A systematic delineation of 3′UTR regulatory elements and their contextual associations

SUMMARY The 3′UTR encodes regulatory information that shapes transcript abundance and subcellular distribution, yet the underlying sequence rules remain incompletely defined. Using SEERS, we quantified the effects of ∼2 million synthetic 3′UTR inserts in A549 and HCT116 cells on RNA output and nuclear-cytoplasmic partitioning. We identify a broad repertoire of short (2∼8 nt) elements whose effects largely align along a major coupled axis that links high expression with cytoplasmic enrichment and low expression with nuclear enrichment, and contribute predominantly in an additive manner. A context-aware deep learning model (TALE) captures most of this behavior while revealing that strong context dependence is uncommon and emerges mainly in rare, extreme contexts consistent with higher-order constraints. Applying TALE to ClinVar 3′UTR variants prioritizes a subset of pathogenic SNVs with aberrant predicted effects, frequently explained by creation or disruption of splice-site-like U1 telescripting signals, highlighting a potent route to 3′UTR-driven disease mechanisms. Competing Interest Statement The authors have declared no competing interest. Footnotes The major changes in the revision include: 1. More rigorous controls for SEERS-associated cellular perturbations: We performed a four-condition perturbation comparison in both A549 and HCT116 with two biological replicates per condition (20 RNA-seq samples total, Fig. 1B-C), and support that SEERS reduces major confounding responses relative to standard MPRA workflows, while we also explicitly acknowledge residual perturbations. 2. Generalizability beyond A549: We carried out a full SEERS-3′UTR screen in HCT116 using the same library and workflow, and we observe strong cross-cell-line concordance of 8-mer regulatory profiles (Fig. 2E). 3. Addressing non-strand-specific elements and transcriptional confounds: We clarified the limitations of the single-promoter/single-reporter design and RNA/DNA normalization, and we added a SEERS-5′UTR experiment to distinguish enhancer-like transcription factor (TF) signals from the 3′UTR findings (Fig. 3). 4. Mechanistic validation of rare strong context-dependent effects: We added experimental validation demonstrating context-dependent enhancement or suppression of a U1 site (Fig. 5C-D). 5. Clearer figures and tighter linkage between Results and Methods: We rewrote and reorganized the manuscript with more precise language and a streamlined presentation, added descriptive subheadings, standardized terminology, and revised figure layouts and legends so that the main conclusions map directly to the data shown.