Literature DB >> 2687596

A novel method for detecting point mutations or polymorphisms and its application to population screening for carriers of phenylketonuria.

S S Sommer1, J D Cassady, J L Sobell, C D Bottema.   

Abstract

We describe a method termed PCR (polymerase chain reaction) amplification of specific alleles (PASA), a generally applicable technique for detection of point mutations or polymorphisms. The ease and technical simplicity of PASA will make genetic analyses more accessible to the general medical community. In addition, PASA shows promise for population screening because the technique is rapid, highly reproducible, inexpensive, nonisotopic, and amenable to automation. PASA is a modification of PCR that depends on the synthesis of a PCR oligonucleotide primer that precisely matches with one of the alleles but mismatches with the other. When the mismatch occurs near the 3' end of the PCR primer, amplification is inefficient. Therefore, preferential amplification of the perfectly matched allele is obtained. We demonstrate the applicability of PASA by performing carrier detection in the family of a patient with phenylketonuria (PKU) and by screening a population of unrelated subjects for the presence of the two mutations most commonly associated with PKU. Multiple persons were screened simultaneously for the mutant alleles because a mutation could be detected in the presence of at least a 40-fold excess of the normal allele. The two PKU mutations could be detected concurrently by using a mixture of only three PCR primers, an indication that simultaneous screening of multiple mutations can be done even if three or more mutations are closely clustered. In addition to the detection of mutations, PASA can be used to detect polymorphic alleles rapidly and to distinguish pseudogenes or repetitive sequences that differ by as little as one base.

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Year:  1989        PMID: 2687596     DOI: 10.1016/s0025-6196(12)65378-6

Source DB:  PubMed          Journal:  Mayo Clin Proc        ISSN: 0025-6196            Impact factor:   7.616


  28 in total

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