Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

Louise A. Huuki-Myers(Johns Hopkins University), Abby Spangler(Johns Hopkins University), Nicholas J. Eagles(Johns Hopkins University), Kelsey D. Montgomery(Johns Hopkins University), Sang Ho Kwon(Johns Hopkins University), Boyi Guo(Johns Hopkins University), Melissa Grant‐Peters(Great Ormond Street Hospital), Heena R. Divecha(Johns Hopkins University), Madhavi Tippani(Johns Hopkins University), Chaichontat Sriworarat(Johns Hopkins University), Annie B. Nguyen(Johns Hopkins University), Prashanthi Ravichandran(Johns Hopkins University), Matthew N. Tran(Johns Hopkins University), Arta Seyedian(Johns Hopkins University), Thomas M. Hyde(Johns Hopkins University), Joel E. Kleinman(Johns Hopkins University), Alexis Battle(Johns Hopkins University), Stephanie C. Page(Johns Hopkins University), Mina Ryten(Great Ormond Street Hospital), Stephanie C. Hicks(Johns Hopkins University), Keri Martinowich(Johns Hopkins University), Leonardo Collado‐Torres(Johns Hopkins University), Kristen R. Maynard(Johns Hopkins University)
bioRxiv (Cold Spring Harbor Laboratory)
February 15, 2023
Cited by 31Open Access
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Abstract

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.


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