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 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...
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...
What is Gene Expression?01:42

What is Gene Expression?

Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
What is Gene Expression?01:36

What is Gene Expression?

A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then processed and...
What is Gene Expression?01:42

What is Gene Expression?

Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...

You might also read

Related Articles

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

Sort by
Same author

Siphonophore genome structure and the evolution of functional specialization.

PloS one·2026
Same author

Sharkmer: repurposing PCR primers for targeted genome assembly using in silico PCR.

Bioinformatics (Oxford, England)·2026
Same author

T-shaped alignments integrating HIV-1 near full-length genome and partial pol sequences can improve phylogenetic inference of transmission clusters.

PLoS computational biology·2025
Same author

Correction: Zooid arrangement and colony growth in Porpita porpita.

Frontiers in zoology·2025
Same author

Zooid arrangement and colony growth in Porpita porpita.

Frontiers in zoology·2025
Same author

Population genomics of a sailing siphonophore reveals genetic structure in the open ocean.

Current biology : CB·2025

Related Experiment Video

Updated: May 10, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Phylogenetic analysis of gene expression.

Casey W Dunn1, Xi Luo, Zhijin Wu

  • 1*Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, USA; Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, RI 02903, USA.

Integrative and Comparative Biology
|June 11, 2013
PubMed
Summary
This summary is machine-generated.

Phylogenetic gene expression analysis can link evolutionary changes in genes to traits. Key challenges include cross-species data standardization, developing comparative methods for large datasets, and handling gene tree incongruence.

More Related Videos

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Related Experiment Videos

Last Updated: May 10, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Area of Science:

  • Evolutionary Biology
  • Genomics
  • Bioinformatics

Background:

  • Phylogenetic analyses of gene expression offer powerful insights into evolutionary biology.
  • These analyses can correlate evolutionary shifts in gene expression with changes in morphology, physiology, and development.
  • Identifying genes linked to specific phenotypes is a key application.

Purpose of the Study:

  • To outline general considerations for designing phylogenetic analyses of gene expression.
  • To propose solutions for key challenges in the field.
  • To address the potential of high-throughput data beyond gene expression.

Main Methods:

  • Standardizing gene expression data across multiple species for comparative analysis.
  • Developing new phylogenetic comparative methods for high-dimensional datasets where variables exceed samples.
  • Implementing approaches to analyze gene expression for genes with phylogenies incongruent with species phylogenies.

Main Results:

  • Identified three primary challenges in phylogenetic gene expression studies: data standardization, appropriate comparative methods, and gene tree incongruence.
  • Proposed solutions to facilitate robust phylogenetic comparative analyses of gene expression.
  • Highlighted the broader applicability of these methods to high-throughput phenotypic data.

Conclusions:

  • Addressing these challenges is crucial for realizing the full potential of phylogenetic gene expression studies.
  • New methods are needed to handle the complexities of large, multidimensional gene expression datasets.
  • The proposed framework supports evolutionary studies of gene expression and other high-throughput data.