Identification of differentially expressed genes in mouse paraspinal muscle in response to microgravity

Identifying the miRNA-gene networks contributes to exploring paravertebral muscle degeneration's underlying pathogenesis and therapy strategy

Low back pain (LBP) is a worldwide problem with public health. Paravertebral muscle degeneration (PMD) is believed to be associated with LBP. Increasing evidence has demonstrated that microRNA (miRNA)-mRNA signaling networks have been implicated in the pathophysiology of diseases. Research suggests that cell death, oxidative stress, inflammatory and immune response, and extracellular matrix (ECM) metabolism are the pathogenesis of PMD; however, the miRNA-mRNA mediated the pathological process of PMD remains elusive. RNA sequencing (RNA-seq) and single cell RNA-seq (scRNA-seq) are invaluable tools for uncovering the functional biology underlying these miRNA and gene expression changes. Using scRNA-seq, we show that multiple immunocytes are presented during PMD, revealing that they may have been implicated with PMD. Additionally, using RNA-seq, we identified 76 differentially expressed genes (DEGs) and 106 differentially expressed miRNAs (DEMs), among which IL-24 and CCDC63 were the top upregulated and downregulated genes in PMD. Comprehensive bioinformatics analyses, including Venn diagrams, differential expression, functional enrichment, and protein-protein interaction analysis, were then conducted to identify six ferroptosis-related DEGs, two oxidative stress-related DEGs, eleven immunity-related DEGs, five ECM-related DEGs, among which AKR1C2/AKR1C3/SIRT1/ALB/IL-24 belong to inflammatory genes. Furthermore, 67 DEMs were predicted to be upstream miRNAs of 25 key DEGs by merging RNA-seq, TargetScan, and mirDIP databases. Finally, a miRNA-gene network was constructed using Cytoscape software and an alluvial plot. ROC curve analysis unveiled multiple key DEGs with the high clinical diagnostic value, providing novel approaches for diagnosing and treating PMD diseases.

Transcriptome analysis of mRNA and miRNA in the development of LeiZhou goat muscles

The progression of muscle development is a pivotal aspect of animal ontogenesis, where miRNA and mRNA exert substantial influence as prominent players. It is important to understand the molecular mechanisms involved in skeletal muscle development to enhance the quality and yield of meat produced by Leizhou goats. We employed RNA sequencing (RNA-SEQ) technology to generate miRNA-mRNA profiles in Leizhou goats, capturing their developmental progression at 0, 3, and 6 months of age. A total of 977 mRNAs and 174 miRNAs were found to be differentially expressed based on our analysis. Metabolic pathways, calcium signaling pathways, and amino acid synthesis and metabolism were found to be significantly enriched among the differentially expressed mRNA in the enrichment analysis. Meanwhile, we found that among these differentially expressed mRNA, some may be related to muscle development, such as MYL10, RYR3, and CSRP3. Additionally,, we identified five muscle-specific miRNAs (miR-127-3p, miR-133a-3p, miR-193b-3p, miR-365-3p, and miR-381) that consistently exhibited high expression levels across all three stages. These miRNAs work with their target genes (FHL3, SESN1, PACSIN3, LMCD1) to regulate muscle development. Taken together, our findings suggest that several miRNAs and mRNAs are involved in regulating muscle development and cell growth in goats. By uncovering the molecular mechanisms involved in muscle growth and development, these findings contribute valuable knowledge that can inform breeding strategies aimed at enhancing meat yield and quality in Leizhou goats.

Identification of key genes and regulatory mechanisms in adult degenerative scoliosis

BACKGROUND

Adult degenerative scoliosis (ADS) is a spinal disorder, but its pathogenesis remain unclear. Therefore, in this study, we utilized data from the GEO database and explored the key genes and regulatory mechanisms involved in ADS.

METHODS

We performed bioinformatics analysis on the GSE209825 dataset of GEO database. Weighted gene co-expression network analysis (WGCNA) was used to identify ADS-related gene modules, and we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. We constructed a protein-protein interaction (PPI) network using the STRING database. We validated the specificity of hub genes in ADS using the GSE34095 dataset and plotted ROC curves for the identification of different degenerative spinal diseases based on the hub genes expression RESULTS: We identified 113 differentially expressed lncRNAs. WGCNA identified the MEblack module had the strongest correlation to ADS. GO and KEGG analyses of target genes in lncRNAs revealed their involvement in immune responses, inflammation, cellular processes, and metabolic pathways. Through PPI and ROC analysis, 10 hub genes linked to ADS diseases with certain specificity were found: ELANE, LTF, DEFA1B, SLC2A4, DEFA1, FAXDC2, LCN2, CTSB, FDFT1, and AURKA.

CONCLUSIONS

We identified 10 potential hub genes associated with ADS and constructed a transcription factors (TFs)-lncRNAs-hub genes regulatory network. These findings provide a new direction and research basis for the targeted treatment and mechanism research of ADS.