SummaryHere we report the generation and analysis of genome-wide exon-level transcriptome data from 16 brain regions comprising the cerebellar cortex, mediodorsal nucleus of the thalamus, striatum, amygdala, hippocampus, and 11 areas of the neocortex. The dataset was generated from 1,340 tissue samples collected from one or both hemispheres of 57 postmortem human brains, spanning from embryonic development to late adulthood and representing males and females of multiple ethnicities. We also performed genotyping of 2.5 million SNPs and assessed copy number variations for all donors. Approximately 86% of protein-coding genes were found to be expressed using stringent criteria, and over 90% of these were differentially regulated at the whole transcript or exon level across regions and/or time. The majority of these spatiotemporal differences occurred before birth, followed by an increase in the similarity among regional transcriptomes during postnatal lifespan. Genes were organized into functionally distinct co-expression networks, and sex differences were present in gene expression and exon usage. Finally, we demonstrate how these results can be used to profile trajectories of genes associated with neurodevelopmental processes, cell types, neurotransmitter systems, autism, and schizophrenia, as well as to discover associations between SNPs and spatiotemporal gene expression. This study provides a comprehensive, publicly available dataset on the spatiotemporal human brain transcriptome and new insights into the transcriptional foundations of human neurodevelopment.

Catechol-O-methyltransferase (COMT) is a key enzyme in the elimination of dopamine in the prefrontal cortex of the human brain. Genetic variation in the COMT gene (MIM 116790) has been associated with altered prefrontal cortex function and higher risk for schizophrenia, but the specific alleles and their functional implications have been controversial. We analyzed the effects of several single-nucleotide polymorphisms (SNPs) within COMT on mRNA expression levels (using reverse-transcriptase polymerase chain reaction analysis), protein levels (using Western blot analysis), and enzyme activity (using catechol methylation) in a large sample (n = 108) of postmortem human prefrontal cortex tissue, which predominantly expresses the -membrane-bound isoform. A common coding SNP, Val158Met (rs4680), significantly affected protein abundance and enzyme activity but not mRNA expression levels, suggesting that differences in protein integrity account for the difference in enzyme activity between alleles. A SNP in intron 1 (rs737865) and a SNP in the 3' flanking region (rs165599)--both of which have been reported to contribute to allelic expression differences and to be associated with schizophrenia as part of a haplotype with Val--had no effect on mRNA expression levels, protein immunoreactivity, or enzyme activity. In lymphocytes from 47 subjects, we confirmed a similar effect on enzyme activity in samples with the Val/Met genotype but no effect in samples with the intron 1 or 3' SNPs. Separate analyses revealed that the subject's sex, as well as the presence of a SNP in the P2 promoter region (rs2097603), had small effects on COMT enzyme activity. Using site-directed mutagenesis of mouse COMT cDNA, followed by in vitro translation, we found that the conversion of Leu at the homologous position into Met or Val progressively and significantly diminished enzyme activity. Thus, although we cannot exclude a more complex genetic basis for functional effects of COMT, Val is a predominant factor that determines higher COMT activity in the prefrontal cortex, which presumably leads to lower synaptic dopamine levels and relatively deleterious prefrontal function.

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type–specific dynamics. We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C, SATB2, SOX5, TCF4, and TSHZ3) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks.

Previous investigations have combined transcriptional and genetic analyses in human cell lines1-3, but few have applied these techniques to human neural tissue4-8. To gain a global molecular perspective on the role of the human genome in cortical development, function and ageing, we explore the temporal dynamics and genetic control of transcription in human prefrontal cortex in an extensive series of post-mortem brains from fetal development through ageing. We discover a wave of gene expression changes occurring during fetal development which are reversed in early postnatal life. One half-century later in life, this pattern of reversals is mirrored in ageing and in neurodegeneration. Although we identify thousands of robust associations of individual genetic polymorphisms with gene expression, we also demonstrate that there is no association between the total extent of genetic differences between subjects and the global similarity of their transcriptional profiles. Hence, the human genome produces a consistent molecular architecture in the prefrontal cortex, despite millions of genetic differences across individuals and races. To enable further discovery, this entire data set is freely available (from Gene Expression Omnibus: accession GSE30272; and dbGaP: accession phs000417.v1.p1) and can also be interrogated via a biologist-friendly stand-alone application (http://www.libd.org/braincloud).

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex (DLPFC). We identified extensive layer-enriched expression signatures, and refined associations to previous laminar markers. We overlaid our laminar expression signatures onto large-scale single nuclei RNA sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially-defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions where morphological architecture is not as well-defined as cortical laminae. We lastly created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).