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

Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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

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.

Modern Molecular Taxonomy

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

Evolutionary Relationships through Genome Comparisons

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...

Evolution of Microbial Genome

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.

You might also read

Related Articles

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

Sort by

Same author

Breast implant surface texture is associated with distinct implant microbiome profiles in humans.

Acta biomaterialia·2026

Same author

Early life bacteria and sibling exposure associate with restoration of the infant gut microbiome after cesarean section.

Nature communications·2026

Same author

Plasmids as persistent genetic reservoirs of bacterial defense systems in wastewater treatment.

Microbiome·2026

Same author

Breast implant microbiome profile correlates with foreign body response severity.

Acta biomaterialia·2025

Same author

Temporal dynamics and microbial interactions shaping the gut resistome in early infancy.

Nature communications·2025

Same author

The influence of early life exposures on the infant gut virome.

Gut microbes·2025

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

Quantitative metagenomic analyses based on average genome size normalization.

Jeremy A Frank¹, Søren J Sørensen

¹Department of Microbiology, University of Copenhagen, Sølvgade 83H, Copenhagen DK-1307, Denmark. jeremyafrank@me.com

Applied and Environmental Microbiology

|February 15, 2011

Summary

This summary is machine-generated.

This study introduces a new method for quantitative microbial community analysis using metagenomics. Normalizing data by average genome size improves comparisons between different environments and reveals metabolic capabilities.

More Related Videos

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Related Experiment Videos

Last Updated: Jun 4, 2026

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

Microbiology
Genomics
Bioinformatics

Background:

Microbial community characterization has evolved from single gene analysis to metagenomics.
Metagenomics provides insights into community composition and metabolic functions.
Comparative metagenomic analyses face biases from varying community structures and sequencing depths.

Purpose of the Study:

To introduce a novel quantitative method for characterizing and comparing microbial communities.
To normalize metagenomic data using average genome size estimation to reduce comparative biases.
To demonstrate the method's utility by analyzing marine metagenomes and autotrophic organism abundances.

Main Methods:

Developed a quantitative method for metagenomic data normalization based on average genome size.
Compared metagenomes from two marine environments using the new method and small-subunit (SSU) rRNA gene analysis.
Quantified the proportion of specific autotrophic organisms (Cyanobacteria, Chlorobi, Desulfobacteraceae) in each community.

Main Results:

The genome size normalization method effectively reduces biases in comparative metagenomics.
Genome proportionality analysis revealed differences in autotrophic organism abundances between marine environments.
Findings highlight the impact of average genome size and SSU rRNA gene copy number on community analysis.

Conclusions:

The proposed normalization method offers a more accurate approach for quantitative metagenomic comparisons.
Understanding genome proportionality is crucial for interpreting microbial community structure and function.
This method enhances our ability to assess microbial metabolic potential and environmental adaptation.