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Veterinary pathology2025; 3009858241312623; doi: 10.1177/03009858241312623

Spatial transcriptomics defines the cell-specific RNA landscape of equine dorsal root ganglia.

Abstract: Equine spinal neurodegenerative conditions are frequently encountered in sport and racing horses and may be career-ending diagnoses. To further define the spatial transcriptomic landscape of equine dorsal root ganglia (DRG) in healthy adult horses, we investigated gene expression differences in distinct DRG regions using the GeoMx Digital Spatial Profiling from NanoString. Four human cell markers demonstrated high fidelity for equine cells; microtubule-associated protein 2 (MAP2), myelin basic protein (MBP), allograft inflammatory 104 factor 1/ionized calcium-binding adaptor molecule 1 (IBA1/AIF1), and Syto83 nuclear marker. Geometric regions of interest were then selected as MBP-rich, IBA1-high, and IBA1-low, and gene expression was compared. Experimental validation was achieved, with genes involved in myelination enriched in MBP-rich regions, and the identification of glia-specific genes enriched in IBA1-high regions. Thus, spatial transcriptomics with human cell markers was successful in equine DRG and can now be applied to determine cell-specific transcriptional changes during disease states.
Publication Date: 2025-02-06 PubMed ID: 39916473DOI: 10.1177/03009858241312623Google Scholar: Lookup
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  • Journal Article

Summary

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The research explores gene expression differences in various regions of healthy horse spinal nerve bundles (dorsal root ganglia-DRG) to understand neurological diseases often seen in sports and racing horses.

Goals of the Study

  • The research aims to give detailed information on the gene expression landscape of healthy horse DRG by examining different regions using GeoMx Digital Spatial Profiling technology from NanoString.
  • It intends to identify and confirm the presence of specific genes in equine (horse) cells using four human cell markers.
  • The end goal is to apply the knowledge learned from the healthy DRG to map cell-specific gene expression changes in disease states.

Rationale and Methodology

  • The researchers used four human cell markers- MAP2, MBP, IBA1/AIF1, and Syto83 nuclear marker- that were found to work well in horse cells.
  • DRG regions rich in specific markers (MBP-rich, IBA1-high, and IBA1-low) were chosen for detailed gene expression analysis.
  • The gene expression of these regions was utilized to ascertain and confirm the genes present in the respective areas.

Results and Validation

  • The research confirmed that genes associated with myelination (a process important for nerve function) were abundant in the MBP-rich regions.
  • Similarly, it identified glia-specific genes (those related to non-neuronal cells in the brain and spinal cord) in the IBA1-high regions.
  • The results provide a baseline for understanding the normal state of gene expression within the horse DRG, which will be useful in future research to detect changes during disease states.

Conclusion and Further Implication

  • The study successfully employed spatial transcriptomics and human cell markers to map the gene expression landscape of the equine DRG.
  • This research provides a baseline understanding of healthy equine DRG that can be used to explore changes at the molecular level when horses develop neurodegenerative conditions.
  • Such knowledge will be instrumental in accurately diagnosing and developing therapeutic approaches for equine neurological diseases, which often lead to career-ending outcomes for sport and racing horses.

Cite This Article

APA
Finno CJ, Rogers SL, Donnelly CG, Affolter VK, Woolard K, Miller AD, Bellone RR, Petersen JL. (2025). Spatial transcriptomics defines the cell-specific RNA landscape of equine dorsal root ganglia. Vet Pathol, 3009858241312623. https://doi.org/10.1177/03009858241312623

Publication

ISSN: 1544-2217
NlmUniqueID: 0312020
Country: United States
Language: English
Pages: 3009858241312623

Researcher Affiliations

Finno, Carrie J
  • University of California Davis, Davis, CA, USA.
Rogers, Stefan-Laural
  • NanoString Technologies, Inc. Seattle, WA, USA.
Donnelly, Callum G
  • Cornell University, Ithaca, NY, USA.
Affolter, Verena K
  • University of California Davis, Davis, CA, USA.
Woolard, Kevin
  • University of California Davis, Davis, CA, USA.
Miller, Andrew D
  • Cornell University, Ithaca, NY, USA.
Bellone, Rebecca R
  • University of California Davis, Davis, CA, USA.
Petersen, Jessica L
  • University of Nebraska-Lincoln, Lincoln, NE, USA.

Conflict of Interest Statement

Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: SR was employed by NanoString Technologies. Other authors have no competing interests to disclose.

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