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Hidden protein-altering variants influence diverse human phenotypes

Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-alt...

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Autores principales: Hujoel, Margaux L.A., Handsaker, Robert E., Sherman, Maxwell A., Kamitaki, Nolan, Barton, Alison R., Mukamel, Ronen E., Terao, Chikashi, McCarroll, Steven A., Loh, Po-Ru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274781/
https://www.ncbi.nlm.nih.gov/pubmed/37333244
http://dx.doi.org/10.1101/2023.06.07.544066
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author Hujoel, Margaux L.A.
Handsaker, Robert E.
Sherman, Maxwell A.
Kamitaki, Nolan
Barton, Alison R.
Mukamel, Ronen E.
Terao, Chikashi
McCarroll, Steven A.
Loh, Po-Ru
author_facet Hujoel, Margaux L.A.
Handsaker, Robert E.
Sherman, Maxwell A.
Kamitaki, Nolan
Barton, Alison R.
Mukamel, Ronen E.
Terao, Chikashi
McCarroll, Steven A.
Loh, Po-Ru
author_sort Hujoel, Margaux L.A.
collection PubMed
description Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-altering SVs from UK Biobank whole-exome sequencing data (n=468,570) using haplotype-informed methods capable of detecting sub-exonic SVs and variation within segmental duplications. Incorporating SVs into analyses of rare variants predicted to cause gene loss-of-function (pLoF) identified 100 associations of pLoF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 appeared to confer one of the strongest protective effects of gene LoF on hypertension risk (OR = 0.86 [0.82–0.90]). Protein-coding variation in rapidly-evolving gene families within segmental duplications—previously invisible to most analysis methods—appeared to generate some of the human genome’s largest contributions to variation in type 2 diabetes risk, chronotype, and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.
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spelling pubmed-102747812023-06-17 Hidden protein-altering variants influence diverse human phenotypes Hujoel, Margaux L.A. Handsaker, Robert E. Sherman, Maxwell A. Kamitaki, Nolan Barton, Alison R. Mukamel, Ronen E. Terao, Chikashi McCarroll, Steven A. Loh, Po-Ru bioRxiv Article Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-altering SVs from UK Biobank whole-exome sequencing data (n=468,570) using haplotype-informed methods capable of detecting sub-exonic SVs and variation within segmental duplications. Incorporating SVs into analyses of rare variants predicted to cause gene loss-of-function (pLoF) identified 100 associations of pLoF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 appeared to confer one of the strongest protective effects of gene LoF on hypertension risk (OR = 0.86 [0.82–0.90]). Protein-coding variation in rapidly-evolving gene families within segmental duplications—previously invisible to most analysis methods—appeared to generate some of the human genome’s largest contributions to variation in type 2 diabetes risk, chronotype, and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date. Cold Spring Harbor Laboratory 2023-06-09 /pmc/articles/PMC10274781/ /pubmed/37333244 http://dx.doi.org/10.1101/2023.06.07.544066 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Hujoel, Margaux L.A.
Handsaker, Robert E.
Sherman, Maxwell A.
Kamitaki, Nolan
Barton, Alison R.
Mukamel, Ronen E.
Terao, Chikashi
McCarroll, Steven A.
Loh, Po-Ru
Hidden protein-altering variants influence diverse human phenotypes
title Hidden protein-altering variants influence diverse human phenotypes
title_full Hidden protein-altering variants influence diverse human phenotypes
title_fullStr Hidden protein-altering variants influence diverse human phenotypes
title_full_unstemmed Hidden protein-altering variants influence diverse human phenotypes
title_short Hidden protein-altering variants influence diverse human phenotypes
title_sort hidden protein-altering variants influence diverse human phenotypes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274781/
https://www.ncbi.nlm.nih.gov/pubmed/37333244
http://dx.doi.org/10.1101/2023.06.07.544066
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