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Related Experiment Video

Updated: Nov 9, 2025

Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

Published on: October 7, 2021

Transcript Identification Through Long-Read Sequencing.

Masahide Seki¹, Miho Oka^1,2, Liu Xu¹

¹Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba, Japan.

Methods in Molecular Biology (Clifton, N.J.)

|April 9, 2021

Summary

This summary is machine-generated.

Long-read RNA sequencing (RNA-seq) identifies full-length RNA structures. A new analytical pipeline using minimap2, TranscriptClean, and TALON enhances isoform identification and expression level estimation from this data.

Keywords:

Alternative splicing Direct RNA sequencing Expression estimation Long-read sequencing Transcript isoform

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Last Updated: Nov 9, 2025

Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

Published on: October 7, 2021

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Long-read sequencing technologies like nanopore and Single Molecule, Real-Time (SMRT) sequencing offer unprecedented ability to resolve full-length RNA molecules.
The complexity of RNA isoforms necessitates advanced analytical tools for accurate characterization.

Purpose of the Study:

To introduce and validate a computational pipeline for analyzing long-read RNA-seq data.
To enable precise isoform identification and expression level estimation.
To highlight novel transcript isoforms discoverable only with long-read sequencing.

Main Methods:

Development of an analytical pipeline integrating minimap2, TranscriptClean, and TALON.
Application of the pipeline to public direct RNA-seq datasets from HAP1 and HEK293 cell lines.
Utilizing long-read sequencing data for comprehensive transcript analysis.

Main Results:

Successful identification of numerous full-length RNA isoforms.
Accurate estimation of transcript expression levels.
Discovery of previously undetected transcript isoforms unique to long-read sequencing.

Conclusions:

The developed pipeline is effective for analyzing long-read RNA-seq data.
Long-read RNA-seq significantly expands the understanding of the transcriptome.
This approach is crucial for comprehensive transcript isoform discovery and quantification.