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Structure of linkage disequilibrium and phenotypic associations in the maize genome - PubMed

  • ️Mon Jan 01 2001

Structure of linkage disequilibrium and phenotypic associations in the maize genome

D L Remington et al. Proc Natl Acad Sci U S A. 2001.

Abstract

Association studies based on linkage disequilibrium (LD) can provide high resolution for identifying genes that may contribute to phenotypic variation. We report patterns of local and genome-wide LD in 102 maize inbred lines representing much of the worldwide genetic diversity used in maize breeding, and address its implications for association studies in maize. In a survey of six genes, we found that intragenic LD generally declined rapidly with distance (r(2) < 0.1 within 1500 bp), but rates of decline were highly variable among genes. This rapid decline probably reflects large effective population sizes in maize during its evolution and high levels of recombination within genes. A set of 47 simple sequence repeat (SSR) loci showed stronger evidence of genome-wide LD than did single-nucleotide polymorphisms (SNPs) in candidate genes. LD was greatly reduced but not eliminated by grouping lines into three empirically determined subpopulations. SSR data also supplied evidence that divergent artificial selection on flowering time may have played a role in generating population structure. Provided the effects of population structure are effectively controlled, this research suggests that association studies show great promise for identifying the genetic basis of important traits in maize with very high resolution.

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Figures

Figure 1
Figure 1

Plots of squared correlations of allele frequencies (r2) against weighted distance between polymorphic sites in six candidate genes: (a) id1, (b) tb1, (c) d8, (d) d3, (e) sh1, and (f) su1. Curves show nonlinear regression of r2 on weighted distance, by using a recombination-drift model for su1 and a mutation-recombination drift model for all other loci. Regression coefficients (b1) and the corrected percentage of variance explained by the models (SSM/SSC) are shown above each plot.

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