SGII: Systematic Identification of Essential lncRNAs in Mouse and Human Genome With lncRNA-Protein-Protein Heterogeneous Interaction Network

• Published in: Frontiers in genetics 2022-03, Vol.13, p.864564-864564
• Main Authors: Xin, Xiao-Hong, Zhang, Ying-Ying, Gao, Chu-Qiao, Min, Hui, Wang, Likun, Du, Pu-Feng
• Format: Article
• Language: English
• Subjects: essential lncRNA; Genetics; lncRNA-protein interaction network; network centrality; protein-protein interaction network; systematic method
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2022.864564

Long noncoding RNAs (lncRNAs) play important roles in a variety of biological processes. Knocking out or knocking down some lncRNA genes can lead to death or infertility. These lncRNAs are called essential lncRNAs. Identifying the essential lncRNA is of importance for complex disease diagnosis and treatments. However, experimental methods for identifying essential lncRNAs are always costly and time consuming. Therefore, computational methods can be considered as an alternative approach. We propose a method to identify essential lncRNAs by combining network centrality measures and lncRNA sequence information. By constructing a lncRNA-protein-protein interaction network, we measure the essentiality of lncRNAs from their role in the network and their sequence together. We name our method as the systematic gene importance index (SGII). As far as we can tell, this is the first attempt to identify essential lncRNAs by combining sequence and network information together. The results of our method indicated that essential lncRNAs have similar roles in the LPPI network as the essential coding genes in the PPI network. Another encouraging observation is that the network information can significantly boost the predictive performance of sequence-based method. All source code and dataset of SGII have been deposited in a GitHub repository (https://github.com/ninglolo/SGII).