OBJECTIVES: Long non-coding RNAs (lncRNAs) are critical for posttranscriptional and transcriptional regulation in eukaryotic cells. However, data on lncRNA expression in the lesion epicentres of spinal tissues after acute traumatic spinal cord injury (ATSCI) are scarce. We aimed to identify lncRNA expression profiles in such centres and predict latent regulatory networks. MATERIALS AND METHODS: High-throughput RNA-sequencing was used to profile the expression and regulatory patterns of lncRNAs, microRNAs and messenger RNAs (mRNAs) in an ATSCI C57BL/6 mouse model. Chromosome distributions, open reading frames (ORFs), transcript abundances, exon numbers and lengths were compared between lncRNAs and mRNAs. Gene ontology, KEGG pathways and binding networks were analysed. The findings were validated by qRT-PCRs and luciferase assays. RESULTS: Intronic lncRNAs were the most common differentially expressed lncRNA. Most lncRNAs had <6 exons, and lncRNAs had shorter lengths and lesser ORFs than mRNAs. MiR-21a-5p had the most significant differential expression and bound to the differentially expressed lncRNA ENSMUST00000195880. The microRNAs and lncRNAs with significant differential expression were screened, and a lncRNA/miRNA/mRNA interaction network was predicted, constructed and verified. CONCLUSIONS: The regulatory actions of this network may play a role in the pathophysiology of ATSCI. Our findings may lead to better understanding of potential ncRNA biomarkers and confer better therapeutic strategies for ATSCIs.
OBJECTIVES: Long non-coding RNAs (lncRNAs) are critical for posttranscriptional and transcriptional regulation in eukaryotic cells. However, data on lncRNA expression in the lesion epicentres of spinal tissues after acute traumatic spinal cord injury (ATSCI) are scarce. We aimed to identify lncRNA expression profiles in such centres and predict latent regulatory networks. MATERIALS AND METHODS: High-throughput RNA-sequencing was used to profile the expression and regulatory patterns of lncRNAs, microRNAs and messenger RNAs (mRNAs) in an ATSCI C57BL/6 mouse model. Chromosome distributions, open reading frames (ORFs), transcript abundances, exon numbers and lengths were compared between lncRNAs and mRNAs. Gene ontology, KEGG pathways and binding networks were analysed. The findings were validated by qRT-PCRs and luciferase assays. RESULTS: Intronic lncRNAs were the most common differentially expressed lncRNA. Most lncRNAs had <6 exons, and lncRNAs had shorter lengths and lesser ORFs than mRNAs. MiR-21a-5p had the most significant differential expression and bound to the differentially expressed lncRNA ENSMUST00000195880. The microRNAs and lncRNAs with significant differential expression were screened, and a lncRNA/miRNA/mRNA interaction network was predicted, constructed and verified. CONCLUSIONS: The regulatory actions of this network may play a role in the pathophysiology of ATSCI. Our findings may lead to better understanding of potential ncRNA biomarkers and confer better therapeutic strategies for ATSCIs.