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Related Experiment Video

Updated: Sep 6, 2025

Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms

Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms

Published on: February 2, 2024

Analysis of mRNA Dynamics Using RNA Sequencing Data.

Rached Alkallas^1,2,3, Hamed S Najafabadi^4,5

¹Department of Human Genetics, McGill University, Montréal, QC, Canada.

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

|July 1, 2022

Summary

This summary is machine-generated.

This study introduces a new method to estimate RNA decay rates using standard RNA sequencing data. This approach helps identify regulatory factors influencing gene expression changes in diseases like Alzheimer's.

Keywords:

Alzheimer’s disease Posttranscriptional regulation RNA binding proteins RNA decay RNA degradation RNA stability RNA-seq microRNAs

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Last Updated: Sep 6, 2025

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Published on: February 2, 2024

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Published on: September 18, 2021

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

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Published on: December 9, 2022

Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

Gene expression is regulated by transcription and RNA decay rates.
Current methods to measure these rates are complex and often limited to in vitro settings.
Most transcriptomic studies analyze RNA abundance changes without distinguishing regulatory mechanisms.

Purpose of the Study:

To develop a protocol for estimating differential RNA stability from standard RNA sequencing data.
To enable the identification of regulatory factors controlling RNA expression.
To apply the protocol to in vivo data and infer regulatory mechanisms in Alzheimer's disease.

Main Methods:

Utilized standard RNA sequencing data.
Developed a protocol to estimate differential RNA molecule stability between conditions.
Applied the protocol to in vivo RNA-seq data from Alzheimer's disease patients.

Main Results:

Successfully estimated differential RNA stability without transcription inhibition or metabolic labeling.
Demonstrated the application of the protocol to identify regulatory factors in Alzheimer's disease.

Conclusions:

The developed protocol offers a feasible method to study RNA decay dynamics using existing RNA-seq data.
This approach facilitates the inference of regulatory factors driving gene expression changes in disease contexts.