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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.
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Related Experiment Video

Updated: Sep 29, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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Research Techniques Made Simple: Spatial Transcriptomics.

Arianna J Piñeiro1, Aubrey E Houser1, Andrew L Ji1

  • 1Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

The Journal of Investigative Dermatology
|March 25, 2022
PubMed
Summary
This summary is machine-generated.

Spatial transcriptomics (ST) maps gene expression within intact tissues, preserving spatial information lost in traditional methods. This approach enhances understanding of cell interactions in skin homeostasis and disease.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Dermatology

Background:

  • Transcriptome profiling reveals gene expression but often loses spatial context.
  • Tissue homogenization and cell dissociation disrupt the in situ architecture.
  • Understanding spatial gene expression is crucial for complex biological systems.

Purpose of the Study:

  • To review spatial transcriptomics (ST) methods.
  • To summarize ST data analysis, including integration with single-cell transcriptomics.
  • To discuss ST applications in dermatologic research.

Main Methods:

  • Review of existing spatial transcriptomics technologies.
  • Summary of computational approaches for ST data analysis.
  • Exploration of ST applications in skin biology.

Main Results:

  • Spatial transcriptomics preserves the in situ spatial contexts of RNA molecules.
  • ST enables the localization of cell types and gene expression within intact tissues.
  • ST methods are being applied to study skin homeostasis and disease.

Conclusions:

  • Spatial transcriptomics offers a powerful approach to investigate tissue architecture and cellular interactions.
  • ST provides novel insights into niche patterning and cell-cell communication in heterogeneous tissues.
  • This technology holds significant promise for advancing dermatologic research and understanding skin diseases.