional genomics
abiotic stress
millets
databases
plant breeding
biotechnology
spellingShingle functional genomics
abiotic stress
millets
databases
plant breeding
biotechnology
functional genomics
abiotic stress
millets
databases
plant breeding
biotechnology
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
Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
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.
format Journal Article
topic_facet functional genomics
abiotic stress
millets
databases
plant breeding
biotechnology
author 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
author_facet 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
author_sort Min Sun
title Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
title_short Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
title_full Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
title_fullStr Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
title_full_unstemmed Milletdb: A multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
title_sort milletdb: a multi-omics database to accelerate the research of functional genomics and molecular breeding of millets
publisher Wiley
publishDate 2023-08-02
url https://hdl.handle.net/10568/131513
https://doi.org/10.1111/pbi.14136
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