文献类型：期刊文献

英文题名：Genome-Wide Identification and Characterization of Long Non-Coding RNAs from Mulberry (Morus notabilis) RNA-seq Data

作者：Song, Xiaobo[1,2] Sun, Liang[3] Luo, Haitao[3] Ma, Qingguo[2] Zhao, Yi[3,4] Pei, Dong[2]

第一作者：Song, Xiaobo;宋晓波

通信作者：Pei, D[1]|[a0005c81e28dc32effca6]裴东;

机构：[1]Beijing Forestry Univ, Coll Biol Sci & Technol, Beijing 100083, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Tree Genet & Breeding, Beijing 100091, Peoples R China;[3]Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China;[4]Chinese Acad Sci, Inst Comp Technol, LuoYang Branch, Precis Med Ctr,Res Inst Informat Ind LuoYang, Luoyang 471000, Peoples R China

年份：2016

卷号：7

期号：3

外文期刊名：GENES

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000373531300001)】；

基金：This study was supported by grants from the Special Research for Public Welfare in Forestry Industry (No. 201304712) and the National Natural Science Foundation of China (Grant No. 31171933).

语种：英文

外文关键词：lncRNAs; Morus notabilis; RNA-seq

摘要：Numerous sources of evidence suggest that most of the eukaryotic genome is transcribed into protein-coding mRNAs and also into a large number of non-coding RNAs (ncRNAs). Long ncRNAs (lncRNAs), a group consisting of ncRNAs longer than 200 nucleotides, have been found to play critical roles in transcriptional, post-transcriptional, and epigenetic gene regulation across all kingdoms of life. However, lncRNAs and their regulatory roles remain poorly characterized in plants, especially in woody plants. In this paper, we used a computational approach to identify novel lncRNAs from a published RNA-seq data set and analyzed their sequences and expression patterns. In total, 1133 novel lncRNAs were identified in mulberry, and 106 of these lncRNAs displayed a predominant tissue-specific expression in the five major tissues investigated. Additionally, functional predictions revealed that tissue-specific lncRNAs adjacent to protein-coding genes might play important regulatory roles in the development of floral organ and root in mulberry. The pipeline used in this study would be useful for the identification of lncRNAs obtained from other deep sequencing data. Furthermore, the predicted lncRNAs would be beneficial towards an understanding of the variations in gene expression in plants.