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Related Concept Videos

Microbial Phylogeny01:28

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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,...
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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Published on: August 14, 2018

Measuring the Temporal Structure in Serially-Sampled Phylogenies.

R R Gray1, O G Pybus, M Salemi

  • 1Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.

Methods in Ecology and Evolution
|November 29, 2011
PubMed
Summary
This summary is machine-generated.

Researchers developed a new Temporal Clustering (TC) statistic to quantify evolutionary patterns in serially-sampled sequences. While many datasets show temporal clustering, this pattern also appears in neutral evolution simulations, complicating interpretations of positive selection.

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Area of Science:

  • Evolutionary biology
  • Phylogenetics
  • Population genetics

Background:

  • Serially-sampled sequences are crucial for studying evolutionary rates and population history.
  • Temporal clustering in phylogenies, where sequences from the same time group together, can indicate biological processes like selection or molecular clock deviations.

Purpose of the Study:

  • To introduce the Temporal Clustering (TC) statistic, a novel quantitative measure for assessing temporal clustering in phylogenies from serially-sampled sequences.
  • To provide a standardized method for comparing temporal clustering across phylogenies of varying sizes.

Main Methods:

  • Development of the Temporal Clustering (TC) statistic to measure topological temporal clustering.
  • Application of the TC statistic to empirical datasets (viruses, ancient DNA) and simulated phylogenies under a neutral coalescent process.

Main Results:

  • Significant temporal clustering was observed in numerous empirical datasets.
  • Temporal clustering was also detected in phylogenies simulated under neutral evolutionary models.

Conclusions:

  • The TC statistic offers a quantitative approach to analyze evolutionary patterns in serially-sampled data.
  • Observed temporal clustering in empirical data does not solely confirm strong positive selection due to its presence in neutral simulations.