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

单细胞转录组分析剖析拟南芥中的 lncRNA 相关基因网络

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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

Abstract

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.

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