Human nervous system development is an intricate and protracted process that requires precise spatio-temporal transcriptional regulation. Here we generated tissue-level and single-cell transcriptomic data from up to sixteen brain regions covering prenatal and postnatal rhesus macaque development. Integrative analysis with complementary human data revealed that global intra-species (ontogenetic) and inter-species (phylogenetic) regional transcriptomic differences exhibit concerted cup-shaped patterns, with a late fetal-to-infancy (perinatal) convergence. Prenatal neocortical transcriptomic patterns revealed transient topographic gradients, whereas postnatal patterns largely reflected functional hierarchy. Genes exhibiting heterotopic and heterochronic divergence included those transiently enriched in the prenatal prefrontal cortex or linked to autism spectrum disorder and schizophrenia. Our findings shed light on transcriptomic programs underlying the evolution of human brain development and the pathogenesis of neuropsychiatric disorders.

Summary The mechanisms underlying Zika virus (ZIKV)-related microcephaly and other neurodevelopment defects remain poorly understood. Here, we describe the derivation and characterization, including single-cell RNA-seq, of neocortical and spinal cord neuroepithelial stem (NES) cells to model early human neurodevelopment and ZIKV-related neuropathogenesis. By analyzing human NES cells, organotypic fetal brain slices and a ZIKV-infected micrencephalic brain, we show that ZIKV infects both neocortical and spinal NES cells and their fetal homolog, radial glial cells (RGCs), causing disrupted mitoses, supernumerary centrosomes, structural disorganization and cell death. ZIKV infection of NES cells and RGCs causes centrosomal depletion and mitochondrial sequestration of phospho-TBK1 during mitosis. We also found that nucleoside analogs inhibit ZIKV replication in NES cells, protecting them from ZIKV-induced pTBK1 relocalization and cell death. We established a model system of human neural stem cells to reveal cellular and molecular mechanisms underlying neurodevelopmental defects associated with ZIKV infection and its potential treatment.

GABAergic interneurons regulate neural circuit activity in the mammalian cerebral cortex. These cortical interneurons are structurally and functionally diverse. Here we use single-cell transcriptomics to study the origins of this diversity in mouse. We identify distinct types of progenitor cells and newborn neurons in the ganglionic eminences, the embryonic proliferative regions that give rise to cortical interneurons. These embryonic precursors show temporally and spatially restricted transcriptional patterns that lead to different classes of interneurons in the adult cerebral cortex. Our findings suggest that shortly after the interneurons become postmitotic, their diversity is already patent in their diverse transcriptional programs which subsequently guide further differentiation in the developing cortex.

Transcription factors (TFs) and microRNAs (miRNAs) can jointly regulate target gene expression in the forms of feed-forward loops (FFLs) or feedback loops (FBLs). These regulatory loops serve as important motifs in gene regulatory networks and play critical roles in multiple biological processes and different diseases. Major progress has been made in bioinformatics and experimental study for the TF and miRNA co-regulation in recent years. To further speed up its identification and functional study, it is indispensable to make a comprehensive review. In this article, we summarize the types of FFLs and FBLs and their identified methods. Then, we review the behaviors and functions for the experimentally identified loops according to biological processes and diseases. Future improvements and challenges are also discussed, which includes more powerful bioinformatics approaches and high-throughput technologies in TF and miRNA target prediction, and the integration of networks of multiple levels.

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified neurons and glia with transcriptomic and enhancer profiles, to characterize the gene regulatory landscape of two major cell classes in the human brain. We then leverage cell-type-specific regulatory landscapes to gain insight into the cellular etiology of several brain disorders. We find that Alzheimer’s disease (AD)-associated epigenetic dysregulation is linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia, suggesting that different cell types may contribute to disease risk, via different mechanisms. Moreover, integration of glutamatergic and GABAergic regulatory maps with genetic risk factors for schizophrenia (SCZ) and bipolar disorder (BD) identifies shared (parvalbumin-expressing interneurons) and distinct cellular etiologies (upper layer neurons for BD, and deeper layer projection neurons for SCZ). Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.