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

Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

27.0K
Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
27.0K
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

4.2K
4.2K
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

1.5K
The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
1.5K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

65.8K
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).
65.8K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

3.7K
3.7K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

9.4K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
9.4K

You might also read

Related Articles

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

Sort by
Same author

Re-Engineering Wimsatt for Limited Beings.

Acta biotheoretica·2026
Same author

Light pollution creates multiple threats to the movement ecology of nocturnal arthropod taxa.

Current biology : CB·2025
Same author

Atlantic-wide connectivity of Ascension Island green turtles revealed by finer-scale mitochondrial DNA markers.

Conservation genetics (Print)·2025
Same author

Predominantly Terrestrial Foraging and Reproductive Gains From a High Trophic Level Diet in Roof-Nesting Herring Gulls (<i>Larus argentatus</i>).

Ecology and evolution·2025
Same author

Long-range pollen transport across the North Sea: Insights from migratory hoverflies landing on a remote oil rig.

The Journal of animal ecology·2025
Same author

Effective Pruning for Top-k Feature Search on the Basis of SHAP Values.

IEEE access : practical innovations, open solutions·2025

Related Experiment Video

Updated: Mar 26, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Gap Gene Regulatory Dynamics Evolve along a Genotype Network.

Anton Crombach1, Karl R Wotton2, Eva Jiménez-Guri2

  • 1EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain anton.crombach@crg.eu yogi.jaeger@crg.eu johannes.jaeger@kli.ac.at.

Molecular Biology and Evolution
|January 23, 2016
PubMed
Summary
This summary is machine-generated.

Evolutionary changes in developmental gene networks, known as system drift, can preserve organismal patterns despite altered gene wiring. Compensatory mechanisms ensure identical final patterns in different species, like the gap gene network in insects.

Keywords:
evolutionary developmental biologyevolutionary systems biologygap gene network.network evolutionreverse engineeringsystem drift

More Related Videos

Quantitative Comparison of cis-Regulatory Element CRE Activities in Transgenic Drosophila melanogaster
08:19

Quantitative Comparison of cis-Regulatory Element CRE Activities in Transgenic Drosophila melanogaster

Published on: December 19, 2011

12.4K
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

1.4K

Related Experiment Videos

Last Updated: Mar 26, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K
Quantitative Comparison of cis-Regulatory Element CRE Activities in Transgenic Drosophila melanogaster
08:19

Quantitative Comparison of cis-Regulatory Element CRE Activities in Transgenic Drosophila melanogaster

Published on: December 19, 2011

12.4K
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

1.4K

Area of Science:

  • Developmental Biology
  • Evolutionary Genetics
  • Systems Biology

Background:

  • Developmental gene networks control organismal patterning.
  • System drift describes evolutionary changes in gene networks while preserving patterning outcomes.
  • The gap gene network in dipteran insects exemplifies system drift.

Purpose of the Study:

  • To model and compare system drift in the gap gene network of two dipteran species.
  • To elucidate the compensatory regulatory mechanisms underlying conserved patterning.
  • To explore implications for genotype networks and evolvability.

Main Methods:

  • Quantitative modeling of gene circuits using expression data from Megaselia abdita.
  • Comparative analysis of M. abdita models with existing Drosophila melanogaster models.
  • Detailed analysis of regulatory network wiring and gene expression dynamics.

Main Results:

  • Significant quantitative differences in early gap gene expression between M. abdita and D. melanogaster.
  • Identical final segmental patterning outcomes despite differing regulatory mechanisms.
  • Identification of specific compensatory regulatory strategies.

Conclusions:

  • Compensatory regulatory mechanisms are key to achieving robust, conserved developmental patterns.
  • Understanding system drift provides insights into genotype networks and evolvability.
  • Comparative modeling of gene networks reveals principles of evolutionary robustness.