THEORETICAL MODIFICATIONS OF RECIPROCAL RECURRENT SELECTION
Author(s) -
Jesús MorenoGonzález,
Michael Grossman
Publication year - 1976
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1093/genetics/84.1.95
Subject(s) - overdominance , biology , crossbreed , population , selection (genetic algorithm) , genetics , dominance (genetics) , reciprocal , gene , demography , allele , linguistics , philosophy , artificial intelligence , sociology , computer science
Reciprocal recurrent selection (RRS), which assumes overdominant loci to be important, alters two genetically different populations to improve their crossbred mean. Individual plants from two populations (A and B) are selfed and also crossed with plants from the reciprocal female tester population (B and A, respectively). Selection is based on the mean of crossbred families, and the selected individuals are randomly mated within A and B to form new populations.—We propose two alternatives to RRS. The first (RRS-I) uses, as the tester of population A, a population (LB) that is derived from population B by family selection for low yield. The second (RRS-II) is similar to RRS-I, but also uses, as the tester of B, a population (LA) that is derived from population A by family selection for low yield.—The expected crossbred means of RRS, RRS-I, and RRS-II were compared, assuming equal σP, at several cycles of selection for incomplete and complete dominance, and for several cases of overdominance (depending on the gene frequencies in A and B, and on the equilibrium gene frequency).—The choice of selection method depends on the importance of the effects of overdominant loci compared to loci exhibiting incomplete or complete dominance. If overdominance is unimportant, RRS-II is the best selection method, followed by RRS-I and RRS. If overdominance is important, both RRS and RRS-I are superior to RRS-II; RRS is preferred to RRS-I if the effects of overdominant loci are sufficiently important. If the genetic model is a mixture of levels of dominance at different loci, a combination of selection systems is suggested.
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