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THE EVOLUTION OF GENETIC CORRELATIONS: AN ANALYSIS OF PATTERNS
Author(s) -
Roff Derek A.
Publication year - 1996
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.1996.tb03913.x
Subject(s) - biology , trait , selection (genetic algorithm) , quantitative genetics , evolutionary biology , correlation , genetic correlation , quantitative trait locus , variation (astronomy) , genetic variation , statistics , genetics , gene , mathematics , geometry , physics , artificial intelligence , computer science , astrophysics , programming language
The genetic correlation is a central parameter of quantitative genetics, providing a measure of the rate at which traits respond to indirect selection (i.e., selection that does not act upon the traits under study, but some other trait with which they have genes in common). In this paper, I review the pattern of variation among four combinations of traits: life history × life history (L × L), morphological × morphological (M × M), life history × morphological (L × M), and behavioral × behavioral (B × B). A few other combinations were investigated, but insufficient data were obtained for separate analysis. A total of 1798 correlations, distributed over 51 different animal and plant species, were analyzed. The analysis was conducted at two levels: first by dividing the data set solely by trait combination, and second by blocking the data by trait combination and species. Because selection will tend to fix alleles that show positive correlations with fitness traits faster than those that are negative and because the latter are expected to arise more frequently by mutation, correlations between life‐history traits are predicted to be more often negative than those between morphological traits. This prediction was supported, with the ranking in decreasing proportion of negative correlations being: L × L > L × M > B × B > M × M. The mean magnitude of the genetic correlation shows little variation among morphological and life‐history combinations, and the distribution of values is remarkably flat. However, the estimated standard errors and the coefficient of variation ( SE/r G ) are large, making it difficult to separate biological factors influencing the pattern of dispersion from experimental error. Analysis of the phenotypic and genetic correlations suggest that for the combinations M × M and L × M, but not L × L or B × B, the phenotypic correlation is an adequate estimate of the genetic correlation.