Literature DB >> 10903380

PCR/SSCP detects reliably and efficiently DNA sequence variations in large scale screening projects.

B Miterski1, R Krüger, P Wintermeyer, J T Epplen.   

Abstract

A simple and fast method with high reliability is necessary for the identification of mutations, polymorphisms and sequence variants (MPSV) within many genes and many samples, e.g. for clarifying the genetic background of individuals with multifactorial diseases. Here we review our experience with the polymerase chain reaction/single-strand conformation polymorphism (PCR/SSCP) analysis to identify MPSV in a number of genes thought to be involved in the pathogenesis of multifactorial neurological disorders, including autoimmune diseases like multiple sclerosis (MS) and neurodegenerative disorders like Parkinson s disease (PD). The method is based on the property of the DNA that the electrophoretic mobility of single stranded nucleic acids depends not only on their size but also on their sequence. The target sequences were amplified, digested into fragments ranging from 50-240 base pairs (bp), heat-denatured and analysed on native polyacrylamide (PAA) gels of different composition. The analysis of a great number of different PCR products demonstrates that the detection rate of MPSV depends on the fragment lengths, the temperature during electrophoresis and the composition of the gel. In general, the detection of MPSV is neither influenced by their location within the DNA fragment nor by the type of substitution, i.e., transitions or transversions. The standard PCR/SSCP system described here provides high reliability and detection rates. It allows the efficient analysis of a large number of DNA samples and many different genes.

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Year:  2000        PMID: 10903380     DOI: 10.2174/1386207003331607

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  1 in total

Review 1.  Characterising functionally important and ecologically meaningful genetic diversity using a candidate gene approach.

Authors:  Stuart B Piertney; Lucy M I Webster
Journal:  Genetica       Date:  2008-09-21       Impact factor: 1.082

  1 in total

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