Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis

作者：Zhaohui He, Yangming Lan, Xinkai Zhou, Bianjiong Yu, Tao Zhu, Fa Yang, Liang-Yu Fu, Haoyu Chao, Jiahao Wang, Rong-Xu Feng, Shimin Zuo, Wenzhi Lan, Chunli Chen, Ming Chen, Xue Zhao, Keming Hu, Dijun Chen · 发表于：Plant Communications · 年份：2023 · DOI：10.1016/j.xplc.2023.100717 · 被引用次数：29 · 研究领域：Cancer-related molecular mechanisms research、Genomics and Phylogenetic Studies、Plant and Fungal Interactions Research

The plant genome produces an extremely large collection of long noncoding RNAs (lncRNAs) that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes. Here, we mapped the transcriptional heterogeneity of lncRNAs and their associated gene regulatory networks at single-cell resolution. We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing (scRNA-seq) datasets from juvenile Arabidopsis seedlings. We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers. We further demonstrated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity. In addition, we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs, and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs. The analysis results are available at the single-cell-based plant lncRNA atlas database (scPLAD; https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstrates the power of integrative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.