Rates of change of genetic parameters of body weight in selected mouse lines.

A method based on the animal model is described which allows the estimation of continuous changes in variance components over time using restricted maximum likelihood (REML). The method was applied to the analysis of a selection experiment in which a foundation population formed from a cross between two inbred strains of mice (C57BL/6J and DBA/2J) was divergently selected for 6 week body weight over 20 generations. The analysis suggested that there was an increase in phenotypic variance of about 50% in the low selected lines over the course of the experiment which was attributed to increases in the environmental and additive variance components. Variance changes in the High selected lines were generally smaller than in the Low lines, although there was an estimated 20% increase in the environmental variance. Simple models to explain these effects involving dominance, linkage and epistasis were explored. Testing which of these was responsible for the variance changes noted in this experiment (if any) is difficult, although the epistasis and dominance models require less stringent conditions than the linkage model, and the dominance model is supported by evidence of heterosis in the F1.

[1]  K. Meyer,et al.  Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm , 1989, Genetics Selection Evolution.

[2]  E. B. Burnside,et al.  Joint sire and cow evaluation for conformation traits using an individual animal model. , 1988, Journal of dairy science.

[3]  R. Sokal Evolutionary Genetics , 1972, The Quarterly Review of Biology.

[4]  W. Ewens Evolution and the Genetics of Populations. Vol. 2, The Theory of Gene Frequencies. Sewall Wright. University of Chicago Press, Chicago, 1969. viii + 512 pp., illus. $15 , 1970 .

[5]  W. G. Hill,et al.  Artificial Selection Experiments , 1992 .

[6]  A. Clutterbuck Gene symbols in Aspergillus nidulans. , 1973, Genetical research.

[7]  W. G. Hill,et al.  Approximation of sampling variances and confidence intervals for maximum likelihood estimates of variance components , 1992 .

[8]  J. James Selection theory versus selection results - a comparison. , 1990 .

[9]  D. Falconer,et al.  Introduction to Quantitative Genetics. , 1962 .

[10]  W. G. Hill Estimation of realised heritabilities from selection experiments. I. Divergent selection. , 1972, Biometrics.

[11]  R. Lewontin The Interaction of Selection and Linkage. I. General Considerations; Heterotic Models. , 1964, Genetics.

[12]  P. Keightley,et al.  Detection of quantitative trait loci from frequency changes of marker alleles under selection. , 1993, Genetical research.

[13]  E. H. Bryant,et al.  The Effect of an Experimental Bottleneck upon Quantitative Genetic Variation in the Housefly. , 1986, Genetics.

[14]  W. J. Boylan,et al.  MASS SELECTION FOR POST-WEANING GROWTH IN MICE. , 1963, Genetics.

[15]  C. Goodnight EPISTASIS AND THE EFFECT OF FOUNDER EVENTS ON THE ADDITIVE GENETIC VARIANCE , 1988, Evolution; international journal of organic evolution.

[16]  K. Meyer,et al.  DFREML—A Set of Programs to Estimate Variance Components Under an Individual Animal Model , 1988 .

[17]  D. Falconer Replicated selection for body weight in mice. , 1973, Genetical research.

[18]  W. G. Hill,et al.  Mixed model analysis of a selection experiment for food intake in mice. , 1991, Genetical research.

[19]  H. Jorjani Causes of disagreement between estimated and realised genetic parameters. , 1990 .

[20]  W G Hill,et al.  Estimation of changes in genetic parameters in selected lines of mice using REML with an animal model. 1. Lean mass , 1992, Heredity.

[21]  J. W. Macarthur Genetics of Body Size and Related Characters. I. Selecting Small and Large Races of the Laboratory Mouse , 1944, The American Naturalist.

[22]  W. G. Hill,et al.  Quantitative genetic variation in body size of mice from new mutations. , 1992, Genetics.

[23]  R. Lewontin,et al.  THE INTERACTION OF SELECTION AND LINKAGE. II. OPTIMUM MODELS. , 1964, Genetics.