Novel SARS-CoV-2 encoded small RNAs in the passage to humans

Author:

Merino Gabriela A123ORCID,Raad Jonathan1ORCID,Bugnon Leandro A1ORCID,Yones Cristian1ORCID,Kamenetzky Laura45,Claus Juan6,Ariel Federico7,Milone Diego H1ORCID,Stegmayer Georgina1ORCID

Affiliation:

1. Research Institute for Signals, Systems and Computational Intelligence (sinc(i)), FICH-UNL, CONICET, Ciudad Universitaria UNL, Santa Fe 3000, Argentina

2. Bioengineering and Bioinformatics Research and Development Institute (IBB), FI-UNER, CONICET, Entre Ríos 3100, Argentina

3. European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire CB101SD, UK

4. Instituto de Investigaciones en Microbiología y Parasitología Médica (IMPaM), Facultad de Medicina, UBA-CONICET, Ciudad Autónoma de Buenos Aires 1121, Argentina

5. Laboratorio de Genómica y Bioinformática de Patógenos, iB3, Instituto de Biociencias, Biotecnología y Biología traslacional, Departamento de Fisiología y Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1121, Argentina

6. Laboratorio de Virología, FBCB, Ciudad Universitaria UNL, Santa Fe 3000, Argentina

7. Instituto de Agrobiotecnología del Litoral (IAL), CONICET, FBCB, Universidad Nacional del Litoral, Santa Fe 3000, Argentina

Abstract

Abstract Motivation The Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) has recently emerged as the responsible for the pandemic outbreak of the coronavirus disease 2019. This virus is closely related to coronaviruses infecting bats and Malayan pangolins, species suspected to be an intermediate host in the passage to humans. Several genomic mutations affecting viral proteins have been identified, contributing to the understanding of the recent animal-to-human transmission. However, the capacity of SARS-CoV-2 to encode functional putative microRNAs (miRNAs) remains largely unexplored. Results We have used deep learning to discover 12 candidate stem-loop structures hidden in the viral protein-coding genome. Among the precursors, the expression of eight mature miRNAs-like sequences was confirmed in small RNA-seq data from SARS-CoV-2 infected human cells. Predicted miRNAs are likely to target a subset of human genes of which 109 are transcriptionally deregulated upon infection. Remarkably, 28 of those genes potentially targeted by SARS-CoV-2 miRNAs are down-regulated in infected human cells. Interestingly, most of them have been related to respiratory diseases and viral infection, including several afflictions previously associated with SARS-CoV-1 and SARS-CoV-2. The comparison of SARS-CoV-2 pre-miRNA sequences with those from bat and pangolin coronaviruses suggests that single nucleotide mutations could have helped its progenitors jumping inter-species boundaries, allowing the gain of novel mature miRNAs targeting human mRNAs. Our results suggest that the recent acquisition of novel miRNAs-like sequences in the SARS-CoV-2 genome may have contributed to modulate the transcriptional reprograming of the new host upon infection. Availability and implementation https://github.com/sinc-lab/sarscov2-mirna-discovery. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

ANPCyT

UNL

UNER

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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