Accounting for expected linkage in biometric analysis of quantitative traits

Accounting for expected linkage in biometric analysis of quantitative traits The problem of accounting for a genetic estimation of expected linkage in the disposition of random loci was solved for the additive-dominant model. The Comstock–Robinson estimations for the sum of squares of dominant effects, the sum of squares of additive effects, and the average degree of dominance were modified. Also, the Wright’s estimation for the number of loci controlling the variation of a quantitative trait was modified and its application sphere was extended. Formulas that should eliminate linkage, on average, were derived for these estimations. Nonbiased estimations were applied to the analysis of maize data. Our result showed that the most likely cause of heterosis is dominance rather than overdominance and that the main part of the heterotic effect is provided by dozens of genes. Russian Journal of Genetics Springer Journals

Accounting for expected linkage in biometric analysis of quantitative traits

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Pleiades Publishing
Copyright © 2015 by Pleiades Publishing, Inc.
Biomedicine; Human Genetics; Animal Genetics and Genomics; Microbial Genetics and Genomics
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