Journal article
Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification
J Ryu, S Barkal, T Yu, M Jankowiak, Y Zhou, M Francoeur, QV Phan, Z Li, M Tognon, L Brown, MI Love, V Bhat, G Lettre, DB Ascher, CA Cassa, RI Sherwood, L Pinello
Nature Genetics | NATURE PORTFOLIO | Published : 2024
Abstract
CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in ..
View full abstractGrants
Awarded by American Heart Association
Funding Acknowledgements
We thank G. Losyev, A. James, Q. Qin, C. Smith, L. Blaine, K. Clement, Z. Patel, S. Yang and H. Boen for technical assistance. Funding for this work was obtained from UM1HG012010 (R.I.S. and L.P.), 1R01HL164409 (C.A.C., R.I.S. and L.P.), 1R01GM143249 (R.I.S.), R01HG010372 (C.A.C. and T.Y.), the American Cancer Society (R.I.S.), the American Heart Association (R.I.S.), the National Organization for Rare Diseases (R.I.S.), 1R35HG010717-01 (L.P.), the National Health and Medical Research Council of Australia (GNT1174405; D.B.A. and Y.Z.), and the Victorian Government's Operational Infrastructure Support Program (Y.Z. and D.B.A.). We are indebted to the UKB and its participants (UKB application 41250 and IRB protocol 2020P002093).