Study / S68V5CH0F2025-09-16

Massively Parallel Polyribosome Profiling Reveals Translation Defects of Human Disease-Relevant UTR Mutations

Wei-Ping Li, Jia-Ying Su, Yu-Chi Chang, Hung-Lun Chiang, Yun-Lin Wang et al.

About this study

The untranslated regions (UTRs) of mRNAs harbor regulatory elements influencing translation efficiency. Although 3.7% of disease-relevant human mutations occur in UTRs, their exact role in pathogenesis remains unclear. Through metagene analysis, we mapped pathogenic UTR mutations to regions near coding sequences, with a focus on the upstream open reading frame (uORF) initiation site. Subsequently, we utilized massively parallel poly(ribo)some profiling to compare the ribosome associations of 6,555 pairs of wildtype and mutant UTR fragments. We identified 46 UTR variants that altered polysome profiles, with enrichment in pathogenic mutations. Both univariate analysis and the elastic net regression model highlighted the significance of motifs of short repeated sequences, including SRSF2 binding sites, as mutation hotspots that lead to aberrant translation. Furthermore, these polysome-shifting mutations exhibited considerable impact on RNA secondary structures, particularly for upstream AUG-containing 5′ UTRs. Integrating these features, our model achieved high accuracy (AUROC > 0.8) in predicting polysome-shifting mutations in the test dataset. Additionally, several lines of evidence indicate that changes in uORF usage underlie the translation deficiency arising from these mutations. Illustrating this, we demonstrate that a pathogenic mutation in the IRF6 5′ UTR suppresses translation of the primary open reading frame by creating a uORF. Remarkably, site-directed ADAR editing of the mutant mRNA rescued this translation deficiency. Overall, our study provides insights into the molecular mechanisms of UTR mutations and their links to clinical impacts through translation defects.

Full author list & citation

Wei-Ping Li, Jia-Ying Su, Yu-Chi Chang, Hung-Lun Chiang, Yun-Lin Wang, Ang-Chu Huang, Yu-Tung Hsieh, Yi-Hsuan Chiang, Yen-Ling Ko, Bing-Jen Chiang, Cheng-Han Yang, Yen-Tsung Huang, Chien-Ling Lin. Massively Parallel Polyribosome Profiling Reveals Translation Defects of Human Disease-Relevant UTR Mutations. 2025-09-16. https://doi.org/10.7554/eLife.98814.2

Experiments 1

E4ODS2XWT

HEK293T pooled 5′/3′ UTR massively parallel polyribosome profiling

A pooled episomal CMV-EGFP reporter library containing 6,555 matched wild-type/mutant human UTR variant pairs was transiently transfected into HEK293T cells. Three dated biological batches were fractionated into MS/monosome, PSL/light-polysome, and PSH/heavy-polysome RNA, which was quantified by targeted amplicon sequencing.

5' UTR / Translation Efficiency MPRA (MPTA)HumanGRCh38
Explore data

Raw source data 11 files

Original supplemental and deposited inputs retained for this study. Download files individually or together as a ZIP; nested folders are preserved. Source reuse terms apply, and sequencing reads may be omitted.

Download all 11 files (ZIP)GSE229492_polysome_3UTR_counts.csvGSE229492_polysome_5UTR_counts.csvGSE229492_utr_pair_map.csvREADME.txtsupplemental_information.pdfSupplemental_Table_S1_primers.xlsxSupplemental_Table_S2_classifications.csvSupplemental_Table_S3_HC_sig_variant_annotations.csvSupplemental_Table_S4_motif_enrichment.csvSupplemental_Table_S5_elastic_net_coefficients.xlsxSupplemental_Table_S6_uATG_luciferase.xlsx

Cite OpenMPRA

Cite the OpenMPRA database. Include your access date because the collection changes over time.

Please also cite the source studies when using their data.