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Related Experiment Videos

Effect of mating structure on variation in linkage disequilibrium

B S Weir, W G Hill

    Genetics
    |June 1, 1980
    PubMed
    Summary

    Understanding genetic linkage disequilibrium requires considering population sampling and mating structures. This study quantifies the variance in observed linkage disequilibrium, crucial for population genetics research.

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    ESTIMATION OF GENE FLOW FROM F-STATISTICS.

    Evolution; international journal of organic evolution·2017

    Area of Science:

    • Population Genetics
    • Quantitative Genetics

    Background:

    • Linkage disequilibrium (LD) arises from non-random association of alleles at different loci.
    • LD is influenced by evolutionary forces such as mutation, selection, genetic drift, and recombination.
    • Accurate measurement of LD is essential for genetic mapping and understanding population structure.

    Purpose of the Study:

    • To develop a theoretical framework for quantifying the variance of linkage disequilibrium.
    • To investigate the impact of population size, mating system, and sampling strategy on LD variance.
    • To provide a method for estimating the reliability of LD measurements.

    Main Methods:

    • Utilized two-locus descent measures to model mating systems.
    • Employed approximate eigenvectors of the transition matrix for descent measures.
    • Derived analytical formulae for the variance of observed disequilibria.

    Main Results:

    • Developed formulae for LD variance incorporating effective population size (Ne), mating structure, sample size (n), and recombination rate.
    • Demonstrated that LD variance is consistent across several mating systems, including monoecious populations (with/without selfing) and dioecious populations with random pairing.
    • Observed a slightly higher variance in monogamous populations, particularly for unlinked loci.

    Conclusions:

    • The derived formulae provide a robust method for assessing the statistical uncertainty in linkage disequilibrium estimates.
    • Understanding the factors contributing to LD variance is critical for interpreting genetic association studies and population genetic inferences.
    • The findings highlight the importance of considering both evolutionary and sampling processes in LD analysis.

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