GreenCells: A comprehensive resource for single-cell analysis of plant lncRNAs

Long non-coding RNAs (lncRNAs) play crucial roles in plant growth, development, and stress responses. With the advancement of single-cell RNA sequencing (scRNA-seq) technology, it is now possible to investigate lncRNA expression and function at single-cell resolution. Although several plant single-cell transcriptome databases have been established, they predominantly focus on protein-coding genes while largely overlooking lncRNAs. To bridge this gap, we developed GreenCells (http://greencells.liu-lab.com/), a comprehensive database specifically designed to explore plant lncRNAs at the single-cell level. By integrating scRNA-seq data from eight plant species, GreenCells has identified 2177 lncRNA marker genes and 68,869 protein-coding marker genes across diverse cell types. The database also features cell type-specific co-expression networks that reveal the regulatory potential of lncRNAs, many of which function as hub genes. For example, co-expression network analysis suggests that lncCOBRA5 may be involved in transmembrane processes. In addition, by comparing bulk and single-cell transcriptome profiles, we identified a set of lncRNAs uniquely expressed in specific cell types that are undetectable in root bulk RNA-seq data. We also observed a strong correlation between tissue-specific and cell type-specific expression patterns of lncRNAs. Overall, GreenCells provides detailed annotations, high-quality visualizations, advanced search functions, and practical analytical tools. It offers a valuable platform for investigating the regulation and expression of plant lncRNAs at single-cell resolution, thereby contributing a new resource to plant functional genomics research.

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Publication Details

Journal
Journal of Biological Chemistry
Published
2025-09-04
DOI
https://doi.org/10.1016/j.jbc.2025.110678
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
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article

GreenCells: A comprehensive resource for single-cell analysis of plant lncRNAs

Jiazhi Liu, Yan Li, Jie Wang, Wenjing Yang et al.
Journal of Biological Chemistry
Cancer-related molecular mechanisms research
article

GreenCells: A comprehensive resource for single-cell analysis of plant lncRNAs

Jiazhi Liu, Yan Li, Jie Wang, Wenjing Yang, Changning Liu, Changling Wu
article en

Abstract

Long non-coding RNAs (lncRNAs) play crucial roles in plant growth, development, and stress responses. With the advancement of single-cell RNA sequencing (scRNA-seq) technology, it is now possible to investigate lncRNA expression and function at single-cell resolution. Although several plant single-cell transcriptome databases have been established, they predominantly focus on protein-coding genes while largely overlooking lncRNAs. To bridge this gap, we developed GreenCells (http://greencells.liu-lab.com/), a comprehensive database specifically designed to explore plant lncRNAs at the single-cell level. By integrating scRNA-seq data from eight plant species, GreenCells has identified 2177 lncRNA marker genes and 68,869 protein-coding marker genes across diverse cell types. The database also features cell type-specific co-expression networks that reveal the regulatory potential of lncRNAs, many of which function as hub genes. For example, co-expression network analysis suggests that lncCOBRA5 may be involved in transmembrane processes. In addition, by comparing bulk and single-cell transcriptome profiles, we identified a set of lncRNAs uniquely expressed in specific cell types that are undetectable in root bulk RNA-seq data. We also observed a strong correlation between tissue-specific and cell type-specific expression patterns of lncRNAs. Overall, GreenCells provides detailed annotations, high-quality visualizations, advanced search functions, and practical analytical tools. It offers a valuable platform for investigating the regulation and expression of plant lncRNAs at single-cell resolution, thereby contributing a new resource to plant functional genomics research.

Journal of Biological ChemistryVol. 301(10)
Kunming Institute of Botany (CN), Chinese Academy of Sciences (CN), Xishuangbanna Tropical Botanical Garden (CN), Max Planck Institute for Plant Breeding Research (DE)
Openalex Percentile: Top 71%
Cancer-related molecular mechanisms research
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