Identification of Key eRNAs for Spinal Cord Injury by Integrated Multinomial Bioinformatics Analysis

利用整合多项式生物信息学分析鉴定脊髓损伤的关键eRNA

阅读:1

Abstract

Background: Spinal cord injury (SCI) is a severe neurological deficit affecting both young and older people worldwide. The potential role of key enhancer RNAs (eRNAs) in SCI remains elusive, which is a prominent challenge in the trauma repair process. This study aims to investigate the roles of key eRNAs, transcription factors (TFs), signaling pathways, and small-molecule inhibitors in SCI using multi-omics bioinformatics analysis. Methods: Microarray data of peripheral blood mononuclear cell (PBMC) samples from 27 healthy volunteers and 25 chronic-phase SCI patients were retrieved from the Gene Expression Omnibus database. Differentially expressed transcription factors (DETFs), differentially expressed enhancer RNAs (DEeRNAs), and differentially expressed target genes (DETGs) were identified using the Linear Models for Microarray Data (limma) package. Fraction of immune cells was estimated using CIBERSORT algorithm. Gene Set Variation Analysis (GSVA) was applied to identify the downstream signaling pathways. The eRNA regulatory network was constructed based on the correlation results. Connectivity Map (CMap) database was used to find potential drugs for SCI patients. The cellular communication analysis was performed to explore the molecular regulation mechanism of SCI based on single-cell RNA sequencing (scRNA-seq) data. Chromatin immunoprecipitation sequencing (ChIP-seq) and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data were used to validate the key regulatory mechanisms. scRNA-seq dataset was used to validate the cell subtype localization of the key eRNAs. Results: In total, 21 DETFs, 24 DEeRNAs, and 829 DETGs were identified. A regulatory network of 13 DETFs, six DEeRNAs, seven DETGs, two hallmark pathways, two immune cells, and six immune pathways was constructed. The link of Splicing factor proline and glutamine rich (SFPQ) (TF) and vesicular overexpressed in cancer prosurvival protein 1 (VOPP1) (eRNA) (R = 0.990, p < 0.001, positive), VOPP1 (eRNA) and epidermal growth factor receptor (EGFR) (target gene) (R = 0.974, p < 0.001, positive), VOPP1, and T helper (Th) cells (R = -0.987, p < 0.001, negative), and VOPP1 and hallmark coagulation (R = 0.937, p < 0.001, positive) was selected. Trichostatin A was considered the best compound target to SCI-related eRNAs (specificity = 0.471, p < 0.001). Conclusion: VOPP1, upregulated by SFPQ, strengthened the transient expression of EGFR. Th cells and coagulation were the potential downstream pathways of VOPP1. This regulatory network and potential inhibitors provide novel diagnostic biomarkers and therapeutic targets for SCI.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。