State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China.
Nucleic Acids Res. 2024 Jan 5;52(D1):D1629-D1638. doi: 10.1093/nar/gkad706.
Recent advancements in single-cell RNA sequencing (scRNA-seq) technology have enabled the comprehensive profiling of gene expression patterns at the single-cell level, offering unprecedented insights into cellular diversity and heterogeneity within plant tissues. In this study, we present a systematic approach to construct a plant single-cell database, scPlantDB, which is publicly available at https://biobigdata.nju.edu.cn/scplantdb. We integrated single-cell transcriptomic profiles from 67 high-quality datasets across 17 plant species, comprising approximately 2.5 million cells. The data underwent rigorous collection, manual curation, strict quality control and standardized processing from public databases. scPlantDB offers interactive visualization of gene expression at the single-cell level, facilitating the exploration of both single-dataset and multiple-dataset analyses. It enables systematic comparison and functional annotation of markers across diverse cell types and species while providing tools to identify and compare cell types based on these markers. In summary, scPlantDB serves as a comprehensive database for investigating cell types and markers within plant cell atlases. It is a valuable resource for the plant research community.
近年来，单细胞 RNA 测序（scRNA-seq）技术的进步使我们能够在单细胞水平上全面描绘基因表达模式，为深入了解植物组织内的细胞多样性和异质性提供了前所未有的视角。在这项研究中，我们提出了一种系统的方法来构建一个植物单细胞数据库，scPlantDB，该数据库可在 https://biobigdata.nju.edu.cn/scplantdb 上公开获取。我们整合了来自 17 个植物物种的 67 个高质量数据集的单细胞转录组谱，包含大约 250 万个细胞。这些数据经过严格的收集、手动注释、严格的质量控制和来自公共数据库的标准化处理。scPlantDB 提供了单细胞水平上基因表达的交互式可视化，便于进行单数据集和多数据集分析的探索。它支持对不同细胞类型和物种中的标记进行系统比较和功能注释，同时提供了基于这些标记识别和比较细胞类型的工具。总之，scPlantDB 是一个用于研究植物细胞图谱中细胞类型和标记的综合性数据库。它是植物研究界的宝贵资源。
