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...

RNA Splicing

RNA Splicing

Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...

You might also read

Related Articles

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

Sort by

Same author

Neural mechanisms of cough: insights from multimodal magnetic resonance imaging-a narrative review.

Journal of thoracic disease·2026

Same author

Optimizing Sowing Date and Nitrogen Management to Trade Off Yield and Nitrate Leaching in Maize-Soybean Intercropping Under CMIP6 Climate Scenarios in the North China Plain.

Plants (Basel, Switzerland)·2026

Same author

Single-nucleus profiling reveals a core disease signature and cell type-specific vulnerabilities in early Rett syndrome.

Science advances·2026

Same author

Histone deacetylase enzyme activity is not the universal anticancer target of HDAC inhibitors.

Signal transduction and targeted therapy·2026

Same author

Astrocytic ACSBG1 depletion improves lipid-cytokine signaling and attenuates α-Synuclein pathology in a Parkinson's disease mouse model.

bioRxiv : the preprint server for biology·2026

Same author

Correction: Misregulated alternative splicing in endometriosis: a role for aberrant mRNA variants in endometriotic cell growth.

Cell death discovery·2026

Same journal

Protein Sequence Analysis Using the MPI Bioinformatics Toolkit.

Current protocols in bioinformatics·2020

Same journal

Exploring Manually Curated Annotations of Intrinsically Disordered Proteins with DisProt.

Current protocols in bioinformatics·2020

Same journal

Network Building with the Cytoscape BioGateway App Explained in Five Use Cases.

Current protocols in bioinformatics·2020

Same journal

Expanding the Perseus Software for Omics Data Analysis With Custom Plugins.

Current protocols in bioinformatics·2020

Same journal

Exploring Non-Coding RNAs in RNAcentral.

Current protocols in bioinformatics·2020

Same journal

How to Illuminate the Dark Proteome Using the Multi-omic OpenProt Resource.

Current protocols in bioinformatics·2020

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 23, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Data Analysis Pipeline for RNA-seq Experiments: From Differential Expression to Cryptic Splicing.

Hari Krishna Yalamanchili^1,2, Ying-Wooi Wan^1,2, Zhandong Liu^2,3,4

¹Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.

Current Protocols in Bioinformatics

|September 14, 2017

Summary

This summary is machine-generated.

This study presents a comprehensive RNA sequencing (RNA-seq) analysis pipeline for understanding the transcriptome. It covers quality checks, gene expression, splicing events, and visualization for robust cellular system analysis.

Keywords:

RNA-seq alternative splicing cryptic splicing differential gene expression differential isoform usage

More Related Videos

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Published on: December 9, 2016

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Related Experiment Videos

Last Updated: Feb 23, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Published on: December 9, 2016

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

RNA sequencing (RNA-seq) is crucial for transcriptome analysis.
Understanding the entire transcriptome is vital for cellular system comprehension.
Existing RNA-seq pipelines have limitations in capturing full transcriptome dynamics.

Purpose of the Study:

To compile and present a robust, commonly used RNA-seq analysis pipeline.
To cover the entire spectrum of transcriptome analysis.
To highlight challenges, parameters, and downstream analyses for each step.

Main Methods:

Quality checks of RNA-seq reads.
Alignment of reads to a reference genome.
Differential gene and transcript expression analysis.
Discovery of cryptic splicing events.
Visualization of transcriptome data.

Main Results:

A comprehensive RNA-seq analysis pipeline is presented.
Key steps include quality control, alignment, expression analysis, splicing detection, and visualization.
Challenges and critical parameters for each step are discussed.

Conclusions:

The presented pipeline offers a thorough approach to transcriptome analysis.
It enhances understanding of cellular systems through detailed RNA-seq data interpretation.
This work provides a state-of-the-art RNA-seq analysis framework.