UTRGAN: learning to generate 5' UTR sequences for optimized translation efficiency and gene expression.

ABSTRACT:

Motivation

The 5' untranslated region (5' UTR) of mRNA is crucial for the molecule's translatability and stability, making it essential for designing synthetic biological circuits for high and stable protein expression. Several UTR sequences are patented and widely used in laboratories. This paper presents UTRGAN, a Generative Adversarial Network (GAN)-based model for generating 5' UTR sequences, coupled with an optimization procedure to ensure high expression for target gene sequences or high ribosome load and translation efficiency.

Results

The model generates sequences mimicking various properties of natural UTR sequences and optimizes them to achieve (i) up to five-fold higher average predicted expression on target genes, (ii) up to two-fold higher predicted mean ribosom

SUBMITTER: Barazandeh S 

PROVIDER: S-EPMC12228966 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature