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Sporadic, Global Linkage Disequilibrium Between Unlinked Segregating Sites
Daniel A Skelly1, Paul M Magwene1, Eric A Stone2
1Department of Biology, Duke University, Durham, North Carolina 27708.
Genetic indistinguishability causes perfect linkage disequilibrium between unlinked genes. Sample size and allele frequency are key factors, impacting association studies by complicating the localization of causal alleles.
Area of Science:
- Population Genetics
- Genomics
- Statistical Genetics
Background:
- Genetic indistinguishability, or perfect linkage disequilibrium (LD) between unlinked loci, can arise from demographic, genetic, or stochastic factors.
- This phenomenon complicates genotype-phenotype association studies by hindering the precise localization of causal alleles.
- Previous research has not thoroughly explored this from a theoretical standpoint or with large, dense whole-genome data.
Purpose of the Study:
- To theoretically model and simulate the prevalence of genetic indistinguishability between unlinked loci.
- To identify the primary determinants of genetic indistinguishability.
- To quantify the occurrence of genetic indistinguishability in model organisms.
Main Methods:
- Derivation of a theoretical model for the prevalence of genetic indistinguishability.
- Simulation studies to verify the theoretical model's accuracy.
- Analysis of large, dense whole-genome polymorphism data from three model organisms.
Main Results:
- Sample size and minor allele frequency are major determinants of perfect LD between unlinked loci.
- Demographic factors, such as deviations from random mating, also significantly influence genetic indistinguishability.
- Thousands of genetically indistinguishable variant pairs with moderate frequencies were identified in model organisms.
Conclusions:
- Genetic indistinguishability is a significant phenomenon in population genetics with implications for association studies.
- Understanding the conditions that promote genetic indistinguishability is crucial for accurate allele localization.
- The study provides a framework for predicting and interpreting genetic indistinguishability in genetic data.
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