CRISPRO Identifies Functional Protein Coding Sequences Based on Genome Editing Dense Mutagenesis
Vivien A. C. SchoonenbergiD, Mitchel A. ColeiD, Qiuming YaoiD, Claudio Macias-TreviñoiD, Falak SheriD, Patrick G. SchuppiD, Matthew C. CanveriD, Takahiro MaedaiD, Luca PinelloiD, Daniel E. BaueriD
Abstract
CRISPR/Cas9 pooled screening permits parallel evaluation of comprehensive guide RNA libraries to systematically perturb protein coding sequences in situ and correlate with functional readouts. For the analysis and visualization of the resulting datasets we have developed CRISPRO, a computational pipeline that maps functional scores associated with guide RNAs to genome, transcript, and protein coordinates and structure. No available tool has similar functionality. The ensuing genotype-phenotype linear and 3D maps raise hypotheses about structure-function relationships at discrete protein regions. Machine learning based on CRISPRO features improves prediction of guide RNA efficacy. The CRISPRO tool is freely available at gitlab.com/bauerlab/crispro.
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