The field ofspatial transcriptomics utilizes technologies that map gene expression data to specific cellular locations within tissues.
Whiletraditional RNA sequencing methods generate quantitative data on gene expression levels, the lack of spatial context prevents a holistic understanding of biological interactions, cell heterogeneity, tissue architecture, tissue development and more. Gene expression can vary wildly in different parts of a tissue, particularly in complex samples, such as a tumor biopsy. The advancement of spatial transcriptomics methods, capturing spatial context withi n intact tissue, offers an entirely new understanding of biology.
In 2024, Shi et al. conducted one of the first bibliometric analyses in spatial transcriptomics, aiming to discover and analyze frontiers and trends in this emerging field.Published inCellular and Molecular Neurobiology*,*the study analyzed 1,467 papers and reviews published between 2006–2023.
The findings point to an ongoing phase of acceleration within the field. “The analysis revealed that the spatial transcriptomics publication and citation results have shown a rapid upward trend over the last three years,” Shi et al.said.
What is a bibliometric analysis?
A quantitative approach that uses large volumes of data from scholarly publications to evaluate the research status of a field. A bibliometric analysis might assess the contributions of certain authors, articles, journals, institutes and countries to a research area. This method can also be used to determine trends, research directions and current applications of a specific research area or technique.
Technology Networksrecently interviewedProfessor Joakim Lundeberg, group leader at the Science for Life Laboratory (SciLifeLab), Sweden, and professor in Gene Technology at the KTH Royal Institute of Technology, Sweden.
Lundeberg is the most productive author in spatial transcriptomics based on Shi et al.’s analysis. He discussed the evolution of spatial transcriptomics techniques, why Sweden is a “hot spot” location for the field and how spatial transcriptomics is enhancing our understanding of human health and disease.
Modern spatial transcriptomics techniques – in situ hybridization, in situ sequencing and in situ capturing
From 2006 to 2019, fewer than 100 papers were published on spatial transcriptomics annually. Then, in 2020, the editors of the journal Nature Methods unanimously selected spatially resolved transcriptomics as their “Method of the Year”. First established in 2007, this accolade recognizes a scientific method that has a profound impact on the progression of science.
The “Method of the Year” award marked a turning point, Lundeberg said: “Several new methods were published, and broader attention was given to this emerging field, accompanied by a rise in publications.”
Indeed, Shi et al.’s data point to a surge in annual publications post-2020, with 630 papers published in 2023 alone.
Lundeberg’s research has contributed substantially to the progression of spatial transcriptomics through the development of novel technologies and their application in basic research.
“We, a team [of scientists] at the KTH Royal Institute of Technology and the Karolinska Institute (Professor Jonas Frisén and colleagues), developed the first method to analyze the transcriptome (i.e., all of the expressed genes) in a tissue section. The technology was coined Spatial Transcriptomics, or ST,” he says. The paper introducing the world to ST was published in Science in 2016.
Current spatial transcriptomics approaches build on decades of advances in RNA detection and analysis, tissue cutting and imaging. Generally speaking, methods are broadly divided into those that use in situ hybridization (ISH), in situ sequencing (ISS) or in situ capturing (ISC) technologies.
ISH-based and ISS-based techniques enable the direct visualization of target RNA molecules within tissue, overcoming the need to extract cells. High efficiency and high spatial resolution are strengths of these approaches, while the reliance on targeting known genes, small fields of view and labor-intensive protocols are drawbacks. In contrast, ISC techniques capture transcripts in situ then sequencing is conducted ex situ, preserving spatial location and harnessing the efficiency ofnext-generation sequencing techniques. ISC techniques can be applied to large areas of tissue but have historically suffered from lower resolution.
“The sequencing-based methods analyze all genes and serve well to provide an unbiased view of tissue ecosystem,” Lundeberg explained. “The hybridization-based methods use targeted panels and provide the opportunity to assess the sub-cellular distribution of expressed genes.”
ST – developed by Lundeberg and colleagues – is an example of an ISC-based approach. Commercialized as Visium™ by 10x Genomics in 2018, it has undergone numerous updates in recent years to improve spatial resolution. Most recently, 10x Genomicsintroduced Visium HD Spatial Gene Expression™, which “provides whole-transcriptome insights at single-cell scale resolution”.
Continue reading below...
Milestones in Spatial Transcriptomics
Over the last few years, several additional platforms have become commercially available, offering researchers a selection of choices depending on their experimental considerations and requirements.
The most commonly used spatial transcriptmics techniques
Equipped with an increasingly large toolbox of techniques, over 2,000 institutes are now conducting spatial transcriptomics research globally. Sweden appears to be a hotspot; in a ranked list of the top 10 most productive sites in the world, the Karolinska Institute takes first place, followed by the KTH Royal Institute of Technology, according to Shi et al.’s data.
Sweden has a track record of developing new technologies and has among the highest number of patents per capita, Lundeberg explained: “Thus, the innovation ecosystem at Swedish Universities and companies is very good.” Commercialization of cutting-edge techniques is of course a huge contributor to their accessibility. Indeed, ST isn’t the only commercialized spatial transcriptomics technique that emerged from a Swedish lab; ISS was originally developed byProfessor Mats Nilsson and colleagues at the SciLifeLab before it was commercialized as Xenium™, again by 10x Genomics.
“These two methods (our ST method – aka Visium – and ISS) have been independently developed at the SciLifeLab in Stockholm, a multidisciplinary center, in two laboratories that are 100 meters apart. It’s pretty amazing,” Lundeberg said. A 2022 review paper – published in Nature Methods – suggests Visium is the most popular technology driving the growth of the field.
Outside Sweden, the US has 4 institutes listed in the top 10, and the UK has 2 – as does China.
“Among the top 10 countries, the United States, Sweden, China and the United Kingdom play a ‘bridging’ role in spatial transcriptomics research, especially Sweden, which ranks second in terms of publications but has a higher number of citations per study, significantly stronger links with other countries on the collaboration map, and more top researchers with frequently cited articles, suggesting Sweden's focus on innovation and collaboration in spatial transcriptomics,” Shi et alsaid.
The increased research interest in spatial transcriptomics is having a significant impact on our understanding of human biology and disease.
Spatial transcriptomics in modern disease research
Initiatives such as theHuman Cell Atlas are incorporating spatial transcriptomics data to study the various cell types of the body’s tissues and organs, and how they evolve as we age, on a large scale.
Continue reading below...
Spatial Transcriptomics in Neuroscience
Oncology is a research space set to benefit significantly from spatial transcriptomics data. Such technologies enable the precise characterization of tumor microenvironments, identifying interactions between malignant cells across different types of cancer, and can offer insights into the evolution of cancer in benign tissues. Collectively, these data can better inform cancer diagnostics, support the development of novel biomarkers and identify new drug targets. Lundeberg highlights a recentstudy on the spatial landscape of immune clonotypes in tonsil and breast cancer, which captured the dynamics of key immunological cell types – B and T cells – in space and time.
According to Shi et al., the application of spatial transcriptomics has “gradually spread from cancer and immunotherapy to other disease areas under continuous development”. Indeed, in nephrology, spatial transcriptomics technologies are helping to elucidate the cellular and molecular mechanisms of certain kidney diseases and kidney allograft rejection.
In neuroscience, researchers are using spatial transcriptomics approaches to deconstruct the cellular architecture of the brain in healthy and diseased states. In November 2024, researchers published a spatial transcriptomic analysis of genetic and sporadic forms of Alzheimer’s disease, adding a new dimension to our understanding of neurodegenerative disease pathology.
Deeper insights into human biology and disease
Shi et al.'s bibliometric analysis confirms that spatial transcriptomics is experiencing a surge in global interest, with research expanding across multiple disciplines. As the field continues to expand, researchers face new challenges in integrating and interpreting multi-omics data in a spatial context, according to Lundeberg: “Integration and interpretation of multiomics data in multiple dimensions [presents] biological and practical challenges that need to be addressed by biologist, experimentalist and computational scientists.”
Overcoming these challenges will be critical for maximizing the potential of spatial transcriptomics, enabling deeper insights into human biology and disease.