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

Mutation, Gene Flow, and Genetic Drift01:09

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).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Genetic Drift03:33

Genetic Drift

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.Life is not fair. A deer grazing contentedly in a field can have her meal cut tragically short by a bolt of lightning. If the doomed doe is one of only three in the population, 1/3 of the population’s gene pool is lost. Random events like this can...
What is Population Genetics?01:25

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.While some alleles of a given gene might be observed commonly, other variants...
Genetics of Speciation02:16

Genetics of Speciation

Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.The genetics of speciation involves the different traits or isolating mechanisms preventing gene exchange, leading to reproductive isolation. Reproductive isolation can be due to reproductive barriers that have effects either before or after the formation of a zygote. Pre-zygotic mechanisms prevent fertilization from occurring, and post-zygotic mechanisms...
Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

You might also read

Related Articles

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

Sort by
Same author

An Integrative RNA Spliceosomic Landscape of Pancreatic Neuroendocrine Tumors Identifies Clinically Relevant Molecular Subgroups.

Endocrine pathology·2026
Same author

Quantifying the impact of health service delivery barriers on access to healthcare: a case study of antiretroviral therapy in Mali.

BMJ global health·2026
Same author

Influence of Both La Nina and Island Isolation During COVID-19 on the Epidemiology of Infectious Diseases in New Caledonia.

Epidemiologia (Basel, Switzerland)·2026
Same author

Incidence of Dementia With Lewy Bodies in Salento, Italy: A Population-Based Study.

Neurology·2026
Same author

Incidence and Prevalence of Dementia With Lewy Bodies: A Systematic Review and Meta-Analysis.

JAMA neurology·2026
Same author

Impact of extreme precipitation events on facility-based births in 21 sub-Saharan African countries.

Nature communications·2026

Related Experiment Video

Updated: Jun 7, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

SPLATCHE2: a spatially explicit simulation framework for complex demography, genetic admixture and recombination.

Nicolas Ray1, Mathias Currat, Matthieu Foll

  • 1EnviroSPACE laboratory, Climate Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Battelle - Building D, 7 route de Drize, 1227 Carouge, Switzerland.

Bioinformatics (Oxford, England)
|October 20, 2010
PubMed
Summary
This summary is machine-generated.

SPLATCHE2 simulates population demography and molecular diversity under various evolutionary scenarios. This spatially explicit framework aids in testing hypotheses and estimating parameters using genetic markers.

More Related Videos

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Related Experiment Videos

Last Updated: Jun 7, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

  • Population genetics
  • Evolutionary biology
  • Computational biology

Background:

  • Understanding population dynamics and genetic diversity is crucial in evolutionary studies.
  • Simulating complex demographic scenarios aids in hypothesis testing.

Purpose of the Study:

  • To introduce SPLATCHE2, a novel program for simulating population demography and molecular diversity.
  • To provide a flexible framework for exploring various evolutionary scenarios and their genetic consequences.

Main Methods:

  • Utilizes a spatially explicit simulation framework accounting for environmental heterogeneity and fluctuations.
  • Employs a coalescent-based approach to generate diverse genetic markers (DNA sequences, SNPs, STRs, RFLPs).
  • Incorporates a recombination model based on the ancestral recombination graph for linked markers.

Main Results:

  • SPLATCHE2 can simulate molecular diversity under complex demographic scenarios.
  • The program supports the simulation of competition between two populations with user-defined admixture.
  • It facilitates the generation of expected genetic diversity for hypothesis testing.

Conclusions:

  • SPLATCHE2 is a versatile tool for simulating population genetics scenarios, aiding in hypothesis testing.
  • The program can be integrated with Approximate Bayesian Computation (ABC) for model parameter estimation.
  • Its spatially explicit nature and ability to handle complex demographics make it valuable for evolutionary research.