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<p>The 5′ UTR is critical for mRNA stability and translation efficiency in therapeutics. We developed UTR-Insight, a model integrating a pretrained language model with a CNN-Transformer architecture, explaining 89.1% of the mean ribosome load (MRL) variation in random 5′ UTRs and 82.8% in endogenous 5′ UTRs, surpassing existing models. Using UTR-Insight, we performed high-throughput in silico screening of hundreds of thousands of endogenous 5′ UTRs from primates, mice, and viruses. The screened sequences increased protein expression by up to 319% compared to the human α-globin 5′ UTR, and UTR-Insight-designed sequences achieved even greater expression levels than high-performing endogenous 5′ UTRs.</p>

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UTR-Insight: integrating deep learning for efficient 5′ UTR discovery and design

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月4日

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  • Saichao Pan,
  • Hanyu Wang,
  • Hang Zhang,
  • Zan Tang,
  • Lianqiang Xu,
  • Zhixiang Yan,
  • Yong Hu

摘要

The 5′ UTR is critical for mRNA stability and translation efficiency in therapeutics. We developed UTR-Insight, a model integrating a pretrained language model with a CNN-Transformer architecture, explaining 89.1% of the mean ribosome load (MRL) variation in random 5′ UTRs and 82.8% in endogenous 5′ UTRs, surpassing existing models. Using UTR-Insight, we performed high-throughput in silico screening of hundreds of thousands of endogenous 5′ UTRs from primates, mice, and viruses. The screened sequences increased protein expression by up to 319% compared to the human α-globin 5′ UTR, and UTR-Insight-designed sequences achieved even greater expression levels than high-performing endogenous 5′ UTRs.