Expression Profiles of Long Noncoding RNAs and Messenger RNAs in a Rat Model of Spinal Cord Injury

Abstract

Spinal cord injury (SCI) is a serious disorder of the central nervous system with a high disability rate. Long noncoding RNAs (lncRNAs) are reported to mediate many biological processes. The aim of this study was to explore lncRNA and mRNA expression profiles and functional networks after SCI. Differentially expressed genes between SCI model rats and sham controls were identified by microarray assays and analyzed by functional enrichment. Key lncRNAs were identified using a support vector machine- (SVM-) recursive feature elimination (RFE) algorithm. A trans and cis regulation model was used to analyze the regulatory relationships between lncRNAs and their targets. An lncRNA-related ceRNA network was established. We identified 5465 differentially expressed lncRNAs (DE lncRNAs) and 8366 differentially expressed mRNAs (DE mRNAs) in the SCI group compared with the sham group ( fold change > 2.0 , p < 0.05 ). Four genes were confirmed by qRT-PCR which were consistent with the microarray data. GSEA analysis showed that most marked changes occurred in pathways related to immune inflammation and nerve cell function, including cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and GABAergic synapse. Enrichment analysis identified 30 signaling pathways, including those associated with immune inflammation response. A total of 40 key lncRNAs were identified using the SVM-RFE algorithm. A key lncRNA-mRNAs coexpression network was generated for 230 951 lncRNA-mRNA pairs with half showing positive correlations. Several key DE lncRNAs were predicted to have “cis”- or “trans”-regulated target genes. The transcription factors, Sp1, JUN, and SOX10, may regulate the interaction between XR_001837123.1 and ETS 1. In addition, five pairs of ceRNA regulatory sequences were constructed. Many mRNAs and lncRNAs were found to be dysregulated after SCI. Bioinformatic analysis showed that DE lncRNAs may play crucial roles in SCI. It is anticipated that these findings will provide new insights into the underlying mechanisms and potential therapeutic targets for SCI.

A spinal cord injury time and severity consensus transcriptomic reference suite in rat reveals translationally-relevant biomarker genes

“…We used the GSE218088 dataset ( 36 ) (ref) published after the study search and selection period as a validation set, given that it meets the inclusion criteria established in the meta-analysis. We aimed to evaluate whether the selected phase-and severity-specific biomarker genes could classify a new transcriptomic profile correctly.…”

Identification of marker genes for spinal cord injury

“…SCI can be categorized into non-traumatic and traumatic SCI based on its causes. Non-traumatic SCI primarily arises from acute and chronic conditions like tumors and intervertebral disc herniation (18,19), while traumatic SCI is predominantly triggered by traffic accidents, sports-related falls, or violent acts, leading to spinal fractures, dislocations, and subsequent cord compression or rupture (20,21). SCI profoundly impacts patients' quality of life, mental and physical well-being, and imposes significant economic burdens on families and society.…”

Analysis and verification of the circRNA regulatory network RNO_CIRCpedia_ 4214/RNO-miR-667-5p/Msr1 axis as a potential ceRNA promoting macrophage M2-like polarization in spinal cord injury

“…An SCI model was established using the Allen strike technique [ 14 ]. Rats were anesthetized by isoflurane inhalation and randomly assigned to the sham and SCI groups ( n = 3/group).…”