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Updated: Aug 12, 2025

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

PASTE2: Partial Alignment of Multi-slice Spatially Resolved Transcriptomics Data.

Xinhao Liu¹, Ron Zeira², Benjamin J Raphael¹

¹Department of Computer Science, Princeton University, 35 Olden St, Princeton, NJ 08540.

Biorxiv : the Preprint Server for Biology

|January 30, 2023

Summary

This summary is machine-generated.

PASTE2 enables 3D reconstruction of spatial transcriptomics (SRT) data by partially aligning multiple tissue slices. This method overcomes limitations of existing approaches, improving gene expression analysis across biological samples.

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Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Spatially resolved transcriptomics (SRT) provides gene expression data within tissue slices.
Current SRT methods lose 3D information due to 2D slicing and struggle with multi-slice integration.
Existing integration methods often ignore spatial context or assume preserved tissue morphology, which is frequently not the case.

Approach:

Introduced PASTE2, a novel method for partial alignment and 3D reconstruction of multi-slice SRT datasets.
PASTE2 utilizes a partial Fused Gromov-Wasserstein Optimal Transport problem solved via a conditional gradient algorithm.
Incorporates model selection for overlap estimation and optional integration of histological images.

Key Points:

PASTE2 achieves more accurate multi-slice alignments compared to existing methods on simulated and real data.
Successfully reconstructed a 3D gene expression map of a Drosophila embryo from 16 Stereo-seq slices.
Demonstrates accurate alignment across multiple SRT technologies.

Conclusions:

PASTE2 effectively integrates multi-slice SRT data, recovering lost 3D spatial information.
Enables enhanced downstream gene expression analyses and detailed 3D spatial studies.
PASTE2 facilitates broader applications of SRT in biological research.