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. 2019 Apr 18;11(8):2352-2368.
doi: 10.18632/aging.101919.

Identification of noncoding RNA expression profiles and regulatory interaction networks following traumatic spinal cord injury by sequence analysis

Affiliations

Identification of noncoding RNA expression profiles and regulatory interaction networks following traumatic spinal cord injury by sequence analysis

Wenzhao Wang et al. Aging (Albany NY). .

Abstract

Aim: To systematically profile and characterize the noncoding RNA (ncRNA) expression pattern in the lesion epicenter of spinal tissues after traumatic spinal cord injury (TSCI) and predicted the structure and potential functions of the regulatory networks associated with these differentially expressed ncRNAs and mRNAs.

Results: A total of 498 circRNAs, 458 lncRNAs, 155 miRNAs and 1203 mRNAs were identified in TSCI mice models to be differentially expressed. The regulatory networks associated with these differentially expressed ncRNAs and mRNAs were constructed.

Materials and methods: We used RNA-Seq, Gene ontology (GO), KEGG pathway analysis and co-expression network analyses to profle the expression and regulation patterns of noncoding RNAs and mRNAs of mice models after TSCI. The findings were validated by quantitative real-time PCR (qRT-PCR) and Luciferase assay.

Conclusion: noncoding RNAs might play important roles via the competing endogenous RNA regulation pattern after TSCI, further findings arising from this study will not only expand the understanding of potential ncRNA biomarkers but also help guide therapeutic strategies for TSCI.

Keywords: axonal regeneration; competing endogenous RNA; noncoding RNA; traumatic spinal cord injury.

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Conflict of interest statement

CONFLICTS OF INTEREST: Grant support was provided by the National Natural Science Fund of China (Nos. 81401014, 81771346), the Chinese Postdoctoral Science Foundation (No. 2014M561935), the Chinese Postdoctoral Science Foundation (No. 2015T80725), and Technology Research and Development Program of Jinan City (No. 201704133).

Figures

Figure 1
Figure 1
Establishment of SCI animal model. (A) BMS scores indicate the motor functional index 3 days after SCI. ***P<0.001. (BD) H&E staining of spinal cord samples from the sham and SCI groups at days 1 and 3 postsurgery.
Figure 2
Figure 2
Expression profiles of DE ncRNAs and mRNAs in the lesion epicenter after SCI. (A) Heat map of DE lncRNAs in the SCI group compared with the sham group. (B) Heat map of DE circRNAs. (C) Volcano plot indicating the differential expression of lncRNAs. (D) Volcano plot of circRNAs. (E) Heat map of DE miRNAs. (G) Volcano plot of miRNAs. (F) Heat map of DE mRNAs. (H) Volcano plot of mRNAs. Up-regulated and down-regulated genes are colored in red and blue, respectively.
Figure 3
Figure 3
Overview of relative differential expression of ncRNAs. (A) Histogram showing the number of dysregulated ncRNAs and mRNAs. (BD) Venn diagram showing the overlap between the target mRNAs of dysregulated ncRNAs and dysregulated mRNAs.
Figure 4
Figure 4
Validation of differential ncRNA and mRNA expression. (A, C) Sequencing results of the ncRNAs and mRNAs. (B, D) Expression of corresponding ncRNAs and mRNAs validated by qRT-PCR.
Figure 5
Figure 5
Enriched GO terms and KEGG pathways of host genes of DE ncRNAs in SCI mice. (A) Top 20 significantly enriched GO terms of DE ncRNAs are shown in the scatterplot. (B) Top 20 significantly enriched GO terms of DE mRNAs. (C) The top 20 significantly enriched KEGG pathways of DE ncRNAs are shown in the scatterplot. (D) The top 20 significantly enriched KEGG pathways of DE mRNAs are listed.
Figure 6
Figure 6
LncRNA–miRNA–mRNA regulatory interaction network analysis.
Figure 7
Figure 7
CircRNA–miRNA–mRNA regulatory interaction network analysis.
Figure 8
Figure 8
Confirmation of the relationships. (A) Relative luciferase expression of wild-type and mutant lncRNAGM33755 UTR-bearing luciferase vectors cotransfected with miR-135b expression vectors. (B) Relative luciferase expression of wild-type and mutant circRNA6370 UTR-bearing luciferase vectors cotransfected with miR-135b expression vectors. n=6, ***P<0.001.

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