Combining spatial transcriptomics with tissue morphology
Abstract Spatial transcriptomics has transformed our understanding of tissue architecture by preserving the spatial context of gene expression patterns. Simultaneously, advances in imaging AI have enabled extraction of morphological features describing the tissue. This review introduces a framework...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58989-8 |
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| _version_ | 1850154859604475904 |
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| author | Eduard Chelebian Christophe Avenel Carolina Wählby |
| author_facet | Eduard Chelebian Christophe Avenel Carolina Wählby |
| author_sort | Eduard Chelebian |
| collection | DOAJ |
| description | Abstract Spatial transcriptomics has transformed our understanding of tissue architecture by preserving the spatial context of gene expression patterns. Simultaneously, advances in imaging AI have enabled extraction of morphological features describing the tissue. This review introduces a framework for categorizing methods that combine spatial transcriptomics with tissue morphology, focusing on either translating or integrating morphological features into spatial transcriptomics. Translation involves using morphology to predict gene expression, creating super-resolution maps or inferring genetic information from H&E-stained samples. Integration enriches spatial transcriptomics by identifying morphological features that complement gene expression. We also explore learning strategies and future directions for this emerging field. |
| format | Article |
| id | doaj-art-a3a66239a71c4beb9d1938ae0ca8f4e4 |
| institution | OA Journals |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-a3a66239a71c4beb9d1938ae0ca8f4e42025-08-20T02:25:08ZengNature PortfolioNature Communications2041-17232025-05-0116111310.1038/s41467-025-58989-8Combining spatial transcriptomics with tissue morphologyEduard Chelebian0Christophe Avenel1Carolina Wählby2Department of Information Technology and SciLifeLab, Uppsala UniversityDepartment of Information Technology and SciLifeLab, Uppsala UniversityDepartment of Information Technology and SciLifeLab, Uppsala UniversityAbstract Spatial transcriptomics has transformed our understanding of tissue architecture by preserving the spatial context of gene expression patterns. Simultaneously, advances in imaging AI have enabled extraction of morphological features describing the tissue. This review introduces a framework for categorizing methods that combine spatial transcriptomics with tissue morphology, focusing on either translating or integrating morphological features into spatial transcriptomics. Translation involves using morphology to predict gene expression, creating super-resolution maps or inferring genetic information from H&E-stained samples. Integration enriches spatial transcriptomics by identifying morphological features that complement gene expression. We also explore learning strategies and future directions for this emerging field.https://doi.org/10.1038/s41467-025-58989-8 |
| spellingShingle | Eduard Chelebian Christophe Avenel Carolina Wählby Combining spatial transcriptomics with tissue morphology Nature Communications |
| title | Combining spatial transcriptomics with tissue morphology |
| title_full | Combining spatial transcriptomics with tissue morphology |
| title_fullStr | Combining spatial transcriptomics with tissue morphology |
| title_full_unstemmed | Combining spatial transcriptomics with tissue morphology |
| title_short | Combining spatial transcriptomics with tissue morphology |
| title_sort | combining spatial transcriptomics with tissue morphology |
| url | https://doi.org/10.1038/s41467-025-58989-8 |
| work_keys_str_mv | AT eduardchelebian combiningspatialtranscriptomicswithtissuemorphology AT christopheavenel combiningspatialtranscriptomicswithtissuemorphology AT carolinawahlby combiningspatialtranscriptomicswithtissuemorphology |