STATISTICAL METHODS FOR STUDYING DISEASE GENE HISTORY
Project Number1R01HG001708-01
Contact PI/Project LeaderFU, YUN-XIN
Awardee OrganizationUNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
Description
Abstract Text
DESCRIPTION: (Applicant's abstract) The Human Genome Project has already
produced numerous long human DNA sequences. Such a long sequence may cover
an entire gene and also its flanking regions. This progress and the advent
of rapid DNA sequencing techniques will allow the sequencing of large DNA
regions of samples from human populations, especially regions containing a
disease-causing mutation. Alternatively, one may study microsatellite
markers closely linked to the mutation. The goal of this project is to
develop population genetics theory, statistical methods and computer
algorithms for studying the history and the mechanism of maintenance of a
disease-causing mutation in a population. The specific aims are (1) to
develop a coalescent theory for a DNA region subject to point mutation,
natural selection and recombination, (2) to develop a coalescent theory for
microsatellite loci subject to stepwise mutation, natural selection and
recombination. Current coalescent methods assume an equilibrium population,
and are not appropriate for studying a recent mutation subject to natural
selection, such as the AF508 mutation of cystic fibrosis. We propose to
develop a coalescent approach incorporating a method for simulating the
history of the subpopulation bearing the mutant. (3) to develop methods for
estimating the age of a disease causing mutation from DNA sequences or from
microsatellite markers. (4) to develop methods for estimating the selection
coefficients and for testing hypotheses about the selection coefficients of
a disease-causing mutation. One of the methods we will develop is for
site-by-site polymorphism data, and does not require the determination of
DNA haplotype sequences. Therefore, the method will be particularly useful
when large scale screening of polymorphisms in a sample is done by DNA
"chips". (5) to develop a computer package for the above methods accessible
on the World Wide Web, and (6) to apply the theory and methods to estimate
the age and selection coefficients of the AF508 mutant of cystic fibrosis.
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Clinical Studies
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