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

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.

Quantifying and Rejecting Outliers: The Grubbs Test

Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier. To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...

Gene Duplication and Divergence

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.

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.

Organization of Genes

Organization of Genes

You might also read

Related Articles

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

Sort by

Same author

Grizzly bear population genomics across a coastal-interior ecotone in British Columbia, Canada.

G3 (Bethesda, Md.)·2025

Same author

Transcription Dynamics and DNA Methylation Responses to Growth Modification.

Marine biotechnology (New York, N.Y.)·2025

Same author

The genome assembly of the westslope cutthroat trout, Oncorhynchus lewisi, reveals interspecific chromosomal rearrangements with the rainbow trout, Oncorhynchus mykiss.

G3 (Bethesda, Md.)·2025

Same author

Masu salmon species complex relationships and sex chromosomes revealed from analyses of the masu salmon (Oncorhynchus masou masou) genome assembly.

G3 (Bethesda, Md.)·2024

Same author

Design principles for molecular animation.

Frontiers in bioinformatics·2024

Same author

Loss of genetic variation and ancestral sex determination system in North American northern pike characterized by whole-genome resequencing.

G3 (Bethesda, Md.)·2024

Search research articles

Related Experiment Video

Updated: May 30, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

GO Trimming: Systematically reducing redundancy in large Gene Ontology datasets.

Stuart G Jantzen¹, Ben Jg Sutherland, David R Minkley

¹Department of Biology & Centre for Biomedical Research, University of Victoria, Victoria, British Columbia, V8W 3N5, Canada. bkoop@uvic.ca.

BMC Research Notes

|July 30, 2011

Summary

GO Trimming is a novel method that reduces redundancy in gene ontology (GO) enrichment lists. This tool helps researchers analyze more manageable and informative GO lists, improving transcriptomic data interpretation.

More Related Videos

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Related Experiment Videos

Last Updated: May 30, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Transcriptomic analyses are increasingly accessible, necessitating standardized data processing and interpretation.
Gene Ontology (GO) analysis is crucial for understanding biological functions but often yields redundant terms.
Existing methods for GO enrichment analysis lack efficient ways to remove redundant terms.

Purpose of the Study:

To introduce a novel method, GO Trimming, for reducing redundancy in enriched GO category lists.
To provide a user-adjustable stringency for removing redundant GO terms.
To offer a more manageable and informative output for GO enrichment analyses.

Main Methods:

Development of a novel algorithm for GO Trimming.
Application of GO Trimming to reduce redundancy in enriched GO lists.
Comparison of GO Trimming with existing methods for redundancy reduction.

Main Results:

GO Trimming successfully reduced an initial list of 90 GO terms to 54, eliminating 36 redundant terms.
The method effectively eliminates redundant terms across the GO hierarchy.
GO Trimming performs well in reducing redundancy, even in large datasets.

Conclusions:

GO Trimming offers a valuable alternative to existing methods for managing redundant GO terms.
This method enables concise presentation of manageable and informative GO lists.
The GO Trimming tool is freely available for implementation.