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

Nucleic Acid Structure01:25

Nucleic Acid Structure

10.3K
The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
10.3K
Nucleic acids02:43

Nucleic acids

197.6K
Nucleic acids are the most important macromolecules for the continuity of life. They carry the cell's genetic blueprint and carry instructions for its functioning.
DNA and RNA
The two main types of nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). DNA is the genetic material in all living organisms, ranging from single-celled bacteria to multicellular mammals. It is in the nucleus of eukaryotes and in the organelles, chloroplasts, and mitochondria. In prokaryotes,...
197.6K
Nucleic Acids02:43

Nucleic Acids

28.6K
28.6K
Nucleic Acids02:43

Nucleic Acids

52.0K
Nucleic acids are the most important macromolecules for the continuity of life. They carry the cell's genetic blueprint and carry instructions for its functioning.
DNA and RNA
The two main types of nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). DNA is the genetic material in all living organisms, ranging from single-celled bacteria to multicellular mammals. It is in the nucleus of eukaryotes and in the organelles, chloroplasts, and mitochondria. In prokaryotes,...
52.0K
Nucleic Acids02:43

Nucleic Acids

9.5K
9.5K

You might also read

Related Articles

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

Sort by
Same author

Impacts of dietary patterns on the gut microbiome: comparing a priori dietary indices and a posteriori dietary patterns.

Food science and biotechnology·2026
Same author

Distinct <i>Cutibacterium acnes</i> subspecies <i>defendens</i> strains classified by multi-omics dissection alleviate inflammatory skin lesions of a rosacea-like mouse model.

Frontiers in microbiomes·2026
Same author

Corrigendum to: Gut Microbiome-Based Strategies for the Control of Carbapenem-Resistant Enterobacteriaceae.

Journal of microbiology and biotechnology·2025
Same author

Strain-Level Differences of <i>Bifidobacterium breve</i> in the Gut Microbiome between Infants with and without Atopic Dermatitis: Insights from Genome Analysis and Immune Assays.

Journal of microbiology and biotechnology·2025
Same author

Corrigendum to: Gut Microbiome-Based Strategies for the Control of Carbapenem-Resistant Enterobacteriaceae.

Journal of microbiology and biotechnology·2025
Same author

Comparison of extracellular vesicles carrying bacterial DNA in urine and serum from a Korean population.

Frontiers in microbiology·2025

Related Experiment Video

Updated: Mar 30, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K

OrthoANI: An improved algorithm and software for calculating average nucleotide identity.

Imchang Lee1,2, Yeong Ouk Kim2,3, Sang-Cheol Park2,3

  • 1School of Biological Sciences, Seoul National University, Seoul 151-742, Republic of Korea.

International Journal of Systematic and Evolutionary Microbiology
|November 21, 2015
PubMed
Summary
This summary is machine-generated.

A new algorithm, OrthoANI, addresses asymmetry in average nucleotide identity (ANI) calculations for bacterial and archaeal species demarcation. OrthoANI improves accuracy and speed for genome-based taxonomic analysis.

More Related Videos

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
18:10

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Published on: June 16, 2011

30.2K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.7K

Related Experiment Videos

Last Updated: Mar 30, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

35.0K
Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
18:10

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Published on: June 16, 2011

30.2K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.7K

Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Species demarcation in Bacteria and Archaea relies on genome relatedness, shifting from DNA-DNA hybridization (DDH) to genome-sequence-based methods.
  • Average nucleotide identity (ANI) is a common genome-sequence-based measure, but reciprocal calculations can yield significantly different results.
  • Reciprocal differences in ANI values, exceeding 1%, pose a challenge for consistent species demarcation.

Purpose of the Study:

  • To develop a novel algorithm that resolves the asymmetry issue in reciprocal average nucleotide identity (ANI) calculations.
  • To introduce OrthoANI, an algorithm that utilizes orthologous gene fragments for more accurate genome-based species demarcation.
  • To provide a robust and faster alternative to existing methods for calculating genome similarity.

Main Methods:

  • Developed the OrthoANI algorithm, which fragments genome sequences and considers only orthologous fragment pairs for identity calculations.
  • Compared OrthoANI with traditional ANI (using BLASTn) across 63,690 genome sequence pairs.
  • Assessed the correlation and performance of OrthoANI against established methods.

Main Results:

  • Identified significant, sometimes exceeding 1%, differences in reciprocal ANI values, highlighting the need for a symmetrical approach.
  • Demonstrated that OrthoANI is highly correlated with ANI (using BLASTn).
  • Observed that OrthoANI yields approximately 0.1% higher values compared to ANI (using BLASTn).

Conclusions:

  • OrthoANI provides a more robust and symmetrical method for calculating average nucleotide identity, essential for accurate species demarcation.
  • The OrthoANI algorithm offers a faster computational approach for genomic taxonomic analyses.
  • Freely available software tools for OrthoANI are provided to facilitate its adoption in microbiology research.