Single-cell genomics and regulatory networks for 388 human brains.

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, multiomics datasets into a resource comprising >2.8 million 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 >550,000 cell type-specific regulatory elements and >1.4 million 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.

Molecular cascades and cell type-specific signatures in ASD revealed by single-cell genomics.

Genomic profiling in postmortem brain from autistic individuals has consistently revealed convergent molecular changes. What drives these changes and how they relate to genetic susceptibility in this complex condition are not well understood. We performed deep single-nucleus RNA sequencing (snRNA-seq) to examine cell composition and transcriptomics, identifying dysregulation of cell type-specific gene regulatory networks (GRNs) in autism spectrum disorder (ASD), which we corroborated using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) and spatial transcriptomics. Transcriptomic changes were primarily cell type specific, involving multiple cell types, most prominently interhemispheric and callosal-projecting neurons, interneurons within superficial laminae, and distinct glial reactive states involving oligodendrocytes, microglia, and astrocytes. Autism-associated GRN drivers and their targets were enriched in rare and common genetic risk variants, connecting autism genetic susceptibility and cellular and circuit alterations in the human brain.

Single-cell genomics and regulatory networks for 388 human brains.

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.

Molecular cascades and cell-type specific signatures in ASD revealed by single cell genomics.

Understanding how genetic variation exerts its effects on the human brain in health and disease has been greatly informed by functional genomic characterization. Studies over the last decade have demonstrated robust evidence of convergent transcriptional and epigenetic profiles in post-mortem cerebral cortex from individuals with Autism Spectrum Disorder (ASD). Here, we perform deep single nuclear (sn) RNAseq to elucidate changes in cell composition, cellular transcriptomes and putative candidate drivers associated with ASD, which we corroborate using snATAC-seq and spatial profiling. We find changes in cell state composition representing transitions from homeostatic to reactive profiles in microglia and astrocytes, a pattern extending to oligodendrocytes and blood brain barrier cells. We identify profound changes in differential expression involving thousands of genes across neuronal and glial subtypes, of which a substantial portion can be accounted for by specific transcription factor networks that are significantly enriched in common and rare genetic risk for ASD. These data, which are available as part of the PsychENCODE consortium, provide robust causal anchors and resultant molecular phenotypes for understanding ASD changes in human brain.