2. Academic Validation
  3. A deep learning approach to identify gene targets of a therapeutic for human splicing disorders

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

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.
PMID: 34099697 DOI: 10.1038/s41467-021-23663-2
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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