Smart spatial omics (S2-omics) optimizes region of interest selection to capture molecular heterogeneity in diverse tissues
Spatial omics technologies have transformed biomedical research by enabling high-resolution molecular profiling while preserving the native tissue architecture. These advances provide unprecedented insights into tissue structure and function. However, the high cost and time-intensive nature of spatial omics experiments necessitate careful experimental design, particularly in selecting regions of interest (ROIs) from large tissue sections. Currently, ROI selection is performed manually, which introduces subjectivity, inconsistency and a lack of reproducibility. Previous studies have shown strong correlations between spatial molecular patterns and histological features, suggesting that readily available and cost-effective histology images can be leveraged to guide spatial omics experiments. Here we present Smart Spatial omics (S2-omics), an end-to-end workflow that automatically selects ROIs from histology images with the goal of maximizing molecular information content in the ROIs. Through comprehensive evaluations across multiple spatial omics platforms and tissue types, we demonstrate that S2-omics enables systematic and reproducible ROI selection and enhances the robustness and impact of downstream biological discovery.
Authors
- Kaidi Jin (ORCID: https://orcid.org/0009-0007-7843-1133)
- Amelia Schroeder
- Idania Carolina Lubo Julio (ORCID: https://orcid.org/0009-0002-0545-1444)
- Tae Hyun Hwang (ORCID: https://orcid.org/0000-0002-6668-7269)
- Sicong Yao (ORCID: https://orcid.org/0009-0001-4636-6812)
- Hanying Yan (ORCID: https://orcid.org/0000-0002-9227-1742)
- Emma E. Furth (ORCID: https://orcid.org/0000-0002-9309-985X)
- Linghua Wang (ORCID: https://orcid.org/0000-0001-9380-0266)
- Tianhao Luo
- Jonathan Levinsohn (ORCID: https://orcid.org/0000-0003-0263-2362)
- Katalin Suszták (ORCID: https://orcid.org/0000-0002-1005-3726)
- Musu Yuan (ORCID: https://orcid.org/0000-0002-5674-1639)
- Parker C. Wilson (ORCID: https://orcid.org/0000-0001-8647-9662)
- Jean R. Clemenceau (ORCID: https://orcid.org/0000-0002-6222-6457)
- Anupma Nayak (ORCID: https://orcid.org/0000-0002-7445-1897)
- Luisa M. Solis Soto (ORCID: https://orcid.org/0000-0002-1253-630X)
- Inyeop Jang
- Bernhard Dumoulin (ORCID: https://orcid.org/0000-0003-4728-4250)
- Minji Kim (ORCID: https://orcid.org/0009-0009-6787-0354)
- Jeong Hwan Park (ORCID: https://orcid.org/0000-0003-4522-9928)
- Yunhe Liu (ORCID: https://orcid.org/0000-0002-2120-952X)
- Mingyao Li (ORCID: https://orcid.org/0000-0001-8180-0621)
- Minghua Deng (ORCID: https://orcid.org/0009-0003-2871-7089)
- Chunyu Luo
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- Seoul National University (KR)
- Peking University (CN)
- Seoul Metropolitan Government (KR)
- SNUH SMG-SNU Boramae Medical Center (KR)
- University of Pennsylvania (US)
- Vanderbilt University Medical Center (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Nature Cell Biology
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1038/s41556-025-01811-w
- Citations
- 4
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 3.22