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

RNA-seq03:21

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...
Ribosome Profiling02:24

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

Cell-type-targeted mitochondrial transplantation rescues cell degeneration.

Nature·2026
Same author

Acute and chronic infections drive distinct trajectories in human memory CD4<sup>+</sup> T cell formation.

Immunity·2026
Same author

Cell-type-focused compound screen in human organoids reveals CK1 inhibition protects cone photoreceptors from death.

Neuron·2026
Same author

Bi-allelic variants in FSD1L cause retinitis pigmentosa with or without neurological involvement.

American journal of human genetics·2026
Same author

Single-cell profiling reveals diverse γδ T cell subsets in ulcerative colitis.

Science immunology·2026
Same author

Retinal ganglion cell survival and functional maturation in transiently vascularized human retinal organoids.

Cell stem cell·2026
Same journal

RNAbpFlow: base pair-augmented SE(3) flow matching for conditional RNA 3D structure generation.

Nature methods·2026
Same journal

Spatio-DARLIN enables robust and efficient in situ lineage tracing in mice at single-cell resolution.

Nature methods·2026
Same journal

EasyGrid: a versatile platform for automated cryo-EM sample preparation and quality control.

Nature methods·2026
Same journal

Cloud-based microscope enables live neuroimaging for 24 h and beyond with worldwide access.

Nature methods·2026
Same journal

Deep molecular profiling in three dimensions.

Nature methods·2026
Same journal

3D pathology-guided microdissection.

Nature methods·2026
See all related articles

Related Experiment Video

Updated: May 7, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Smart-seq2 for sensitive full-length transcriptome profiling in single cells.

Simone Picelli1, Åsa K Björklund, Omid R Faridani

  • 1Ludwig Institute for Cancer Research, Stockholm, Sweden.

Nature Methods
|September 24, 2013
PubMed
Summary
This summary is machine-generated.

Smart-seq2 enhances single-cell gene expression analysis by improving cDNA library yield and length. This novel method offers better detection, coverage, and accuracy for transcriptome studies at a lower cost.

More Related Videos

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Related Experiment Videos

Last Updated: May 7, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Area of Science:

  • Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • Single-cell gene expression analysis is crucial for understanding cellular heterogeneity.
  • Existing methods face limitations in coverage, sensitivity, or throughput.
  • There is a need for more efficient and cost-effective single-cell transcriptomics.

Purpose of the Study:

  • To introduce Smart-seq2, an improved method for single-cell RNA sequencing.
  • To enhance cDNA library yield, length, detection, coverage, and accuracy.
  • To provide a lower-cost, high-performance alternative for single-cell transcriptome analysis.

Main Methods:

  • Development of Smart-seq2 with optimized reverse transcription, template switching, and preamplification steps.
  • Generation of cDNA libraries from individual cells using the Smart-seq2 protocol.
  • Comparative analysis of Smart-seq2 libraries against previous Smart-seq libraries.

Main Results:

  • Smart-seq2 significantly increased the yield and length of cDNA libraries.
  • Improved detection sensitivity and coverage of the transcriptome were observed.
  • Reduced bias and enhanced accuracy in gene expression profiling were achieved.
  • The method utilizes off-the-shelf reagents, reducing overall costs.

Conclusions:

  • Smart-seq2 represents a substantial advancement in single-cell RNA sequencing technology.
  • The improved method offers superior performance in characterizing cellular heterogeneity.
  • Smart-seq2 provides a cost-effective and accurate solution for researchers in genomics and molecular biology.