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Related Concept Videos

RNA-seq03:21

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...
Ribosome Profiling02:24

Ribosome Profiling

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
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Related Experiment Video

Updated: Jun 14, 2026

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing
09:49

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing

Published on: December 3, 2019

Deep sequencing of coding and non-coding RNA in the CNS.

Marcel van der Brug1, Michael A Nalls, Mark R Cookson

  • 1Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, 35 Convent Drive, Bethesda, MD 20892, USA.

Brain Research
|March 24, 2010
PubMed
Summary

Deep sequencing offers a powerful, unbiased method for analyzing gene expression. This technology enables detailed RNA analysis, including alternative splicing and untranslated regions, advancing brain research.

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Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing (DIVA-Seq)

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Last Updated: Jun 14, 2026

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing
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Published on: December 3, 2019

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06:38

Isolation of Adult Spinal Cord Nuclei for Massively Parallel Single-nucleus RNA Sequencing

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Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing (DIVA-Seq)
07:49

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing (DIVA-Seq)

Published on: October 26, 2018

Area of Science:

  • Genomics
  • Molecular Biology
  • Neuroscience

Background:

  • Traditional gene expression analysis methods like cloning and microarrays have limitations.
  • The need for high-throughput, unbiased quantification of biological events is growing.
  • Advancements in sequencing technology offer new possibilities for biological research.

Purpose of the Study:

  • To review deep sequencing techniques for identifying and quantifying RNA species.
  • To highlight the advantages of deep sequencing, such as high coverage depth.
  • To discuss the application of deep sequencing in brain gene expression studies.

Main Methods:

  • Deep sequencing (also known as next-generation sequencing) for massively parallel RNA identification and quantification.
  • Analysis of alternative splicing and untranslated region (UTR) utilization.
  • Application of these methods to characterize gene expression in the brain.

Main Results:

  • Deep sequencing provides high-depth coverage, enabling detailed analysis of RNA.
  • This technique allows for the identification of novel RNA species and isoforms.
  • Applications in brain research reveal complex gene expression patterns.

Conclusions:

  • Deep sequencing is a transformative technology for gene expression analysis.
  • Its high-throughput nature and depth of coverage offer significant advantages over older methods.
  • Future developments in deep sequencing will further enhance our understanding of biological systems, particularly in neuroscience.