SeekSpace™ Powers Decoding of Complex Ocular Tissues and Unlocks Spatial Pathological Insights into Retinal Artery Occlusion

Research Challenges in Spatial Profiling of the Eye:

• Conventional spatial transcriptomics relies on image segmentation and deconvolution, which can generate artifacts in densely packed ocular tissues lacking clear marker genes.
• Additional tissue sections are often required to improve data quality, raising experimental costs.
• Manual marker-driven scRNA-seq annotation introduces subjective bias and may miss cell populations with subtle transcriptomic features.

Finding 1: Building a comprehensive whole-eye spatial atlas via physical single-nucleus resolution

SeekSpace™ processed three frozen mouse eye sections and captured 17,835 nuclei. Researchers performed unsupervised clustering to obtain 37 initial subclusters, which were annotated into 17 distinct cell types using canonical markers and, for challenging compartments such as the lens and ciliary body with scarce molecular markers, by integrating single-cell spatial coordinates with histological anatomical evidence. Spatial neighborhood enrichment analysis confirmed that transcriptomic clustering reconstructs anatomical layering, including retinal synaptic layers and the corneal stroma–epithelium complex.

Finding 2: Spatial-evidence-driven automated annotation and rod subcluster discovery

Trained on the spatially anchored dataset from SeekSpace™, the SVM-based eClassifier enables unbiased automated cell identification for external scRNA-seq datasets. Over 86% of cells retained consistent cell-type assignments before and after label correction. Benefiting from the dual transcriptomic–spatial readouts, researchers further partitioned rod photoreceptors into five functional subclusters (C1–C5). The Rbp3-positive, translation-active C1 subcluster was found specifically enriched in the peripheral retina. eClassifier trained on SeekSpace™ subcluster annotations enabled high-throughput subtyping of rod cells from large-scale scRNA-seq datasets.

Finding 3: Selective depletion of the C1 rod subpopulation in RAO

Although the total number of rod cells remained stable after RAO, significant subcluster remodeling occurred with prominent selective loss of the C1 subpopulation — the highly active peripheral-retina rod subcluster. RNAscope in situ assays confirmed the peripheral localization of the C1-specific marker Rbp3, with its positive cell population substantially reduced under RAO injury. This demonstrates that single-nucleus-resolution subtyping provides precise references for high-throughput single-cell analysis and in situ pathological validation.

This study builds a comprehensive mouse whole-eye single-cell spatial atlas and uncovers compartmentalized pathological signatures of RAO. The single-cell spatial reference data was generated using SeekSpace™, which served as the reference backbone for the ASCAL pipeline. Different spatial transcriptomics platforms and computational tools serve complementary research needs. SeekSpace™ offers particular strengths in studies that require:

• Physical single-nucleus resolution without deconvolution-based inference
• Dual readout of transcriptomic profiles paired with native in situ spatial coordinates
• Cell-type identification for tissues lacking well-defined marker genes
• High-confidence spatial references for large-scale scRNA-seq annotation
• High-quality spatial profiling for complex, densely packed tissue architectures

Contact

For more information about SeekSpace^TM , please contact us at:  
info@seekgene.com

For Research Use Only. Not for use in diagnostic procedures.