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Accounting for small variations in the tracrRNA sequence improves sgRNA activity predictions for CRISPR screening

Author

Listed:
  • Peter C. DeWeirdt

    (Broad Institute of MIT and Harvard)

  • Abby V. McGee

    (Broad Institute of MIT and Harvard)

  • Fengyi Zheng

    (Broad Institute of MIT and Harvard)

  • Ifunanya Nwolah

    (Broad Institute of MIT and Harvard
    Arbor Biotechnologies)

  • Mudra Hegde

    (Broad Institute of MIT and Harvard
    Thermo Fisher Scientific)

  • John G. Doench

    (Broad Institute of MIT and Harvard)

Abstract

CRISPR technology is a powerful tool for studying genome function. To aid in picking sgRNAs that have maximal efficacy against a target of interest from many possible options, several groups have developed models that predict sgRNA on-target activity. Although multiple tracrRNA variants are commonly used for screening, no existing models account for this feature when nominating sgRNAs. Here we develop an on-target model, Rule Set 3, that makes optimal predictions for multiple tracrRNA variants. We validate Rule Set 3 on a new dataset of sgRNAs tiling essential and non-essential genes, demonstrating substantial improvement over prior prediction models. By analyzing the differences in sgRNA activity between tracrRNA variants, we show that Pol III transcription termination is a strong determinant of sgRNA activity. We expect these results to improve the performance of CRISPR screening and inform future research on tracrRNA engineering and sgRNA modeling.

Suggested Citation

  • Peter C. DeWeirdt & Abby V. McGee & Fengyi Zheng & Ifunanya Nwolah & Mudra Hegde & John G. Doench, 2022. "Accounting for small variations in the tracrRNA sequence improves sgRNA activity predictions for CRISPR screening," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33024-2
    DOI: 10.1038/s41467-022-33024-2
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    References listed on IDEAS

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    1. Kendall R. Sanson & Ruth E. Hanna & Mudra Hegde & Katherine F. Donovan & Christine Strand & Meagan E. Sullender & Emma W. Vaimberg & Amy Goodale & David E. Root & Federica Piccioni & John G. Doench, 2018. "Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities," Nature Communications, Nature, vol. 9(1), pages 1-15, December.
    2. Xi Xiang & Giulia I. Corsi & Christian Anthon & Kunli Qu & Xiaoguang Pan & Xue Liang & Peng Han & Zhanying Dong & Lijun Liu & Jiayan Zhong & Tao Ma & Jinbao Wang & Xiuqing Zhang & Hui Jiang & Fengping, 2021. "Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    3. Fiona M. Behan & Francesco Iorio & Gabriele Picco & Emanuel Gonçalves & Charlotte M. Beaver & Giorgia Migliardi & Rita Santos & Yanhua Rao & Francesco Sassi & Marika Pinnelli & Rizwan Ansari & Sarah H, 2019. "Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens," Nature, Nature, vol. 568(7753), pages 511-516, April.
    4. Joshua M. Dempster & Clare Pacini & Sasha Pantel & Fiona M. Behan & Thomas Green & John Krill-Burger & Charlotte M. Beaver & Scott T. Younger & Victor Zhivich & Hanna Najgebauer & Felicity Allen & Ema, 2019. "Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    5. Peter C. DeWeirdt & Annabel K. Sangree & Ruth E. Hanna & Kendall R. Sanson & Mudra Hegde & Christine Strand & Nicole S. Persky & John G. Doench, 2020. "Genetic screens in isogenic mammalian cell lines without single cell cloning," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
    6. Annabel K. Sangree & Audrey L. Griffith & Zsofia M. Szegletes & Priyanka Roy & Peter C. DeWeirdt & Mudra Hegde & Abby V. McGee & Ruth E. Hanna & John G. Doench, 2022. "Benchmarking of SpCas9 variants enables deeper base editor screens of BRCA1 and BCL2," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
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    Cited by:

    1. Luke Hoberecht & Pirunthan Perampalam & Aaron Lun & Jean-Philippe Fortin, 2022. "A comprehensive Bioconductor ecosystem for the design of CRISPR guide RNAs across nucleases and technologies," Nature Communications, Nature, vol. 13(1), pages 1-20, December.

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