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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Russian Journal of Genetics Springer Journals

Accounting for expected linkage in biometric analysis of quantitative traits

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Publisher
Springer Journals
Copyright
Copyright © 2015 by Pleiades Publishing, Inc.
Subject
Biomedicine; Human Genetics; Animal Genetics and Genomics; Microbial Genetics and Genomics
ISSN
1022-7954
eISSN
1608-3369
D.O.I.
10.1134/S1022795415060113
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Russian Journal of GeneticsSpringer Journals

Published: Aug 21, 2015

References

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