Literature DB >> 21424828

The efficacy of detecting variants with small effects on the Affymetrix 6.0 platform using pooled DNA.

Charleston W K Chiang1, Zofia K Z Gajdos, Joshua M Korn, Johannah L Butler, Rachel Hackett, Candace Guiducci, Thutrang T Nguyen, Rainford Wilks, Terrence Forrester, Katherine D Henderson, Loic Le Marchand, Brian E Henderson, Christopher A Haiman, Richard S Cooper, Helen N Lyon, Xiaofeng Zhu, Colin A McKenzie, Mark R Palmert, Joel N Hirschhorn.   

Abstract

Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.

Entities:  

Mesh:

Year:  2011        PMID: 21424828      PMCID: PMC3474315          DOI: 10.1007/s00439-011-0974-0

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


  38 in total

1.  Simple method to analyze SNP-based association studies using DNA pools.

Authors:  Peter M Visscher; Stéphanie Le Hellard
Journal:  Genet Epidemiol       Date:  2003-05       Impact factor: 2.135

2.  SNPs, microarrays and pooled DNA: identification of four loci associated with mild mental impairment in a sample of 6000 children.

Authors:  Lee M Butcher; Emma Meaburn; Jo Knight; Pak C Sham; Leonard C Schalkwyk; Ian W Craig; Robert Plomin
Journal:  Hum Mol Genet       Date:  2005-03-30       Impact factor: 6.150

3.  Two-stage designs in case-control association analysis.

Authors:  Yijun Zuo; Guohua Zou; Hongyu Zhao
Journal:  Genetics       Date:  2006-04-19       Impact factor: 4.562

4.  Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies.

Authors:  Andrew D Skol; Laura J Scott; Gonçalo R Abecasis; Michael Boehnke
Journal:  Nat Genet       Date:  2006-01-15       Impact factor: 38.330

5.  The prevalence of hypertension in seven populations of west African origin.

Authors:  R Cooper; C Rotimi; S Ataman; D McGee; B Osotimehin; S Kadiri; W Muna; S Kingue; H Fraser; T Forrester; F Bennett; R Wilks
Journal:  Am J Public Health       Date:  1997-02       Impact factor: 9.308

6.  Common Kibra alleles are associated with human memory performance.

Authors:  Andreas Papassotiropoulos; Dietrich A Stephan; Matthew J Huentelman; Frederic J Hoerndli; David W Craig; John V Pearson; Kim-Dung Huynh; Fabienne Brunner; Jason Corneveaux; David Osborne; M Axel Wollmer; Amanda Aerni; Daniel Coluccia; Jürgen Hänggi; Christian R A Mondadori; Andreas Buchmann; Eric M Reiman; Richard J Caselli; Katharina Henke; Dominique J-F de Quervain
Journal:  Science       Date:  2006-10-20       Impact factor: 47.728

7.  Chip-based genotyping by mass spectrometry.

Authors:  K Tang; D J Fu; D Julien; A Braun; C R Cantor; H Köster
Journal:  Proc Natl Acad Sci U S A       Date:  1999-08-31       Impact factor: 11.205

8.  A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics.

Authors:  L N Kolonel; B E Henderson; J H Hankin; A M Nomura; L R Wilkens; M C Pike; D O Stram; K R Monroe; M E Earle; F S Nagamine
Journal:  Am J Epidemiol       Date:  2000-02-15       Impact factor: 4.897

9.  A three-stage genome-wide association study of general cognitive ability: hunting the small effects.

Authors:  Oliver S P Davis; Lee M Butcher; Sophia J Docherty; Emma L Meaburn; Charles J C Curtis; Michael A Simpson; Leonard C Schalkwyk; Robert Plomin
Journal:  Behav Genet       Date:  2010-03-21       Impact factor: 2.805

10.  Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans.

Authors:  Emma Meaburn; Lee M Butcher; Leonard C Schalkwyk; Robert Plomin
Journal:  Nucleic Acids Res       Date:  2006-02-14       Impact factor: 16.971

View more
  2 in total

1.  Comparison of genotyping using pooled DNA samples (allelotyping) and individual genotyping using the affymetrix genome-wide human SNP array 6.0.

Authors:  Alexander Teumer; Florian D Ernst; Anja Wiechert; Katharina Uhr; Matthias Nauck; Astrid Petersmann; Henry Völzke; Uwe Völker; Georg Homuth
Journal:  BMC Genomics       Date:  2013-07-26       Impact factor: 3.969

2.  A permutation test for oligoset DNA pooling studies.

Authors:  Hsiao-Yuan Huang; Jui-Hsiang Lin; Wen-Chung Lee
Journal:  PLoS One       Date:  2015-03-12       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.