Sex effects on gene expression across the human cerebral cortex at single cell resolution
DeCasien, A. R.; Auluck, P.; Liu, S.; Marenco, S. R.; Cookson, M. R.; Raznahan, A.
Show abstract
Sex differences in brain-related health outcomes may be a consequence of differences in gene expression. However, most current knowledge relies on studies of bulk tissue or isolated brain regions. Here, we present a large-scale single-cell analysis of transcriptomic sex differences in the human brain, using 169 samples from 15 females and 15 males across six cortical regions, selected based on in vivo neuroimaging measures of sex-biased volume. We find that sex effects on gene expression are highly patterned across cortical regions, cell types, and genes. They are most pronounced in: i) multiple cell types in the fusiform cortex (linked to male-biased volume and sex-biased behaviors); ii) oligodendrocytes, astrocytes, and excitatory neurons across regions; and iii) a subset of sex chromosome and autosomal genes. Over 3,000 unique genes exhibit sex-biased expression, with 133 genes (119 autosomal) showing consistent sex differences across all region x cell type combinations. Sex chromosome genes show the largest sex differences in expression, driven by conserved X-Y gametologs, cell-type-specific biases in certain X- and Y-linked genes, and escape from X-inactivation - with the list of known escapees substantially expanded through our single-cell allele-specific expression analysis. Broader effects of sex on autosomal expression are captured in 13 core signatures with varying cell type vs. region specificity. These signatures are: i) shaped by regional differences in metabolism and laminar architecture; ii) enriched for diverse cellular compartments and biological processes; iii) regulated by sex steroids and X-linked transcription factors; and iv) linked to sex-specific genetic risk factors in sex-biased neuropsychiatric and neurodegenerative diseases. This study substantially advances the breadth, depth, and granularity of knowledge on sex differences in the human brain, and provides a new open data resource to support future research.
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