Edinburgh Research Explorer

Spatial transcriptomics identifies spatially dysregulated expression of GRM3 and USP47 in amyotrophic lateral sclerosis

Research output: Contribution to journalArticle

Abstract

AIMS: The mechanisms underlying the selective degeneration of motor neurones in amyotrophic lateral sclerosis (ALS) are poorly understood. The aim of this study was to implement spatially resolved RNA-sequencing in human post-mortem cortical tissue from an ALS patient harbouring the C9orf72 hexanucleotide repeat expansion to identify dysregulated transcripts that may account for differential vulnerabilities of distinct (i) cell types and (ii) brain regions in the pathogenesis of ALS.

METHODS: Using spatial transcriptomics (ST) we analysed the transcriptome of post-mortem brain tissue, with spatial resolution down to 100 μm. Validation of these findings was then performed using BaseScope, an adapted, in situ hybridisation technique with single-transcript single-cell-resolution, providing extensive regional and cell-type specific confirmation of these dysregulated transcripts. The validation cohort was then extended to include multiple post-mortem brain regions and spinal cord tissue from an extended cohort of C9orf72, sporadic ALS (sALS) and SOD1 ALS cases.

RESULTS: We identified sixteen dysregulated transcripts of proteins that have roles within six disease-related pathways. Furthermore, these complementary molecular pathology techniques converged to identify two spatially dysregulated transcripts, GRM3 and USP47, that are commonly dysregulated across sALS, SOD1 and C9orf72 cases alike.

CONCLUSIONS: This study presents the first description of ST in human post-mortem cortical tissue from an ALS patient harbouring the C9orf72 hexanucleotide repeat expansion. These data taken together highlight the importance of preserving spatial resolution, facilitating the identification of genes whose dysregulation may in part underlie regional susceptibilities to ALS, crucially highlighting potential therapeutic and diagnostic targets.

Download statistics

No data available

ID: 130289198