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CRISPRO identifies functional protein coding sequences based on genome editing dense mutagenesis

Schoonenberg, Vivien A. C.; Cole, Mitchel A.; Yao, Qiuming; Macias-Trevino, Claudio; Sher, Falak; Schupp, Patrick G.; Canver, Matthew C.; Maeda, Takahiro; Pinello, Luca; Bauer, Daniel E.

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 currently 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.

 

v1.0.1: Update CRISPRO prediction scores for hg19.

D.E.B. was supported by NIDDK (K08DK093705, R03DK109232), NHLBI (DP2OD022716, P01HL032262), the Burroughs Wellcome Fund, the American Society of Hematology, and an Epigenetics Seed Grant from Harvard Medical School. L.P. was supported by a National Human Genome Research Institute (NHGRI) Career Development Award (R00HG008399). V.A.C.S. was supported by an Individual Travel Grant (ITG) from Radboud University.
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