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NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases

NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases
NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases
Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50–$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.
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Nalls, Mike A.
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Bras, Jose
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Bertram, Lars
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Wood, Nick
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Morrison, Karen
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Nalls, Mike A.
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Plagnol, Vincent
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Sutherland, Margaret
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Bertram, Lars
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Pliner, Hannah
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Heutink, Peter
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Martinez, Maria
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Gasser, Thomas
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Traynor, Bryan J.
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Wood, Nick
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Hardy, John
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Singleton, Andrew B.
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Morrison, Karen
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Nalls, Mike A., Bras, Jose and Hernandez, Dena G. et al. (2015) NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases. Neurobiology of Aging, 36 (3), 1605.e7-1605.e12. (doi:10.1016/j.neurobiolaging.2014.07.028). (PMID:25444595)

Record type: Article

Abstract

Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50–$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.

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More information

Accepted/In Press date: 23 July 2014
Published date: March 2015
Organisations: Medical Education

Identifiers

Local EPrints ID: 398181
URI: http://eprints.soton.ac.uk/id/eprint/398181
PURE UUID: aac1755b-f87e-4988-82c4-61d5f9daf062
ORCID for Karen Morrison: ORCID iD orcid.org/0000-0003-0216-5717

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Date deposited: 20 Jul 2016 13:31
Last modified: 26 Nov 2019 01:32

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Contributors

Author: Mike A. Nalls
Author: Jose Bras
Author: Dena G. Hernandez
Author: Margaux F. Keller
Author: Elisa Majounie
Author: Alan E. Renton
Author: Mohamad Saad
Author: Iris Jansen
Author: Rita Guerreiro
Author: Steven Lubbe
Author: Vincent Plagnol
Author: J. Raphael Gibbs
Author: Claudia Schulte
Author: Nathan Pankratz
Author: Margaret Sutherland
Author: Lars Bertram
Author: Christina M. Lill
Author: Anita L. DeStefano
Author: Tatiana Faroud
Author: Nicholas Eriksson
Author: Joyce Y. Tung
Author: Connor Edsall
Author: Noah Nichols
Author: Janet Brooks
Author: Sampath Arepalli
Author: Hannah Pliner
Author: Chris Letson
Author: Peter Heutink
Author: Maria Martinez
Author: Thomas Gasser
Author: Bryan J. Traynor
Author: Nick Wood
Author: John Hardy
Author: Andrew B. Singleton
Author: Karen Morrison ORCID iD

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