Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

mRNA Stability and Gene Expression

mRNA Stability and Gene Expression

mRNA Stability and Gene Expression

mRNA Stability and Gene Expression

The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity.
Cis-acting Elements involved in mRNA stability

RNA Stability

RNA Stability

Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...

RNA Stability

RNA Stability

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Fusion gene heterogeneity and kinase enrichment in high-grade serous carcinomas.

Neoplasia (New York, N.Y.)·2026

Same author

Patient-derived organoids from metastatic colorectal cancer mirror tumor heterogeneity and predict patient survival and drug sensitivity.

Cell reports. Medicine·2026

Same author

CD38<sup>hi</sup>CD19<sup>dim</sup> cells in lymph nodes predict favorable prognosis in patients with stage III melanoma receiving adjuvant PD-1-blockade.

Frontiers in oncology·2026

Same author

Spatial Robustness of Prostate Cancer Biomarkers Evaluated by Spatial Transcriptomics.

The Prostate·2026

Same author

Pembrolizumab in advanced malignant peripheral nerve sheath tumors: a single-arm phase 2 trial.

NPJ precision oncology·2026

Same author

Common gene mutations in 103 authenticated colorectal cancer cell lines.

Oncogenesis·2026

Same journal

Widening Health Inequality and Causal Metabolic Drivers in Global Colorectal Cancer: A Multi-Dimensional Study.

Cancer informatics·2026

Same journal

GFAP-Dependent Transcriptional Dynamics and Cellular Heterogeneity in Primary, Recurrent, and Grade III Gliomas.

Cancer informatics·2026

Same journal

Translating Data Into Clinical Tools: An Integrative Strategy for Precision Biomarker Identification in Soft Tissue Sarcoma Diagnosis and Prognosis.

Cancer informatics·2026

Same journal

The MAPK Pathway Coordinates an Immunosuppressive Microenvironment in Colorectal Cancer: A Single-Cell Guided Prognostic Model.

Cancer informatics·2026

Same journal

Multi-Scale Cross-Attention Multiple Instance Learning Network for Automated Classification of Colorectal Polyps.

Cancer informatics·2026

Same journal

LEPR Contributes to Lung Squamous Cell Carcinoma: Insights From Mendelian Randomization and Experimental Studies.

Cancer informatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 1, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

TIN: An R Package for Transcriptome Instability Analysis.

Bjarne Johannessen¹, Anita Sveen¹, Rolf I Skotheim²

¹Department of Molecular Oncology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway ; Centre for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway.

Cancer Informatics

|October 9, 2015

Summary

This summary is machine-generated.

Transcriptome instability (TIN) is a novel splicing characteristic in cancers. The R package TIN analyzes aberrant exon usage and its correlation with splicing factors using microarray data.

Keywords:

R software alternative splicing exon microarray splicing factor transcriptome instability

More Related Videos

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Related Experiment Videos

Last Updated: Apr 1, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Area of Science:

Molecular Biology
Bioinformatics
Cancer Genomics

Background:

Alternative splicing regulates eukaryotic gene expression and is crucial for cellular function.
Dysregulated pre-mRNA splicing contributes to human disease development and progression.
High-throughput technologies enable genome-wide detection of mRNA isoforms and aberrant splicing.

Purpose of the Study:

To introduce the R package TIN for analyzing transcriptome instability (TIN).
To provide tools for estimating aberrant exon usage from exon-level microarray data.
To facilitate the analysis of correlations between TIN and splicing factor expression.

Main Methods:

Development of the R package TIN, available via Bioconductor.
Utilizes exon-level microarray expression profiles for analysis.
Implements methods for estimating aberrant exon usage and correlation patterns.

Main Results:

The TIN package offers a computational framework for assessing genome-wide splicing patterns.
Enables the identification of aberrant exon usage across multiple samples.
Allows for the investigation of relationships between TIN and splicing factor expression.

Conclusions:

Transcriptome instability (TIN) is proposed as a genome-wide characteristic of certain solid cancers.
The TIN R package provides essential tools for researchers studying splicing alterations in cancer.
This approach aids in understanding the role of splicing dysregulation in oncogenesis.