A deep learning approach to identify gene targets of a therapeutic for human splicing disorders

  • Nat Commun. 2021 Jun 7;12(1):3332. doi: 10.1038/s41467-021-23663-2.
Dadi Gao   #  1  2  3 Elisabetta Morini   #  1  2 Monica Salani   #  1 Aram J Krauson  1 Anil Chekuri  1  2 Neeraj Sharma  4 Ashok Ragavendran  1  3 Serkan Erdin  1  3 Emily M Logan  1 Wencheng Li  5 Amal Dakka  5 Jana Narasimhan  5 Xin Zhao  5 Nikolai Naryshkin  5 Christopher R Trotta  5 Kerstin A Effenberger  5 Matthew G Woll  5 Vijayalakshmi Gabbeta  5 Gary Karp  5 Yong Yu  5 Graham Johnson  6 William D Paquette  7 Garry R Cutting  4 Michael E Talkowski  8  9  10 Susan A Slaugenhaupt  11  12
Affiliations
  • 1. Center for Genomic Medicine, Massachusetts General Hospital Research Institute, Boston, MA, USA.
  • 2. Department of Neurology, Massachusetts General Hospital Research Institute and Harvard Medical School, Boston, MA, USA.
  • 3. Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • 4. McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • 5. PTC Therapeutics, Inc., South Plainfield, NJ, USA.
  • 6. NuPharmAdvise LLC, Sanbornton, NH, USA.
  • 7. Albany Molecular Research Inc., Albany, NY, USA.
  • 8. Center for Genomic Medicine, Massachusetts General Hospital Research Institute, Boston, MA, USA. [email protected].
  • 9. Department of Neurology, Massachusetts General Hospital Research Institute and Harvard Medical School, Boston, MA, USA. [email protected].
  • 10. Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA. [email protected].
  • 11. Center for Genomic Medicine, Massachusetts General Hospital Research Institute, Boston, MA, USA. [email protected].
  • 12. Department of Neurology, Massachusetts General Hospital Research Institute and Harvard Medical School, Boston, MA, USA. [email protected].
  • # Contributed equally.
Abstract

Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing due to mutation lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of splicing modulator compounds (SMCs) have been recently identified and establish that pre-mRNA splicing represents a target for therapy. We describe herein the identification of BPN-15477, a SMC that restores correct splicing of ELP1 exon 20. Using transcriptome Sequencing from treated fibroblast cells and a machine learning approach, we identify BPN-15477 responsive sequence signatures. We then leverage this model to discover 155 human disease genes harboring ClinVar mutations predicted to alter pre-mRNA splicing as targets for BPN-15477. Splicing assays confirm successful correction of splicing defects caused by mutations in CFTR, LIPA, MLH1 and MAPT. Subsequent validations in two disease-relevant cellular models demonstrate that BPN-15477 increases functional protein, confirming the clinical potential of our predictions.

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