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

Genetics of Speciation02:16

Genetics of Speciation

19.3K
Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
19.3K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.5K
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).
58.5K
Speciation Rates01:07

Speciation Rates

21.2K
Overview
21.2K
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

3.9K
Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
3.9K
Genetic Drift03:33

Genetic Drift

39.8K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
39.8K
Gene Flow02:39

Gene Flow

35.2K
Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
35.2K

You might also read

Related Articles

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

Sort by
Same author

Scaling up Bayesian population phylogenomics through virtual dimension reduction.

Nature communications·2026
Same author

Bayesian test of gene flow between sister lineages using genomic data.

Systematic biology·2026
Same author

The impact of incomplete taxon sampling on inference of gene flow by Bayesian and summary methods using genomic sequence data.

Systematic biology·2026
Same author

Improved Bayesian inference of hybrids using genome sequences.

bioRxiv : the preprint server for biology·2026
Same author

On the robustness of Bayesian inference of gene flow to intragenic recombination and natural selection.

Molecular biology and evolution·2025
Same author

Mutation ages and population origins inferred from genomes in structured populations.

Genetics·2025

Related Experiment Video

Updated: Jul 12, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

15.9K

Efficient Bayesian inference under the multispecies coalescent with migration.

Tomáš Flouri1, Xiyun Jiao2, Jun Huang3

  • 1Department of Genetics, Evolution, and Environment, University College London, London WC1E 6BT, United Kingdom.

Proceedings of the National Academy of Sciences of the United States of America
|October 23, 2023
PubMed
Summary

New Bayesian methods analyze genome data to reveal gene flow patterns in species evolution. This research enhances understanding of speciation and adaptation using genomic datasets.

Keywords:
BPPgene flowgenomicsmigrationmultispecies coalescent

More Related Videos

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.4K
Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K

Related Experiment Videos

Last Updated: Jul 12, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

15.9K
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.4K
Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K

Area of Science:

  • Population Genetics
  • Genomics
  • Evolutionary Biology

Background:

  • Genome sequence analyses reveal widespread interspecific gene flow, crucial for speciation and adaptation.
  • Current methods for inferring gene flow from genomic data are computationally intensive and limited to small datasets.

Purpose of the Study:

  • To implement a multispecies coalescent-with-migration model in the Bayesian program BPP for analyzing large genomic datasets.
  • To develop efficient Markov chain Monte Carlo (MCMC) algorithms for posterior sampling in gene flow analyses.
  • To enable testing of continuous versus pulsed gene flow models.

Main Methods:

  • Utilized the multispecies coalescent-with-migration model within the BPP software.
  • Developed novel MCMC algorithms for efficient posterior sampling.
  • Applied the methods to analyze genome-scale datasets, including thousands of loci.

Main Results:

  • The BPP program, with new MCMC algorithms, can efficiently analyze genome-scale datasets for gene flow.
  • The implemented models allow estimation of migration rates, species divergence times, and population sizes.
  • Analyses of Anopheles mosquito genomic data provided insights into gene flow modes and rates.

Conclusions:

  • The developed Bayesian approach offers a computationally efficient tool for inferring gene flow from large genomic datasets.
  • This method advances our understanding of the role of gene flow in evolutionary processes like speciation and adaptation.
  • The study highlights the utility of genomic data for detailed investigations into the dynamics of interspecific gene flow.