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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

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...

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

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...

Pre-mRNA Processing: RNA Splicing

Pre-mRNA Processing: 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...

Chromatin Structure and RNA Splicing

Chromatin Structure and RNA Splicing

In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...

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Related Experiment Video

Updated: May 30, 2026

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

Bayesian prediction of tissue-regulated splicing using RNA sequence and cellular context.

Hui Yuan Xiong¹, Yoseph Barash, Brendan J Frey

¹Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.

Bioinformatics (Oxford, England)

|August 2, 2011

Summary

Researchers developed a new Bayesian method to decipher the splicing code, improving prediction accuracy by 52% and reducing classification errors by 22% for RNA splicing regulation.

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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

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Last Updated: May 30, 2026

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

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

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Alternative splicing significantly contributes to cellular diversity in mammals and is implicated in various human diseases.
Understanding the regulation of alternative splicing is crucial for advancing biological and medical research.

Purpose of the Study:

To infer a 'splicing code' that predicts RNA splicing regulation based on RNA, DNA, and epigenetic features across different cell types.
To develop a robust statistical method for analyzing complex splicing patterns and identifying regulatory mechanisms.

Main Methods:

A Bayesian statistical inference approach was employed, utilizing an adaptively selected number of hidden variables.
The method constructs a network by combining feature subgroups and allows for feature sharing across different tissues.
A Gibbs sampler was used for prediction hedging and to determine the statistical significance of identified features.

Main Results:

The developed method was benchmarked against existing approaches using data from 3665 cassette exons and 1014 RNA features across 4 mouse tissue types.
The Bayesian method demonstrated superior performance, achieving a 52% improvement in splicing code quality and up to a 22% reduction in classification error compared to state-of-the-art methods.
Novel combinations of regulatory features and tissue-specific feature subgroup sharing were identified.

Conclusions:

The novel Bayesian method provides a powerful tool for dissecting the complex 'splicing code' and understanding RNA splicing regulation.
This approach enhances the accuracy of predicting splicing patterns and offers new insights into the interplay of regulatory elements and tissue-specific splicing.
The findings have significant implications for disease research and the development of targeted therapies.