Allele Frequency Distributions in Pooled DNA Samples: Applications to Mapping Complex Disease Genes
Author(s) -
Sarah H. Shaw,
Minerva M. Carrasquillo,
Carl Kashuk,
Erik G. Puffenberger,
Aravinda Chakravarti
Publication year - 1998
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.8.2.111
Subject(s) - biology , genotyping , genetics , microsatellite , allele , allele frequency , genetic marker , dna sequencer , genotype , primer (cosmetics) , polymerase chain reaction , gene , chemistry , organic chemistry
Genetic studies of complex hereditary disorders require for their mapping the determination of genotypes at several hundred polymorphic loci in several hundred families. Because only a minority of markers are expected to show linkage and association in family data, a simple screen of genetic markers to identify those showing linkage in pooled DNA samples can greatly facilitate gene identification. All studies involving pooled DNA samples require the comparison of allele frequencies in appropriate family samples and subsamples. We have tested the accuracy of allele frequency estimates, in various DNA samples, by pooling DNA from multiple individuals prior to PCR amplification. We have used the ABI 377 automated DNA sequencer and GENESCAN software for quantifying total amplification using a 5′ fluorescently labeled forward PCR primer and relative peak heights to estimate allele frequencies in pooled DNA samples. In these studies, we have genotyped 11 microsatellite markers in two separate DNA pools, and an additional four markers in a third DNA pool, and compared the estimated allele frequencies with those determined by direct genotyping. In addition, we have evaluated whether pooled DNA samples can be used to accurately assess allele frequencies on transmitted and untransmitted chromosomes, in a collection of families for fine-structure gene mapping using allelic association. Our studies show that accurate, quantitative data on allele frequencies, suitable for identifying markers for complex disorders, can be identified from pooled DNA samples. This approach, being independent of the number of samples comprising a pool, promises to drastically reduce the labor and cost of genotyping in the initial identification of disease loci. Additional applications of DNA pooling are discussed. These developments suggest that new statistical methods for analyzing pooled DNA data are required.
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