College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, China.
School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia, USA.
Plant Biotechnol J. 2023 Nov;21(11):2348-2357. doi: 10.1111/pbi.14136. Epub 2023 Aug 2.
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.
小米是一类营养丰富、抗逆性强的粗杂粮,可保障极端气候地区人群的粮食安全,并为其他作物提供抗逆相关的遗传资源。然而,目前还没有一个平台可以对小米进行全面、系统的多组学分析,这严重阻碍了小米中抗逆相关基因的挖掘和分子育种。在此,我们开发了一个免费的、可在线访问的、用户友好的小米多组学数据库平台(Milletdb,http://milletdb.novogene.com)。该数据库包含 6 种小米及其 1 种近缘种的基因组、基于图的珍珠 millet 泛基因组和抗逆相关的多组学数据,使其成为目前最完整的小米多组学数据库。我们还在数据库中存储了 2 年、3 种环境条件[田间(无胁迫)、早旱和晚旱]下 20 个与产量相关性状的 GWAS(全基因组关联研究)结果,供用户识别支持产量提高的抗逆相关基因。Milletdb 还通过提供 20 种不同的工具(如“基因定位”、“共表达”、“KEGG/GO 富集分析”等),简化了小米的功能基因组分析。在 Milletdb 平台上,通过“GWAS”鉴定了一个潜在的调节产量和响应不同环境胁迫的基因 PMA1G03779.1。利用 Milletdb 提供的工具,我们发现与胁迫相关的 PLATZ 转录因子(TFs)家族在 87.5%的小米品种中扩张,并有助于营养生长和非生物胁迫响应。Milletdb 可以有效地为小米的关键基因挖掘、基因组编辑和分子育种研究人员提供帮助。