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Genome-Wide Identification and Functional Prediction of Long Non-coding RNAs in the Genesis of Populus euphratica Oliv. Heteromorphic Leaves

한국식물학회지 2020년 63권 2호 p.131 ~ 140
 ( Guo Zhongzhong ) - Tarim University College of Life Science

 ( Qin Shaowei ) - Tarim University College of Life Science
 ( Li Cailin ) - Tarim University College of Life Science
 ( Bao Lianghong ) - Tarim University College of Life Science
 ( Yan Weiwei ) - Tarim University College of Life Science
 ( Wu Haizhu ) - Tarim University College of Life Science
 ( Zhao Lifeng ) - Tarim University College of Life Science

Abstract


Recent extensive studies of long non-coding RNAs (lncRNAs) have shown that lncRNAs play an important role in plant development and growth. Populus euphratica Oliv. is the only natural tree species in the Taklimakan desert with leaves that change shapes at different growth stages. LncRNAs can affect biological functions in P. euphratica heterophyllous morphogenesis, but there are few reports on this subject in the literature. In this study, chain-specific transcriptome sequencing and small RNA sequencing were performed using linear, lanceolate, broad-ovate and ovoid leaves of P. euphratica. A total of 442 novel P. euphratica lncRNAs were predicted and the expression profiles of 4460 lncRNAs were analyzed. 371 lncRNAs were significantly different among the varied leaf shapes studied. Using co-expression analysis and according to the principle of competing endogenous RNA (ceRNA), we found that 28 lncRNAs could regulate the expression of 133 mRNAs by antagonizing 17 miRNAs. These mRNAs are involved in 23 biological functions, such as cell growth, developmental processes, metabolic processes and biological regulation, thereby affecting the formation of P. euphratica heteromorphic leaves. These results provide the foundation to study the formation of P. euphratica heteromorphic leaves, revealing the function of lncRNAs in the development of leaves in plants.

키워드

Populus euphratica oliv.; Heteromorphic leaf; LncRNA; Function prediction
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