EukaUTR: a foundation model unifying functional modelling and design of eukaryotic 3' UTRs
Mei LangiD, Xingyu FangiD, Mingxuan CheniD, Zhen WangiD, Zhaowen Cheng, Xiagu Zhu, Kin Yip TamiD, Junwei Zhang, Xiaolin LiiD
Abstract
Eukaryotic mRNA 3' UTRs encode regulatory information that shapes post-transcriptional control, RNA fate and gene expression. However, a 3' UTR-specific foundation model that spans broad eukaryotic sequence diversity while supporting both functional prediction and sequence design is lacking. Here we present EukaUTR, a 3' UTR-specific foundation model trained on a large-scale eukaryotic 3' UTR sequence corpus spanning diverse evolutionary lineages. Across 13 prediction tasks spanning post-transcriptional regulation, RNA fate and expression output, EukaUTR models matched or exceeded the strongest external baselines on nearly all tasks, with relative improvements of up to 27.45%. EukaUTR also generated de novo 3' UTRs with natural-like sequence and regulatory properties. EukaUTR-Guide further derived stability-associated signals from small sequence sets to guide editing towards enhanced predicted stability. Together, EukaUTR provides a sequence-to-function-to-design framework for transferable 3' UTR modelling and design.
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