组学
物候学
生物
基因组学
计算生物学
代谢组学
生物信息学
生物技术
基因组
基因
遗传学
作者
Zhiquan Yang,Shengbo Wang,Lulu Wei,Yiming Huang,Dongxu Liu,Yupeng Jia,Chengfang Luo,Yu-Chen Lin,Congyuan Liang,Yue Hu,Cheng Dai,Liang Guo,Yongming Zhou,Qingyong Yang
标识
DOI:10.1016/j.molp.2023.03.007
摘要
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.
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