Characterising the loss-of-function impact of 5’ untranslated region variants in 15,708 individuals

Genome Aggregation Database Production Team, Genome Aggregation Database Consortium, Nicola Whiffin, Konrad J. Karczewski, Xiaolei Zhang, Sonia Chothani, Miriam J. Smith, D. Gareth Evans, Angharad M. Roberts, Nicholas M. Quaife, Sebastian Schafer, Owen Rackham, Jessica Alföldi, Anne H. O’Donnell-Luria, Laurent C. Francioli, Irina M. Armean, Eric Banks, Louis Bergelson, Kristian Cibulskis, Ryan L. CollinsKristen M. Connolly, Miguel Covarrubias, Beryl Cummings, Mark J. Daly, Stacey Donnelly, Yossi Farjoun, Steven Ferriera, Stacey Gabriel, Laura D. Gauthier, Jeff Gentry, Namrata Gupta, Thibault Jeandet, Diane Kaplan, Kristen M. Laricchia, Christopher Llanwarne, Eric V. Minikel, Ruchi Munshi, Benjamin M. Neale, Sam Novod, Nikelle Petrillo, Timothy Poterba, David Roazen, Valentin Ruano-Rubio, Andrea Saltzman, Kaitlin E. Samocha, Molly Schleicher, Cotton Seed, Matthew Solomonson, Jose Soto, Terho Lehtimäki, Kari M. Mattila, Jaana Suvisaari

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)


Upstream open reading frames (uORFs) are tissue-specific cis-regulators of protein translation. Isolated reports have shown that variants that create or disrupt uORFs can cause disease. Here, in a systematic genome-wide study using 15,708 whole genome sequences, we show that variants that create new upstream start codons, and variants disrupting stop sites of existing uORFs, are under strong negative selection. This selection signal is significantly stronger for variants arising upstream of genes intolerant to loss-of-function variants. Furthermore, variants creating uORFs that overlap the coding sequence show signals of selection equivalent to coding missense variants. Finally, we identify specific genes where modification of uORFs likely represents an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in neurofibromatosis. Our results highlight uORF-perturbing variants as an under-recognised functional class that contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data in studying non-coding variant classes.

Original languageEnglish
Article number2523
JournalNature Communications
Issue number1
Publication statusPublished - May 2020
Publication typeA1 Journal article-refereed

Publication forum classification

  • Publication forum level 3

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)


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