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. 2021 Mar;7(3):e06395.
doi: 10.1016/j.heliyon.2021.e06395. Epub 2021 Feb 27.

In silico analysis of altered expression of long non-coding RNA in SARS-CoV-2 infected cells and their possible regulation by STAT1, STAT3 and interferon regulatory factors

Sayantan Laha  1 , Chinmay Saha  2 , Susmita Dutta  3 , Madhurima Basu  3 , Raghunath Chatterjee  1 , Sujoy Ghosh  3 , Nitai P Bhattacharyya  3
Affiliations

In silico analysis of altered expression of long non-coding RNA in SARS-CoV-2 infected cells and their possible regulation by STAT1, STAT3 and interferon regulatory factors

Sayantan Laha et al. Heliyon. 2021 Mar.

Abstract

Altered expression of long noncoding RNA (lncRNA), longer than 200 nucleotides without potential for coding protein, has been observed in diverse human diseases including viral diseases. It is largely unknown whether lncRNA would deregulate in SARS-CoV-2 infection, causing ongoing pandemic COVID-19. To identify, if lncRNA was deregulated in SARS-CoV-2 infected cells, we analyzed in silico the data in GSE147507. It was revealed that expression of 20 lncRNA like MALAT1, NEAT1 was increased and 4 lncRNA like PART1, TP53TG1 was decreased in at least two independent cell lines infected with SARS-CoV-2. Expression of NEAT1 was also increased in lungs tissue of COVID-19 patients. The deregulated lncRNA could interact with more than 2800 genes/proteins and 422 microRNAs as revealed from the database that catalogs experimentally determined interactions. Analysis with the interacting gene/protein partners of deregulated lncRNAs revealed that these genes/proteins were associated with many pathways related to viral infection, inflammation and immune functions. To find out whether these lncRNAs could be regulated by STATs and interferon regulatory factors (IRFs), we used ChIPBase v2.0 that catalogs experimentally determined binding from ChIP-seq data. It was revealed that any one of the transcription factors IRF1, IRF4, STAT1, STAT3 and STAT5A had experimentally determined binding at regions within -5kb to +1kb of the deregulated lncRNAs in at least 2 independent cell lines/conditions. Our analysis revealed that several lncRNAs could be regulated by IRF1, IRF4 STAT1 and STAT3 in response to SARS-CoV-2 infection and lncRNAs might be involved in antiviral response. However, these in silico observations are necessary to be validated experimentally.

Keywords: COVID-19; Interferon regulatory factors; Long non-coding RNA; MALAT1; NEAT1; SARS-CoV-2.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Heatmap representing the expression of the 24 lncRNAs found to be upregulated (20) or downregulated (4) in SARS-CoV-2 infected cells wrt to mock-treated cells, for more than one experimental condition. The rows represent the lncRNAs while the columns are the experimental samples grouped according to mock-treatment or SARS-CoV-2 treatment, in A549 and Calu cell lines. The samples are named according to the experimental set they have been taken from (Series2, Series5, Series6, Series7 and Series16), followed by the cell line (A549/ Calu) and the treatment (Mock/ SARS-CoV-2).
Figure 2
Figure 2
Summary of the interaction of lncRNA with DNA, mRNA, microRNA (miRNA) and proteins taken from NPInter v4.0 (http://bigdata.ibp.ac.cn/npinter4). This experimental data was obtained in high throughput assays in different cell lines and catalogued in the database; whether similar interactions could also be obtained in cell lines infected with SARS-CoV-2 remain unknown.
Figure 3
Figure 3
Total binding sites of the TFs IFR1-IFR5, IRF8, IRF9, STAT1-STAT4, STA5A, STAT6 and MYC at -30Kb to +10Kb of the TSS of the deregulated lncRNA obtained from ChIPBase in different cell lines and conditions by ChIP-seq.
Figure 4
Figure 4
Overrepresentation of binding sites of the transcription factors IRFs, STATs and MYC at the putative promoters of the deregulated lncRNA in comparison of the randomly chosen 22 TFs denoted by Set 1–4. For details see the supplementary Text Supplementary Text ST2.2.
Figure 5
Figure 5
A: Binding of different transcription factors at the putative promoters of MALAT1 (hg38 chr11:65,497,688-65,506,431 Size: 8,744 Total Exon Count: 4 Strand: +) and NEAT1 (hg38 chr11:65,422,798-65,445,540 Size: 22,743 Total Exon Count: 1 Strand: +) in more than one independent experiment observed from ChiP-seq data in ChIPBase. For MALAT1 data for MYC (sample ID HUMHG01680), IRF1 (HUMHG05454, treated with IFNA), IRF4 (HUMHG04579), STAT1 (HUMHG00980, stimulated by IFNG), STAT3 (HUMHG04914) and STAT5A (HUMHG05298) is shown. For NEAT1 data for MYC (HUMHG01680), IRF1 (HUMHG05454, treated with IFNA), IRF4 (HUMHG03345), STAT1 (HUMHG00980 treated with IFNG), STAT3 (HUMHG02787) and STAT5A (HUMHG05298). Binding positions of these transcription factors at the putative promoters of MALAT1 and NEAT1 in other samples are shown in the Supplementary Table SXT6.
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References

    1. Akhade V.S., Pal D., Kanduri C. Long noncoding RNA: genome organization and mechanism of action. Adv. Exp. Med. Biol. 2017;1008:47–74. - PubMed
    1. Noh J.H., Kim K.M., McClusky W.G., Abdelmohsen K., Gorospe M. Cytoplasmic functions of long noncoding RNAs. Wiley Interdiscipl. Rev. RNA. 2018;9:e1471. - PMC - PubMed
    1. Yao R.W., Wang Y., Chen L.L. Cellular functions of long noncoding RNAs. Nat. Cell Biol. 2019;21:542–551. - PubMed
    1. Atianand M.K., Caffrey D.R., Fitzgerald K.A. Immunobiology of long noncoding RNAs. Annu. Rev. Immunol. 2017;35:177–198. - PMC - PubMed
    1. Stojic L., Lun A.T.L., Mascalchi P., Ernst C., Redmond A.M., Mangei J., Barr A.R., Bousgouni V., Bakal C., Marioni J.C., Odom D.T., Gergely F. A high-content RNAi screen reveals multiple roles for long noncoding RNAs in cell division. Nat. Commun. 2020;11:1851. - PMC - PubMed