Evidence map›Paper›PMID 41696049›Full record

ArticleEvolutionary bioinformatics online2026

Computational Optimization of CRISPR-Cas13a sgRNAs Targeting the SARS-CoV-2 Spike Gene for SHERLOCK-Based Diagnostics.

Maryam Ahmadzadeh, Fatemeh Akbarian, Mohammad Hossein Sanati, Hanieh Motaharirad, Fatemeh Farrokhi

Abstract read
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Article in Evolutionary bioinformatics online, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Maryam AhmadzadehGenetics Group, Department of Basic Sciences, Ale-Taha Institute of Higher Education, Tehran, Iran.
Fatemeh AkbarianGenetics Group, Department of Basic Sciences, Ale-Taha Institute of Higher Education, Tehran, Iran.ORCID https://orcid.org/0000-0002-4009-0827
Mohammad Hossein SanatiMedical Genetics Department, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.
Hanieh MotahariradDepartment of Embryology, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, Tehran, Iran.
Fatemeh FarrokhiGenetics Group, Department of Basic Sciences, Ale-Taha Institute of Higher Education, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global health crisis, emphasizing the urgent need for accurate and rapid diagnostic tools. Modern molecular biology technologies, including CRISPR-Cas systems, provide highly efficient strategies for viral detection. Bioinformatic pipelines are essential for identifying conserved genomic regions and enabling rational single-guide RNA (sgRNA) design. Methods: This study aimed to design specific sgRNAs targeting the spike gene of SARS-CoV-2 isolates from Iranian patients using the SHERLOCK diagnostic platform. Complete genomes of the RefSeq virus and 470 SARS-CoV-2 isolates, representing all variants of concern (VOCs) detected in Iran, were retrieved from the NCBI and GISAID databases. Multiple sequence alignment with ClustalW identified conserved sequences within the receptor-binding domain (RBD) that differ from the RBD of SARS-CoV and MERS-CoV RefSeq genomes. Based on these regions, sgRNAs and isothermal amplification primers were designed using ADAPT, OLIGO7, and the UCSC Genome Browser to maximize diagnostic sensitivity and specificity. Secondary and tertiary structures of sgRNA-target complexes were analyzed via RNAfold and RNAup to select the most efficient sgRNA-amplicon combination. Results: Twenty-two-nucleotide sgRNA candidates were initially selected based on sequence alignment, showing high similarity to the SARS-CoV-2 RefSeq and low homology to SARS-CoV and MERS-CoV genomes. Analyses of secondary structures, RNA-RNA interactions, and free energy identified 6 sgRNAs with favorable 2-dimensional conformations and strong interaction profiles. Among these, the sgRNA1-Amplicon2 sequence exhibited the most stable 3-dimensional structure and a molecular docking score of -309.67, indicating high sensitivity and specificity for viral detection. Conclusion: This study successfully designed an sgRNA with high sensitivity and specificity for rapid SARS-CoV-2 detection using the CRISPR-Cas13a system, informed by genomic analysis of Iranian isolates. The proposed approach provides an efficient framework for the rapid design and deployment of CRISPR-based diagnostic tools applicable to diverse viral pathogens.

Indexed as

bioinformaticsisothermal amplificationmolecular dockingreceptor binding domain (RBD)single-guide RNA (sgRNA)viral diagnostics

Identifiers

PMID41696049
PMCPMC12905083

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