Dengue and Zika RNA-RNA interactomes reveal pro- and anti-viral RNA in human cells

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Abstract

Background

Identifying host factors is key to understanding RNA virus pathogenicity. Besides proteins, RNAs can interact with virus genomes to impact replication.

Results

Here, we use proximity ligation sequencing to identify virus-host RNA interactions for four strains of Zika virus (ZIKV) and one strain of dengue virus (DENV-1) in human cells. We find hundreds of coding and non-coding RNAs that bind to DENV and ZIKV viruses. Host RNAs tend to bind to single-stranded regions along the virus genomes according to hybridization energetics. Compared to SARS-CoV-2 interactors, ZIKV-interacting host RNAs tend to be downregulated upon virus infection. Knockdown of several short non-coding RNAs, including miR19a-3p, and 7SK RNA results in a decrease in viral replication, suggesting that they act as virus-permissive factors. In addition, the 3′UTR of DYNLT1 mRNA acts as a virus-restrictive factor by binding to the conserved dumbbell region on DENV and ZIKV 3′UTR to decrease virus replication. We also identify a conserved set of host RNAs that interacts with DENV, ZIKV, and SARS-CoV-2, suggesting that these RNAs are broadly important for RNA virus infection.

Conclusions

This study demonstrates that host RNAs can impact virus replication in permissive and restrictive ways, expanding our understanding of host factors and RNA-based gene regulation during viral pathogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-023-03110-9.

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Most cited references 25

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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The global distribution and burden of dengue

Samir Bhatt, Peter W. Gething, Oliver J Brady … (2013)

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes 1 . For some patients dengue is a life-threatening illness 2 . There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread 3 . The contemporary worldwide distribution of the risk of dengue virus infection 4 and its public health burden are poorly known 2,5 . Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanisation. Using cartographic approaches, we estimate there to be 390 million (95 percent credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of clinical or sub-clinical severity). This infection total is more than three times the dengue burden estimate of the World Health Organization 2 . Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help guide improvements in disease control strategies using vaccine, drug and vector control methods and in their economic evaluation. [285]

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ViennaRNA Package 2.0

Ronny Lorenz, Stephan H Bernhart, Christian Höner zu Siederdissen … (2011)

Background Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties. Results The ViennaRNA Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the Turner 2004 parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying RNAlib and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as centroid structures and maximum expected accuracy structures derived from base pairing probabilities, or z-scores for locally stable secondary structures, and support for input in fasta format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions. Conclusions The ViennaRNA Package 2.0, supporting concurrent computations via OpenMP, can be downloaded from http://www.tbi.univie.ac.at/RNA.

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Author and article information

Contributors

Pei-Yong Shi: peshi@utmb.edu

Roland G. Huber: rghuber@bii.a-star.edu.sg

Yue Wan: wany@gis.a-star.edu.sg

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 5 December 2023

Publication date PMC-release: 5 December 2023

Publication date Collection: 2023

Volume: 24

Electronic Location Identifier: 279

Affiliations

[1 ]Stem Cell and Regenerative Biology, Genome Institute of Singapore, ( https://ror.org/05k8wg936) Singapore, 138672 Singapore

[2 ]Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, ( https://ror.org/016tfm930) Galveston, TX 77555 USA

[3 ]GRID grid.428397.3, ISNI 0000 0004 0385 0924, Program in Emerging Infectious Diseases, , Duke-NUS Graduate Medical School, ; 8 College Road, Singapore, 169857 Singapore

[4 ]Cancer Science Institute of Singapore, National University of Singapore, ( https://ror.org/01tgyzw49) Singapore, 117599 Singapore

[5 ]Saw Swee Hock School of Public Health, National University of Singapore, ( https://ror.org/01tgyzw49) Singapore, 117549 Singapore

[6 ]Department of Pharmacy, National University of Singapore, ( https://ror.org/01tgyzw49) Singapore, 117559 Singapore

[7 ]Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, ( https://ror.org/01tgyzw49) Singapore, 117597 Singapore

[8 ]Biomolecular Function Discovery, Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), ( https://ror.org/044w3nw43) Matrix #07-01, Singapore, 138671 Singapore

[9 ]School of Biological Sciences, Nanyang Technological University, ( https://ror.org/02e7b5302) Singapore, Singapore

Article

Publisher ID: 3110

DOI: 10.1186/s13059-023-03110-9

PMC ID: 10696742

PubMed ID: 38053173

SO-VID: 8d1955a2-14cb-4d07-a5e4-e4503ea1bdd5

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 18 April 2023

Date accepted : 15 November 2023

Funding

Funded by: A*STAR

Funded by: FundRef http://dx.doi.org/10.13039/501100001381, National Research Foundation Singapore;

Funded by: EMBO Young Investigatorship

Funded by: CIFAR global scholarship

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ScienceOpen disciplines: Genetics

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ScienceOpen disciplines: Genetics

Dengue and Zika RNA-RNA interactomes reveal pro- and anti-viral RNA in human cells

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Abstract

Background

Results

Conclusions

Supplementary Information

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 25

Fast and accurate short read alignment with Burrows–Wheeler transform

The global distribution and burden of dengue

ViennaRNA Package 2.0

Author and article information

Contributors

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