Literature DB >> 18551557

Successful amplification of degraded DNA for use with high-throughput SNP genotyping platforms.

Simon Mead1, Mark Poulter, John Beck, James Uphill, Chris Jones, Cheng Eng Ang, Charles A Mein, John Collinge.   

Abstract

Highly accurate and high-throughput SNP genotyping platforms are increasingly popular but the performance of suboptimal DNA samples remains unclear. The aim of our study was to determine the best platform, amplification technique, and loading concentration to maximize genotype accuracy and call rate using degraded samples. We amplified high-molecular weight genomic DNA samples recently extracted from whole blood and degraded DNA samples extracted from 50-year-old patient sera. Two whole-genome amplification (WGA) methodologies were used: an isothermal multiple displacement amplification method (MDA) and a fragmentation-PCR-based method (GenomePlex [GPLEX]; Sigma-Aldrich, St. Louis, MO). Duplicate runs were performed on genome-wide dense SNP arrays (Nsp-Mendel; Affymetrix) and custom SNP platforms based on molecular inversion probes (Targeted Genotyping [TG]; Affymetrix) and BeadArray technology (Golden Gate [GG]; Illumina). Miscalls and no-calls on Mendel arrays were correlated with each other, with confidence scores from the Bayesian calling algorithm, and with average probe intensity. Degraded DNA amplified with MDA gave low call rates and concordance across all platforms at standard loading concentrations. The call rate with MDA on GG was improved when a 5 x concentration of amplified DNA was used. The GPLEX amplification gave high call rate and concordance for degraded DNA at standard and higher loading concentrations on both TG and GG platforms. Based on these analyses, after standard filtering for SNP and sample performance, we were able to achieve a mean call rate of 99.7% and concordance 99.7% using degraded samples amplified by GPLEX on GG technology at 2 x loading concentration. These findings may be useful for investigators planning case-control association studies with patient samples of suboptimal quality.

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Year:  2008        PMID: 18551557     DOI: 10.1002/humu.20782

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  8 in total

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2.  Assessing the utility of whole-genome amplified serum DNA for array-based high throughput genotyping.

Authors:  Kristine L Bucasas; Gagan A Pandya; Sonal Pradhan; Robert D Fleischmann; Scott N Peterson; John W Belmont
Journal:  BMC Genet       Date:  2009-12-18       Impact factor: 2.797

3.  Whole-genome amplification enables accurate genotyping for microarray-based high-density single nucleotide polymorphism array.

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Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-12       Impact factor: 4.254

4.  Copy number and loss of heterozygosity detected by SNP array of formalin-fixed tissues using whole-genome amplification.

Authors:  Angela Stokes; Ignat Drozdov; Eliete Guerra; Christos A Ouzounis; Saman Warnakulasuriya; Michael J Gleeson; Mark McGurk; Mahvash Tavassoli; Edward W Odell
Journal:  PLoS One       Date:  2011-09-26       Impact factor: 3.240

5.  Genetic variation in cell death genes and risk of non-Hodgkin lymphoma.

Authors:  Johanna M Schuetz; Denise Daley; Jinko Graham; Brian R Berry; Richard P Gallagher; Joseph M Connors; Randy D Gascoyne; John J Spinelli; Angela R Brooks-Wilson
Journal:  PLoS One       Date:  2012-02-07       Impact factor: 3.240

6.  Genotyping of Single Nucleotide Polymorphisms in DNA Isolated from Serum Using Sequenom MassARRAY Technology.

Authors:  Tess V Clendenen; Justin Rendleman; Wenzhen Ge; Karen L Koenig; Isaac Wirgin; Diane Currie; Roy E Shore; Tomas Kirchhoff; Anne Zeleniuch-Jacquotte
Journal:  PLoS One       Date:  2015-08-14       Impact factor: 3.240

7.  Genetic risk factors for variant Creutzfeldt-Jakob disease: a genome-wide association study.

Authors:  Simon Mead; Mark Poulter; James Uphill; John Beck; Jerome Whitfield; Thomas E F Webb; Tracy Campbell; Gary Adamson; Pelagia Deriziotis; Sarah J Tabrizi; Holger Hummerich; Claudio Verzilli; Michael P Alpers; John C Whittaker; John Collinge
Journal:  Lancet Neurol       Date:  2009-01       Impact factor: 44.182

8.  Caught in the middle with multiple displacement amplification: the myth of pooling for avoiding multiple displacement amplification bias in a metagenome.

Authors:  Rachel Marine; Coleen McCarren; Vansay Vorrasane; Dan Nasko; Erin Crowgey; Shawn W Polson; K Eric Wommack
Journal:  Microbiome       Date:  2014-01-30       Impact factor: 14.650

  8 in total

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