Phylogenetic Inference and Parsimony Analysis

  • Llewellyn D. DensmoreIII
Part of the Methods in Molecular Biology™ book series (MIMB, volume 176)

Abstract

Application of phylogenetic inference methods to comparative endocrinology studies has provided researchers with a new set of tools to aid in understanding the evolution and distribution of gene families. Phylogeny, as defined by Hillis et al. (1), is the “historical relationships among lineages of organisms or their parts (e.g., genes).” Inferring phylogeny is a way of generating a best estimate of the evolutionary history of organisms (or gene families), based on the information (often incomplete, as in a gene sequence) that is available. The use of phylogenetic analyses, specifically those methods that are based on maximum parsimony, has changed the way in which characters and character states are determined and interpreted. Maximum parsimony (often simply called “parsimony”) seeks to estimate a parameter based on the minimum number of events required to explain the data. In this type of phylogenetic analysis, the best or optimal tree (generally portrayed as either a cladogram or phylogram, see Note1) is that topology which requires the fewest number of character-state changes (see below). That tree is arrived at based upon consideration of shared, derived characters. This method assumes that when two taxa (or genes) share a homologous derived character state, they do so because a common ancestor of both had that character state. One goal of phylogenetic analysis that is always implied (and often stated) is to avoid using characters that are homoplastic. Characters that have homoplasy have similarities in character states for reasons other than inheritance from a common ancestor, including convergent and parallel evolution or a reversal of state (e.g., A → G → A).

Keywords

Estrogen Codon Pyrimidine Purine 

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Copyright information

© Humana Press Inc. 2001

Authors and Affiliations

  • Llewellyn D. DensmoreIII
    • 1
  1. 1.Department of Biological SciencesTexas Tech UniversityLubbockTX

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