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

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.

Sanger Sequencing

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

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...

Complementary DNA

Complementary DNA

Complementary DNA

Complementary DNA

Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

You might also read

Related Articles

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

Sort by

Same author

Health Risk and Pathogenesis of PM<sub>2.5</sub> in Human Systems.

Toxics·2026

Same author

Alcohol consumption and molecular subtypes of colorectal cancer: pooled observational and Mendelian randomization analyses.

The American journal of clinical nutrition·2026

Same author

Androgen activity in the male embryonic hindbrain drives lethal PFA ependymoma.

Nature·2026

Same author

Association of germline variants with KRAS-mutation status in colorectal cancer.

Scientific reports·2026

Same author

Discovery of myristic acid, from chick early amniotic fluid for the treatment of acute gastric ulcers by targeting pyruvate carboxylase to improve TCA cycle.

The Journal of nutritional biochemistry·2026

Same author

A novel synergistic action of phage vB_PaeP_GZMU_A1002 with allicin against carbapenem-resistant Pseudomonas aeruginosa.

Biology direct·2026

Same journal

Chromosomal scale genome assembly of medicinal plant Sophora tonkinensis.

BMC genomics·2026

Same journal

Variant-specific RNA testing resolves variants of uncertain significance in exome testing.

BMC genomics·2026

Same journal

Kaiso overexpression promotes an interferon immune response in murine intestines.

BMC genomics·2026

Same journal

Genomic evidence of ecological flexibility and cross-niche CRISPR spacerome targeting phage-plasmid hybrids in Latilactobacillus curvatus.

BMC genomics·2026

Same journal

Fgf evolution in vertebrates: insights from cyclostomes.

BMC genomics·2026

Same journal

Metabolic reprogramming, oxidative stress, and mitophagy in JSRV Env-transformed BEAS-2B cells: insights from integrated transcriptomics and metabolomics.

BMC genomics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 9, 2026

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

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

Published on: April 4, 2018

Cloud-based uniform ChIP-Seq processing tools for modENCODE and ENCODE.

Quang M Trinh¹, Fei-Yang Arthur Jen, Ziru Zhou

¹Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800, Toronto, ON, M5G 0A3, Canada.

|July 24, 2013

Summary

This summary is machine-generated.

The modENCODE project offers a vast encyclopedia of functional genomic elements for C. elegans and D. melanogaster. New cloud-based resources and Galaxy workflows simplify data analysis, enabling reproducible research and efficient knowledge extraction from large genomic datasets.

More Related Videos

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Related Experiment Videos

Last Updated: May 9, 2026

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

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

Published on: April 4, 2018

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Area of Science:

Genomics
Bioinformatics
Model Organism Research

Background:

The Model Organism ENCyclopedia of DNA Elements (modENCODE) project provides extensive functional genomic data for C. elegans and D. melanogaster.
The large volume of modENCODE data (nearly 10 terabytes) presents challenges for researchers seeking to extract meaningful biological insights.
Reinterpreting or combining modENCODE data with other datasets requires significant time and logistical effort.

Purpose of the Study:

To address the challenges of analyzing large modENCODE datasets.
To provide accessible and standardized computational resources for modENCODE data analysis.
To facilitate reproducible research by offering consistent analytical frameworks.

Main Methods:

Release of uniform computing resources on cloud platforms (Amazon Cloud, Bionimbus Cloud) integrated with Galaxy.
Development of specific Galaxy workflows for analyzing ChIP-seq data, adhering to established quality control (QC) and peak calling standards.
Creation of pre-configured machine images for cloud environments, including Galaxy, modENCODE data, and all necessary software dependencies.

Main Results:

Uniform computing resources and Galaxy workflows are now available for analyzing modENCODE data.
Cloud-based machine images simplify the setup and execution of complex genomic analyses.
Standardized QC and peak calling ensure consistency across different research groups.

Conclusions:

The provided resources establish a framework for consistent and reproducible analyses of modENCODE data.
Researchers can now focus more on biological interpretation and less on data management and infrastructure setup.
Enhanced accessibility to modENCODE data promotes efficient knowledge discovery in model organism genomics.