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Related Concept Videos

Pre-mRNA Processing: RNA Splicing01:32

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...
RNA Splicing01:32

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 Splicing01:32

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 Splicing02:18

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 Splicing02:18

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...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

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Related Experiment Video

Updated: Jun 28, 2026

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

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

Published on: December 9, 2016

Decoding splicing variants in high-throughput sequencing: a functional validation approach integrating deep learning

Clément Hersent1,2, Lise Larrieu3, Patricia Fergelot4

  • 1Laboratoire de Génétique Moléculaire de Maladies Rares, Site Unique de Biologie, CHU de Montpellier, Montpellier, France. clement.hersent@inserm.fr.

European Journal of Human Genetics : EJHG
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

Predicting the impact of intronic variants on RNA splicing is challenging. Combining multiple prediction tools with functional studies revealed splicing abnormalities in most neurodegenerative disease cases, highlighting the need for transcript analysis in diagnostics.

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Related Experiment Videos

Last Updated: Jun 28, 2026

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

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
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • High-throughput sequencing identifies intronic variants in disease genes.
  • Predicting the splicing impact of these variants, especially atypical ones, remains difficult.
  • Deep learning and motif-based tools have limitations in detecting novel regulatory mechanisms.

Purpose of the Study:

  • To evaluate the splicing consequences of intronic variants in neurodegenerative diseases.
  • To assess the performance of various splicing prediction tools, including deep learning and motif-based approaches.
  • To investigate the role of splicing enhancers and regulatory proteins like SRSF2.

Main Methods:

  • Selection of nine intronic variants with uncertain splicing impact from neurodegenerative disease patients.
  • Application of multiple complementary splicing prediction tools.
  • Functional RNA studies including transcript analysis in blood and minigene assays.

Main Results:

  • Splicing abnormalities were detected in eight of nine tested variants.
  • All tested prediction algorithms showed limitations, missing certain splicing events or generating false positives.
  • A deep intronic variant activated a splicing enhancer, potentially involving SRSF2 and leading to pseudoexon inclusion.

Conclusions:

  • Splicing prediction tools are complementary but not fully sufficient for pathogenicity assessment.
  • Transcript-level confirmation is critical for accurate interpretation of intronic variants.
  • Integrating diverse prediction methods and functional validation is essential for diagnostic pipelines.