Evidence map›Paper›PMID 38514586›Full record

ArticleJournal of applied genetics2024

In silico approach for the identification of tRNA-derived small non-coding RNAs in SARS-CoV infection.

Swati Ajmeriya, Deepak Ramkumar Bharti, Amit Kumar, Shweta Rana, Harpreet Singh, Subhradip Karmakar

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Article in Journal of applied genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Swati AjmeriyaDepartment of Biochemistry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India.ORCID https://orcid.org/0000-0002-2015-0335
Deepak Ramkumar BhartiTrinity Translation Medicine Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0002-4186-4038
Amit KumarICMR-AIIMS Computational Genomics Center, Division of Biomedical Informatics, Division, Indian Council of Medical Research, Ansari Nagar, New Delhi, India.ORCID https://orcid.org/0000-0003-2775-6919
Shweta RanaICMR-AIIMS Computational Genomics Center, Division of Biomedical Informatics, Division, Indian Council of Medical Research, Ansari Nagar, New Delhi, India.ORCID https://orcid.org/0000-0003-4053-6267
Harpreet SinghICMR-AIIMS Computational Genomics Center, Division of Biomedical Informatics, Division, Indian Council of Medical Research, Ansari Nagar, New Delhi, India.ORCID https://orcid.org/0000-0002-5838-1884
Subhradip KarmakarDepartment of Biochemistry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India. subhradip.k@aiims.edu.ORCID https://orcid.org/0000-0002-4757-8729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

tsRNAs (tRNA-derived small non-coding RNAs), including tRNA halves (tiRNAs) and tRNA fragments (tRFs), have been implicated in some viral infections, such as respiratory viral infections. However, their involvement in SARS-CoV infection is completely unknown. A comprehensive analysis was performed to determine tsRNA populations in a mouse model of SARS-CoV-infected samples containing the wild-type and attenuated viruses. Data from the Gene Expression Omnibus (GEO) dataset at NCBI (accession ID GSE90624 ) was used for this study. A count matrix was generated for the tRNAs. Differentially expressed tRNAs, followed by tsRNAs derived from each significant tRNAs at different conditions and time points between the two groups WT(SARS-CoV-MA15-WT) vs Mock and ΔE (SARS-CoV-MA15-ΔE) vs Mock were identified. Notably, significantly differentially expressed tRNAs at 2dpi but not at 4dpi. The tsRNAs originating from differentially expressed tRNAs across all the samples belonging to each condition (WT, ΔE, and Mock) were identified. Intriguingly, tRFs (tRNA-derived RNA fragments) exhibited higher levels compared to tiRNAs (tRNA-derived stress-induced RNAs) across all samples associated with WT SARS-CoV strain compared to ΔE and mock-infected samples. This discrepancy suggests a non-random formation of tsRNAs, hinting at a possible involvement of tsRNAs in SARS-CoV viral infection.

Indexed as

Severe acute respiratory syndrome-related coronavirusVirus DiseasesAnimalsMiceRNA, TransferRNA, TransferCoronavirusDeep sequencingSARS-CoVsncRNAtiRNAstRFs

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.