Modeling the Evolution of Human Brain Development Using Organoids.

In a recent issue of Nature, Kanton et al. explore human brain evolution and development by profiling the single-cell transcriptomes and epigenomes of cerebral organoids derived from human, chimpanzee, and macaque stem cells. Their results reveal key molecular characteristics that differentiate humans and non-human primates at the earliest stages of brain development.

Hominini-specific regulation of CBLN2 increases prefrontal spinogenesis.

The similarities and differences between nervous systems of various species result from developmental constraints and specific adaptations1-4. Comparative analyses of the prefrontal cortex (PFC), a cerebral cortex region involved in higher-order cognition and complex social behaviours, have identified true and potential human-specific structural and molecular specializations4-8, such as an exaggerated PFC-enriched anterior-posterior dendritic spine density gradient5. These changes are probably mediated by divergence in spatiotemporal gene regulation9-17, which is particularly prominent in the midfetal human cortex15,18-20. Here we analysed human and macaque transcriptomic data15,20 and identified a transient PFC-enriched and laminar-specific upregulation of cerebellin 2 (CBLN2), a neurexin (NRXN) and glutamate receptor-δ GRID/GluD-associated synaptic organizer21-27, during midfetal development that coincided with the initiation of synaptogenesis. Moreover, we found that species differences in level of expression and laminar distribution of CBLN2 are, at least in part, due to Hominini-specific deletions containing SOX5-binding sites within a retinoic acid-responsive CBLN2 enhancer. In situ genetic humanization of the mouse Cbln2 enhancer drives increased and ectopic laminar Cbln2 expression and promotes PFC dendritic spine formation. These findings suggest a genetic and molecular basis for the anterior-posterior cortical gradient and disproportionate increase in the Hominini PFC of dendritic spines and a developmental mechanism that may link dysfunction of the NRXN-GRID-CBLN2 complex to the pathogenesis of neuropsychiatric disorders.

Regulation of prefrontal patterning and connectivity by retinoic acid.

The prefrontal cortex (PFC) and its connections with the mediodorsal thalamus are crucial for cognitive flexibility and working memory1 and are thought to be altered in disorders such as autism2,3 and schizophrenia4,5. Although developmental mechanisms that govern the regional patterning of the cerebral cortex have been characterized in rodents6-9, the mechanisms that underlie the development of PFC-mediodorsal thalamus connectivity and the lateral expansion of the PFC with a distinct granular layer 4 in primates10,11 remain unknown. Here we report an anterior (frontal) to posterior (temporal), PFC-enriched gradient of retinoic acid, a signalling molecule that regulates neural development and function12-15, and we identify genes that are regulated by retinoic acid in the neocortex of humans and macaques at the early and middle stages of fetal development. We observed several potential sources of retinoic acid, including the expression and cortical expansion of retinoic-acid-synthesizing enzymes specifically in primates as compared to mice. Furthermore, retinoic acid signalling is largely confined to the prospective PFC by CYP26B1, a retinoic-acid-catabolizing enzyme, which is upregulated in the prospective motor cortex. Genetic deletions in mice revealed that retinoic acid signalling through the retinoic acid receptors RXRG and RARB, as well as CYP26B1-dependent catabolism, are involved in proper molecular patterning of prefrontal and motor areas, development of PFC-mediodorsal thalamus connectivity, intra-PFC dendritic spinogenesis and expression of the layer 4 marker RORB. Together, these findings show that retinoic acid signalling has a critical role in the development of the PFC and, potentially, in its evolutionary expansion.

The evolution of the human brain and disease susceptibility.

Evolutionary perspective is critical for understanding human biology, human medicine, and the traits that make human beings unique. One of the crucial characteristics that sets humans apart from other extant species is our cognitive ability, which allows for complex processes including symbolic thought, theory of mind, and syntactical-grammatical language, and is thought to arise from the expansion and specialization of the human nervous system. It has been hypothesized that the same evolutionary changes that allowed us to develop these valuable skills made humans susceptible to neurodevelopmental and neurodegenerative disease. Unfortunately, our lack of access to our extinct ancestors makes this a difficult hypothesis to test, but recent collaborations between the fields of evolution, genetics, genomics, neuroscience, neurology and psychiatry have begun to provide some clues. Here, we will outline recent work in those fields that have utilized our growing knowledge of disease risk genes and loci, identified by wide-scale genetic studies, and nervous system development and function to draw conclusions about the impact of human-specific aspects of evolution. We will discuss studies that assess evolution at a variety of scales including at the levels of whole brain regions, cell types, synapses, metabolic processes, gene expression patterns, and gene regulation. At all of these levels, there is preliminary evidence that human-specific brain features are linked to neurodevelopmental and neurodegenerative disease risk.

A statistical framework for cross-tissue transcriptome-wide association analysis.

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies.

Integrative functional genomic analysis of human brain development and neuropsychiatric risks.

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.