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Related Concept Videos

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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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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Related Experiment Video

Updated: Sep 28, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Clinical and translational values of spatial transcriptomics.

Linlin Zhang1, Dongsheng Chen2, Dongli Song1

  • 1Zhongshan Hospital, Department of Pulmonary and Critical Care Medicine, Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Shanghai, 200000, China.

Signal Transduction and Targeted Therapy
|April 2, 2022
PubMed
Summary
This summary is machine-generated.

Spatial transcriptomics (ST) combined with single-cell RNA sequencing (scRNA-seq) reveals in situ intercellular communication and molecular pathogenesis. This review evaluates ST

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Area of Science:

  • Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • Spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) are crucial for linking tissue pathology with molecular changes.
  • These technologies enable the study of in situ intercellular molecular communications and spatiotemporal molecular medicine.

Purpose of the Study:

  • To overview the development of ST.
  • To evaluate the clinical and translational value of ST for understanding disease pathogenesis and identifying biomarkers.
  • To compare sequencing-based and imaging-based ST technologies, highlighting their opportunities and challenges.

Main Methods:

  • Review of ST development, including sequencing- and imaging-based technologies.
  • Discussion of bioinformatics tools for analyzing spatial gene expression patterns and cellular interactions.
  • Exploration of ST applications in various human diseases.

Main Results:

  • ST offers a powerful approach to bridge pathology and molecular alterations in human tissues.
  • Comparison of ST technologies reveals distinct advantages and disadvantages.
  • Bioinformatics tools are essential for dissecting spatial data and understanding cellular interactions.

Conclusions:

  • ST has significant potential in clinical and translational medicine, with applications in neurology, embryo development, oncology, and inflammation.
  • Successful translation of ST from bench to clinic requires clear clinical objectives, optimized protocols, and simplified analysis.
  • Addressing challenges in repeatability and interpretation is key for clinical implementation of ST.