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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 microarray-based...

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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.
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The technique helps...

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Related Experiment Video

Updated: May 26, 2026

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

High-throughput Screening of Sequence Elements Associated with RNA Localization.

Xinquan Zeng¹, Yusen Lin¹, Meiting Cai¹

¹Dermatology Hospital, Southern Medical University, Guangzhou 510180, China.

Computational and Structural Biotechnology Journal

|May 25, 2026

Summary

This summary is machine-generated.

We developed SRLE-seq, a sequencing method to identify RNA localization elements. This approach discovered novel elements controlling nuclear retention and export, improving RNA localization prediction accuracy.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Molecular Biology
Genomics
Cell Biology

Background:

RNA molecules must reach specific cellular locations for proper function.
Mechanisms governing RNA transport and subcellular localization are not fully understood.

Purpose of the Study:

To introduce SRLE-seq (Screening RNA Localization Elements by Sequencing) for identifying and prioritizing functional RNA localization elements.
To investigate novel sequence elements involved in RNA nuclear retention and export.

Main Methods:

Screening randomized fragments of MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) using SRLE-seq.
Analyzing 6-mer sequences for functions related to nuclear retention and export.
Integrating SRLE-seq nuclear retention scores into a deep learning model for RNA subcellular localization prediction.

Main Results:

SRLE-seq successfully identified known and two novel RNA nuclear retention elements.
Identified 110 6-mers associated with nuclear retention and 49 with nuclear export.
Incorporating SRLE-seq data improved RNA subcellular localization prediction accuracy to 72% using a deep learning model.
Discovered that identified 6-mers regulate RNA localization via RNA-binding proteins.

Conclusions:

SRLE-seq is an efficient sequencing-based method for prioritizing RNA localization elements.
The identified elements and SRLE-seq provide a valuable resource for studying RNA-binding protein-mediated RNA localization.