Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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...
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.
Convergent Evolution01:54

Convergent Evolution

Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.The structures that arise from convergent evolution are called analogous structures. They are similar in function even if they are dissimilar in structure. Further, structures can be analogous while also...
Speciation Rates01:07

Speciation Rates

Speciation can proceed at markedly different rates, and evolutionary biologists commonly describe these differences through the models of gradualism and punctuated equilibrium. Both patterns explain how new species arise, but they differ in the tempo and continuity of evolutionary change. In both cases, evolutionary change arises from heritable variation within populations, with natural selection often shaping traits that improve survival and reproduction under specific environmental conditions.
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,...
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...

You might also read

Related Articles

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

Sort by
Same author

Reconciling fast Hepatitis B evolutionary rates with ancient co-divergence.

bioRxiv : the preprint server for biology·2026
Same author

Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: An historical and phylogeographical retrospective.

PLoS pathogens·2025
Same author

How fast are viruses spreading in the wild?

PLoS biology·2024
Same author

Modeling the velocity of evolving lineages and predicting dispersal patterns.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

Modeling the velocity of evolving lineages and predicting dispersal patterns.

bioRxiv : the preprint server for biology·2024
Same author

On the connections between the spatial Lambda-Fleming-Viot model and other processes for analysing geo-referenced genetic data.

Theoretical population biology·2024

Related Experiment Video

Updated: Jun 15, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Bayesian estimation of divergence times from large sequence alignments.

Stéphane Guindon1

  • 1Department of Statistics, University of Auckland, Auckland, New Zealand. guindon@stat.auckland.ac.nz

Molecular Biology and Evolution
|March 3, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a new Bayesian method for estimating molecular divergence times, improving computational efficiency for large phylogenomic datasets. The novel Gibbs sampling approach offers faster and more reliable divergence time estimations compared to traditional methods.

More Related Videos

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

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

Related Experiment Videos

Last Updated: Jun 15, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

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:

  • Computational Biology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Bayesian estimation of divergence times from molecular sequences commonly uses Markov chain Monte Carlo (MCMC) techniques.
  • Metropolis-Hastings (MH) samplers are widely applied but computationally intensive, posing challenges for large phylogenomic datasets.
  • Estimating divergence times can be difficult and time-consuming with weak or conflicting phylogenetic signals, necessitating more efficient methods.

Purpose of the Study:

  • To develop a novel, computationally efficient Bayesian approach for estimating molecular divergence times.
  • To improve the accuracy and speed of phylogenetic analyses, particularly for large and complex datasets.
  • To provide a more suitable method for analyzing sequence alignments with weak or conflicting phylogenetic signals.

Main Methods:

  • A new Bayesian approach was developed, estimating the posterior density of substitution rates and node times.
  • Prior distributions were defined for rates (accounting for autocorrelation) and node ages (uniform densities).
  • The likelihood function was approximated using a multivariate normal density, enabling the use of a Gibbs sampling algorithm.

Main Results:

  • The new Gibbs sampling algorithm was implemented and tested on four real-world datasets.
  • The proposed method demonstrated superior performance compared to the standard Metropolis-Hastings (MH) approach.
  • The analysis confirmed the method's suitability for large and/or phylogenetically challenging datasets.

Conclusions:

  • The developed Gibbs sampling method offers a more efficient and reliable alternative for Bayesian divergence time estimation.
  • This approach addresses the computational limitations of traditional MH samplers in phylogenomics.
  • The method is well-suited for analyzing large-scale molecular sequence data and datasets with complex evolutionary signals.