Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Genome Size and the Evolution of New Genes

Genome Size and the Evolution of New Genes

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.

Genome Size and the Evolution of New Genes

Genome Size and the Evolution of New Genes

Gene Evolution - Fast or Slow?

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?

Gene Evolution - Fast or Slow?

The Evidence for Evolution

The Evidence for Evolution

Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.

Convergent Evolution

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.

You might also read

Related Articles

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

Sort by

Same author

Decoding common and rare noncoding variant effects across cellular and developmental contexts.

Nature genetics·2026

Same author

<i>Special Issue:</i> 13th International Conference on Computational Advances in Bio and Medical Sciences.

Journal of computational biology : a journal of computational molecular cell biology·2026

Same author

Vascular smooth muscle cell state trajectories mediate molecular mechanisms of coronary disease risk.

Nature communications·2026

Same author

SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.

Bioinformatics (Oxford, England)·2025

Same author

DupLoss-2: Improved Phylogenomic Species Tree Inference under Gene Duplication and Loss.

Systematic biology·2025

Same author

Interactions Between Dietary Metabolites and Regulatory Risk Variants for Human Colon Cancer.

bioRxiv : the preprint server for biology·2025

Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026

Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026

Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026

Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026

Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026

Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 29, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

SaGePhy: an improved phylogenetic simulation framework for gene and subgene evolution.

Soumya Kundu¹, Mukul S Bansal^1,2

¹Department of Computer Science & Engineering, Storrs, CT, USA.

Bioinformatics (Oxford, England)

|February 5, 2019

Summary

This summary is machine-generated.

SaGePhy is a new software package for simulating gene and subgene evolution. It offers advanced features for phylogenetic tree simulation, including horizontal gene transfer and domain evolution.

More Related Videos

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Related Experiment Videos

Last Updated: Jan 29, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Area of Science:

Computational Biology
Phylogenetics
Evolutionary Genomics

Background:

Phylogenetic simulation is crucial for understanding evolutionary processes.
Existing software often lacks comprehensive features for gene and subgene evolution.
Accurate simulation requires modeling complex events like duplication, transfer, and loss.

Purpose of the Study:

To introduce SaGePhy, a novel software package for enhanced phylogenetic simulation.
To provide a tool that models gene and subgene evolution with advanced features.
To facilitate the generation of diverse phylogenetic trees, including species, gene, and domain trees.

Main Methods:

Utilizes a probabilistic birth-death process for evolutionary simulation.
Incorporates gene/subgene duplication, horizontal gene/subgene transfer, and gene/subgene loss.
Implements subgene/domain level evolution within gene trees and simultaneous simulation of horizontal transfers.
Features probabilistic sampling for gene- and domain-family birth events.

Main Results:

SaGePhy enables the simulation of complex evolutionary scenarios.
The software supports the generation of species, gene, and subgene/domain trees.
Unique features include subgene evolution and simultaneous simulation of additive/replacing horizontal transfers.
SaGePhy offers probabilistic sampling for birth events in gene and domain families.

Conclusions:

SaGePhy is a powerful and versatile tool for phylogenetic simulation.
It addresses limitations in existing software by offering advanced evolutionary modeling capabilities.
The open-source and platform-independent nature of SaGePhy promotes accessibility and broad adoption in the research community.