Locked nucleic acid (LNA) single nucleotide polymorphism (SNP) genotype analysis and validation using real-time PCR

Loading...
Thumbnail Image
File version
Author(s)
Johnson, Matthew
Haupt, Larisa
Griffiths, Lyn
Primary Supervisor
Other Supervisors
Editor(s)
Date
2004
Size

238176 bytes

46350 bytes

File type(s)

application/pdf

text/plain

Location
Abstract

With an increased emphasis on genotyping of single nucleotide polymorphisms (SNPs) in disease association studies, the genotyping platform of choice is constantly evolving. In addition, the development of more specific SNP assays and appropriate genotype validation applications is becoming increasingly critical to elucidate ambiguous genotypes. In this study, we have used SNP specific Locked Nucleic Acid (LNA) hybridization probes on a real-time PCR platform to genotype an association cohort and propose three criteria to address ambiguous genotypes. Based on the kinetic properties of PCR amplification, the three criteria address PCR amplification efficiency, the net fluorescent difference between maximal and minimal fluorescent signals and the beginning of the exponential growth phase of the reaction. Initially observed SNP allelic discrimination curves were confirmed by DNA sequencing (n = 50) and application of our three genotype criteria corroborated both sequencing and observed real-time PCR results. In addition, the tested Caucasian association cohort was in Hardy-Weinberg equilibrium and observed allele frequencies were very similar to two independently tested Caucasian association cohorts for the same tested SNP. We present here a novel approach to effectively determine ambiguous genotypes generated from a real-time PCR platform. Application of our three novel criteria provides an easy to use semi-automated genotype confirmation protocol.

Journal Title

Nucleic Acids Research

Conference Title
Book Title
Edition
Volume

32

Issue

6

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© 2005 Johnson, Matthew Peter et al. This is an open access paper. http://creativecommons.org/licenses/by/3.0/ license that permits unrestricted use, provided that the paper is properly attributed.

Item Access Status
Note
Access the data
Related item(s)
Subject

Environmental sciences

Biological sciences

Information and computing sciences

Persistent link to this record
Citation
Collections