Predicting adenine base editing efficiencies in different cellular contexts by deep learning.

Journal: Genome biology
PMID: 40340964

Abstract

BACKGROUND: Adenine base editors (ABEs) enable the conversion of A•T to G•C base pairs. Since the sequence of the target locus influences base editing efficiency, efforts have been made to develop computational models that can predict base editing outcomes based on the targeted sequence. However, these models were trained on base editing datasets generated in cell lines and their predictive power for base editing in primary cells in vivo remains uncertain.

Authors

  • Lucas Kissling
    Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
  • Amina Mollaysa
    Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
  • Sharan Janjuha
    Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
  • Nicolas Mathis
    Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
  • Kim F Marquart
    Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
  • Yanik Weber
    Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.
  • Woohyun J Moon
    Acuitas Therapeutics Inc., Vancouver, BC, Canada.
  • Paulo J C Lin
    Acuitas Therapeutics Inc., Vancouver, BC, Canada.
  • Steven H Y Fan
    Acuitas Therapeutics Inc., Vancouver, BC, Canada.
  • Hiromi Muramatsu
    Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Máté Vadovics
    Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Ahmed Allam
    Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
  • Norbert Pardi
    Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Ying K Tam
    Acuitas Therapeutics Inc., Vancouver, BC, Canada.
  • Michael Krauthammer
    Yale School of Medicine, New Haven, CT.
  • Gerald Schwank
    Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland. schwank@pharma.uzh.ch.

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