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The Limits to Knowledge in Quantitative Genetics

  • Michael Lynch
Part of the Evolutionary Biology book series (EBIO, volume 32)

Abstract

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.

Keywords

Quantitative Trait Locus Quantitative Trait Quantitative Trait Locus Analysis Additive Genetic Variance Quantitative Genetic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Michael Lynch
    • 1
  1. 1.Department of BiologyUniversity of OregonEugeneUSA

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