Non-Coding RNA Analyses of Seasonal Cambium Activity in Populus tomentosa .
Huimin XuBo ChenYuanyuan ZhaoYayu GuoGuijun LiuRuili LiViktoria V Zeisler-DiehlYanmei ChenXinqiang HeLukas SchreiberJinxing LinPublished in: Cells (2022)
Non-coding RNA, known as long non-coding RNA (lncRNA), circular RNA (circRNA) and microRNA (miRNA), are taking part in the multiple developmental processes in plants. However, the roles of which played during the cambium activity periodicity of woody plants remain poorly understood. Here, lncRNA/circRNA-miRNA-mRNA regulatory networks of the cambium activity periodicity in Populus tomentosa was constructed, combined with morphologic observation and transcriptome profiling. Light microscopy and Periodic Acid Schiff (PAS) staining revealed that cell walls were much thicker and number of cell layers was increased during the active-dormant stage, accompanied by abundant change of polysaccharides. The novel lncRNAs and circRNAs were investigated, and we found that 2037 lncRNAs and 299 circRNAs were differentially expression during the vascular cambium period, respectively. Moreover, 1046 genes were identified as a target gene of 2037 novel lncRNAs, and 89 of which were the miRNA precursors or targets. By aligning miRNA precursors to the 7655 lncRNAs, 21 lncRNAs were identified as precursors tof 19 known miRNAs. Furthermore, the target mRNA of lncRNA/circRNA-miRNA network mainly participated in phytohormone, cell wall alteration and chlorophyll metabolism were analyzed by GO enrichment and KEGG pathway. Especially, circRNA33 and circRNA190 taking part in the phytohormone signal pathway were down-regulated during the active-dormant transition. Xyloglucan endotransglucosylase/hydrolase protein 24-like and UDP-glycosyltransferase 85A1 involved in the cell wall modification were the targets of lncRNA MSTRG.11198.1 and MSTRG.1050.1. Notably, circRNA103 and MSTRG.10851.1 regulate the cambium periodicity may interact with the miR482. These results give a new light into activity-dormancy regulation, associated with transcriptional dynamics and non-coding RNA networks of potential targets identification.
Keyphrases
- long non coding rna
- poor prognosis
- cell wall
- genome wide identification
- single cell
- genome wide analysis
- transcription factor
- network analysis
- long noncoding rna
- genome wide
- rna seq
- gene expression
- mass spectrometry
- dna methylation
- stem cells
- mesenchymal stem cells
- copy number
- bone marrow
- risk assessment
- bioinformatics analysis
- water soluble