The Limits to Knowledge in Quantitative Genetics
The limitations to our understanding of evolutionary genetic phenomena lie primarily in the empirical domain, as mathematicians have repeatedly shown that they are up to the challenges of modeling essentially any population genetic phenomenon that can be envisioned. Until recently, one of the major constraints in our attempts to understand the mechanisms by which populations evolve has been the inaccessibility of the gene. Advances in molecular technology now enable us to routinely survey populations for variation at the molecular level, although almost all such surveys involving functional genes are focused on coding regions as opposed to the frequently much more complex (and potentially more significant) regulatory regions. The latter shortcoming will certainly be surmounted in the near future, and it is fair to say that no longer are there really any fundamental limitations (other than financial ones) to our ability to monitor the dynamics of individual alleles in natural or artificial populations. Nevertheless, despite the major advances in mathematical theory and in molecular technology, one might argue that we are not much closer to a mechanistic understanding of the evolution of complex phenotypes than we were in 1920. One of the major challenges confronting evolutionary geneticists is still the development of a general and biologically based synthesis that will facilitate such understanding.
KeywordsQuantitative Trait Locus Quantitative Trait Quantitative Trait Locus Analysis Additive Genetic Variance Quantitative Genetic
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- Buhner, M. G., 1971, The effects of selection on genetic variability, Am. Natur. 105:210–211.Google Scholar
- Crow, J. F., 1992, Mutation, mean fitness, and genetic load, Oxford Surv. Evol. Biol. 9:3–42.Google Scholar
- Fisher, R. A., 1918, The correlation between relatives on the supposition of Mendelian inheritance, Trans. R. Soc. Edinburgh 52:399–433.Google Scholar
- Gerhart, J., and Kirschner, M., 1997, Cells, Embryos, and Evolution, Blackwell Science, Inc., Maiden, Massachusetts.Google Scholar
- Lande, R., 1988, Quantitative genetics and evolutionary theory, in: Proceedings of the Second International Conference on Quantitative Genetics (B. S. Weir, E. J. Eisen, M. M. Goodman, and G Namkoong, eds.), pp. 71–84, Sinauer Associates, Sunderland, Massachusetts.Google Scholar
- Lynch, M., 1996, A quantitative genetic perspective on conservation issues, in: Conservation Genetics: Case Histories from Nature (J. Avise and J. Hamrick, eds.), pp. 471–501, Chapman and Hall, New York.Google Scholar
- Lynch, M., and Lande, R., 1993, Evolution and extinction in response to environmental change, in: Biotic Interactions and Global Change (P. Kareiva, J. Kingsolver, and R. Huey, eds.), pp. 234–250, Sinauer Associates, Sunderland, Massachusetts.Google Scholar
- Lynch, M., and Walsh, B., 1998, Genetics and Analysis of Quantitative Traits, Sinauer Associates, Sunderland, Massachusetts.Google Scholar
- Templeton, A. R., Hollocher, H., Lawler, S., and Johnston, J. S., 1989, Natural selection and ribosomal DNA in Drosophila, Genetics 31:296–303.Google Scholar
- Wu, C.-I., and Palopoli, M. F., 1994, Genetics of postmating reproductive isolation in animals, Annu. Rev. Ecol. Syst. 27:283–308.Google Scholar