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

Genome Aggregation Database Production Team; Genome Aggregation Database Consortium

doi:10.1038/s41467-019-10717-9

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

Genome Aggregation Database Production Team, Genome Aggregation Database Consortium

Department of Human Biology

Research output: Contribution to journal › Article › peer-review

Abstract

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 language	English
Article number	2523
Journal	Nature Communications
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41467-019-10717-9
State	Published - 27 May 2020

Bibliographical note

Funding Information:
N.W. is supported by a Rosetrees and Stoneygate Imperial College Research Fellowship. This work was supported by the Wellcome Trust (107469/Z/15/Z), the Medical Research Council (UK), the NIHR Biomedical Research Unit in Cardiovascular Disease at Royal Brompton and Harefield NHS Foundation Trust and Imperial College London, the NIHR Imperial College Biomedical Research Centre, the Fondation Leducq (11 CVD-01), a Health Innovation Challenge Fund award from the Wellcome Trust and Department of Health, UK (HICF-R6–373), and by NIDDK U54DK105566 and NIGMS R01GM104371. D.G.E. and M.J.S. are funded by the NIHR Biomedical research centre Manchester (IS-BRC-1215-20007). L.C.F. is supported by the Swiss National Science Foundation (Advanced Postdoc.Mobility 177853). N.Q. is supported by the Imperial College Academic Health Science Centre. The results published here are in part based upon data: (1) generated by The Cancer Genome Atlas managed by the NCI and NHGRI (accession: phs000178.v10.p8). Information about TCGA can be found at http:// cancergenome.nih.gov, (2) generated by the Genotype-Tissue Expression Project (GTEx) managed by the NIH Common Fund and NHGRI (accession: phs000424.v7.p2), (3) generated by the Exome Sequencing Project, managed by NHLBI, (4) generated by the Alzheimer’s Disease Sequencing Project (ADSP), managed by the NIA and NHGRI (accession: phs000572.v7.p4). The views expressed in this work are those of the authors and not necessarily those of any of the funders. We would like to thank Dr. Christopher M Yates for his statistical advice.

Publisher Copyright:
© 2020, The Author(s).

ASJC Scopus subject areas

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-019-10717-9

Cite this

@article{7c563b8f830f4091abbb121384340ca4,

title = "Characterising the loss-of-function impact of 5{\textquoteright} untranslated region variants in 15,708 individuals",

abstract = "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.",

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

note = "Funding Information: N.W. is supported by a Rosetrees and Stoneygate Imperial College Research Fellowship. This work was supported by the Wellcome Trust (107469/Z/15/Z), the Medical Research Council (UK), the NIHR Biomedical Research Unit in Cardiovascular Disease at Royal Brompton and Harefield NHS Foundation Trust and Imperial College London, the NIHR Imperial College Biomedical Research Centre, the Fondation Leducq (11 CVD-01), a Health Innovation Challenge Fund award from the Wellcome Trust and Department of Health, UK (HICF-R6–373), and by NIDDK U54DK105566 and NIGMS R01GM104371. D.G.E. and M.J.S. are funded by the NIHR Biomedical research centre Manchester (IS-BRC-1215-20007). L.C.F. is supported by the Swiss National Science Foundation (Advanced Postdoc.Mobility 177853). N.Q. is supported by the Imperial College Academic Health Science Centre. The results published here are in part based upon data: (1) generated by The Cancer Genome Atlas managed by the NCI and NHGRI (accession: phs000178.v10.p8). Information about TCGA can be found at http:// cancergenome.nih.gov, (2) generated by the Genotype-Tissue Expression Project (GTEx) managed by the NIH Common Fund and NHGRI (accession: phs000424.v7.p2), (3) generated by the Exome Sequencing Project, managed by NHLBI, (4) generated by the Alzheimer{\textquoteright}s Disease Sequencing Project (ADSP), managed by the NIA and NHGRI (accession: phs000572.v7.p4). The views expressed in this work are those of the authors and not necessarily those of any of the funders. We would like to thank Dr. Christopher M Yates for his statistical advice. Publisher Copyright: {\textcopyright} 2020, The Author(s).",

year = "2020",

month = may,

day = "27",

doi = "10.1038/s41467-019-10717-9",

language = "English",

volume = "11",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

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TY - JOUR

T1 - Characterising the loss-of-function impact of 5’ untranslated region variants in 15,708 individuals

AU - Genome Aggregation Database Production Team

AU - Genome Aggregation Database Consortium

AU - Whiffin, Nicola

AU - Karczewski, Konrad J.

AU - Zhang, Xiaolei

AU - Chothani, Sonia

AU - Smith, Miriam J.

AU - Evans, D. Gareth

AU - Roberts, Angharad M.

AU - Quaife, Nicholas M.

AU - Schafer, Sebastian

AU - Rackham, Owen

AU - Alföldi, Jessica

AU - O’Donnell-Luria, Anne H.

AU - Francioli, Laurent C.

AU - Armean, Irina M.

AU - Banks, Eric

AU - Bergelson, Louis

AU - Cibulskis, Kristian

AU - Collins, Ryan L.

AU - Connolly, Kristen M.

AU - Covarrubias, Miguel

AU - Cummings, Beryl

AU - Daly, Mark J.

AU - Donnelly, Stacey

AU - Farjoun, Yossi

AU - Ferriera, Steven

AU - Gabriel, Stacey

AU - Gauthier, Laura D.

AU - Gentry, Jeff

AU - Gupta, Namrata

AU - Jeandet, Thibault

AU - Kaplan, Diane

AU - Laricchia, Kristen M.

AU - Llanwarne, Christopher

AU - Minikel, Eric V.

AU - Munshi, Ruchi

AU - Neale, Benjamin M.

AU - Novod, Sam

AU - Petrillo, Nikelle

AU - Poterba, Timothy

AU - Roazen, David

AU - Ruano-Rubio, Valentin

AU - Saltzman, Andrea

AU - Samocha, Kaitlin E.

AU - Schleicher, Molly

AU - Seed, Cotton

AU - Solomonson, Matthew

AU - Soto, Jose

AU - Tiao, Grace

AU - Tibbetts, Kathleen

AU - Atzmon, Gil

N1 - Funding Information: N.W. is supported by a Rosetrees and Stoneygate Imperial College Research Fellowship. This work was supported by the Wellcome Trust (107469/Z/15/Z), the Medical Research Council (UK), the NIHR Biomedical Research Unit in Cardiovascular Disease at Royal Brompton and Harefield NHS Foundation Trust and Imperial College London, the NIHR Imperial College Biomedical Research Centre, the Fondation Leducq (11 CVD-01), a Health Innovation Challenge Fund award from the Wellcome Trust and Department of Health, UK (HICF-R6–373), and by NIDDK U54DK105566 and NIGMS R01GM104371. D.G.E. and M.J.S. are funded by the NIHR Biomedical research centre Manchester (IS-BRC-1215-20007). L.C.F. is supported by the Swiss National Science Foundation (Advanced Postdoc.Mobility 177853). N.Q. is supported by the Imperial College Academic Health Science Centre. The results published here are in part based upon data: (1) generated by The Cancer Genome Atlas managed by the NCI and NHGRI (accession: phs000178.v10.p8). Information about TCGA can be found at http:// cancergenome.nih.gov, (2) generated by the Genotype-Tissue Expression Project (GTEx) managed by the NIH Common Fund and NHGRI (accession: phs000424.v7.p2), (3) generated by the Exome Sequencing Project, managed by NHLBI, (4) generated by the Alzheimer’s Disease Sequencing Project (ADSP), managed by the NIA and NHGRI (accession: phs000572.v7.p4). The views expressed in this work are those of the authors and not necessarily those of any of the funders. We would like to thank Dr. Christopher M Yates for his statistical advice. Publisher Copyright: © 2020, The Author(s).

PY - 2020/5/27

Y1 - 2020/5/27

N2 - 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.

AB - 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.

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DO - 10.1038/s41467-019-10717-9

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SN - 2041-1723

VL - 11

JO - Nature Communications

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

Abstract

Bibliographical note

ASJC Scopus subject areas

UN SDGs

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