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Related Experiment Video

Updated: May 22, 2026

Generation and Downstream Analysis of Single-Cell and Single-Nuclei Transcriptomes in Brain Organoids
05:45

Generation and Downstream Analysis of Single-Cell and Single-Nuclei Transcriptomes in Brain Organoids

Published on: March 29, 2024

Application of spatial transcriptomics across organoids for a high-resolution, spatial whole-transcriptome

Maria Rosaria Nucera1,2,3, Natalie Charitakis1,2,3, Ryan F Leung1,2,3

  • 1Stem Cell Medicine Theme, Murdoch Children's Research Institute, Parkville, VIC, Australia.

Iscience
|May 21, 2026
PubMed

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Summary

This study introduces stereo-seq for spatial transcriptomics in stem cell-derived organoids. It optimizes RNA capture and analysis for accurate disease modeling and tissue characterization.

Area of Science:

  • Biotechnology
  • Genomics
  • Developmental Biology

Background:

  • Stem cell-derived organoids are valuable for modeling diseases.
  • Comparing organoids to in vivo tissues requires spatial transcriptomic analysis.
  • Current spatial transcriptomics methods face challenges in organoid applications.

Purpose of the Study:

  • To systematically profile multiple stem cell-derived organoids using spatial transcriptomics.
  • To optimize and validate stereo-seq for organoid characterization.
  • To develop novel analytical methods for regional analysis of organoid data.

Main Methods:

  • Utilized stereo-seq, a full transcriptome spatial assay with on-chip in situ RNA capture.
  • Applied the assay to diverse organoid models: brain, heart muscle, heart valve, kidney, lung, cartilage, and hematopoietic.
Keywords:
bioinformaticshealth sciencesmedicine

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Related Experiment Videos

Last Updated: May 22, 2026

Generation and Downstream Analysis of Single-Cell and Single-Nuclei Transcriptomes in Brain Organoids
05:45

Generation and Downstream Analysis of Single-Cell and Single-Nuclei Transcriptomes in Brain Organoids

Published on: March 29, 2024

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

  • Developed a bespoke analysis method for partitioning organoid samples into regions.

    • Main Results:

    • Demonstrated the feasibility of systematic spatial transcriptomic profiling across multiple organoid types.
    • Identified and addressed limitations in RNA capture efficiency compared to reference tissues.
    • Successfully applied a novel regional analysis method for organoid characterization.

    Conclusions:

    • Stereo-seq is a powerful tool for characterizing stem cell-derived organoids.
    • Optimized methods enhance RNA capture and enable detailed regional analysis.
    • Findings provide a foundation for advanced organoid-based disease modeling and research.