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Updated: Aug 5, 2026

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Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
Published on: October 31, 2025
Fishing with two lines: a hybrid approach to spatial transcriptomics discovery
Arianna L Williams-Katek1, Saahithi Mallapragada2,3, Evan D Mee2
1Division of Bioinnovation and Genome Sciences, Translational Genomics Research Institute (TGen), Phoenix, AZ, USA awilliams@tgen.org.
Life Science Alliance
|July 27, 2026
Summary
This study introduces a dual-chemistry spatial transcriptomics method. It combines high sensitivity and broad gene coverage on a single tissue section for enhanced biological discovery.
Area of Science:
- Molecular Biology
- Genomics
- Biotechnology
Background:
- Spatial transcriptomics enables gene expression analysis within intact tissue context.
- Current methods present a trade-off between the number of genes detected and the sensitivity of detection per gene.
Purpose of the Study:
- To develop a novel dual-chemistry method for spatial transcriptomics.
- To overcome the limitations of current spatial transcriptomics assays by combining high sensitivity and broad gene coverage.
Main Methods:
- A dual-chemistry approach was developed, co-hybridizing Xenium V1 (480 genes) and Prime 5K (5,001 genes) probes.
- Sequential decoding chemistries for V1 and Prime panels were performed on a single tissue section.
- The method was validated on human lung tissue microarrays.
Main Results:
- High concordance was observed between independent V1 and Prime chemistry runs and the dual-chemistry approach.
- Overlapping genes showed similar expression patterns, confirming assay fidelity.
- The dual-chemistry method successfully retained more cells and provided comprehensive gene expression data.
Conclusions:
- The developed dual-chemistry method enhances spatial transcriptomics by integrating high-sensitivity and broad-coverage panels.
- This approach enables deeper biological insights and discovery by maximizing information from single tissue sections.
- The method offers a powerful tool for comprehensive spatial gene expression profiling.
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