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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...

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...

pre-mRNA Processing

pre-mRNA Processing

In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a “cap” to the 5’ end of the growing transcript. In this process, a 5’ phosphate is replaced by modified guanosine that has a methyl group attached to it (7-Methyl...

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Related Experiment Video

Updated: Jan 11, 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

IPScan: Detecting novel intronic PolyAdenylation events with RNA-seq data.

Naima Ahmed Fahmi¹, Sze Cheng², Jeovani Overstreet¹

¹Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America.

Plos Computational Biology

|November 11, 2025

Summary

This summary is machine-generated.

Intronic PolyAdenylation (IPA) generates diverse protein isoforms, impacting cancer. A new tool, IPScan, precisely identifies and quantifies these events, aiding cancer research.

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Last Updated: Jan 11, 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

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

Published on: December 2, 2009

Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

Intronic PolyAdenylation (IPA) is a post-transcriptional mechanism that increases transcriptome and proteome diversity by truncating transcript coding regions.
This process generates novel protein isoforms, some linked to cancer progression, potentially by losing tumor-suppressive functions and contributing to oncogenesis.
Existing RNA-seq methods face challenges in accurately detecting and quantifying novel IPA events.

Purpose of the Study:

To develop a computational pipeline, IPScan, for precise identification, quantification, and visualization of Intronic PolyAdenylation events.
To address the limitations of current methods in detecting and quantifying novel IPA events.

Main Methods:

Development of the IPScan computational pipeline for IPA event analysis.
Benchmarking IPScan against existing methods using simulated data, human and mouse cell lines.
Analysis of The Cancer Genome Atlas (TCGA) breast cancer datasets.
Quantification and validation of differential IPA events using qPCR.

Main Results:

IPScan enables precise identification, quantification, and visualization of IPA events.
The pipeline demonstrated robust performance when benchmarked against existing methods and real-world datasets, including TCGA breast cancer data.
Differential IPA events were successfully quantified under various biological conditions and validated experimentally.

Conclusions:

IPScan is an effective computational tool for the accurate detection and quantification of Intronic PolyAdenylation events.
This tool can advance the understanding of IPA's role in biological processes, particularly in cancer.
The findings highlight the importance of IPA in generating protein diversity and its implications in oncogenesis.