Description

Spatial Transcriptomics analysis of the ALS spinal cord

Silas Maniatis¹, Sanja Vickovic², Tarmo Aijo³, Dayanne Martins de Castro^3,5, Richard Bonneau^4,5, Joakim Lundeberg², Hemali Phatnani¹

¹New York Genome Center, New York, NY, USA; ²Science for Life Laboratory, Division of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden; ³Simons Center for Data Analysis, New York, NY, USA; ⁴Center for Computational Biology, Flatiron Institute, New York, NY, USA; ⁵Departments of Biology and Computer Science, Center for Genomics and Systems Biology, New York University, New York, NY, USA

In ALS, symptoms typically appear first in a single limb and subsequently spread, ultimately leading to complete paralysis. Mounting evidence suggests that ALS pathology involves dysfunction of both motor neurons and glia. This implies that dysregulated intercellular signaling contributes to the disease. Understanding the cartography of gene expression in the spinal cord as ALS progresses will provide insight into the molecular basis of each cell type’s contribution to the disease, and how events initiated in one cell type or one region of the spinal cord ultimately lead to widespread MN loss. In the work presented here, we use a novel method for spatially resolved RNAseq, termed Spatial Transcriptomics, to identify gene expression programs associated with the initiation and spread of ALS pathology. When combined with computational tools that we have developed for Spatial Transcriptomics data analysis, our data reveal previously unknown changes in gene expression related to ALS disease state in the SOD1-G93A mouse spinal cord. These changes occur in multiple cell types, and appear first in ventral regions. We validate these findings and set them in the context of previously identified ALS disease mechanisms using FISH and IF. As Spatial Transcriptomics does not require genetic manipulation, we are able to apply the same methodology to post-mortem spinal cords from human ALS patients. Our results demonstrate the power of spatially resolved, transcriptome wide gene expression analysis for understanding the molecular basis of neurodegenerative disease.