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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...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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...
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...

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

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ASPIC: a web resource for alternative splicing prediction and transcript isoforms characterization.

Tiziana Castrignanò1, Raffaella Rizzi, Ivano Giuseppe Talamo

  • 1Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universita' e Ricerca, CASPUR, Rome, Italy.

Nucleic Acids Research
|July 18, 2006
PubMed
Summary
This summary is machine-generated.

This article introduces a web-based tool designed to help researchers identify and analyze different versions of messenger RNA produced from the same gene, a process known as alternative splicing. By comparing genomic data with known transcript sequences, the platform provides detailed visual and structural information about these variations to improve gene annotation.

Keywords:
alternative splicingmRNA isoformsgene annotationbioinformatics tools

Frequently Asked Questions

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Area of Science:

  • Bioinformatics and computational biology research within ASPIC genomics
  • Molecular genetics and transcriptomics

Background:

No prior work had resolved how to fully integrate diverse transcriptomic datasets into accessible annotation pipelines. It was already known that gene expression complexity relies heavily on diverse mRNA processing events. That uncertainty drove the development of improved computational strategies for identifying these patterns. Prior research has shown that eukaryotic genomes utilize specific mechanisms to expand their functional repertoire. This gap motivated the creation of specialized platforms for analyzing structural variations in gene products. Scientists previously struggled to synthesize massive sequence repositories into coherent biological insights. That limitation hindered our understanding of how single loci generate multiple functional outcomes. The current landscape requires robust digital infrastructure to manage the growing volume of available biological information.

Purpose Of The Study:

The primary aim of this project involves creating a web-based resource for predicting alternative splicing and characterizing transcript isoforms. The authors sought to address the challenge of underutilized information in current genome annotation pipelines. They intended to provide a platform that simplifies the investigation of complex gene expression patterns. The researchers aimed to leverage the vast amount of available sequence data to improve biological insights. They wanted to build a tool that offers both graphical and tabular outputs for easier data interpretation. The project was motivated by the need for more comprehensive methods to analyze mRNA structural variations. They aimed to connect their algorithm with major public databases for enhanced functionality. The team sought to empower users to analyze their own genes through an accessible online facility.

Main Methods:

The developers implemented a specialized algorithm within a web-based framework to facilitate user-driven investigations. Their approach relies on the systematic comparison of transcript sequences against reference genomic data. The team designed the interface to handle submissions from diverse biological species. They integrated dynamic links to established public databases to enhance the depth of structural information. The architecture supports both visual and numerical representations of predicted splicing events. Researchers access these features through a centralized online portal. The system includes a dedicated facility for uploading custom sequence files for immediate processing. This design focuses on streamlining the interpretation of complex gene expression data.

Main Results:

The platform successfully generates graphical and tabular views of splicing patterns for investigated genes. It identifies all full-length mRNA isoforms that align with detected splice sites. The resource effectively integrates data from Ensembl and Unigene to provide functional context. It offers a comprehensive solution for detecting patterns that standard pipelines often miss. The tool processes sequences from a wide variety of species to support broad research applications. It provides structural annotations for each predicted variant to clarify its biological relevance. The system demonstrates high compatibility with existing genomic information sources. Users obtain detailed insights into the coding capacity of genes through this unified digital environment.

Conclusions:

The authors propose that their platform enhances the utility of existing genomic databases for researchers. They suggest that integrating diverse data sources improves the accuracy of transcript isoform identification. The team claims that their web resource facilitates a more comprehensive view of gene structure. They indicate that the tool supports the investigation of splicing patterns across various species. The researchers conclude that their approach addresses limitations in current annotation pipelines. They imply that the graphical outputs assist in interpreting complex mRNA variants. The study demonstrates that computational tools can effectively bridge the gap between raw sequence data and functional annotation. They maintain that their resource provides a versatile environment for exploring the coding capacity of eukaryotic genomes.

The platform identifies alternative splicing patterns by performing a comparative analysis of user-provided transcript sequences against existing genomic data. This mechanism allows the system to predict all full-length mRNA isoforms that remain compatible with the detected splice sites within a specific gene locus.

The resource utilizes the ASPIC algorithm to process data. It also maintains dynamic interconnections with external repositories, specifically the Ensembl and Unigene databases, to ensure that the structural and functional annotations provided to the user remain current and contextually relevant.

A web-based interface is necessary to provide users with graphical and tabular visualizations of splicing patterns. This format allows researchers to interact with complex structural data, which would otherwise remain difficult to interpret when using raw, unformatted sequence files from large genomic databases.

The upload facility acts as a primary input mechanism, enabling researchers to submit their own gene sequences for analysis. This component ensures that the tool remains flexible, allowing for the investigation of specific genes that might not yet be fully represented in standard public databases.

The system measures the compatibility of mRNA isoforms by evaluating them against identified splice sites. This phenomenon allows the software to filter out non-viable transcript structures, ensuring that the predicted isoforms are biologically plausible based on the provided genomic and transcriptomic evidence.

The researchers propose that their tool improves the overall quality of gene annotation. By utilizing information that is often overlooked by standard pipelines, they claim that their approach provides a more detailed characterization of the transcriptome than conventional methods currently offer.