Summary Hongkong kumquat (Fortunella hindsii) is a wild citrus species characterized by dwarf plant height and early flowering. Here, we identified the monoembryonic F. hindsii (designated as ‘Mini‐Citrus’) for the first time and constructed its selfing lines. This germplasm constitutes an ideal model for the genetic and functional genomics studies of citrus, which have been severely hindered by the long juvenility and inherent apomixes of citrus. F. hindsii showed a very short juvenile period (~8 months) and stable monoembryonic phenotype under cultivation. We report the first de novo assembled 373.6 Mb genome sequences (Contig‐N50 2.2 Mb and Scaffold‐N50 5.2 Mb) for F. hindsii. In total, 32 257 protein‐coding genes were annotated, 96.9% of which had homologues in other eight Citrinae species. The phylogenomic analysis revealed a close relationship of F. hindsii with cultivated citrus varieties, especially with mandarin. Furthermore, the CRISPR/Cas9 system was demonstrated to be an efficient strategy to generate target mutagenesis on F. hindsii. The modifications of target genes in the CRISPR‐modified F. hindsii were predominantly 1‐bp insertions or small deletions. This genetic transformation system based on F. hindsii could shorten the whole process from explant to T1 mutant to about 15 months. Overall, due to its short juvenility, monoembryony, close genetic background to cultivated citrus and applicability of CRISPR, F. hindsii shows unprecedented potentials to be used as a model species for citrus research.
Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.
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