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Computing genetic similarity coefficients from RAPD data: correcting for the effects of PCR artifacts caused by variation in experimental conditions.

Department of Horticultural Sciences, Cornell University, Geneva, New York 14456-0462, USA.

Abstract

The production of informative random amplified polymorphic DNA (RAPD) markers using PCR and a single primer is often accompanied by the generation of artifactual (noninformative) bands as well. When RAPD data are used to compute genetic similarity coefficients, these artifacts (false positives, false negatives, or both) can cause large biases in the numerical values of the coefficients. As a result, some workers have been reluctant to use RAPD markers in the estimation of genetic similarities. Artifactual bands are of two types: those caused by variation in experimental conditions, and those caused by characteristics of the DNA to be amplified. A procedure is described that allows for correction of the bias caused by the first type of artifact, providing that replicate DNA samples have been extracted, amplified, and scored. The resulting data are used to obtain an estimate of the proportion of false-positive and false-negatives bands. These values are then used to correct the bias in the computed similarity coefficients. Two examples are given, one in which bias correction is critical to the results, and one in which it is less important. The maximum percent bias, computed from the estimated proportions of false positives and false negatives in the RAPD data set, is proposed as a criterion for determining whether bias correction of the similarity coefficients is required or not. Although all reasonable efforts should be made to optimize PCR protocols to eliminate artifactual bands, when this is not possible, the methods described allow RAPD markers to compute genetic similarities reliably and accurately, even when artifactual bands resulting from variation in experimental conditions are present.

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