Interpreting studies that compare high- and low-selected lines on new characters
- Norman D. Henderson
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The attempt to characterize high- and low-selected lines on new variables poses serious interpretative problems when replicate lines are not available. Modest but significant line differences on new measures may be due to genetic drift totally irrelevant to the originally selected trait. Often these differences are exaggerated by inappropriate analysis using individual subject measurements rather than family means. Mean differences in high- and low-selected lines on new characters should not be ascribed to the originally selected trait unless (1) genetic drift can be estimated through the use of replicate lines, (2) the standardized mean difference exceeds 1/4 of the equivalent difference on the original selected trait, or (3) strong predictions involving multiple noncontingent measures are unconditionally supported. For most purposes of analysis, line means can be considered individual data points which can be used to compute correlations among measures. An alternative to selection with replicates—two-stage testing of commercially available inbred strains—should be considered when large genetic correlations between the characters are expected.
- Alf, E. A., and Abrahams, N. M. (1975). The use of extreme groups in assessing relationships.Psychometrica 40:563–571.
- Bulmer, M. G. (1971). The effect of selection on genetic variability.Am. Nat. 105:201–211.
- Bulmer, M. G. (1976). The effect of selection on genetic variability: A simulation study.Genet. Res. 28:101–117.
- Carey, G. (1988). Inference about genetic correlations.Behav. Genet. 18:329–338.
- Crow, J. F. (1954). Breeding structure of populations. II. Effective population number. InStatistics and Mathematics in Biology, Iowa State University Press, Ames.
- DeFries, J. C., and Hegmann, J. P. (1970). Genetic analysis of open-field behavior. In Lindzey, G., and Thiessen, D. D. (eds.),Contributions to Behavior-Genetic Analysis: The Mouse as a Prototype, Appleton-Century-Crofts, New York, pp. 23–56.
- DeFries, J. C., Gervais, M. C., and Thomas, E. A. (1978). Response to 30 generations of selection for open-field activity in laboratory mice.Behav. Genet. 8:3–13.
- Falconer, D. S. (1981).Introduction to Quantitative Genetics, 2nd ed., Longman, London.
- Hegmann, J. P., and DeFries, J. C. (1968). Open-field behavior in mice: Genetic analysis of repeated measures.Psychon. Sci. 13:27–28.
- Nielsen, B. V., and Andersen, S. (1987). Selection for growth on normal and reduced protein diets in mice. I. Direct and correlated responses for growth.Genet. Res. 50:7–15.
- Pearson, K. (1903). Mathematical contributions to the theory of evolution. XI. On the influence of natural selection on the variability and correlation of organs.Trans. Roy. Soc. (Lond.) Ser. A 200:1–66.
- Rendel, J. M. (1977). Canalisation in quantitative genetics. InProceedings of the International Conference on Quantitative Genetics, Iowa State University Press, Ames.
- Robertson, A. (1961). Inbreeding in artificial selection programmes.Genet. Res. 2:189–194.
- Wier, B. S., and Cockerham, C. C. (1977). Two-locus theory in quantitative genetics. InProceedings of the International Conference on Quantitative Genetics, Iowa State University Press, Ames.
- Wright, S. (1931). Evolution in Mendelian populations.Genetics 16:97–159.
- Interpreting studies that compare high- and low-selected lines on new characters
Volume 19, Issue 4 , pp 473-502
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers-Plenum Publishers
- Additional Links
- selected lines
- artificial selection
- strain differences
- genetic correlations
- genetic drift
- Author Affiliations
- 1. Oberlin College, 44074, Oberlin, Ohio