title: Multiplex pyrosequencing assay using AdvISER-MH-PYRO algorithm: a case for rapid and cost-effective genotyping analysis of prostate cancer risk-associated SNPs.
abstract: BACKGROUND
  Single Nucleotide Polymorphisms (SNPs) identified in Genome Wide Association Studies (GWAS) have generally moderate association with related complex diseases. Accordingly, Multilocus Genetic Risk Scores (MGRSs) have been computed in previous studies in order to assess the cumulative association of multiple SNPs. When several SNPs have to be genotyped for each patient, using successive uniplex pyrosequencing reactions increases analytical reagent expenses and Turnaround Time (TAT). While a set of several pyrosequencing primers could theoretically be used to analyze multiplex amplicons, this would generate overlapping primer-specific pyro-signals that are visually uninterpretable.
  
  
  METHODS
  In the current study, two multiplex assays were developed consisting of a quadruplex (n=4) and a quintuplex (n=5) polymerase chain reaction (PCR) each followed by multiplex pyrosequencing analysis. The aim was to reliably but rapidly genotype a set of prostate cancer-related SNPs (n=9). The nucleotide dispensation order was selected using SENATOR software. Multiplex pyro-signals were analyzed using the new AdvISER-MH-PYRO software based on a sparse representation of the signal. Using uniplex assays as gold standard, the concordance between multiplex and uniplex assays was assessed on DNA extracted from patient blood samples (n = 10).
  
  
  RESULTS
  All genotypes (n=90) generated with the quadruplex and the quintuplex pyroquencing assays were perfectly (100 %) concordant with uniplex pyrosequencing. Using multiplex genotyping approach for analyzing a set of 90 patients allowed reducing TAT by approximately 75 % (i.e., from 2025 to 470 min) while reducing reagent consumption and cost by approximately 70 % (i.e., from ~229 US$ /patient to ~64 US$ /patient).
  
  
  CONCLUSIONS
  This combination of quadruplex and quintuplex pyrosequencing and PCR assays enabled to reduce the amount of DNA required for multi-SNP analysis, and to lower the global TAT and costs of SNP genotyping while providing results as reliable as uniplex analysis. Using this combined multiplex approach also substantially reduced the production of waste material. These genotyping assays appear therefore to be biologically, economically and ecologically highly relevant, being worth to be integrated in genetic-based predictive strategies for better selecting patients at risk for prostate cancer. In addition, the same approach could now equally be transposed to other clinical/research applications relying on the computation of MGRS based on multi-SNP genotyping.
authors.affiliation: Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expérimentale et Clinique (IREC), Université catholique de Louvain, Clos chapelle-aux-champs B1.30.24, Brussels, 1200, Belgium.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Ambroise
authors.affiliation: Service d'Urologie, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, 1200, Belgium.
authors.forename: Valentina
authors.initials: V
authors.lastname: Butoescu
authors.affiliation: Epidemiology and Biostatistics Department (EPID), Institut de Recherche Expérimentale et Clinique (IREC), Université catholique de Louvain, Brussels, 1200, Belgium. annie.robert@uclouvain.be.
authors.forename: Annie
authors.initials: A
authors.lastname: Robert
authors.affiliation: Service d'Urologie, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, 1200, Belgium. bertrand.tombal@uclouvain.be.
authors.forename: Bertrand
authors.initials: B
authors.lastname: Tombal
authors.affiliation: Center for Applied Molecular Technologies (CTMA), Institut de Recherche Expérimentale et Clinique (IREC), Université catholique de Louvain, Clos chapelle-aux-champs B1.30.24, Brussels, 1200, Belgium. jean-luc.gala@uclouvain.be.
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Gala
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D003362:Cost-Benefit Analysis; D004252:DNA Mutational Analysis / Q000191:economics / Q000379:methods; D020022:Genetic Predisposition to Disease; D060005:Genotyping Techniques / Q000191:economics / Q000379:methods*; D006801:Humans; D008297:Male; D060885:Multiplex Polymerase Chain Reaction / Q000191:economics / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D011471:Prostatic Neoplasms / Q000235:genetics*; D015203:Reproducibility of Results