Xu Chaoqun, Song Ling-Yu, Li Jing, Zhang Lu-Dan, Guo Ze-Jun, Ma Dong-Na, Dai Ming-Jin, Li Qing-Hua, Liu Jin-Yu, Zheng Hai-Lei
Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, China.
Houji Laboratory in Shanxi Province, Shanxi Agricultural University, Shanxi, China.
Plant Cell Environ. 2025 May;48(5):2950-2962. doi: 10.1111/pce.15318. Epub 2024 Dec 11.
Mangroves are dominant flora of intertidal zones along tropical and subtropical coastline around the world that offer important ecological and economic value. Recently, the genomes of mangroves have been decoded, and massive omics data were generated and deposited in the public databases. Reanalysis of multi-omics data can provide new biological insights excluded in the original studies. However, the requirements for computational resource and lack of bioinformatics skill for experimental researchers limit the effective use of the original data. To fill this gap, we uniformly processed 942 transcriptome data, 386 whole-genome sequencing data, and provided 13 reference genomes and 40 reference transcriptomes for 53 mangroves. Finally, we built an interactive web-based database platform MangroveDB (https://github.com/Jasonxu0109/MangroveDB), which was designed to provide comprehensive gene expression datasets to facilitate their exploration and equipped with several online analysis tools, including principal components analysis, differential gene expression analysis, tissue-specific gene expression analysis, GO and KEGG enrichment analysis. MangroveDB not only provides query functions about genes annotation, but also supports some useful visualization functions for analysis results, such as volcano plot, heatmap, dotplot, PCA plot, bubble plot, population structure, and so on. In conclusion, MangroveDB is a valuable resource for the mangroves research community to efficiently use the massive public omics datasets.
红树林是全球热带和亚热带海岸潮间带的优势植物群落,具有重要的生态和经济价值。近年来,红树林的基因组已被解码,产生了大量组学数据并存入公共数据库。对多组学数据进行重新分析可以提供原始研究中未涉及的新生物学见解。然而,实验研究人员对计算资源的需求以及生物信息学技能的缺乏限制了原始数据的有效利用。为了填补这一空白,我们统一处理了942个转录组数据、386个全基因组测序数据,并为53种红树林提供了13个参考基因组和40个参考转录组。最后,我们构建了一个基于网络的交互式数据库平台MangroveDB(https://github.com/Jasonxu0109/MangroveDB),旨在提供全面的基因表达数据集以方便探索,并配备了几个在线分析工具,包括主成分分析、差异基因表达分析、组织特异性基因表达分析、GO和KEGG富集分析。MangroveDB不仅提供有关基因注释的查询功能,还支持对分析结果进行一些有用的可视化功能,如火山图、热图、点图、主成分分析图、气泡图、群体结构等。总之,MangroveDB是红树林研究社区有效利用大量公共组学数据集的宝贵资源。