Spatial Transcriptomics: A step closer to 4D-Sequencing

– Ayushman Kumar Banerjee, Research Intern at Institute of Bioinformatics, Bangalore

Back in 2018, 10X Genomics acquired Stockholm-based Spatial Transcriptomics marking another milestone in the domain of omics analytics. As the term suggests, spatial transcriptomics (ST) is an in-situ quantification technology that allows visualization of transcriptomes in specific tissue selections. The central idea behind ST is to identify gene expression patterns while also retaining information about the spatial data of the tissues under study.

This video elucidates 10X Genomics’ Spatial Transcriptomics platform called Visium: 

Human Genome Project (HGP) and associated tools

When the Human Genome Project (HGP) was finally completed after 13 long years, in April of 2003, it resulted in the availability of an enormous amount of genetic data to be analyzed. HGP was further extended and has since seen developments of several tools like HapMap – which catalogues several geospatially differing variants, sequencing of several other organisms and several databases, for example, dbSNP – database for single nucleotide variants, dbVar – database for genomic structural variants and others. Soon in 2015, with companies like Illumina and Roche’s developing high-throughput sequencing techniques which consumed lesser sequencing times, it allowed RNA-Seq to eventually replace microarray analysis. Today, RNA-Seq has established itself as the most dominant technology to study condition-based temporal gene expression profiles. And with the introduction of spatial transcriptomics, we can delve further into understanding cellular interaction and communication dynamics on a spatial scale.

Spatial Transcriptomics and scRNA-Seq

Now, ST combined with scRNA-Seq (single-cell RNA-Seq) has shown promise in the field of neuroscience, increasing the granularity in terms of data interpretation. Spatial transcriptomics is broadly categorized into two main types; fluorescence in-situ hybridization (FISH), and single cell-based RNA-Seq technique (scRNA-Seq). Single-cell resolution enables us to have access to sufficient throughput to grasp the cellular complexity of crucial brain regions with these methods being applicable across several species, including humans. We know that the structural make-up of the brain is such that it is inherently related to its functions, be it the dependence of functional circuitry on axonal projections, dendritic architecture or the neuronal morphology in general. Single-cell transcriptomics alone has paved the way for better understanding of different cell types the brain is composed of, and establishing relationship between function, development and disease associations with these cell types is a gap that ST shows hope to fill. 

AlzMap and neurodegenerative disorders

If figures released by the United Nations are to be believed, more than 50 million people are living with Alzheimer’s disease or other forms of dementia. If breakthroughs are not discovered, the numbers could easily reach 150+ million in the next three decades. Addressing this in their recent study, Chen et al. used human and mouse brain models to demonstrate multicellular gene co-expression in Alzheimer’s disease and in the process identified a plaque-induced gene (PIG) and oligodendrocyte gene (OLIG) responses that are conserved across over several neurodegenerative disorders.

In their study, they have focused on finding molecular disturbances, or cellular interactions that cause the amyloid plaque based PIG and OLIG responses in Alzheimer’s disease. And as a result, they have generated a large dataset (https://www. alzmap.org/) of transcriptional changes in the mouse and human brain as a function of increasing amyloid pathology. In conclusion, Chen and group were able to demonstrate that the amyloid plaques did in fact contribute to disease progression in Alzheimer’s disease. However, to ascertain whether their removal would affect disease prognosis if at all, remains to be studied.

Spatio-temporal alterations during cell development

Another field of study, where ST has found enormous application is cellular communication, with combined efforts of scRNA-Seq, FISH-ST and barcoding. However, even a combination of these techniques is unable to fare well due to the lack of sensitivity towards RNA detection. Which is why these hybrid methodologies still require substantial technological refinement and tweaking before they can be used to their full potential. Nevertheless, current techniques can still be utilized to make an attempt to understand Spatio-temporal alterations during different stages in cell development, or disease progression.

Spatial transcriptomics technique has an immense potential to help generate detailed molecular maps when integrated with complex tissue systems and RNA-Seq data. ST has the capability of identifying genes which exhibit spatial expression patterns, and in doing so, help extract novel markers with more specificity in different cell types. And to end with, perhaps the only significant drawback ST has is the lack of generic protocols which calls for another area of study to develop a more robust and generalized protocol.

Also read: ALIEN HAND SYNDROME- an intermittent catastrophe

References:

1. Mapping Cellular Coordinates through Advances in Spatial Transcriptomics Technology, Molecules and Cells. 43 (2020). https://doi.org/10.14348/MOLCELLS.2020.0020.
2. W.-T. Chen, A. Lu, K. Craessaerts, B. Pavie, C. Sala Frigerio, N. Corthout, X. Qian, J. Laláková, M. Kühnemund, I. Voytyuk, L. Wolfs, R. Mancuso, E. Salta, S. Balusu, A. Snellinx, S. Munck, A. Jurek, J. Fernandez Navarro, T.C. Saido, I. Huitinga, J. Lundeberg, M. Fiers, B. De Strooper, Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer’s Disease, Cell. 182 (2020) 976-991.e19. https://doi.org/10.1016/j.cell.2020.06.038.
3. E. Lein, L.E. Borm, S. Linnarsson, The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing, Science. 358 (2017) 64–69. https://doi.org/10.1126/science.aan6827.
   

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