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

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...

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...

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....

You might also read

Related Articles

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

Sort by

Same author

Phosphatidylserine and RhoB connect PI4P and PA metabolism to maintain plasma membrane identity.

The Journal of cell biology·2026

Same author

Singlet oxygen spills sterol secrets.

Nature chemical biology·2026

Same author

Structural innovation in the evolution of plant chemical defense.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Cullin-3 adaptor SHKBP1 inhibits SQSTM1/p62 oligomerization and Keap1 sequestration.

The Journal of cell biology·2026

Same author

Membrane editing with proximity labeling reveals regulators of lipid homeostasis.

Nature chemical biology·2026

Same author

Phosphatidylserine and RhoB connect phosphatidylinositol 4-phosphate and phosphatidic acid metabolism at the plasma membrane.

bioRxiv : the preprint server for biology·2025

Same journal

A human-specific genetic modifier reconfigures large-scale cortical network dynamics underlying behavioral performance.

bioRxiv : the preprint server for biology·2026

Same journal

<i>Staphylococcus aureus</i> uses a eukaryotic-like uridyltransferase to make UDP-GlcNAc for cell wall synthesis.

bioRxiv : the preprint server for biology·2026

Same journal

Dynamic redistribution of eIF4F controls cap-dependent translation initiation.

bioRxiv : the preprint server for biology·2026

Same journal

When does additional information improve accuracy of RNA secondary structure prediction?

bioRxiv : the preprint server for biology·2026

Same journal

Normative brain-state trajectories reveal deviation from healthy aging in Alzheimer's disease.

bioRxiv : the preprint server for biology·2026

Same journal

Noradrenergic infraslow rhythm during sleep is the critical link between heart-rate dynamics and memory consolidation.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 1, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

Barcode-free multiplex plasmid sequencing using Bayesian analysis and nanopore sequencing.

Masaaki Uematsu¹, Jeremy M Baskin^1,2

¹Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY, 14853, USA.

Biorxiv : the Preprint Server for Biology

|April 24, 2023

Summary

This summary is machine-generated.

We developed SAVEMONEY, a computational tool to multiplex plasmids for nanopore sequencing. This method significantly reduces the cost of whole-plasmid sequencing, making it more accessible for life science research.

More Related Videos

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Published on: December 14, 2017

Related Experiment Videos

Last Updated: Aug 1, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Published on: December 14, 2017

Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

Plasmid construction is essential in life science research.
Sequence verification is a costly bottleneck in plasmid construction.
Long-read sequencing offers whole-plasmid analysis but remains expensive for routine use.

Purpose of the Study:

To develop a cost-effective computational method for whole-plasmid sequencing.
To enable multiplexing of multiple plasmids for nanopore sequencing.
To reduce the cost of plasmid sequence verification.

Main Methods:

Developed SAVEMONEY (Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You), a computational approach.
SAVEMONEY optimizes plasmid mixtures for pre-sequencing analysis.
Post-sequencing analysis involves classification, alignment, and Bayesian consensus determination.

Main Results:

SAVEMONEY allows mixing plasmids differing by as few as two bases.
Multiplexing up to six plasmids per 180 reads maintains high consensus accuracy.
The method computationally de-mixes sequences from mixed samples.

Conclusions:

SAVEMONEY significantly reduces the effective cost of whole-plasmid sequencing.
This approach democratizes nanopore sequencing for routine plasmid verification.
The cost per run can be lower than traditional Sanger sequencing.