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.

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

You might also read

Related Articles

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

Sort by

Same author

One mother for two species via obligate cross-species cloning in ants.

Nature·2025

Same author

DNA methylome-wide alterations associated with estrogen receptor-dependent effects of bisphenols in breast cancer.

Clinical epigenetics·2019

Same author

Insights into the evolution of the new variant rabbit haemorrhagic disease virus (GI.2) and the identification of novel recombinant strains.

Transboundary and emerging diseases·2018

Same author

DNA methylation signal has a major role in the response of human breast cancer cells to the microenvironment.

Oncogenesis·2017

Same author

Positive selection on sperm ion channels in a brooding brittle star: consequence of life-history traits evolution.

Molecular ecology·2017

Same author

Discovery of parvovirus-related sequences in an unexpected broad range of animals.

Scientific reports·2016

Same journal

From Gene Copies to Cell Numbers: Advancing Quantitative Approaches in Protistan Ecology Using Digital PCR.

Molecular ecology resources·2026

Same journal

EasyCen: A Lightweight Framework for Centromere Localisation and Repeat-Organisation Profiling in Telomere-to-Telomere Genomes.

Molecular ecology resources·2026

Same journal

A Practical Framework for GT-Seq Panel Optimization.

Molecular ecology resources·2026

Same journal

Comparison of Environmental DNA and Bulk DNA Metabarcoding for Assessing Terrestrial Arthropod Diversity Across Three Habitat Types on Guam.

Molecular ecology resources·2026

Same journal

pr2-Wormifier: A Bioinformatics Pipeline to Create Custom Reference Databases for Improved Metabarcoding of Marine Protists.

Molecular ecology resources·2026

Same journal

Individual Identification of Prey in Carnivore Scats.

Molecular ecology resources·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 22, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Reference-free transcriptome assembly in non-model animals from next-generation sequencing data.

V Cahais¹, P Gayral, G Tsagkogeorga

¹CNRS UMR 5554, Institut des Sciences de l'Evolution de Montpellier, Université Montpellier 2, Place E. Bataillon, 34095 Montpellier, France.

Molecular Ecology Resources

|May 1, 2012

Summary

This summary is machine-generated.

Next-generation sequencing (NGS) enables population genomics in wild animals using transcriptomes. Combining sequencing data and filtering contigs improves gene assembly accuracy for genetic marker development.

More Related Videos

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

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Related Experiment Videos

Last Updated: May 22, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

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

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Area of Science:

Genomics
Bioinformatics
Animal Ecology

Background:

Next-generation sequencing (NGS) offers potential for population genomic studies in wild, non-model organisms.
Transcriptome sequencing is a popular approach, but assembling gene-coding sequences from short reads presents challenges like gene duplications and alternative splicing.

Purpose of the Study:

To develop and validate a robust method for assembling gene-coding sequences from NGS transcriptome data for non-model organisms.
To assess the quality of de novo transcriptome assemblies and identify strategies for improvement.

Main Methods:

Transcriptome assembly of five diverse non-model animal species using 454 and Illumina sequencing reads.
Development of a procedure to annotate assembled contigs using reference genomes (for two species).
Analysis of assembly quality based on contig length, coverage, and annotation.

Main Results:

Combining 454 and Illumina data yielded the highest quality transcriptome assemblies.
Standard de novo assemblies contained a significant proportion of irrelevant cDNA predictions.
Filtering contigs by length and coverage effectively cleaned the assemblies.

Conclusions:

Robust, reference-free assembly of thousands of genes from transcriptomic NGS data is achievable.
This facilitates transcriptome-based population genomics in animals.
A Galaxy pipeline for the optimized assembly strategy is provided.