Differential expression of circular RNAs in the frontal cortex of rats under ischemia-reperfusion conditions

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Abstract

Circular RNAs (circRNAs) are covalently closed non-coding RNAs that have increased metabolic stability and are capable of regulating gene expression. CircRNAs are considered as potential biomarkers and therapeutic targets for various diseases, including ischemic stroke. The transient right middle cerebral artery occlusion (tMCAO) model is actively used in stroke transcriptomics. In this study, we used whole-genome RNA sequencing to study the circRNA expression profile in the frontal cortex of rat brain 24 h after tMCAO. We identified 64 differentially expressed circRNAs (Fold change >1.5; Padj <0.05), which predominantly increased their levels compared to sham-operated animals. According to MRI data, the studied frontal cortex region included the penumbra zone, cell survival in which is important for stroke recovery. Also, using our previously obtained data on differential mRNA expression in this brain region, we bioinformatically predicted mRNA–miRNA–circRNA regulatory networks. Functional analysis of these networks showed that genes whose expression may depend on circRNA activity during ischemia are responsible for synaptic signaling and inflammatory response. Our study shows a significant role of circRNA-mediated transcriptome regulation in the penumbra-associated brain region during ischemia and allows us to consider circRNAs as potential targets for new strategies for the treatment of stroke and post-stroke complications.

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About the authors

I. V. Mozgovoy

National Research Centre “Kurchatov Institute”

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

Y. Y. Shpetko

National Research Centre “Kurchatov Institute”

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

A. E. Denisova

Pirogov Russian National Research Medical University

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 117997 Moscow

V. V. Stavchansky

National Research Centre “Kurchatov Institute”

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

M. A. Vinogradina

National Research Centre “Kurchatov Institute”

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

L. V. Gubsky

Pirogov Russian National Research Medical University; Federal Center for the Brain and Neurotechnology, Federal Medical Biological Agency

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 117997 Moscow; 117513 Moscow

L. V. Dergunova

National Research Centre “Kurchatov Institute”

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

S. A. Limborska

National Research Centre “Kurchatov Institute”

Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

I. B. Filippenkov

National Research Centre “Kurchatov Institute”

Author for correspondence.
Email: filippenkov-ib.img@yandex.ru
Russian Federation, 123182 Moscow

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2. Fig. 1. RNA-Seq analysis of differential expression of circRNAs in the rat frontal cortex 24 h after tMCAO. a – The total number of annotated circRNAs is shown in the gray circle; the numbers of DECs that increased and decreased their levels in the IR vs. LO comparison (fold change > 1.5; Padj < 0.05) are shown in white and black sectors of the circle, respectively. b – Volcano plot of RNA-Seq results. c – The first 10 DECs that showed the greatest change in expression in the IR vs. LO comparison (5 that showed the greatest increase in expression and 5 that showed the greatest decrease in expression). d – PCR verification of RNA-Seq results. Each PCR data comparison group includes 5 animals; each RNA-seq data comparison group included 3 animals; symbols “*” and “#” mark statistically significant results according to RNA-Seq and PCR data, respectively. NRs – normalized number of RNA-Seq reads; ΔCt = Ct(tar) – Ct(ref), where Ct(tar) is the average Ct value for the studied circRNAs and Ct(ref) is the average Ct value for the mRNA of the comparison gene (Gapdh); group “IR” – rats were decapitated 24 h after tMCAO; group “LO” – rats were decapitated 24 h after sham operation

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3. Fig. 2. Analysis of the structure of circRNA in the frontal cortex of rats 24 h after tMCAO. a – Exon-intron structure of the Psd2 gene. Exons are shown as numbered rectangles. Exons 13 and 8, connected by an arc, are involved in the formation of circRNA circPsd2-13.8. Primers (F-forward, R-reverse) and their direction are shown by arrows. b – Electrophoresis of the PCR product of the reaction carried out with these primers; on the left – the position of the GeneRuler 100 bp DNA Ladder marker (Thermo Fisher Scientific). c – A fragment of the PCR product sequence, including the backsplicing site between exons 13 and 8, according to the results of Sanger sequencing. g – The structure of the circPsd2-13.8 circRNA. The exons of the Psd2 gene included in the circRNA are shown as white numbers on the segments of the ring; the number inside the ring is the length of the entire circRNA; the black arc indicates the resulting PCR product

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4. Fig. 3. Comparative analysis of differential expression of circRNA and mRNA in the frontal cortex 24 h after tMCAO. a – Venn diagram showing the intersection of the genes encoding DECs obtained in this study with the DEGs identified earlier. b – The first 10 DECs with the highest fold change in expression and the corresponding DEGs from the intersection in the Venn diagram (5 showing the highest increase in expression and 5 showing the highest decrease in expression). c – DECs whose genes were not reliably identified as DEGs. NRs – normalized read counts; group “IR” – rats were decapitated 24 h after tMCAO; group “LO” – rats were decapitated 24 h after sham operation

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5. Fig. 4. Bioinformatics approach used to identify the DEC–miRNA–DEG network. a – Schematic representation of the sequence of actions during network identification. b – Venn diagram showing the number of common and unique miRNA–DEC pairs, according to the three programs. c – Venn diagram showing the number of common and unique miRNA–DEG pairs, according to the three programs

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6. Fig. 5. KEGG signaling pathways associated with genes in the DEC–miRNA–DEG network. a – Top 10 pathways with the highest association significance with a set of 2258 DEGs. For each pathway, the number of up- and down-regulated DEGs associated with the pathway and the pathway significance level (Padj, adjusted with the Benjamini–Hochberg correction) are shown. b – Number of up- and down-regulated circRNAs (DECs) competing with DEGs from the pathway

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7. Fig. 6. Element of the KEGG-microRNA-DEG ​​network associated with the glutamatergic synapse signaling pathway. DEGs (mRNAs) are shown as rectangles (inner circle); KEGs are shown as ovals (outer circle). MicroRNAs are shown as lines connecting the nodes of the network. Thus, KEGGs and DEGs connected by a line compete with each other for binding to one or more microRNAs.

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8. Appendix 1. Experimental flow chart
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9. Appendix 2. Method of establishing the tMCAO model and MRI analysis of ischemic brain injury in rats
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10. Appendix 3. Processing RNA-Seq results using DESeq2 (v. 1.32.0).
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11. Appendix 4. Genes encoding DEC in the rat frontal cortex 24 h after tMCAO
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12. Appendix 5. DEC-miRNA-DEG ​​interaction network in rat frontal cortex 24 hours after tMCAO
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13. Appendix 6. Analysis of signaling pathways associated with DEGs involved in the DEC-miRNA-DEG ​​network in the rat frontal cortex 24 hours after tMCAO (based on David 2021)
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