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Related Concept Videos

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...
Evolution of Microbial Genome01:08

Evolution of Microbial Genome

Microbial genome evolution is a highly dynamic process shaped by continual gene gain and loss across species and strains. This genomic flexibility allows microorganisms to adapt rapidly to environmental pressures and interactions with other organisms. Central to understanding this diversity is the distinction between the core and pan genomes.The core genome comprises the genes shared by all sampled strains of a species, representing essential functions needed for fundamental cellular processes.
Genome Size and the Evolution of New Genes03:21

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 Genes03:21

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.
Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles, which...

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Related Experiment Video

Updated: May 10, 2026

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

Stability along with extreme variability in core genome evolution.

Yuri I Wolf1, Sagi Snir, Eugene V Koonin

  • 1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.

Genome Biology and Evolution
|July 4, 2013
PubMed
Summary
This summary is machine-generated.

The Universal Pace Maker (UPM) model explains genome evolution better than the Molecular Clock (MC) model. Gene evolutionary rates vary widely, making individual gene rates poor predictors of conservation across lineages.

Keywords:
evolutionary ratemolecular clockuniversal genesuniversal pacemaker of genome evolution

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • The distribution of evolutionary distances between orthologous genes is remarkably consistent across diverse life forms.
  • Existing models like the Molecular Clock (MC) struggle to explain this evolutionary pattern.
  • The Universal Pace Maker (UPM) model offers a better fit by proposing synchronized rate changes within lineages.

Purpose of the Study:

  • To investigate the universality of evolutionary rate distributions in closely related genomes.
  • To analyze the contribution of gene-specific rates versus lineage-wide rate shifts in genome evolution.
  • To evaluate the predictive power of gene-specific rates for evolutionary conservation.

Main Methods:

  • Comparative genomics analysis of orthologous genes in bacterial and archaeal taxa.
  • Statistical modeling to compare the Universal Pace Maker (UPM) model against the Molecular Clock (MC) model.
  • Quantification of gene-specific relative evolutionary rates and their variability.

Main Results:

  • The Universal Pace Maker (UPM) model provides a superior explanation for phylogenetic data compared to the Molecular Clock (MC) model.
  • Gene-specific relative rates account for over half the variance in evolutionary distances.
  • Despite this, extremely broad ranges of relative rate variability exist even for conserved genes, limiting predictive accuracy.

Conclusions:

  • Genome evolution is characterized by coordinated rate changes within lineages, as proposed by the UPM model.
  • While gene-specific rates are influential, their high variability makes them unreliable predictors of evolutionary conservation.
  • Understanding lineage-specific evolutionary dynamics is crucial for interpreting genomic data.