Yang Zhiquan, Wang Shengbo, Wei Lulu, Huang Yiming, Liu Dongxu, Jia Yupeng, Luo Chengfang, Lin Yuchen, Liang Congyuan, Hu Yue, Dai Cheng, Guo Liang, Zhou Yongming, Yang Qing-Yong
National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510405, China.
National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Mol Plant. 2023 Apr 3;16(4):775-789. doi: 10.1016/j.molp.2023.03.007. Epub 2023 Mar 14.
In the post-genome-wide association study era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we report a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics, and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.
在后全基因组关联研究时代,多组学技术在候选基因挖掘和功能基因组学研究中展现出了巨大的力量和潜力。然而,由于缺乏有效的数据整合和多组学分析平台,此类技术在油菜(一种全球重要的油料作物)中仍未得到广泛应用。在此,我们报道了一个油菜多组学数据库(BnIR;http://yanglab.hzau.edu.cn/BnIR),该数据库提供了包括基因组学、转录组学、变异组学、表观基因组学、表型组学和代谢组学在内的六种组学数据集,以及通过多种统计方法得到的众多“变异-基因表达-表型”关联。此外,还集成了一系列多组学搜索和分析工具,以方便浏览和应用这些数据集。BnIR是目前为止最全面的油菜多组学数据库,两项案例研究证明了它挖掘与特定性状相关的候选基因并分析其潜在调控机制的能力。