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

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  • Xueyan Liu, Critical Care Medici at Shenzhen People's Hospital.
  • ,
  • Yong Xu, Shenzhen People's Hospital
  • ,
  • Ran Wang, Computer Science at The Chinese University of Hong Kong.
  • ,
  • Sheng Liu, BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China; Lars Bolund Institute of Regenerative Medicine, BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China.
  • ,
  • Jun Wang, BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China; Lars Bolund Institute of Regenerative Medicine, BGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China.
  • ,
  • YongLun Luo
  • Kwong-Sak Leung, Computer Science at the Chinese University of Hong Kong, Hong Kong, China.
  • ,
  • Lixin Cheng, Bioinformatics at Shenzhen People's Hospital, China.

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.

OriginalsprogEngelsk
TidsskriftBriefings in bioinformatics
Vol/bind22
Nummer1
Sider (fra-til)581-588
Antal sider8
ISSN1467-5463
DOI
StatusUdgivet - jan. 2021

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