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

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...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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...

You might also read

Related Articles

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

Sort by

Same author

Integrated multi-omics analysis uncovers cervicovaginal ecological networks and their association with <i>Chlamydia trachomatis</i> load.

Infection and immunity·2026

Same author

A transfer RNA inosine modification drives genome-wide synonymous recoding across human commensal bacterial families.

PNAS nexus·2026

Same author

Antenatal Screening for Sexually Transmitted Infections to Reduce Preterm Birth or Low Birthweight (Philani Ndiphile Study): A Randomized Three-Group Trial.

medRxiv : the preprint server for health sciences·2026

Same author

<i>Limosilactobacillus reuteri</i> alleviates proinflammatory T-cell-mediated liver injury and transcriptomic changes in immunocompromised mice.

Frontiers in immunology·2026

Same author

Water mass specific genes dominate the Southern Ocean microbiome.

Nature communications·2026

Same author

Wind shear enhances soil moisture influence on rapid thunderstorm growth.

Nature·2026

Search research articles

Related Experiment Video

Updated: Jun 6, 2026

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

A framework for analysis of metagenomic sequencing data.

A Murat Eren¹, Michael J Ferris, Christopher M Taylor

¹Department of Computer Science, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70148, USA. aeren@uno.edu

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

|December 2, 2010

Summary

New software simplifies analyzing microbial DNA (16S rRNA) from the human body. This tool aids in understanding how microbial community changes link to diseases like bacterial vaginosis.

More Related Videos

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

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

Related Experiment Videos

Last Updated: Jun 6, 2026

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

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

Area of Science:

Microbiology
Bioinformatics
Genomics

Background:

The human body hosts a vast microbial ecosystem, with microbial cells outnumbering human cells.
Alterations in microbial community composition are linked to various diseases, including intestinal, respiratory, and skin conditions.

Purpose of the Study:

To introduce a novel, user-friendly software framework for analyzing and visualizing large-scale metagenomic sequence data.
To address the challenges of interpreting millions of microbial genetic sequences.

Main Methods:

The framework utilizes high-throughput pyrosequencing data, specifically 16S rRNA gene sequences in FASTA format.
It automates standard metagenomic analyses, including composition and diversity assessments.
The software provides extensible visualization and interpretation capabilities for complex datasets.

Main Results:

The developed framework successfully processes and analyzes large volumes of metagenomic data.
It has been applied to identify microbial composition differences between healthy individuals and those with diseases.
Specific examples include distinguishing microbiota in bacterial vaginosis and necrotizing enterocolitis.

Conclusions:

The new software framework significantly enhances the ability to analyze and interpret metagenomic data.
It facilitates a deeper understanding of the human microbiome's role in health and disease.
This tool is crucial for advancing research in microbial ecology and personalized medicine.