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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51187

Title: Functional Enrichment Analysis based on Long Noncoding RNA Associations
Authors: Kuo-Sheng Hung
Chung-Chi Hsiao
Tun-Wen Pai
Chin-Hwa Hu
Wen-Shyong Tzou
Wen-Der Wang
Yet-Ren Chen
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: lncRNA
Differential expression
Gene ontology (GO)
KEGG
Neuron development
Date: 2018-03
Issue Date: 2018-11-15T03:52:40Z
Publisher: BMC Systems Biology
Abstract: Abstract: Background
Differential gene expression analysis using RNA-seq data is a popular approach for discovering specific regulation mechanisms under certain environmental settings. Both gene ontology (GO) and KEGG pathway enrichment analysis are major processes for investigating gene groups that participate in common biological responses or possess related functions. However, traditional approaches based on differentially expressed genes only detect a few significant GO terms and pathways, which are frequently insufficient to explain all-inclusive gene regulation mechanisms.

Methods
Transcriptomes of survivin (birc5) gene knock-down experimental and wild-type control zebrafish embryos were sequenced and assembled, and a differential expression (DE) gene list was obtained for traditional functional enrichment analysis. In addition to including DE genes with significant fold-change levels, we considered additional associated genes near or overlapped with differentially expressed long noncoding RNAs (DE lncRNAs), which may directly or indirectly activate or inhibit target genes and play important roles in regulation networks. Both the original DE gene list and the additional DE lncRNA-associated genes were combined to perform a comprehensive overrepresentation analysis.

Results
In this study, a total of 638 DE genes and 616 DE lncRNA-associated genes (lncGenes) were leveraged simultaneously in searching for significant GO terms and KEGG pathways. Compared to the traditional approach of only using a differential expression gene list, the proposed method of employing DE lncRNA-associated genes identified several additional important GO terms and KEGG pathways. In GO enrichment analysis, 60% more GO terms were obtained, and several neuron development functional terms were retrieved as complete annotations. We also observed that additional important pathways such as the FoxO and MAPK signaling pathways were retrieved, which were shown in previous reports to play important roles in apoptosis and neuron development functions regulated by the survivin gene.

Conclusions
We demonstrated that incorporating genes near or overlapped with DE lncRNAs into the DE gene list outperformed the traditional enrichment analysis method for effective biological functional interpretations. These hidden interactions between lncRNAs and target genes could facilitate more comprehensive analyses.
Relation: 12(4) pp.45
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51187
Appears in Collections:[資訊工程學系] 期刊論文

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