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Related Concept Videos

Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...
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Phylogeny

Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire...
Microbial Phylogeny01:28

Microbial Phylogeny

Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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A Practical Guide to Phylogenetics for Nonexperts
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A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Evolving view on phylogenetic networks.

Claudia Solís-Lemus1

  • 1Wisconsin Institute for Discovery, Department of Plant Pathology, University of Wisconsin-Madison, 500 Lincoln Dr, Madison, WI 53706.

Systematic Biology
|July 9, 2026
PubMed
Summary

Phylogenetic networks offer a powerful alternative to traditional evolutionary trees, capturing complex reticulate evolutionary processes like hybridization. This work reviews network models and methods, advancing our understanding of life's intricate evolutionary history.

Keywords:
horizontal gene transferhybridizationintrogressionreassortmentrecombination

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Area of Science:

  • Evolutionary Biology
  • Phylogenetics
  • Computational Biology

Background:

  • Traditional bifurcating phylogenetic trees are insufficient for representing reticulate evolutionary processes such as hybridization, introgression, and horizontal gene transfer.
  • Phylogenetic networks have emerged as a crucial tool, initially as split graphs for visualizing tree discordance and subsequently as explicit probabilistic models.
  • These networks provide a more biologically realistic framework for understanding complex evolutionary histories.

Purpose of the Study:

  • To describe the taxonomy of phylogenetic network representations, distinguishing principal classes of explicit networks.
  • To evaluate the biological interpretability and estimability of these network models from empirical data.
  • To trace the evolution of inferential methods for phylogenetic networks.

Main Methods:

  • Review and categorization of phylogenetic network models, including split graphs and explicit probabilistic models.
  • Analysis of the historical development of network inferential methods, from early tests to modern probabilistic approaches.
  • Examination of statistical identifiability and computational scalability as driving forces in method evolution.

Main Results:

  • A comprehensive overview of the diverse landscape of phylogenetic network representations and their underlying biological assumptions.
  • Identification of key inferential methods and their evolutionary trajectories, shaped by practical computational and statistical constraints.
  • Demonstration of the convergence of methodologies from population genetics, phylogenomics, and network theory into a unified framework.

Conclusions:

  • A shift towards a 'network thinking' paradigm is integrating disparate methods for analyzing reticulate evolution.
  • This integrated framework enhances the analysis of both sequence- and species-level reticulate processes, improving robustness to errors.
  • Phylogenetic networks provide a richer, more accurate representation of the evolutionary history of life, moving beyond the limitations of tree-based models.