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Spinal cord injury (SCI) is a severe event that occurs in the central nervous system (CNS). Long noncoding RNAs (lncRNAs) have already been proven to play key roles in different diseases of the CNS. Nevertheless, the roles of messenger RNAs (mRNAs) and lncRNAs one week after SCI remain to be elucidated. We established a rat model of SCI and examined the differential levels of mRNAs and lncRNAs, and then, the differentially expressed mRNAs (DE mRNAs) and lncRNAs (DE lncRNAs) were investigated. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DE lncRNAs and mRNAs were subsequently carried out to explore crucial biological processes and signaling pathways. Moreover, we constructed protein–protein interaction (PPI) networks, the STRING database, and identified the 10 high degree core nodes. We also established a co-expression network by calculating the correlation between lncRNA expression profile and mRNA expression profile. The identified DE lncRNAs and DE mRNAs may potentially be critical targets for the diagnosis and treatment of SCI in the future. Abbreviations: SCI: spinal cord injury; CNS: central nervous system; YLDs: years of life lived with disability; lncRNAs: long noncoding RNAs; mRNAs: messenger RNAs; DE: differentially expressed; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GSEA: gene set enrichment analysis; RIN: Renewable Identification Number; PCA: principal component analysis; PPI: protein–protein interaction; MF, molecular function; BP: biological process; CC: cellular component; MCODE: molecular complex detection

Cerebral ischaemiareperfusion injury is an important pathological process in nervous system diseases during which neurons undergo oxygenglucose deprivation and reoxygenation (OGD/R) injury. No study has used epitranscriptomics to explore the characteristics and mechanism of injury. N6methyladenosine (m6A) is the most abundant epitranscriptomic RNA modification. However, little is known about m6A modifications in neurons, especially during OGD/R. m6A RNA immunoprecipitation sequencing (MeRIPseq) and RNA-sequencing data for normal and OGD/R-treated neurons were analysed by bioinformatics. MeRIP quantitative real-time polymerase chain reaction was used to determine the m6A modification levels on specific RNAs. We report the m6A modification profiles of the mRNA and circRNA transcriptomes of normal and OGD/R-treated neurons. Expression analysis revealed that the m6A levels did not affect m6A mRNA or m6A circRNA expression. We found crosstalk between m6A mRNAs and m6A circRNAs and identified three patterns of m6A circRNA production in neurons; thus, distinct OGD/R treatments induced the same genes to generate different m6A circRNAs. Additionally, m6A circRNA biogenesis during distinct OGD/R processes was found to be time specific. These results expand our understanding of m6A modifications in normal and OGD/R-treated neurons, providing a reference to explore epigenetic mechanisms and potential treatments for OGD/R-related diseases.

Abstract N1-Methyladenosine (m1A) is an abundant modification of transcripts, plays important roles in regulating mRNA structure and translation efficiency, and is dynamically regulated under stress. However, the characteristics and functions of mRNA m1A modification in primary neurons and oxygen glucose deprivation/reoxygenation (OGD/R) induced remain unclear. We first constructed a mouse cortical neuron OGD/R model and then used methylated RNA immunoprecipitation (MeRIP) and sequencing technology to demonstrate that m1A modification is abundant in neuron mRNAs and dynamically regulated during OGD/R induction. Our study suggests that Trmt10c, Alkbh3, and Ythdf3 may be m1A-regulating enzymes in neurons during OGD/R induction. The level and pattern of m1A modification change significantly during OGD/R induction, and differential methylation is closely associated with the nervous system. Our findings show that m1A peaks in cortical neurons aggregate at both the 5’ and 3’ untranslated regions. m1A modification can regulate gene expression, and peaks in different regions have different effects on gene expression. By analysing m1A-seq and RNA-seq data, we show a positive correlation between differentially methylated m1A peaks and gene expression. The correlation was verified by using qRT-PCR and MeRIP-RT-PCR. Moreover, we selected human tissue samples from Parkinson’s disease (PD) and Alzheimer’s disease (AD) patients from the Gene Expression Comprehensive (GEO) database to analyse the selected differentially expressed genes (DEGs) and differential methylation modification regulatory enzymes, respectively, and found similar differential expression results. We highlight the potential relationship between m1A modification and neuronal apoptosis following OGD/R induction. Furthermore, by mapping mouse cortical neurons and OGD/R-induced modification characteristics, we reveal the important role of m1A modification in OGD/R and gene expression regulation, providing new ideas for research on neurological damage.

BackgroundAging is an influential risk factor for progression of both degenerative and oncological diseases of the bone. Osteosarcoma, considered the most common primary mesenchymal tumor of the bone, is a worldwide disease with poor 5-year survival. This study investigated the role of aging-/senescence-induced genes (ASIGs) in contributing to osteosarcoma diagnosis, prognosis, and therapeutic agent prediction.MethodsTherapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) were used to collect relevant gene expression and clinical data of osteosarcoma and paracancerous tissues. Patients were clustered by consensus using prognosis-related ASIGs. ssGSEA, ESTIMATE, and TIMER were used to determine the tumor immune microenvironment (TIME) of subgroups. Functional analysis of differentially expressed genes between subgroups, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVAs), was performed to clarify functional status. Prognostic risk models were constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. SCISSOR was used to identify relevant cells in osteosarcoma single-cell data for different risk groups. The effect of immunotherapy was predicted based on TIDE scores and chemotherapy drug sensitivity using CTRP and PRISM.ResultsThree molecular subgroups were identified based on prognostic differentially expressed ASIGs. Immunological infiltration levels of the three groups differed significantly. Based on GO and KEGG analyses, differentially expressed genes between the three subgroups mainly relate to immune and aging regulation pathways; GSVA showed substantial variations in multiple Hallmark pathways among the subgroups. The ASIG risk score built based on differentially expressed genes can predict patient survival and immune status. We also developed a nomogram graph to accurately predict prognosis in combination with clinical characteristics. The correlation between the immune activation profile of patients and the risk score is discussed. Through single-cell analysis of the tumor microenvironment, we identified distinct risk-group-associated cells with significant differences in immune signaling pathways. Immunotherapeutic efficacy and chemotherapeutic agent screening were evaluated based on risk score.ConclusionAging-related prognostic genes can distinguish osteosarcoma molecular subgroups. Our novel aging-associated gene signature risk score can be used to predict the osteosarcoma immune landscape and prognosis. Moreover, the risk score correlates with the TIME and provides a reference for immunotherapy and chemotherapy in terms of osteosarcoma.

Epigenetic modifications play an important role in central nervous system disorders. As a widespread posttranscriptional RNA modification, the role of the m5C modification in cerebral ischemia-reperfusion injury (IRI) remains poorly defined. Here, we successfully constructed a neuronal oxygen-glucose deprivation/reoxygenation (OGD/R) model and obtained an overview of the transcriptome-wide m5C profiles using RNA-BS-seq. We discovered that the distribution of neuronal m5C modifications was highly conserved, significantly enriched in CG-rich regions and concentrated in the mRNA translation initiation regions. After OGD/R, modification level of m5C increased, whereas the number of methylated mRNA genes decreased. The amount of overlap of m5C sites with the binding sites of most RNA-binding proteins increased significantly, except for that of the RBM3-binding protein. Moreover, hypermethylated genes in neurons were significantly enriched in pathological processes, and the hub hypermethylated genes RPL8 and RPS9 identified by the protein-protein interaction network were significantly related to cerebral injury. Furthermore, the upregulated transcripts with hypermethylated modification were enriched in the processes involved in response to stress and regulation of apoptosis, and these processes were not identified in hypomethylated transcripts. In final, we verified that OGD/R induced neuronal apoptosis in vitro using TUNEL and western blot assays. Our study identified novel m5C mRNAs associated with ischemia-reperfusion in neurons, providing valuable perspectives for future studies on the role of the RNA methylation in cerebral IRI.