4.7 Article

A network-based algorithm for the identification of moonlighting noncoding RNAs and its application in sepsis

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 1, 页码 581-588

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbz154

关键词

moonlighting RNA; lncRNA; functional module; RNA-protein interaction; sepsis

资金

  1. Health and Family Planning Commission of Shenzhen Municipality [SZXJ2017027]

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MoonFinder v2.0 is an algorithm dedicated to predicting human mlncRNAs, providing a comprehensive framework and a moonlighting coefficient for assessing their cellular functions. Studies have shown that mlncRNAs exhibit specific expression characteristics in sepsis and tend to be mutually exclusive in terms of coexpression compared to other lncRNAs.
Moonlighting proteins provide more options for cells to execute multiple functions without increasing the genome and transcriptome complexity. Although there have long been calls for computational methods for the prediction of moonlighting proteins, no method has been designed for determining moonlighting long noncoding ribonucleicacidz (RNAs) (mlncRNAs). Previously, we developed an algorithm MoonFinder for the identification of mlncRNAs at the genome level based on the functional annotation and interactome data of lncRNAs and proteins. Here, we update MoonFinder to MoonFinder v2.0 by providing an extensive framework for the detection of protein modules and the establishment of RNA-module associations in human. A novel measure, moonlighting coefficient, was also proposed to assess the confidence of an ncRNA acting in a moonlighting manner. Moreover, we explored the expression characteristics of mlncRNAs in sepsis, in which we found that mlncRNAs tend to be upregulated and differentially expressed. Interestingly, the mlncRNAs are mutually exclusive in terms of coexpression when compared to the other lncRNAs. Overall, MoonFinder v2.0 is dedicated to the prediction of human mlncRNAs and thus bears great promise to serve as a valuable R package for worldwide research communities (https://cran.r-project.org/web/packages/MoonFinder/index.html). Also, our analyses provide the first attempt to characterize mlncRNA expression and coexpression properties in adult sepsis patients, which will facilitate the understanding of the interaction and expression patterns of mlncRNAs.

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