This weeks top spatial transcriptomics paper
🧠 Neurobiology & Neurodegeneration
An emergent disease-associated motor neuron state precedes cell death in ALS.
Using longitudinal single-nucleus transcriptomics, chromatin accessibility, and spatial transcriptomics in the SOD1-G93A ALS mouse model, the authors define a distinct “disease-associated motor neuron” (DM) state that emerges before neuronal death. Transcription factor networks that drive the transition into this DM state are conserved in human ALS motor neurons and are enriched for ALS genetic risk variants, indicating an active, genetically linked pathogenic program.
Impact: Establishes a conserved pre-degenerative motor neuron state in ALS that could be targeted before irreversible neuronal loss.
Gautier O et al., Cell, https://doi.org/10.1016/j.cell.2026.05.047
🧬 Reproductive Biology
The temporal architecture of the seminiferous epithelial cycle revealed by spatial transcriptomics.
Using seqFISH+ spatial transcriptomics on over 860,000 cells in mouse testis, this study reconstructs the full temporal progression of the seminiferous epithelial cycle at tubule-level resolution. The authors uncover a striking cyclic transcriptional program in Sertoli cells that is synchronized with spermatogenesis and persists even in germ-cell-depleted testes, revealing intrinsic somatic timing mechanisms.
Impact: Provides a high-resolution spatial-temporal atlas of spermatogenesis and Sertoli cell biology.
Chakravorty A et al., Cell, https://doi.org/10.1016/j.cell.2026.04.036
❤️ Cardiac Biology & Disease
Integrative Molecular Analyses of Inflammatory and Autoimmune Signals in Cardiac Sarcoidosis.
This study tackles the enigmatic patchy granulomas of cardiac sarcoidosis by integrating molecular analyses of inflammatory and autoimmune signaling in affected myocardium. By contrasting granulomatous, fibrotic, and preserved regions, the work begins to resolve how distinct immune programs shape arrhythmogenic and fibrotic cardiac remodeling.
Impact: Illuminates immune and autoimmune pathways underpinning the spatially heterogeneous pathology of cardiac sarcoidosis.
Neyazi M et al., Circulation, https://doi.org/10.1161/CIRCULATIONAHA.126.079304
Spatial transcriptomics reveals coordinated ventricular patterning and maturation in the developing human heart.
By generating a spatiotemporal transcriptomic atlas of human hearts from 8–15 post-conception weeks, the authors map anatomically coherent ventricular compartments and specialized subpopulations such as papillary muscle and the atrioventricular plane. Trajectory analyses reveal an endocardium-to-epicardium gradient and coordinated maturation programs, with shared increases in contractile and metabolic genes and region-specific specialization.
Impact: Delivers a reference spatial framework for human ventricular development, informing both congenital disease and regenerative cardiology.
Yao Z et al., Nature Communications, https://doi.org/10.1038/s41467-026-74476-0
🧪 Immunology & Hematology
Neutrophil-derived S100A8/A9 impairs megakaryocyte maturation in immune thrombocytopenia.
Single-cell and spatial transcriptomics of bone marrow from immune thrombocytopenia (ITP) patients uncover a neutrophil–megakaryocyte axis driven by neutrophil-derived S100A8/A9. This alarmin engages TLR4 and activates JNK/c-Jun signaling to repress GATA1, thereby blocking megakaryocyte maturation and platelet production.
Impact: Identifies a druggable inflammatory pathway linking neutrophils to defective thrombopoiesis in ITP.
Qi J et al., Nature Communications, https://doi.org/10.1038/s41467-026-74774-7
🎗️ Cancer Research
Spatial analyses implicate high stromal tumour-infiltrating CD8(+) lymphocytes as a negative predictive marker for chemotherapy in estrogen receptor-positive breast cancer.
Spatial analysis in ER-positive breast cancer reveals that high densities of stromal CD8+ tumour-infiltrating lymphocytes are associated with poorer responses to chemotherapy. By resolving where immune cells reside relative to tumor compartments, the study refines how immune contexture predicts treatment outcome.
Impact: Positions stromal CD8+ T cell infiltration as a spatially defined biomarker for chemotherapy response in ER+ breast cancer.
Kinsella Z et al., Nature Communications, https://doi.org/10.1038/s41467-026-73432-2
🧰 Technology & Methods Development
Integrative cross-sample alignment and spatially differential gene analysis for spatial transcriptomics.
The authors present CODA, a framework that aligns diverse spatial transcriptomics datasets across slices and platforms by learning a shared latent space, performing global affine alignment, transformer-based feature matching, and local nonlinear refinement. CODA delivers accurate, efficient cross-sample registration and robust identification of spatially informative genes, validated by immunofluorescence and enrichment analyses.
Impact: Provides a powerful, generalizable toolkit for multi-sample and multi-platform comparative spatial transcriptomics.
Tan Y et al., Nature Communications, https://doi.org/10.1038/s41467-026-72862-2
SMURF: soft-segmentation for single-cell reconstruction and topological analysis of spatial transcriptomic data.
SMURF is a deep learning-based soft-segmentation and manifold unrolling framework that assigns mRNAs from capture spots to nearby nuclei and flattens complex tissue architectures into Cartesian space. Applied across platforms, including Visium HD of mouse ileum, SMURF improves single-cell transcript assignment, reveals zonated villus gene programs, and links transcriptional gradients to environmental signals along the gut.
Impact: Enhances single-cell reconstruction and topological analysis across spatial platforms, enabling finer-grained tissue zonation studies.
Guo J et al., Nature Communications, https://doi.org/10.1038/s41467-026-74464-4
In situ graphene-seq: spatial transcriptomics and chronic electrophysiological characterization of tissue microenvironments.
In situ graphene-seq integrates stretchable mesh nanoelectronics with transparent graphene/PEDOT:PSS electrodes and imaging-based in situ sequencing to couple chronic electrophysiology with spatial transcriptomics at single-cell resolution. Demonstrated in human iPSC-derived cardiomyocyte–endothelial co-cultures, the platform links spatial gene expression heterogeneity to local electrical activity within tissue microenvironments.
Impact: Introduces a multimodal platform that unifies functional electrophysiology with spatial transcriptomics for dynamic tissue analysis.
Lee J et al., Nature Communications, https://doi.org/10.1038/s41467-026-73883-7
SegJointGene: joint cell segmentation and spatial gene prioritization by information entropy guided convolutional neural networks.
SegJointGene uses information-entropy–guided convolutional neural networks to jointly perform cell segmentation and prioritize spatially informative genes, explicitly leveraging molecular signals to overcome limitations of nucleus-only segmentation. This approach is designed for densely packed, morphologically complex tissues where accurate cell boundary delineation is critical for downstream spatial analyses.
Impact: Offers an integrated deep learning solution that improves cell segmentation quality while highlighting key spatial genes for follow-up.
Ma H et al., Bioinformatics, https://doi.org/10.1093/bioinformatics/btag447