Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Ribosome Profiling

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...

Pleiotropy

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

IAPEz retrotransposons regulate the first lineage segregation in mouse pre-implantation development.

Nucleic acids research·2026

Same author

Developmental chronology of mouse embryo from 2-cell stage through birth.

Nature cell biology·2026

Same author

The 2025 Westlake Autumn Symposium for Al Proteomics and Virtual Cell.

Genomics, proteomics & bioinformatics·2026

Same author

Divergent stem cell mechanisms govern the primary body axis and appendage regeneration in the axolotl.

Science advances·2026

Same author

Nat10-mediated ac4C epitranscriptomics orchestrates hematopoietic stem/progenitor cell fate determination via translation control.

Science advances·2026

Same author

DECIPHER for learning disentangled cellular embeddings in large-scale heterogeneous spatial omics data.

Nature communications·2025

Same journal

Delocalized Redox Framework of Indanthrone Enables Low-Strain and Durable Mn<sup>2+</sup>/H<sup>+</sup> Storage in Aqueous Batteries.

Small methods·2026

Same journal

Sandgrouse Feather-Inspired Multiscale Hierarchical Microstructured Surfaces via IICSA for Controlled Liquid Regulation.

Small methods·2026

Same journal

Smart Antibacterial Janus Fabric Based on PVDF/Ag-Decorated-MXene for Unidirectional Water Transport and Thermal Management.

Small methods·2026

Same journal

Synergistic Anion Confinement in a Poly(Ionic Liquid)/MOF Composite Electrolyte Decouples Ionic Conductivity and Mechanical Strength for High-Performance Solid-State Lithium Metal Batteries.

Small methods·2026

Same journal

Fractionation-Free Protein Corona Quantification Through Synchrotron-Based Small-Angle X-ray Scattering.

Small methods·2026

Same journal

Coronamicroparticle Arrays with Stable Superamphiphobicity.

Small methods·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 29, 2025

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

Learning Phenotype Associated Signature in Spatial Transcriptomics with PASSAGE.

Chen-Kai Guo^1,2, Chen-Rui Xia^3,4, Guangdun Peng^1,2

¹Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, University of Chinese Academy of Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China.

|February 5, 2025

Summary

This summary is machine-generated.

Spatially resolved transcriptomics (SRT) analysis can now identify phenotype-associated spatial signatures using PASSAGE, a novel deep learning framework. This tool effectively characterizes cellular organization in complex tissues, improving disease and physiological state understanding.

Keywords:

deep learning graph neural network spatial signature identification spatial transcriptomics

More Related Videos

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

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

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

Published on: July 6, 2022

Related Experiment Videos

Last Updated: May 29, 2025

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

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

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

Published on: July 6, 2022

Area of Science:

Genomics
Computational Biology
Bioinformatics

Background:

Spatially resolved transcriptomics (SRT) offers high-resolution insights into cellular organization in tissues.
Current computational tools for SRT primarily use unsupervised methods, neglecting crucial sample characteristics like disease states.
There is a need for advanced computational frameworks that integrate sample phenotypes into spatial transcriptomic analysis.

Purpose of the Study:

To introduce PASSAGE (Phenotype Associated Spatial Signature Analysis with Graph-based Embedding), a deep learning framework for phenotype-associated spatial signature analysis.
To enable the characterization of complex cellular patterns across multiple spatial slices, incorporating physiological and pathological states.
To provide a robust computational tool for advancing the understanding of tissue organization.

Main Methods:

Development of a deep learning framework named PASSAGE.
Utilizing graph-based embedding for spatial signature analysis.
Integrating phenotype information into the analysis of spatial transcriptomic data.

Main Results:

PASSAGE demonstrates outstanding performance in systematic benchmarks.
The framework effectively characterizes phenotype-associated spatial signatures across heterogeneous tissue slices.
PASSAGE successfully identified sophisticated signatures in real-world case studies.

Conclusions:

PASSAGE is a powerful deep learning tool for phenotype-associated spatial signature analysis in complex tissues.
The framework enhances the interpretation of spatial transcriptomic data by integrating sample characteristics.
PASSAGE advances the field of spatial transcriptomics for understanding tissue biology in health and disease.