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Related Concept Videos

RNA-seq03:21

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 microarray-based...
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific primer.
Since the...
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...

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Related Experiment Video

Updated: Jul 6, 2026

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries
07:35

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries

Published on: December 1, 2023

Computational Prediction of Chimeric RNAs from Long Reads Using CTAT-LR-Fusion.

Shafaque Zahra1, Hui Li2,3

  • 1Department of Pathology, University of Virginia, Charlottesville, VA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|July 4, 2026
PubMed
Summary

Accurate identification of chimeric transcripts is vital for understanding diseases and developing therapies. This guide details CTAT-LR-fusion for predicting fusion transcripts using long-read RNA sequencing, enhancing cancer and genetic disease research.

Keywords:
CTAT-LR-fusion toolChimeric RNAComputational biologyFusion transcriptsLong-read RNA sequencingPacBio HiFiRNA-seqTranscriptomics

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Last Updated: Jul 6, 2026

Computational Analysis Tutorial for Chimeric Small Noncoding RNA: Target RNA Sequencing Libraries
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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

  • Genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • Chimeric or fusion transcripts are critical in disease mechanisms and therapeutic targeting.
  • Accurate identification of these transcripts is essential for biological and medical research.
  • Long-read RNA sequencing offers superior detection of complex transcriptomic structures compared to short-read methods.

Purpose of the Study:

  • To provide a comprehensive guide to computational prediction of fusion transcripts using long-read RNA sequencing data.
  • To introduce CTAT-LR-fusion as a tool for analyzing long-read RNA-seq data.
  • To offer a practical framework for researchers investigating the fusion transcript landscape.

Main Methods:

  • Utilizing long-read RNA sequencing technologies for transcriptomic analysis.
  • Employing the CTAT-LR-fusion computational tool for predicting fusion transcripts.
  • Discussing key features, installation, and usage of CTAT-LR-fusion.

Main Results:

  • Demonstration of CTAT-LR-fusion's capability in identifying full-length fusion transcripts.
  • Detailed explanation of output interpretation for practical application.
  • Highlighting the advantages of long-read sequencing in detecting complex chimeric RNAs.

Conclusions:

  • Long-read RNA sequencing and tools like CTAT-LR-fusion are transforming the study of transcriptomic complexity.
  • Accurate prediction of fusion transcripts aids in understanding cancer and genetic diseases.
  • This guide equips researchers with the knowledge to explore the fusion transcript landscape effectively.