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Related Concept Videos

RNA-seq03:21

RNA-seq

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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...
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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.
Applications of ribosome profiling
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Related Experiment Video

Updated: Sep 17, 2025

An Oligonucleotide-based Tandem RNA Isolation Procedure to Recover Eukaryotic mRNA-Protein Complexes
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eNRSA: a faster and more powerful approach for nascent transcriptome analysis.

Jing Wang1,2, Hua-Chang Chen1,2, Scott W Hiebert3,4

  • 1Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.

Gigascience
|July 4, 2025
PubMed
Summary

Nascent RNA sequencing analysis is improved with eNRSA, a faster and more versatile tool. It enhances the study of gene regulation and enhancer activity across diverse organisms and complex designs.

Keywords:
adaptive major transcriptalternative transcription start site (ATSS)alternative transcription termination site (ATTS)nascent transcriptome analysistranscription readthrough

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Nascent RNA sequencing (NRSA) is vital for studying gene regulation and enhancer activity in response to stimuli.
  • Existing NRSA tools have limitations in organism compatibility and handling complex study designs.

Purpose of the Study:

  • To develop an enhanced Nascent RNA sequencing analysis (eNRSA) tool.
  • To improve NRSA functionality, versatility, and speed for broader biological applications.

Main Methods:

  • Developed eNRSA with adaptive major transcript selection.
  • Enabled support for any organism and complex study designs.
  • Incorporated identification of alternative transcription start/termination sites and readthrough events.

Main Results:

  • eNRSA offers enhanced capabilities for analyzing nascent transcriptomic data.
  • Achieved approximately a 20-fold increase in analysis speed.
  • Significantly reduced memory usage compared to previous tools.

Conclusions:

  • eNRSA is a faster, more versatile, and powerful tool for nascent transcriptome analysis.
  • Expanded applicability to diverse organisms and complex experimental designs.
  • Facilitates deeper insights into gene regulation and enhancer function.