Synthetic lethality-based prediction of anti-SARS-CoV-2 targets. Pal et al

Published: 19 April 2022| Version 1 | DOI: 10.17632/42sxkx9sdb.1
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Description

Supplementary data for the paper: "Synthetic lethality-based prediction of anti-SARS-CoV-2 targets". Table S1: Enriched Reactome pathways for DE gene sets (FDR<0.1). (Related to STAR Methods and Figure 2). Table S2: List of synthetic lethal pairs in each of the transcriptomic dataset used in this study and the list of unified 454 SL/SDL partner genes. (Related to STAR Methods and Figure 1). Table S3: List of 140 candidate targets and three subsets comprising known drug targets, hub SL/SDL partner genes when each one of them are paired up with multiple DE genes and genes with enriched Reactome pathways. Pathway enrichment analysis (FDR <0.1) for SL/SDL partner genes, DE genes and combination pathway enrichment analysis for DE gene-SL/SDL partner gene pairs for 140 candidates. List of 135 candidates overlapping with genome-wide siRNA screen. (Related to STAR Methods and Figure 1 and 2). Table S4: Targeted siRNA screen results for selected 26 targets and annotation of 26 candidate targets with reference to SARS-CoV-2 or any other virus in the literature. (Related to STAR Methods and Figure 3).

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Institutions

National Institutes of Health, National Cancer Institute, Sanford Burnham Prebys Medical Discovery Institute

Categories

Transcriptome, Drug, Antiviral Therapy, CRISPR/Cas9, COVID-19

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