Differential Expression Profiles and Functional Prediction of Circular RNAs and Long Non-coding RNAs in the Hippocampus of Nrf2-Knockout Mice

Abstract

Background Nrf2 (nuclear factor, erythroid 2 like 2) is believed to play a major role in neurodegenerative diseases. The present study attempts to investigate the hippocampal circRNA and lncRNA expression profiles associated with Nrf2-mediated neuroprotection. Methods The hippocampal mRNA, circRNA and lncRNA expression profiles of Nrf2 (−/−) mice were determined by a microarray analysis. Bioinformatics analyses, including identification of differentially expressed mRNAs (DEmRNAs), circRNAs (DEcircRNAs) and lncRNAs (DElncRNAs), DEcircRNA-miRNA-DEmRNA interaction network construction, DElncRNA-DEmRNA co-expression network construction, and biological function annotation, were conducted. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the dysregulated expression of circRNAs and lncRNAs derived from the microarray data of the hippocampus of Nrf2 (−/−) mice. Results Compared to wild-type Nrf2 (+/+) mice, 412 DEmRNAs (109 up- and 303 down-regulated mRNAs), 1279 DEcircRNAs (632 up- and 647 down-regulated circRNAs), and 303 DElncRNAs (50 up- and 253 down-regulated lncRNAs) were identified in the hippocampus of Nrf2 (−/−) mice. Additionally, in the qRT-PCR validation results, the expression patterns of selected DEcircRNAs and DElncRNAs were generally consistent with results in the microarray data. The DEcircRNA-miRNA-DEmRNA interaction networks revealed that mmu_circRNA_44531, mmu_circRNA_34132, mmu_circRNA_000903, mmu_circRNA_018676, mmu_circRNA_45901, mmu_circRNA_33836, mmu_circRNA_ 34137, mmu_circRNA_34106, mmu_circRNA_008691, and mmu_circRNA_003237 were predicted to compete with 47, 54, 45, 57, 63, 81, 121, 85, 181, and 43 DEmRNAs, respectively. ENSMUST00000125413, NR_028123, uc008nfy.1, AK076764, AK142725, AK080547, and AK035903 were co-expressed with 178, 89, 149, 179, 142, 55, and 112 DEmRNAs in the Nrf2 (−/−) hippocampus, respectively. Conclusion Our study might contribute to exploring the key circRNAs and lncRNAs associated with Nrf2-mediated neuroprotection.

Functional predication of differentially expressed circRNAs/lncRNAs in the prefrontal cortex of Nrf2-knockout mice

“…DEcircRNAs, DElncRNAs and DEmRNAs in the substantia nigra, corpus striatum and hippocampus were screened in our previous studies of Nrf2 (-/-) and Nrf2 (+/+) mice [ 23 – 25 ]. The shared DEcircRNAs, DElncRNAs and DEmRNAs among these areas and the prefrontal cortex were determined using the Bioinformatics and Evolutionary Genomics tool ( http://bioinformatics.psb.ugent.be/webtools/Venn/ ).…”

“…In previous studies, we examined the effects of Nrf2-related circRNAs and lncRNAs on the brain by detecting the altered expression of circRNAs, lncRNAs and mRNAs in different brain areas in Nrf2-null (Nrf2 (-/-)) mice, including substantia nigra, corpus striatum and hippocampus [ 23 – 25 ]. The prefrontal cortex has often been called the command and control center of the brain, and is mainly responsible for cognitive control, especially the ability to orchestrate thought and action in accordance with internal goals [ 26 ].…”

Circular RNAs: Novel Players in the Oxidative Stress‐Mediated Pathologies, Biomarkers, and Therapeutic Targets

“…The same group did the same investigation on the hippocampus and identified several other circRNAs that could be involved. They constructed a differentially expressed ceRNA network related to the PD and studied their functional and pathway relations [ 40 ]. Another work discovered that circRNAs also play a protective role employing different pathways.…”

Differential Expression and Bioinformatics Analysis of circRNA in Non-small Cell Lung Cancer

“…In order to understand the potential functions of circRNAs, GO, and KEGG pathway enrichment analysis of target genes were performed by using the "cluster profiler" package in the R software. GO analysis cover three areas, cellular components (CC), molecular functions (MF), and biological processes (BP), each category explains the biological function of genes at different levels (Zhang et al, 2019). The KEGG pathway enrichment analysis is used for the degree of enrichment of differential genes in pathway terms.…”