Spatial transcriptomics combined with single-nucleus RNA sequencing reveals glial cell heterogeneity in the human spinal cord.

Abstract

Glial cells play crucial roles in regulating physiological and pathological functions, including sensation, the response to infection and acute injury, and chronic neurodegenerative disorders. Glial cells include astrocytes, microglia, and oligodendrocytes in the central nervous system, and satellite glial cells and Schwann cells in the peripheral nervous system. Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models, few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord. Here, we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes, microglia, and oligodendrocytes in the human spinal cord. To explore the conservation and divergence across species, we compared these findings with those from mice. In the human spinal cord, astrocytes, microglia, and oligodendrocytes were each divided into six distinct transcriptomic subclusters. In the mouse spinal cord, astrocytes, microglia, and oligodendrocytes were divided into five, four, and five distinct transcriptomic subclusters, respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice. Additionally, we detected sex differences in gene expression in human spinal cord glial cells. Specifically, in all astrocyte subtypes, the levels of NEAT1 and CHI3L1 were higher in males than in females, whereas the levels of CST3 were lower in males than in females. In all microglial subtypes, all differentially expressed genes were located on the sex chromosomes. In addition to sex-specific gene differences, the levels of MT-ND4, MT2A, MT-ATP6, MT-CO3, MT-ND2, MT-ND3, and MT-CO2 in all spinal cord oligodendrocyte subtypes were higher in females than in males. Collectively, the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cord-related illnesses, including chronic pain, amyotrophic lateral sclerosis, and multiple sclerosis.