ALLELE FREQUENCY-DISTRIBUTIONS IN POOLED DNA SAMPLES - APPLICATIONS TO MAPPING COMPLEX DISEASE GENES

Citation
Sh. Shaw et al., ALLELE FREQUENCY-DISTRIBUTIONS IN POOLED DNA SAMPLES - APPLICATIONS TO MAPPING COMPLEX DISEASE GENES, PCR methods and applications, 8(2), 1998, pp. 111-123
Citations number
26
Categorie Soggetti
Biothechnology & Applied Migrobiology",Biology,"Genetics & Heredity
ISSN journal
10549803
Volume
8
Issue
2
Year of publication
1998
Pages
111 - 123
Database
ISI
SICI code
1054-9803(1998)8:2<111:AFIPDS>2.0.ZU;2-T
Abstract
Genetic studies of complex hereditary disorders require for their mapp ing the determination of genotypes at several hundred polymorphic loci in several hundred families. Because only a minority of markers are e xpected to show linkage and association in family data, a simple scree n of genetic markers to identify those showing linkage in pooled DNA s amples can greatly facilitate gene identification. All studies involvi ng 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 th e ABI 377 automated DNA sequencer and GENESCAN software for quantifyin g total amplification using a 5' fluorescently labeled forward PCR pri mer and relative peak heights to estimate allele frequencies in pooled DNA samples. In these studies, we have genotyped 11 microsatellite ma rkers in two separate DNA pools, and an additional Four markers in a t hird DNA pool, and compared the estimated allele frequencies with thos e determined by direct genotyping. In addition, we have evaluated whet her pooled DNA samples can be used to accurately assess allele frequen cies on transmitted and untransmitted chromosomes, in a collection of families for fine-structure gene mapping using allelic association. Ou r studies show that accurate, quantitative data on allele frequencies, suitable for identifying markers for complex disorders, can be identi fied From pooled DNA samples. This approach, being independent of the number of samples comprising a pool, promises to drastically reduce th e labor and cost of genotyping in the initial identification of diseas e loci. Additional applications of DNA pooling are discussed. These de velopments suggest that new statistical methods For analyzing pooled D NA data are required.