A map of the SARS-CoV-2 RNA structurome

Abstract SARS-CoV-2 has exploded throughout the human population. To facilitate efforts to gain insights into SARS-CoV-2 biology and to target the virus therapeutically, it is essential to have a roadmap of likely functional regions embedded in its RNA genome. In this report, we used a bioinformatics approach, ScanFold, to deduce the local RNA structural landscape of the SARS-CoV-2 genome with the highest likelihood of being functional. We recapitulate previously-known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a large reservoir of potential drug targets for RNA-binding small molecules. Results are enhanced via the re-analyses of publicly-available genome-wide biochemical structure probing datasets that are broadly in agreement with our models. Additionally, ScanFold was updated to incorporate experimental data as constraints in the analysis to facilitate comparisons between ScanFold and other RNA modelling approaches. Ultimately, ScanFold was able to identify eight highly structured/conserved motifs in SARS-CoV-2 that agree with experimental data, without explicitly using these data. All results are made available via a public database (the RNAStructuromeDB: https://structurome.bb.iastate.edu/sars-cov-2) and model comparisons are readily viewable at https://structurome.bb.iastate.edu/sars-cov-2-global-model-comparisons.

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An in silico map of the SARS-CoV-2 RNA Structurome

10.1101/2020.04.17.045161 ◽

2020 ◽

Cited By ~ 21

Author(s):

Ryan J. Andrews ◽

Jake M. Peterson ◽

Hafeez S. Haniff ◽

Jonathan Chen ◽

Christopher Williams ◽

...

Keyword(s):

Small Molecules ◽

Rna Structure ◽

Drug Targets ◽

Rna Binding ◽

Rna Virus ◽

Human Pathogens ◽

Public Database ◽

Positive Sense ◽

Basic Biology ◽

Potential Drug Targets

AbstractSARS-CoV-2 is a positive-sense single-stranded RNA virus that has exploded throughout the global human population. This pandemic coronavirus strain has taken scientists and public health researchers by surprise and knowledge of its basic biology (e.g. structure/function relationships in its genomic, messenger and template RNAs) and modes for therapeutic intervention lag behind that of other human pathogens. In this report we used a recently-developed bioinformatics approach, ScanFold, to deduce the RNA structural landscape of the SARS-CoV-2 transcriptome. We recapitulate known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that the SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a huge reservoir of potential drug targets for RNA-binding small molecules. Our results also predict regions that are accessible for intermolecular interactions, which can aid in the design of antisense therapeutics. All results are made available via a public database (the RNAStructuromeDB) where they may hopefully drive drug discovery efforts to inhibit SARS-CoV-2 pathogenesis.

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The global and local distribution of RNA structure throughout the SARS-CoV-2 genome

10.1101/2020.07.06.190660 ◽

2020 ◽

Cited By ~ 2

Author(s):

Rafael de Cesaris Araujo Tavares ◽

Gandhar Mahadeshwar ◽

Anna Marie Pyle

Keyword(s):

Rna Structure ◽

Drug Targets ◽

Structural Complexity ◽

Viral Agent ◽

Rna Structures ◽

Viral Rnas ◽

Functional Regions ◽

Structural Density ◽

Rna Genome ◽

High Base

AbstractSARS-CoV-2 is the causative viral agent of COVID-19, the disease at the center of the current global pandemic. While knowledge of highly structured regions is integral for mechanistic insights into the viral infection cycle, very little is known about the location and folding stability of functional elements within the massive, ~30kb SARS-CoV-2 RNA genome. In this study, we analyze the folding stability of this RNA genome relative to the structural landscape of other well-known viral RNAs. We present an in-silico pipeline to locate regions of high base pair content across this long genome and also identify well-defined RNA structures, a method that allows for direct comparisons of RNA structural complexity within the several domains in SARS-CoV-2 genome. We report that the SARS-CoV-2 genomic propensity to stable RNA folding is exceptional among RNA viruses, superseding even that of HCV, one of the most highly structured viral RNAs in nature. Furthermore, our analysis reveals varying levels of RNA structure across genomic functional regions, with accessory and structural ORFs containing the highest structural density in the viral genome. Finally, we take a step further to examine how individual RNA structures formed by these ORFs are affected by the differences in genomic and subgenomic contexts. The conclusions reported in this study provide a foundation for structure-function hypotheses in SARS-CoV-2 biology, and in turn, may guide the 3D structural characterization of potential RNA drug targets for COVID-19 therapeutics.

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FoldAtlas: a repository for genome-wide RNA structure probing data

Bioinformatics ◽

10.1093/bioinformatics/btw611 ◽

2016 ◽

Vol 33 (2) ◽

pp. 306-308 ◽

Cited By ~ 10

Author(s):

Matthew Norris ◽

Chun Kit Kwok ◽

Jitender Cheema ◽

Matthew Hartley ◽

Richard J. Morris ◽

...

Keyword(s):

Rna Structure ◽

Structure Probing ◽

Genome Wide

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Identifying Novel Psoriatic Disease Drug Targets Using a Genetics-Based Priority Index Pipeline

Journal of Psoriasis and Psoriatic Arthritis ◽

10.1177/24755303211026023 ◽

2021 ◽

pp. 247553032110260

Author(s):

Audrey Bui ◽

Jared Liu ◽

Julie Hong ◽

Edward Hadeler ◽

Megan Mosca ◽

...

Keyword(s):

Psoriatic Arthritis ◽

Drug Targets ◽

Association Studies ◽

Therapeutic Targets ◽

Genome Wide Association Studies ◽

Priority Index ◽

Psoriatic Disease ◽

Genome Wide ◽

Pathway Crosstalk ◽

Potential Drug Targets

Background: Despite numerous genome-wide association studies conducted in psoriasis and psoriatic arthritis, only a small fraction of the identified genes has been therapeutically targeted. Objective: We sought to identify and analyze potential therapeutic targets for psoriasis and psoriatic arthritis (PsA) using the priority index (Pi), a genetics-dependent drug target prioritization approach. Methods: Significant genetic variants from GWAS for psoriasis, PsA, and combined psoriatic disease were annotated and run through the Pi pipeline. Potential drug targets were identified based on genomic predictors, annotation predictors, pathway enrichment, and pathway crosstalk. Results: Several gene targets were identified for psoriasis and PsA that demonstrated biological associations to their respective diseases. Some are currently being explored as potential therapeutic targets (i.e. ICAM1, NF-kB, REV3 L, ADRA1B for psoriasis; CCL11 for PsA); others have not yet been investigated (i.e. LNPEP, LCE3 for psoriasis; UBLCP1 for PsA). Additionally, many nodal points of potential intervention were identified as promising therapeutic targets. Of these, some are currently being studied such as TYK2 for psoriasis, and others have yet to be explored (i.e. PPP2CA, YAP1, PI3 K, AKT, FOXO1, RELA, CSF2, IFNGR1, IFNGR2 for psoriasis; GNAQ, PLCB1, GNAI2 for PsA). Conclusion: Through Pi, we identified data-driven candidate therapeutic gene targets and pathways for psoriasis and PsA. Given the sparse PsA specific genetic studies and PsA specific drug targets, this analysis could prove to be particularly valuable in the pipeline for novel psoriatic therapies.

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Genome-wide application of RNAi to the discovery of potential drug targets

FEBS Letters ◽

10.1016/j.febslet.2005.08.015 ◽

2005 ◽

Vol 579 (26) ◽

pp. 5988-5995 ◽

Cited By ~ 20

Author(s):

Masanori Ito ◽

Kenji Kawano ◽

Makoto Miyagishi ◽

Kazunari Taira

Keyword(s):

Drug Targets ◽

Potential Drug ◽

Genome Wide ◽

Potential Drug Targets

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Microbial Genome-Wide Association Studies: Lessons from Human GWAS

10.1101/093211 ◽

2016 ◽

Cited By ~ 4

Author(s):

Robert A. Power ◽

Julian Parkhill ◽

Tulio de Oliveira

Keyword(s):

Disease Transmission ◽

Drug Targets ◽

Association Studies ◽

Genome Wide Association ◽

Microbial Genome ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Disease Aetiology ◽

Number Of Microorganisms ◽

Potential Drug Targets

AbstractThe reduced costs of sequencing have led to the availability of whole genome sequences for a large number of microorganisms, enabling the application of microbial genome wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS is likely to further advance our understanding of infectious diseases. By building on the success of GWAS, microbial GWAS have the potential to rapidly provide important insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this review, we outline the methodologies of GWAS, the state of the field of microbial GWAS today, and how lessons from GWAS can direct the future of the field.

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Genomic and multi-tissue proteomic integration for understanding the biology of disease and other complex traits

10.1101/2020.06.25.20140277 ◽

2020 ◽

Cited By ~ 1

Author(s):

Chengran Yang ◽

Fabiana G. Farias ◽

Laura Ibanez ◽

Brooke Sadler ◽

Maria Victoria Fernandez ◽

...

Keyword(s):

Gene Expression ◽

Complex Traits ◽

Drug Targets ◽

Genetic Architecture ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Protein Levels ◽

Genome Wide ◽

Novel Biomarkers ◽

Potential Drug Targets

AbstractExpression quantitative trait loci (eQTL) mapping has successfully resolved some genome-wide association study (GWAS) loci for complex traits1–6. However, there is a need for implementing additional “omic” approaches to untangle additional loci and provide a biological context for GWAS signals. We generated a detailed landscape of the genomic architecture of protein levels in multiple neurologically relevant tissues (brain, cerebrospinal fluid (CSF) and plasma), by profiling thousands of proteins in a large and well-characterized cohort. We identified 274, 127 and 32 protein quantitative loci (pQTL) for CSF, plasma and brain respectively. We demonstrated that cis-pQTL are more likely to be shared across tissues but trans-pQTL are tissue-specific. Between 78% to 87% of pQTL are not eQTL, indicating that protein levels have a different genetic architecture than gene expression. By combining our pQTL with Mendelian Randomization approaches we identified potential novel biomarkers and drug targets for neurodegenerative diseases including Alzheimer disease and frontotemporal dementia. In the context of personalized medicine, these results highlight the need for implementing additional functional genomic approaches beyond gene expression in order to understand the biology of complex traits, and to identify novel biomarkers and potential drug targets for those traits.

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Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide

10.1101/173831 ◽

2017 ◽

Cited By ~ 4

Author(s):

Claudia L Satizabal ◽

Hieab HH Adams ◽

Derrek P Hibar ◽

Charles C White ◽

Jason L Stein ◽

...

Keyword(s):

Drug Targets ◽

Brain Structures ◽

Association Analyses ◽

Subcortical Brain ◽

Genome Wide ◽

Evolutionarily Conserved ◽

Subcortical Brain Structures ◽

The Uk ◽

Potential Drug Targets ◽

Subcortical Volumes

AbstractSubcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

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