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Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits

Next-generation association studies can be empowered by sequence-based imputation and by studying founder populations. Here we report ∼9.5 million variants from whole-genome sequencing (WGS) of a Cretan-isolated population, and show enrichment of rare and low-frequency variants with predicted functi...

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Autores principales: Southam, Lorraine, Gilly, Arthur, Süveges, Dániel, Farmaki, Aliki-Eleni, Schwartzentruber, Jeremy, Tachmazidou, Ioanna, Matchan, Angela, Rayner, Nigel W., Tsafantakis, Emmanouil, Karaleftheri, Maria, Xue, Yali, Dedoussis, George, Zeggini, Eleftheria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5458552/
https://www.ncbi.nlm.nih.gov/pubmed/28548082
http://dx.doi.org/10.1038/ncomms15606
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author Southam, Lorraine
Gilly, Arthur
Süveges, Dániel
Farmaki, Aliki-Eleni
Schwartzentruber, Jeremy
Tachmazidou, Ioanna
Matchan, Angela
Rayner, Nigel W.
Tsafantakis, Emmanouil
Karaleftheri, Maria
Xue, Yali
Dedoussis, George
Zeggini, Eleftheria
author_facet Southam, Lorraine
Gilly, Arthur
Süveges, Dániel
Farmaki, Aliki-Eleni
Schwartzentruber, Jeremy
Tachmazidou, Ioanna
Matchan, Angela
Rayner, Nigel W.
Tsafantakis, Emmanouil
Karaleftheri, Maria
Xue, Yali
Dedoussis, George
Zeggini, Eleftheria
author_sort Southam, Lorraine
collection PubMed
description Next-generation association studies can be empowered by sequence-based imputation and by studying founder populations. Here we report ∼9.5 million variants from whole-genome sequencing (WGS) of a Cretan-isolated population, and show enrichment of rare and low-frequency variants with predicted functional consequences. We use a WGS-based imputation approach utilizing 10,422 reference haplotypes to perform genome-wide association analyses and observe 17 genome-wide significant, independent signals, including replicating evidence for association at eight novel low-frequency variant signals. Two novel cardiometabolic associations are at lead variants unique to the founder population sequences: chr16:70790626 (high-density lipoprotein levels beta −1.71 (SE 0.25), P=1.57 × 10(−11), effect allele frequency (EAF) 0.006); and rs145556679 (triglycerides levels beta −1.13 (SE 0.17), P=2.53 × 10(−11), EAF 0.013). Our findings add empirical support to the contribution of low-frequency variants in complex traits, demonstrate the advantage of including population-specific sequences in imputation panels and exemplify the power gains afforded by population isolates.
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spelling pubmed-54585522017-07-11 Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits Southam, Lorraine Gilly, Arthur Süveges, Dániel Farmaki, Aliki-Eleni Schwartzentruber, Jeremy Tachmazidou, Ioanna Matchan, Angela Rayner, Nigel W. Tsafantakis, Emmanouil Karaleftheri, Maria Xue, Yali Dedoussis, George Zeggini, Eleftheria Nat Commun Article Next-generation association studies can be empowered by sequence-based imputation and by studying founder populations. Here we report ∼9.5 million variants from whole-genome sequencing (WGS) of a Cretan-isolated population, and show enrichment of rare and low-frequency variants with predicted functional consequences. We use a WGS-based imputation approach utilizing 10,422 reference haplotypes to perform genome-wide association analyses and observe 17 genome-wide significant, independent signals, including replicating evidence for association at eight novel low-frequency variant signals. Two novel cardiometabolic associations are at lead variants unique to the founder population sequences: chr16:70790626 (high-density lipoprotein levels beta −1.71 (SE 0.25), P=1.57 × 10(−11), effect allele frequency (EAF) 0.006); and rs145556679 (triglycerides levels beta −1.13 (SE 0.17), P=2.53 × 10(−11), EAF 0.013). Our findings add empirical support to the contribution of low-frequency variants in complex traits, demonstrate the advantage of including population-specific sequences in imputation panels and exemplify the power gains afforded by population isolates. Nature Publishing Group 2017-05-26 /pmc/articles/PMC5458552/ /pubmed/28548082 http://dx.doi.org/10.1038/ncomms15606 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Southam, Lorraine
Gilly, Arthur
Süveges, Dániel
Farmaki, Aliki-Eleni
Schwartzentruber, Jeremy
Tachmazidou, Ioanna
Matchan, Angela
Rayner, Nigel W.
Tsafantakis, Emmanouil
Karaleftheri, Maria
Xue, Yali
Dedoussis, George
Zeggini, Eleftheria
Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
title Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
title_full Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
title_fullStr Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
title_full_unstemmed Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
title_short Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
title_sort whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5458552/
https://www.ncbi.nlm.nih.gov/pubmed/28548082
http://dx.doi.org/10.1038/ncomms15606
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