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

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Phylogenetic Trees

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.

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...

You might also read

Related Articles

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

Sort by

Same author

Multi-region m<sup>6</sup>A epitranscriptome profiling of the human brain reveals spatial and temporal variation and enrichment of disease-associated loci.

Nature neuroscience·2025

Same author

Epitranscriptomic dysregulation in neurodegenerative diseases and its implications for disease pathology and mechanisms.

Neurochemistry international·2025

Same author

Recruitment of CTCF to an <i>Fto</i> enhancer is responsible for transgenerational inheritance of BPA-induced obesity.

Proceedings of the National Academy of Sciences of the United States of America·2022

Same author

Differential RNA methylation analysis for MeRIP-seq data under general experimental design.

Bioinformatics (Oxford, England)·2022

Same author

Epitranscriptomic dynamics in brain development and disease.

Molecular psychiatry·2022

Same author

Dysregulated mitochondrial and cytosolic tRNA m1A methylation in Alzheimer's disease.

Human molecular genetics·2021

Same journal

Tracking Synthetic Adhesins on Bacterial Surfaces with Immunofluorescence Microscopy.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Post-Selection Methods for Analyzing mRNA Display Selections and Optimization of Hits.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

High-Performance Computing in Tandem Mass Spectrometry (MS/MS) Peptide Identification.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Engineering and Adapting Disulfide-Containing Proteins to Enable Intracellular Functionality.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

AI-Driven Protein Research: From Prediction to Design.

Methods in molecular biology (Clifton, N.J.)·2026

Same journal

Methods for the In Vitro Selection of Protein and Peptide Libraries Using mRNA Display.

Methods in molecular biology (Clifton, N.J.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 12, 2025

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

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

Published on: December 9, 2022

Analyzing mRNA Epigenetic Sequencing Data with TRESS.

Zhenxing Guo¹, Andrew M Shafik², Peng Jin²

¹Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, GA, USA.

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

|February 1, 2023

Summary

This summary is machine-generated.

This study introduces TRESS, a Bioconductor package for analyzing MeRIP-seq data to identify N6-methyladenosine (m⁶A) modifications across transcriptomes. It provides detailed procedures for researchers to profile and understand gene regulation via RNA epigenetics.

Keywords:

Differential RNA methylation MeRIP-seq Peak detection RNA epigenetics

More Related Videos

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

Related Experiment Videos

Last Updated: Aug 12, 2025

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

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

Published on: December 9, 2022

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

RNA epigenetics, particularly N6-methyladenosine (m⁶A) modification, is crucial for gene regulation.
MeRIP-seq (m⁶A-RNA immunoprecipitation sequencing) is a key technology for profiling these modifications across the transcriptome.
Analyzing MeRIP-seq data is essential for identifying m⁶A-methylated regions and understanding their roles under various conditions.

Purpose of the Study:

To provide researchers with detailed, step-by-step procedures for MeRIP-seq data analysis.
To introduce and guide the use of the TRESS Bioconductor package for efficient MeRIP-seq analysis.
To facilitate the identification of m⁶A-methylated regions and their biological significance.

Main Methods:

Development and implementation of the TRESS Bioconductor package.
Detailed procedural guidelines for MeRIP-seq data analysis workflows.
Bioinformatic approaches for identifying m⁶A peaks and differential methylation.

Main Results:

The TRESS package offers a comprehensive pipeline for MeRIP-seq data analysis.
Step-by-step instructions enable researchers to effectively identify m⁶A modification sites.
The procedures facilitate comparative analyses across different biological conditions.

Conclusions:

TRESS provides a valuable resource for researchers studying RNA epigenetics and m⁶A modifications.
The package simplifies complex MeRIP-seq data analysis, promoting wider adoption and discovery.
Accurate identification of m⁶A regions using TRESS aids in understanding gene regulation.