bioRxivNeurosciencePreprint
A spatial transcriptomic atlas of autism-associated genes identifies convergence in the developing human thalamus
Alexander Aivazidis, Fani MemiiD, Koen RademakeriD, Mahmoud KokoiD, Kenny RobertsiD, Andrew L. TrinhiD, Robert PetryszakiD, Vitalii KleshchevnikoviD, Elizabeth J. TuckiD, Steven LisgoiD, Tong LiiD, Stanislaw MakarchukiD, Martin PreteiD, Tomasz Jan NowakowskiiD, Hilary C. MartiniD, Omer Ali BayraktariD
- Citations
- 6
Abstract
Autism is a highly heritable neurodevelopmental condition that manifests across a wide phenotypic spectrum. Rare and de novo loss-of-function mutations strongly predispose to autism and co-occurring developmental and intellectual disabilities in over 10% of autistic individuals. Understanding whether these variants converge on specific regional brain circuits or widely alter human brain development is crucial to understanding the etiology of profound autism. To date, transcriptomic atlases have mainly implicated the developing cerebral cortex, yet other brain areas have received relatively little attention. Here, we present a single-cell resolution spatial transcriptomic atlas of 250 autism susceptibility genes during human brain development. Profiling over 10 million cells across the midgestation forebrain, we found convergence of these genes across a small number of regional programs. The developing thalamus showed the most prevalent expression of autism susceptibility genes, followed by germinal zones throughout the brain. Within the thalamus, excitatory neurons showed the most enriched expression, which varied across thalamic nuclei harboring distinct circuits. Across the germinal zones, neural progenitors in the medial ganglionic eminences that generate parvalbumin- and somatostanin-positive interneurons showed highest expression. Our findings reveal the prevalent expression of autism associated genes beyond the developing cerebral cortex and implicate the developing human thalamus as a major hub of autism susceptibility.
- organism: human
- assay: spatial transcriptomics
- research focus: cell type annotation
- approach: statistical model
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