Single-cell genomics and regulatory networks for 388 human brains

Emani, P. S.; Liu, J. J.; Clarke, D.; Jensen, M.; Warrell, J.; Gupta, C.; Meng, R.; Lee, C. Y.; Xu, S.; Dursun, C.; Lou, S.; Chen, Y.; Chu, Z.; Galeev, T.; Hwang, A.; Li, Y.; Ni, P.; Zhou, X.; PsychENCODE Consortium,; Bakken, T. E.; Bendl, J.; Bicks, L.; Chatterjee, T.; Cheng, L.; Cheng, Y.; Dai, Y.; Duan, Z.; Flaherty, M.; Fullard, J. F.; Gancz, M.; Garrido-Martin, D.; Gaynor-Gillett, S.; Grundman, J.; Hawken, N.; Henry, E.; Hoffman, G. E.; Huang, A.; Jiang, Y.; Jin, T.; Jorstad, N. L.; Kawaguchi, R.; Khullar, S.; Liu, J.; Liu, S.; Ma, S.; Margolis, M.; Mazariegos, S.; Moore, J.; M

doi:10.1101/2024.03.18.585576

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bioRxiv · 10.1101/2024.03.18.585576

Single-cell genomics and regulatory networks for 388 human brains

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Abstract

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized [~]250 disease-risk genes and drug targets with associated cell types. Summary Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/585576v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@70b24org.highwire.dtl.DTLVardef@6c9eddorg.highwire.dtl.DTLVardef@131fae2org.highwire.dtl.DTLVardef@4e0f1e_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Emani, P. S., Liu, J. J., Clarke, D., Jensen, M., Warrell, J., Gupta, C., Meng, R., Lee, C. Y., Xu, S., Dursun, C., Lou, S., Chen, Y., Chu, Z., Galeev, T., Hwang, A., Li, Y., Ni, P., Zhou, X., PsychENCODE Consortium,, Bakken, T. E., Bendl, J., Bicks, L., Chatterjee, T., Cheng, L., Cheng, Y., Dai, Y., Duan, Z., Flaherty, M., Fullard, J. F., Gancz, M., Garrido-Martin, D., Gaynor-Gillett, S., Grundman, J., Hawken, N., Henry, E., Hoffman, G. E., Huang, A., Jiang, Y., Jin, T., Jorstad, N. L., Kawaguchi, R., Khullar, S., Liu, J., Liu, S., Ma, S., Margolis, M., Mazariegos, S., Moore, J., M. 2024-03-19. Single-cell genomics and regulatory networks for 388 human brains. https://doi.org/10.1101/2024.03.18.585576

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