4.5 Article

Integrated analysis of differentially expressed genes and construction of a competing endogenous RNA network in human Huntington neural progenitor cells

Journal

BMC MEDICAL GENOMICS
Volume 14, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12920-021-00894-2

Keywords

RNA; lncRNA; Huntington disease; ceRNA; Bioinformatics

Funding

  1. National Natural Science Foundation of China [81371271]
  2. Liaoning BaiQianWan Talents Program
  3. 345 Talent Project of Shengjing Hospital of China Medical University

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Our study systematically analyzed gene expression profiles of neural progenitor cells (NPCs) from HD patients and controls, identifying DE mRNAs and DE lncRNAs and creating a ceRNA network. Functional analysis revealed that DE lncRNAs are mainly associated with transcriptional regulation, and KEGG enrichment analysis showed their involvement in various signaling pathways. The PPI network indicated that transcription factors in the ceRNA network interacted with each other, suggesting lncRNAs may play a role in transcriptional regulation in HD.
Background Huntington's disease (HD) is one of the most common polyglutamine disorders, leading to progressive dyskinesia, cognitive impairment, and neuropsychological problems. Besides the dysregulation of many protein-coding genes in HD, previous studies have revealed a variety of non-coding RNAs that are also dysregulated in HD, including several long non-coding RNAs (lncRNAs). However, an integrated analysis of differentially expressed (DE) genes based on a competing endogenous RNA (ceRNA) network is still currently lacking. Methods In this study, we have systematically analyzed the gene expression profile data of neural progenitor cells (NPCs) derived from patients with HD and controls (healthy controls and the isogenic controls of HD patient cell lines corrected using a CRISPR-Cas9 approach at the HTT locus) to screen out DE mRNAs and DE lncRNAs and create a ceRNA network. To learn more about the possible functions of lncRNAs in the ceRNA regulatory network in HD, we conducted a functional analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) and established a protein-protein interaction (PPI) network for mRNAs interacting with these lncRNAs. Results We identified 490 DE mRNAs and 94 DE lncRNAs, respectively. Of these, 189 mRNAs and 20 lncRNAs were applied to create a ceRNA network. The results showed that the function of DE lncRNAs mainly correlated with transcriptional regulation as demonstrated by GO analysis. Also, KEGG enrichment analysis showed these lncRNAs were involved in tumor necrosis factor, calcium, Wnt, and NF-kappa B signaling pathways. Interestingly, the PPI network revealed that a variety of transcription factors in the ceRNA network interacted with each other, suggesting such lncRNAs may regulate transcription in HD by controlling the expression of such protein-coding genes, especially transcription factors. Conclusions Our research provides new clues for uncovering the mechanisms of lncRNAs in HD and can be used as the focus for further investigation.

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