Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Speciation Rates

Speciation Rates

Gene Evolution - Fast or Slow?

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?

Gene Evolution - Fast or Slow?

Microbial Phylogeny

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 Comparisons

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...

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Designing Weights for Quartet-Based Methods When Data are Heterogeneous Across Lineages.

Bulletin of mathematical biology·2023

Same author

SAQ: Semi-Algebraic Quartet Reconstruction.

IEEE/ACM transactions on computational biology and bioinformatics·2021

Same author

Correction to: Matrix group structure and Markov invariants in the strand symmetric phylogenetic substitution model.

Journal of mathematical biology·2021

Same author

The impracticalities of multiplicatively-closed codon models: a retreat to linear alternatives.

Journal of mathematical biology·2020

Same author

Corrigendum to: IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era.

Molecular biology and evolution·2020

Same author

Accuracy of ancestral state reconstruction for non-neutral traits.

Scientific reports·2020

Search research articles

Related Experiment Video

Updated: Apr 15, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

A New Hierarchy of Phylogenetic Models Consistent with Heterogeneous Substitution Rates.

Michael D Woodhams¹, Jesús Fernández-Sánchez², Jeremy G Sumner²

¹School of Physical Sciences, University of Tasmania, Hobart, TAS 7005, Australia and Departament de Matemàtica Aplicada I, Universitat Politècnica de Catalunya, Barcelona, Spain michael.woodhams@utas.edu.au.

Systematic Biology

|April 11, 2015

Summary

This summary is machine-generated.

Phylogenetic methods using DNA substitution models face inconsistencies when evolutionary processes change. Nonhomogeneous Lie Markov models offer a consistent alternative, outperforming the general time-reversible model in diverse biological datasets.

Keywords:

Lie Markov models Model selection ModelTest multiplicative closure phylogenetics

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

Related Experiment Videos

Last Updated: Apr 15, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

Area of Science:

Evolutionary biology
Computational biology
Phylogenetics

Background:

Standard Markov models for DNA substitutions can be mathematically inconsistent if the substitution process varies over evolutionary time.
The general time-reversible (GTR) model and its submodels are prominent examples of such inconsistent models.
This inconsistency poses challenges for accurate phylogenetic inference.

Purpose of the Study:

To evaluate the performance of nonhomogeneous Lie Markov models as a consistent alternative to standard models.
To test a hierarchy of Lie Markov models with varying parameter richness.
To compare the efficacy of Lie Markov models against the widely used GTR model.

Main Methods:

Testing a range of Lie Markov models with different parameter complexities.
Utilizing diverse biological datasets for model evaluation.
Benchmarking performance against the general time-reversible (GTR) model.

Main Results:

Lie Markov models demonstrate good overall performance compared to the GTR model.
The best-performing Lie Markov models incorporated 8-10 parameters.
Effective models distinguished between purines and pyrimidines, indicating improved accuracy.

Conclusions:

Nonhomogeneous Lie Markov models provide a mathematically consistent framework for phylogenetic analysis, even with changing DNA substitution processes.
Models with moderate parameter richness, distinguishing between nucleotide types, offer superior performance.
These findings advance the development of more robust phylogenetic inference methods.