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Abstract Alternative splicing (AS) of pre-mRNA plays a crucial role in tissue-specific gene regulation, with disease implications due to splicing defects. Predicting and manipulating AS can therefore uncover new regulatory mechanisms and aid in therapeutics design. We introduce TrASPr+BOS, a generative AI model with Bayesian Optimization for predicting and designing RNA for tissue-specific splicing outcomes. TrASPr is a multi-transformer model that can handle different types of AS events and generalize to unseen cellular conditions. It then serves as an oracle, generating labeled data to train a Bayesian Optimization for Splicing (BOS) algorithm to design RNA for condition-specific splicing outcomes. We show TrASPr+BOS outperforms existing methods, enhancing tissue-specific AUPRC by up to 2.4 fold and capturing tissue-specific regulatory elements. We validate hundreds of predicted novel tissue-specific splicing variations and confirm new regulatory elements using dCas13. We envision TrASPr+BOS as a light yet accurate method researchers can probe or adopt for specific tasks.
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A simple method to visualize pre-mRNA splicing with the naked eye using a genetically encoded visual splicing reporter
A genetically encoded splicing reporter allows naked-eye visualization of pre-mRNA splicing and requires no expensive equipment or substrate.
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- Award ID(s):
- 2014408
- PAR ID:
- 10546133
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Plant Physiology
- Volume:
- 196
- Issue:
- 2
- ISSN:
- 0032-0889
- Format(s):
- Medium: X Size: p. 726-730
- Size(s):
- p. 726-730
- Sponsoring Org:
- National Science Foundation
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