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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: Aug 29, 2025

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
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Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular

Kyoko Muto1, Issei Tsuchiya1, Soo Hyeon Kim2

  • 1Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan.

Scientific Reports
|September 12, 2022
PubMed
Summary
This summary is machine-generated.

We developed semibulk RNA sequencing (sbRNA-seq), a cost-effective method to link gene expression with spatial context. This technique reveals cellular interactions missed by single-cell RNA sequencing, enhancing biological data interpretation.

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Area of Science:

  • Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • Single-cell RNA sequencing (scRNA-seq) lacks spatial context, limiting biological interpretation.
  • Understanding cell location and microenvironment is crucial for analyzing scRNA-seq data.
  • Existing spatial transcriptomics platforms can be costly and complex.

Purpose of the Study:

  • To develop an inexpensive, high-throughput method preserving spatial organization for RNA sequencing.
  • To introduce semibulk RNA sequencing (sbRNA-seq) for associating spatial and gene expression data.
  • To validate sbRNA-seq's utility in both animal models and human disease specimens.

Main Methods:

  • Utilized a microfluidic device to encapsulate barcoded beads and cell aggregates (semibulks) into single droplets.
  • Performed sbRNA-seq on mouse kidney and human breast cancer specimens.
  • Validated findings using spatial transcriptome analysis.

Main Results:

  • Successfully associated pathological and gene expression information in mouse kidney models.
  • Demonstrated high consistency between sbRNA-seq and spatial transcriptome analysis results.
  • Identified spatial interactions between immune cells and cancer-associated fibroblasts in human breast cancer, which were not clear from scRNA-seq alone.

Conclusions:

  • Semibulk RNA sequencing (sbRNA-seq) offers a convenient and versatile approach to integrate spatial information with transcriptome data.
  • sbRNA-seq provides valuable insights into cellular microenvironments and interactions.
  • This method enhances the biological interpretation of sequencing data, particularly for complex tissues and diseases.