Applications of Spatial Transcriptomics in Veterinary Medicine: A Scoping Review of Research, Diagnostics, and Treatment Strategies

Abstract

Spatial transcriptomics is an emerging technology that maps gene expression within tissue architecture. Its expanding use in medicine and veterinary science supports research, precision diagnostics, biomarker discovery, and development of targeted treatment strategies. While spatial transcriptomics applications in human health are well-documented with significant publication diversity and volume, published applications in veterinary medicine remain limited. A comprehensive search of PubMed was conducted, focusing on studies published from 2016 to early 2025 that employed spatial transcriptomics in the context of disease research, diagnosis, or treatment in human or animal health. The review followed the Arksey and O'Malley framework and adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. A total of 1398 studies met the inclusion criteria. The studies highlighted emerging trends of comparative research with animal model use for human health research. Commonly used spatial transcriptomics platforms included 10× Visium, Slide-seq, Nanostring (GeoMx, CosMX), and multiplexed error-robust fluorescence in situ hybridization (MERFISH). Key gaps in publications include limited veterinary representation, interspecies comparisons, standardized methods, public data use, and therapeutic studies, alongside biases in disease, species, organ, and geography. This review presents the current landscape of spatial transcriptomics publications for human and animal research and medicine, providing comprehensive data and highlighting underrepresented research areas and gaps for future consideration.

Keywords: spatial; transcriptomics; veterinary medicine.

Figure 1

Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) flow diagram. Flow diagram of study selection for the scoping review, following PRISMA-ScR guidelines and including identification, screening, eligibility, inclusion, and reasons for exclusion.

Figure 2

Publications by Year. Annual count of ST publications from 2016 to early 2025. Peaks correspond to major milestones, including the 2016 introduction, commercial release of Visium in 2019, and increased activity during the COVID-19 pandemic. Publication data for 2025 are current through 7 February 2025.

Figure 3

Animal model versus human model publications. Among the studies included, 1062 used human models, and 619 used animal models. Combined models within publications are represented as individual datapoints.

Figure 4

Species across publications. The figure shows the number of publications utilizing ST across various species. While human (n = 1062) and mouse (n = 527) dominate, a diversity of other models is emerging. Non-human primates (n = 21) and rat (n = 16) are used in translational and preclinical research. Lower-frequency models reflect specialized biological questions: for example, fish and frog (developmental biology), chicken (avian immunology), pig and cattle (large-animal translational models), axolotl (regenerative medicine), roundworm (aging and development), hamster and ferret (respiratory infectious disease models), bat (zoonotic virus reservoir studies), dog and horse (veterinary and comparative medicine), salamander (regeneration), and rabbit and zebra finch (neuroscience and vocalization). The inclusion of such rare species highlights the expanding utility of ST in comparative and cross-species biology.

Figure 5

Application category for publication. Categorization of studies by primary research aim. Mechanistic studies were most common, followed by therapeutic and diagnostic.

Figure 6

Frequency of publications by body system. The digestive and nervous systems were the most frequently studied, appearing in 208 publications and 189 publications, respectively. The reproductive and immune systems were also prominent, with 183 and 125 publications, respectively. In contrast, systems such as cardiovascular, urinary, integumentary, and musculoskeletal were represented less frequently, each with 60 or fewer publications.

Figure 7

Frequency of cancer subtypes in publications. Breast, liver, colorectal, brain, and lung cancers were the most frequently studied, reflecting their clinical significance and spatial heterogeneity. Other cancer types, such as gastric, head and neck, and prostate cancers, also appeared regularly, while rare cancers like testicular and nasopharyngeal cancer were minimally represented.

Figure 8

Frequency of application by disease category. The highest number of publications focus on cancer (565), followed by neurodevelopmental (188) and reproductive diseases (137). Less represented categories include gastrointestinal (66), rare diseases (62), infectious diseases (60), metabolic diseases (24), and psychiatric disorders (19).

Figure 9

Frequency of named ST platforms in publications. 10× Genomics Visium was the most widely used platform, reflecting its accessibility and compatibility with formalin-fixed tissues. High-resolution and specialized platforms such as Slide-seq, Slide-seqV2, MERFISH, Seq-Scope, and Stereo-seq were also represented, though less frequently. The figure highlights both the dominance of Visium in mainstream research and the growing adoption of alternative technologies tailored for specific resolution and throughput needs.

Figure 10

Frequency of software tools used in ST publications. Seurat was the most widely used tool (927 publications), followed by Space Ranger, Cell Ranger, Monocle, and Harmony. Other tools, including Scanpy, SpatialDE, and Giotto, were used less frequently, reflecting both dominant platforms and an expanding ecosystem of specialized applications.