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Mapping by admixture linkage disequilibrium in human populations: limits and guidelines
J C Stephens1, D Briscoe, S J O'Brien
1Laboratory of Viral Carcinogenesis, National Cancer Institute, National Institutes of Health, Frederick Cancer Research and Development Center, MD 21702-1201.
American Journal of Human Genetics
|October 1, 1994
Summary
This study introduces a new method for locating genes responsible for complex human hereditary conditions using association analysis in admixed populations. The approach leverages linkage disequilibrium to efficiently map genes that are difficult to track through traditional pedigree analysis.
Area of Science:
- Human genetics
- Population genetics
- Genetic epidemiology
Background:
- Identifying genes for hereditary conditions with low penetrance or environmental triggers is challenging using traditional pedigree analysis.
- Uncertainty in family member phenotypes complicates gene localization for complex human diseases.
Purpose of the Study:
- To develop and validate an efficient gene localization strategy for human hereditary conditions.
- To explore parameters influencing linkage disequilibrium in admixed populations for gene mapping.
Main Methods:
- Conducted analytic and computer simulations to assess linkage disequilibrium.
- Quantified the impact of genetic, genomic, and population parameters on gene localization.
- Investigated populations with a history of genetic admixture, such as African Americans and Hispanic populations.
Main Results:
- High linkage disequilibrium is generated and maintained in populations with recent admixture (3-20 generations ago).
- Identified optimal parameters for efficient gene mapping: sample sizes of 200-300 patients, 200-300 markers at 20-cM intervals, and allele frequency differences of >= 0.3.
- Achieved >95% ascertainment efficiency for gene localization.
Conclusions:
- Association analysis utilizing linkage disequilibrium is effective for locating genes in admixed populations.
- Established guidelines for an efficient gene mapping strategy, particularly for genes not easily tracked in pedigrees.
- Provides a robust approach for identifying genetic factors underlying complex hereditary diseases.