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 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...

RNA Splicing

RNA Splicing

Pre-mRNA Processing: RNA Splicing

Pre-mRNA Processing: RNA Splicing

Chromatin Structure and RNA Splicing

Chromatin Structure and RNA Splicing

Alternative RNA Splicing

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...

Alternative RNA Splicing

Alternative RNA Splicing

You might also read

Related Articles

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

Sort by

Same author

The RNA binding protein ZFP36L2 displays tissue-selective mRNA targeting in mice.

RNA biology·2026

Same author

FINDER converts zero-background kinetic fingerprinting into area-scalable attomolar biomarker detection.

bioRxiv : the preprint server for biology·2026

Same author

Open questions on viral frameshifting: Exploiting the structural plasticity of the frameshifting element for therapeutic intervention.

Biophysical journal·2026

Same author

ASPL-driven subunit exchange remodels VCP/p97 hexamers and is impaired by a multisystem proteinopathy mutation.

bioRxiv : the preprint server for biology·2026

Same author

Genome-wide chromatin recording resolves dynamic cell state changes.

bioRxiv : the preprint server for biology·2026

Same author

Npl4 decodes polyubiquitin length and gates D1-D2 coupling in human VCP/p97.

bioRxiv : the preprint server for biology·2026

Same journal

ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.

Nature methods·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

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 2, 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

Single Molecule Cluster Analysis dissects splicing pathway conformational dynamics.

Mario R Blanco^1,2, Joshua S Martin³, Matthew L Kahlscheuer¹

¹Department of Chemistry, Single Molecule Analysis Group, University of Michigan, Ann Arbor, Michigan, USA.

|September 29, 2015

Summary

This summary is machine-generated.

Single Molecule Cluster Analysis (SiMCAn) deciphers complex biomolecular dynamics using single-molecule fluorescence resonance energy transfer (smFRET). This method reveals key conformations and mechanisms in cellular machines like the spliceosome.

More Related Videos

A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

Published on: September 15, 2021

Merging Absolute and Relative Quantitative PCR Data to Quantify STAT3 Splice Variant Transcripts

Merging Absolute and Relative Quantitative PCR Data to Quantify STAT3 Splice Variant Transcripts

Published on: October 9, 2016

Related Experiment Videos

Last Updated: Apr 2, 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

A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

Published on: September 15, 2021

Merging Absolute and Relative Quantitative PCR Data to Quantify STAT3 Splice Variant Transcripts

Merging Absolute and Relative Quantitative PCR Data to Quantify STAT3 Splice Variant Transcripts

Published on: October 9, 2016

Area of Science:

Biophysics
Molecular Biology
Computational Biology

Background:

Biomolecular machines exhibit complex conformational dynamics crucial for their function.
Analyzing these dynamics at the single-molecule level is essential for understanding cellular processes.
Existing methods may face challenges in dissecting intricate dynamic behaviors.

Purpose of the Study:

To introduce Single Molecule Cluster Analysis (SiMCAn), a novel computational method.
To apply SiMCAn to investigate the conformational dynamics of the spliceosome during mRNA splicing.
To demonstrate SiMCAn's utility in identifying intermediate states and regulatory mechanisms.

Main Methods:

Utilizing hierarchical clustering of hidden Markov modeling-fitted single-molecule fluorescence resonance energy transfer (smFRET) trajectories.
Applying SiMCAn to analyze smFRET data from selectively blocked splicing reactions.
Studying the conformational dynamics of precursor mRNA during the spliceosome cycle.

Main Results:

SiMCAn successfully identified distinct conformations and dynamic behaviors of ATP-dependent spliceosome intermediates.
The method revealed an open conformation in a 3' splice-site mutant, suggesting a substrate proofreading mechanism.
SiMCAn enabled rapid interpretation of complex single-molecule behaviors.

Conclusions:

SiMCAn provides a powerful tool for dissecting complex conformational dynamics in biomolecular machines.
The study elucidates key mechanistic insights into the spliceosome's splicing cycle.
SiMCAn is broadly applicable for analyzing dynamic cellular machinery.