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Estimation of Population Parameters and Detection of Natural Selection from DNA Sequences

  • Wen-Hsiung Li
  • Yun-Xin Fu

Abstract

A great difficulty in population genetics is our inability to measure any of the basic parameters that are involved in the theory of population genetics. For example, we do not know the long-term effective population size (Ne) of any species and the mutation rate µ per sequence per generation for any gene. Fortunately, the situation is improvingly as a result of the introduction of various molecular techniques into population genetics. In particular, the feasibility of obtaining a fairly large number of DNA sequences from a population has enabled us to obtain better estimates of certain parameters such as θ =4Neeμ.

Another challenging problem to population geneticists is how to detect the presence of natural selection in a DNA region, i.e., to test the hypothesis that a DNA region is subject to no selective constraints. Again, this problem has become simpler because of our ability to obtain a large sample of sequences from a population.

The aim of this article is to review the mathematical theory that has been developed in recent years for dealing with the above two problems. The theory is based largely on the coalescent theory. Hudson8 gave an excellent review of the theory.

Keywords

Natural Selection Effective Population Size Population Parameter Unbiased Estimator Ancestral Sequence 
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 Dordrecht 1994

Authors and Affiliations

  • Wen-Hsiung Li
  • Yun-Xin Fu

There are no affiliations available

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