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Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic a... Full description

Journal Title: The American Journal of Human Genetics 01 June 2017, Vol.100(6), pp.865-884
Main Author: Tachmazidou, Ioanna
Other Authors: Süveges, Dániel , Min, Josine L , Ritchie, Graham R.S , Steinberg, Julia , Walter, Klaudia , Iotchkova, Valentina , Schwartzentruber, Jeremy , Huang, Jie , Memari, Yasin , Mccarthy, Shane , Crawford, Andrew A , Bombieri, Cristina , Cocca, Massimiliano , Farmaki, Aliki-Eleni , Gaunt, Tom R , Jousilahti, Pekka , Kooijman, Marjolein N
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 0002-9297 ; E-ISSN: 1537-6605 ; DOI: 10.1016/j.ajhg.2017.04.014
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recordid: elsevier_sdoi_10_1016_j_ajhg_2017_04_014
title: Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits
format: Article
creator:
  • Tachmazidou, Ioanna
  • Süveges, Dániel
  • Min, Josine L
  • Ritchie, Graham R.S
  • Steinberg, Julia
  • Walter, Klaudia
  • Iotchkova, Valentina
  • Schwartzentruber, Jeremy
  • Huang, Jie
  • Memari, Yasin
  • Mccarthy, Shane
  • Crawford, Andrew A
  • Bombieri, Cristina
  • Cocca, Massimiliano
  • Farmaki, Aliki-Eleni
  • Gaunt, Tom R
  • Jousilahti, Pekka
  • Kooijman, Marjolein N
subjects:
  • Uk10k
  • Genetic Association Study
  • Next-Generation Whole-Genome Sequencing
  • Imputation
  • UK Biobank
  • Anthropometry
  • Dxa Traits
  • Biology
ispartof: The American Journal of Human Genetics, 01 June 2017, Vol.100(6), pp.865-884
description: Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and...
language: eng
source:
identifier: ISSN: 0002-9297 ; E-ISSN: 1537-6605 ; DOI: 10.1016/j.ajhg.2017.04.014
fulltext: fulltext
issn:
  • 0002-9297
  • 00029297
  • 1537-6605
  • 15376605
url: Link


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titleWhole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits
creatorTachmazidou, Ioanna ; Süveges, Dániel ; Min, Josine L ; Ritchie, Graham R.S ; Steinberg, Julia ; Walter, Klaudia ; Iotchkova, Valentina ; Schwartzentruber, Jeremy ; Huang, Jie ; Memari, Yasin ; Mccarthy, Shane ; Crawford, Andrew A ; Bombieri, Cristina ; Cocca, Massimiliano ; Farmaki, Aliki-Eleni ; Gaunt, Tom R ; Jousilahti, Pekka ; Kooijman, Marjolein N
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descriptionDeep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and...
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Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and...

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Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and...

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lad01The American Journal of Human Genetics
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date2017-06-01