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Related Concept Videos

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,...
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...
Phylogeny01:23

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...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...

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Related Experiment Video

Updated: Jul 4, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Smoothly Time-Varying Continuous Time Markov Chains in Phylogenetics.

Pratyusa Datta1, Philippe Lemey2, Marc A Suchard1

  • 1Department of Biostatistics, University of California Los Angeles.

Arxiv
|July 3, 2026
PubMed
Summary

Estimating evolutionary rates is challenging due to sampling time. A new spline clock model accurately captures time-varying evolutionary rates, improving phylogenetic analyses for evolutionary biology and infectious disease research.

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Last Updated: Jul 4, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

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Published on: August 14, 2018

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12:00

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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Area of Science:

  • Evolutionary biology
  • Molecular phylogenetics
  • Computational biology

Background:

  • Estimating evolutionary rates from molecular sequence data is crucial but challenged by sampling timeframes.
  • Accurate reconstruction of evolutionary histories is vital for understanding biological diversity and disease dynamics.

Purpose of the Study:

  • To introduce a novel method, the spline clock model, for accurately estimating time-varying evolutionary rates.
  • To address the challenge of temporal dependence in molecular clock models.

Main Methods:

  • Modeling sequence substitution using inhomogeneous continuous-time Markov chains (ICTMCs).
  • Parameterizing evolutionary rates as smooth functions of time via cubic B-spline basis expansion.
  • Utilizing Gauss-Legendre quadrature for efficient likelihood evaluation and Gaussian Markov random field priors for spline coefficients.

Main Results:

  • The spline clock model demonstrated superior accuracy and precision in recovering true time-varying rates compared to existing models in simulations.
  • Strong time-varying evolutionary signals were identified in foamy virus evolution and SARS-CoV-2 spatial diffusion across Europe.

Conclusions:

  • The spline clock model offers a flexible and accurate approach for analyzing molecular sequence data with time-varying evolutionary rates.
  • This method enhances phylogenetic inference, with significant implications for evolutionary biology and infectious disease epidemiology.