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bioRxiv · 10.1101/2022.02.28.482271

Reduced gene templates for supervisedanalysis of scale-limited CRISPR-Cas9 fitnessscreens

Vinceti, A.·Perron, U.·Trastulla, L.·Iorio, F.
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Abstract

Pooled genome-wide CRISPR-Cas9 screens are furthering our mechanistic understanding of human biology and have allowed us to identify new oncology therapeutic targets. Scale-limited CRISPR-Cas9 screens - typically employing guide RNA libraries targeting subsets of functionally related genes, individual biological pathways, or portions of the druggable genome - constitute an optimal setting for investigating narrow hypotheses and they are easier to execute on complex models, such as organoids and in vivo models. Different supervised methods are used for the computational analysis of genome-wide CRISPR-Cas9 screens; most are not well suited for scale-limited screens as they require large sets of positive/negative control genes (gene templates) to be included among the screened ones. We have developed a computational framework identifying optimal subsets of known essential and nonessential genes (at different subsampling percentages) that can be used as templates for supervised analyses of scale-limited CRISPR-Cas9 screens, while having a reduced impact on the size of the employed library. HighlightsO_LIScale-limited CRISPR-Cas9 screens are experimentally easier than genome-wide screens C_LIO_LIReference gene templates are used for supervised analyses of genome-wide screens C_LIO_LIReduced templates allow supervised analyses of scale-limited CRISPR-Cas9 screens C_LIO_LIWe present optimal reduced templates and a computational method to assemble them C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/482271v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1dcf4corg.highwire.dtl.DTLVardef@1149e3borg.highwire.dtl.DTLVardef@a04788org.highwire.dtl.DTLVardef@b84fc9_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Vinceti, A., Perron, U., Trastulla, L., Iorio, F.. 2022-03-01. Reduced gene templates for supervisedanalysis of scale-limited CRISPR-Cas9 fitnessscreens. https://doi.org/10.1101/2022.02.28.482271

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