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

From DNA to Protein03:06

From DNA to Protein

18.6K
The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...
18.6K
The Central Dogma01:25

The Central Dogma

127.2K
Overview
127.2K
Genome Copying Errors02:46

Genome Copying Errors

4.3K
DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
4.3K
Coordination of Gene Expression Processes in Bacteria01:29

Coordination of Gene Expression Processes in Bacteria

44
The DNA replication, transcription, and translation processes are intricately coupled in bacteria, allowing efficient gene expression and rapid protein synthesis. While this physical and functional coordination is advantageous, it introduces challenges that bacteria overcome through specific regulatory mechanisms.Coupling of Replication, Transcription, and TranslationThe coupling of replication, transcription, and translation is a hallmark of bacterial gene expression. As the replisome unwinds...
44
Position-effect Variegation02:32

Position-effect Variegation

6.4K
In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
6.4K
Epistasis Analysis01:09

Epistasis Analysis

5.1K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.1K

You might also read

Related Articles

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

Sort by
Same author

Correction: The evolutionary footprint of histidine in hemoglobin and myoglobin: an implication towards their function.

Journal of biological inorganic chemistry : JBIC : a publication of the Society of Biological Inorganic Chemistry·2026
Same author

The evolutionary footprint of histidine in hemoglobin and myoglobin: an implication towards their function.

Journal of biological inorganic chemistry : JBIC : a publication of the Society of Biological Inorganic Chemistry·2026
Same author

Decoding the Torsional Dynamics of Main-Chain Atoms Within CαNN Motif Facilitating Specific Anion Recognition.

Proteins·2025
Same author

Effects of an e-Media-Supported, Exercise-Based Phase II Cardiac Rehabilitation in Coronary Artery Bypass Grafting Surgery Patients: A Randomized Controlled Trial.

Cureus·2024
Same author

CDH1 gene as biomarker towards breast cancer prediction.

Journal of biomolecular structure & dynamics·2024
Same author

Leishmania surface molecule lipophosphoglycan-TLR2 interaction moderates TPL2-mediated TLR2 signalling for parasite survival.

Immunology·2023

Related Experiment Video

Updated: Jul 27, 2025

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae
10:18

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Published on: April 25, 2015

10.4K

Analysing the genetic code degeneracy: a consequence towards bacterial staining.

Ekonthung Ezung1, Sridevi S2, Sourin Banerjee1

  • 1Department of Biotechnology, Maulana Abul Kalam Azad University of Technology (Formerly known as West Bengal University of Technology), West Bengal, India.

Journal of Biomolecular Structure & Dynamics
|June 6, 2023
PubMed
Summary
This summary is machine-generated.

Genetic code degeneracy, where multiple messenger RNA (mRNA) codons code for a single amino acid, impacts biological functions. This study introduces mathematical models to analyze codon bias and its role in bacterial gene characteristics.

Keywords:
Genetic code degeneracyb-typegram negative bacteriagram-positive bacteriahamming distance

More Related Videos

Generation of Null Mutants to Elucidate the Role of Bacterial Glycosyltransferases in Bacterial Motility
12:29

Generation of Null Mutants to Elucidate the Role of Bacterial Glycosyltransferases in Bacterial Motility

Published on: March 11, 2022

2.3K
Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers
10:41

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Published on: June 24, 2019

8.4K

Related Experiment Videos

Last Updated: Jul 27, 2025

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae
10:18

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Published on: April 25, 2015

10.4K
Generation of Null Mutants to Elucidate the Role of Bacterial Glycosyltransferases in Bacterial Motility
12:29

Generation of Null Mutants to Elucidate the Role of Bacterial Glycosyltransferases in Bacterial Motility

Published on: March 11, 2022

2.3K
Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers
10:41

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Published on: June 24, 2019

8.4K

Area of Science:

  • Molecular Biology
  • Genetics
  • Bioinformatics

Background:

  • The genetic code exhibits degeneracy, with 61 mRNA codons specifying 20 amino acids, leading to a non-one-to-one mapping.
  • This codon degeneracy is a fundamental aspect of biological systems, influencing protein synthesis and function.
  • Previous efforts have not fully elucidated the mechanisms or implications of this degeneracy.

Purpose of the Study:

  • To investigate the impact of genetic code degeneracy on biological behaviors.
  • To develop mathematical models to understand the bias in codon usage.
  • To explore the differential characteristics of bacterial genes based on codon degeneracy.

Main Methods:

  • Utilized mathematical models incorporating nucleotide base bias (b-type) and Hamming distances.
  • Applied these models to analyze the genetic features of bacterial genes.
  • Focused on comparing gram-positive and gram-negative bacteria.

Main Results:

  • The study presents a novel mathematical framework to quantify the effect of genetic code degeneracy.
  • The models successfully captured characteristic features of bacterial genes.
  • Demonstrated a potential to differentiate between gram-positive and gram-negative bacteria based on genetic code bias.

Conclusions:

  • This research provides the first mathematical model to address the impact of genetic code degeneracy on biological properties.
  • The findings offer a new perspective on understanding the behavioral differences between bacterial groups.
  • Opens avenues for exploring differential biological properties driven by codon bias.