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spatialDLPFC Poster GBD23

spatialDLPFC Poster GBD23

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

Poster for the Genome of Brain Disorders 2023

Pre-print: https://www.biorxiv.org/content/10.1101/2023.02.15.528722v1

Links from poster:
spatialDLPFC: https://research.libd.org/spatialDLPFC/
spatialLIBD: https://research.libd.org/spatialLIBD/
spatial registration tutorial: https://research.libd.org/spatialLIBD/articles/guide_to_spatial_registration.html

Louise Huuki-Myers

May 17, 2023
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  1. Integrated single cell and unsupervised spatial transcriptomic analysis
    defines molecular anatomy of the human dorsolateral prefrontal cortex
    Louise A. Huuki-Myers1, Abby Spangler1, Nicholas J. Eagles1, Kelsey D. Montgomery1, Sang Ho Kwon1,2, Boyi Guo3, Melissa Grant-Peters4,5, Heena R. Divecha1, Madhavi
    Tippani1, Chaichontat Sriworarat1,2, Annie B. Nguyen1, Prashanthi Ravichandran6, Matthew N. Tran1, Arta Seyedian1, PsychENCODE consortium,Thomas M. Hyde1,7,8, Joel E.
    Kleinman1,7, Alexis Battle6,9,10,11 , Stephanie C. Page1, Mina Ryten4,5,12, Stephanie C. Hicks3,11, Keri Martinowich1,2,7, Leonardo Collado-Torres1*, Kristen R. Maynard1,2,7*
    1. Lieber Institute for Brain Development, 2. The Solomon H. Snyder Department of Neuroscience Johns Hopkins School of Medicine (JHSM), 3. Department of Biostatistics Johns Hopkins Bloomberg School of Public Health, 4. Genetics and Genomic Medicine Great Ormond
    Street Institute of Child Health University College London, 5. Aligning Science Across Parkinson’s Collaborative Research Network, 6. Department of Biomedical Engineering JHSM, 7. Department of Psychiatry and Behavioral Sciences JHSM, 8. Department of Neurology JHSM,
    9. Department of Computer Science JHU, 10. Department of Genetic Medicine JHSM, 11. Malone Center for Engineering in Healthcare JHU, 12. NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London
    Overview
    Methods
    Assay n Number of
    Samples
    Number of
    Donors
    10x Visium 113,927 spots 30 10
    snRNA-seq 77,604 nuclei 19 10
    !
    Spatially resolved transcriptomics enables analysis
    of molecular organization of the human DLPFC
    !
    Unbiased spatial domains, identified with 10x
    Visium data and un-supervised clustering, look
    beyond classic histological layers
    !
    Integration with single nucleus RNA-sequencing
    data revealed distinct cell type compositions and
    cell-cell interactions within spatial domains
    !
    Enrichment analysis link genes associated with
    neuropsychiatric disorders to discrete spatial
    domains.
    !
    The research results and integrated datasets are
    available to the scientific community at
    research.libd.org/spatialDLPFC/
    Access this Dataset
    Spatial Data Shiny App
    snRNA-seq on iSEE App
    preprint SpatialDLPFC
    Interactive
    Websites
    SpatialLIBD
    R Package &
    Data
    Download
    Poster
    speakerdeck.com/
    lahuuki
    Acknowledgements
    Maynard et al., Nat Neurosci, 2021, 10.1038/s41593-020-00787-0
    Zhao et al., Nat BioTech, 2021, 10.1038/s41587-021-00935-2
    Emani et al, 2022, (syn30106435) 10.7303/syn4921369
    Presenter
    Louise
    Huuki-Myers
    Staff Scientist at LIBD
    @lahuuki
    lahuuki.github.io
    PsychENCODE Consortium
    snRNA-seq
    Identification of Data-Driven Spatial Domains
    BayesSpace: spatially-aware unsupervised clustering Spk
    Ds
    • K = 2: white matter vs. grey matter
    • K = 9: classic histological layers
    • K = 16: laminar with 2+ domains per histological layer
    k = number of domains
    s = domain number
    DE Genes in Spatial Domains
    Sp9
    D1
    is enriched for CLDN5: vascular domain (endothelial cells)
    Pairwise DE for Layer 1 sub-domains
    1
    2
    logcounts
    min > 0
    CLDN5
    1
    2
    3
    logcounts
    min > 0
    1
    2
    3
    logcounts
    min > 0
    Identified 29 fine resolution clusters across 70k nuclei
    Annotation
    Confidence
    X - high
    * - low
    Spot Deconvolution
    Spatially Map Disease Ligand Receptor Interactions
    Spatial Registration of Neuropsychiatric Data Sets
    • Benchmarked 3 spot deconvolution methods with Visium-SPG
    • Predicted cell type composition of spatial domains with
    Cell2Location & Tangram – produced different results
    • Identified Schizophrenia associated LR pairs in cell-cell
    communication analysis
    • Found co-localization of EFNA5 & EPHA5 in Sp9
    D7
    ~L6
    • Demonstrate reproducibility of snRNA-seq cell type population
    spatial registration
    • Gene set enrichment analysis of DE genes from ASD and PTSD
    data show enrichment with specific spatial domians
    Annotate 12 layer specific populations
    Paired Single Nucleus RNA-seq
    Tutorial: Spatial
    Registration

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