Spatial transcriptomic survey of human embryonic cerebral cortex by single-cell RNA-seq analysis

Single cell spatial biology over developmental time can decipher pediatric brain pathologies

Pediatric low grade brain tumors and neurodevelopmental disorders share proteins, signaling pathways, and networks. They also share germline mutations and an impaired prenatal differentiation origin. They may differ in the timing of the events and proliferation. We suggest that their pivotal distinct, albeit partially overlapping, outcomes relate to the cell states, which depend on their spatial location, and timing of gene expression during brain development. These attributes are crucial as the brain develops sequentially, and single-cell spatial organization influences cell state, thus function. Our underlying premise is that the root cause in neurodevelopmental disorders and pediatric tumors is impaired prenatal differentiation. Data related to pediatric brain tumors, neurodevelopmental disorders, brain cell (sub)types, locations, and timing of expression in the developing brain are scant. However, emerging single cell technologies, including transcriptomic, spatial biology, spatial high-resolution imaging performed over the brain developmental time, could be transformational in deciphering brain pathologies thereby pharmacology.

Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

A novel TAp73-inhibitory compound counteracts stemness features of glioblastoma stem cells

Glioblastoma (GB) is the most common and fatal type of primary malignant brain tumor for which effective therapeutics are still lacking. GB stem cells, with tumor-initiating and self-renewal capacity, are mostly responsible for GB malignancy, representing a crucial target for therapies. The TP73 gene, which is highly expressed in GB, gives rise to the TAp73 isoform, a pleiotropic protein that regulates neural stem cell biology; however, its role in cancer has been highly controversial. We inactivated TP73 in human GB stem cells and revealed that TAp73 is required for their stemness potential, acting as a regulator of the transcriptional stemness signatures, highlighting TAp73 as a possible therapeutic target. As proof of concept, we identified a novel natural compound with TAp73-inhibitory capacity, which was highly effective against GB stem cells. The treatment reduced GB stem cell-invasion capacity and stem features, at least in part by TAp73 repression. Our data are consistent with a novel paradigm in which hijacking of p73-regulated neurodevelopmental programs, including neural stemness, might sustain tumor progression, pointing out TAp73 as a therapeutic strategy for GB.

The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons

The outstanding human cognitive capacities are computed in the cerebral cortex, a mammalian-specific brain region and the place of massive biological innovation. Long noncoding RNAs have emerged as gene regulatory elements with higher evolutionary turnover than mRNAs. The many long noncoding RNAs identified in neural tissues make them candidates for molecular sources of cerebral cortex evolution and disease. Here, we characterized the genomic and cellular shifts that occurred during the evolution of the long noncoding RNA repertoire expressed in the developing cerebral cortex and explored putative roles for these long noncoding RNAs in the evolution of the human brain. Using transcriptomics and comparative genomics, we comprehensively annotated the cortical transcriptomes of humans, rhesus macaques, mice, and chickens and classified human cortical long noncoding RNAs into evolutionary groups as a function of their predicted minimal ages. Long noncoding RNA evolutionary groups showed differences in expression levels, splicing efficiencies, transposable element contents, genomic distributions, and transcription factor binding to their promoters. Furthermore, older long noncoding RNAs showed preferential expression in germinative zones, outer radial glial cells, and cortical inhibitory (GABAergic) neurons. In comparison, younger long noncoding RNAs showed preferential expression in cortical excitatory (glutamatergic) neurons, were enriched in primate and human-specific gene co-expression modules, and were dysregulated in neurodevelopmental disorders. These results suggest different evolutionary routes for older and younger cortical long noncoding RNAs, highlighting old long noncoding RNAs as a possible source of molecular evolution of conserved developmental programs; conversely, we propose that the de novo expression of primate- and human-specific young long noncoding RNAs is a putative source of molecular evolution and dysfunction of cortical excitatory neurons, warranting further investigation.

Neurodegeneration and glial morphological changes are both prevented by TRPM2 inhibition during the progression of a Parkinson's disease mouse model

Parkinson's disease (PD) is a neurodegenerative disease characterized by dopaminergic neuron death and neuroinflammation. Emerging evidence points to the involvement of the transient receptor potential melastatin 2 (TRPM2) channel in neuron death and glial activation in several neurodegenerative diseases. However, the involvement of TRPM2 in PD and specifically its relation to the neuroinflammation aspect of the disease remains poorly understood. Here, we hypothesized that AG490, a TRPM2 inhibitor, can be used as a treatment in a mouse model of PD. Mice underwent stereotaxic surgery for 6-hydroxydopamine (6-OHDA) administration in the right striatum. Motor behavioral tests (apomorphine, cylinder, and rotarod) were performed on day 3 post-injection to confirm the PD model induction. AG490 was then daily injected i.p. between days 3 to 6 after surgery. On day 6, motor behavior was assessed again. Substantia nigra (SNc) and striatum (CPu) were collected for immunohistochemistry, immunoblotting, and RT-qPCR analysis on day 7. Our results revealed that AG490 post-treatment reduced motor behavior impairment and nigrostriatal neurodegeneration. In addition, the compound prevented TRPM2 upregulation and changes of the Akt/GSK-3β/caspase-3 signaling pathway. The TRPM2 inhibition also avoids the glial morphology changes observed in the PD group. Remarkably, the morphometrical analysis revealed that the ameboid-shaped microglia, found in 6-OHDA-injected animals, were no longer present in the AG490-treated group. These results indicate that AG490 treatment can reduce dopaminergic neuronal death and suppress neuroinflammation in a PD mouse model. Inhibition of TRPM2 by AG490 could then represent a potential therapeutical strategy to be evaluated for PD treatment.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Gene regulatory landscape of cerebral cortex folding

Folding of the cerebral cortex is a key aspect of mammalian brain development and evolution, and defects are linked to severe neurological disorders. Primary folding occurs in highly stereotyped patterns that are predefined in the cortical germinal zones by a transcriptomic protomap. The gene regulatory landscape governing the emergence of this folding protomap remains unknown. We characterized the spatiotemporal dynamics of gene expression and active epigenetic landscape (H3K27ac) across prospective folds and fissures in ferret. Our results show that the transcriptomic protomap begins to emerge at early embryonic stages, and it involves cell-fate signaling pathways. The H3K27ac landscape reveals developmental cell-fate restriction and engages known developmental regulators, including the transcription factor Cux2. Manipulating Cux2 expression in cortical progenitors changed their proliferation and the folding pattern in ferret, caused by selective transcriptional changes as revealed by single-cell RNA sequencing analyses. Our findings highlight the key relevance of epigenetic mechanisms in defining the patterns of cerebral cortex folding.

A Review of the Application of Spatial Transcriptomics in Neuroscience

Since spatial transcriptomics can locate and distinguish the gene expression of functional genes in special regions and tissue, it is important for us to investigate the brain development, the development mechanism of brain diseases, and the relationship between brain structure and function in Neuroscience (or Brain science). While previous studies have introduced the crucial spatial transcriptomic techniques and data analysis methods, there are few studies to comprehensively overview the key methods, data resources, and technological applications of spatial transcriptomics in Neuroscience. For these reasons, we first investigate several common spatial transcriptomic data analysis approaches and data resources. Second, we introduce the applications of the spatial transcriptomic data analysis approaches in Neuroscience. Third, we summarize the integrating spatial transcriptomics with other technologies in Neuroscience. Finally, we discuss the challenges and future research directions of spatial transcriptomics in Neuroscience.

A distinct "repair" role of regulatory T cells in fracture healing

Regulatory T cells (Tregs) suppress immune responses and inflammation. Here, we described the distinct nonimmunological role of Tregs in fracture healing. The recruitment from the circulation pool, peripheral induction, and local expansion rapidly enriched Tregs in the injured bone. The Tregs in the injured bone displayed superiority in direct osteogenesis over Tregs from lymphoid organs. Punctual depletion of Tregs compromised the fracture healing process, which leads to increased bone nonunion. In addition, bone callus Tregs showed unique T-cell receptor repertoires. Amphiregulin was the most overexpressed protein in bone callus Tregs, and it can directly facilitate the proliferation and differentiation of osteogenic precursor cells by activation of phosphatidylinositol 3-kinase/protein kinase B signaling pathways. The results of loss- and gain-function studies further evidenced that amphiregulin can reverse the compromised healing caused by Treg dysfunction. Tregs also enriched in patient bone callus and amphiregulin can promote the osteogenesis of human pre-osteoblastic cells. Our findings indicate the distinct and nonredundant role of Tregs in fracture healing, which will provide a new therapeutic target and strategy in the clinical treatment of fractures.

Autism gene variants disrupt enteric neuron migration and cause gastrointestinal dysmotility

The comorbidity of autism spectrum disorders and severe gastrointestinal symptoms is well-established, yet the molecular underpinnings remain unknown. The identification of high-confidence large-effect autism risk genes offers the opportunity to identify convergent, underlying biology by studying these genes in the context of the gastrointestinal system. Here we show that the expression of these genes is enriched in human prenatal gut neurons as well as their migratory progenitors, suggesting that the development and/or function of these neurons may be disrupted by autism-associated pathogenic variants, leading to gastrointestinal dysfunction. Here we document the prevalence of gastrointestinal issues in patients with large-effect variants in sixteen of these genes, highlighting dysmotility, consistent with potential enteric neuron dysfunction. Using the high-throughput diploid frog Xenopus tropicalis , we individually target five of these genes ( SYNGAP1, CHD8, SCN2A, CHD2 , and DYRK1A ) and observe disrupted enteric neuronal progenitor migration for each. More extensive analysis of DYRK1A reveals that perturbation causes gut dysmotility in vivo , which can be ameliorated by treatment with a selective serotonin reuptake inhibitor (escitalopram) or a serotonin receptor 6 agonist, identified by in vivo drug screening. This work suggests that atypical development of enteric neurons contributes to the gastrointestinal distress commonly seen in individuals with autism and that increasing serotonin signaling may be a productive therapeutic avenue.

Integrative spatial analysis reveals a multi-layered organization of glioblastoma

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

Identifying tumor type and cell type-specific gene expression alterations in pediatric central nervous system tumors

Central nervous system (CNS) tumors are the leading cause of pediatric cancer death, and these patients have an increased risk for developing secondary neoplasms. Due to the low prevalence of pediatric CNS tumors, major advances in targeted therapies have been lagging compared to other adult tumors. We collect single nuclei RNA-seq data from 84,700 nuclei of 35 pediatric CNS tumors and three non-tumoral pediatric brain tissues and characterize tumor heterogeneity and transcriptomic alterations. We distinguish cell subpopulations associated with specific tumor types including radial glial cells in ependymomas and oligodendrocyte precursor cells in astrocytomas. In tumors, we observe pathways important in neural stem cell-like populations, a cell type previously associated with therapy resistance. Lastly, we identify transcriptomic alterations among pediatric CNS tumor types compared to non-tumor tissues, while accounting for cell type effects on gene expression. Our results suggest potential tumor type and cell type-specific targets for pediatric CNS tumor treatment. Here we address current gaps in understanding single nuclei gene expression profiles of previously under-investigated tumor types and enhance current knowledge of gene expression profiles of single cells of various pediatric CNS tumors.

Identity and nature of neural stem cells in the adult human subventricular zone

The existence of neural stem cells (NSCs) in adult human brain neurogenic regions remains unresolved. To address this, we created a cell atlas of the adult human subventricular zone (SVZ) derived from fresh neurosurgical samples using single-cell transcriptomics. We discovered 2 adult radial glia (RG)-like populations, aRG1 and aRG2. aRG1 shared features with fetal early RG (eRG) and aRG2 were transcriptomically similar to fetal outer RG (oRG). We also captured early neuronal and oligodendrocytic NSC states. We found that the biological programs driven by their transcriptomes support their roles as early lineage NSCs. Finally, we show that these NSCs have the potential to transition between states and along lineage trajectories. These data reveal that multipotent NSCs reside in the adult human SVZ.

Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity

Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.

APOE3 Christchurch modulates β-catenin/Wnt signaling in iPS cell-derived cerebral organoids from Alzheimer's cases

A patient with the PSEN1 E280A mutation and homozygous for APOE3 Christchurch (APOE3Ch) displayed extreme resistance to Alzheimer's disease (AD) cognitive decline and tauopathy, despite having a high amyloid burden. To further investigate the differences in biological processes attributed to APOE3Ch, we generated induced pluripotent stem (iPS) cell-derived cerebral organoids from this resistant case and a non-protected control, using CRISPR/Cas9 gene editing to modulate APOE3Ch expression. In the APOE3Ch cerebral organoids, we observed a protective pattern from early tau phosphorylation. ScRNA sequencing revealed regulation of Cadherin and Wnt signaling pathways by APOE3Ch, with immunostaining indicating elevated β-catenin protein levels. Further in vitro reporter assays unexpectedly demonstrated that ApoE3Ch functions as a Wnt3a signaling enhancer. This work uncovered a neomorphic molecular mechanism of protection of ApoE3 Christchurch, which may serve as the foundation for the future development of protected case-inspired therapeutics targeting AD and tauopathies.

Modeling the precise interaction of glioblastoma with human brain region-specific organoids

Glioblastoma is a highly aggressive malignant tumor of the central nervous system, but the interaction between glioblastoma and different types of neurons remains unclear. Here, we established a co-culture model in vitro using 3D printed molds with microchannels, in which glioblastoma organoids (GB), dorsal forebrain organoids (DO, mainly composed of excitatory neurons), and ventral forebrain organoids (VO, mainly composed of inhibitory neurons) were assembled. Our results indicate that DO has a greater impact on altered gene expression profiles of GB, resulting in increased invasive potential. GB cells preferentially invaded DO along axons, whereas this phenomenon was not observed in VO. Furthermore, GB cells selectively inhibited neurite outgrowth in DOs and reduced the expression of the vesicular GABA transporter (VGAT), leading to neuronal hyperexcitability. By revealing how glioblastoma interacts with brain cells, our study provides a more comprehensive understanding of this disease.

Molecular signatures of cortical expansion in the human fetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, μBrain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The μBrain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.

A novel batch-effect correction method for scRNA-seq data based on Adversarial Information Factorization

Single-cell RNA sequencing (scRNA-seq) technology produces an unprecedented resolution at the level of a unique cell, raising great hopes in medicine. Nevertheless, scRNA-seq data suffer from high variations due to the experimental conditions, called batch effects, preventing any aggregated downstream analysis. Adversarial Information Factorization provides a robust batch-effect correction method that does not rely on prior knowledge of the cell types nor a specific normalization strategy while being adapted to any downstream analysis task. It compares to and even outperforms state-of-the-art methods in several scenarios: low signal-to-noise ratio, batch-specific cell types with few cells, and a multi-batches dataset with imbalanced batches and batch-specific cell types. Moreover, it best preserves the relative gene expression between cell types, yielding superior differential expression analysis results. Finally, in a more complex setting of a Leukemia cohort, our method preserved most of the underlying biological information for each patient while aligning the batches, improving the clustering metrics in the aggregated dataset.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Deciphering Drug Targets and Actions with Single-Cell and Spatial Resolution

Recent advances in chemical, molecular, and genetic approaches have provided us with an unprecedented capacity to identify drug-target interactions across the whole proteome and genome. Meanwhile, rapid developments of single-cell and spatial omics technologies are revolutionizing our understanding of the molecular architecture of biological systems. However, a significant gap remains in how we align our understanding of drug actions, traditionally based on molecular affinities, with the in vivo cellular and spatial tissue heterogeneity revealed by these newer techniques. Here, we review state-of-the-art methods for profiling drug-target interactions and emerging multiomics tools to delineate the tissue heterogeneity at single-cell resolution. Highlighting the recent technical advances enabling high-resolution, multiplexable in situ small-molecule drug imaging (clearing-assisted tissue click chemistry, or CATCH), we foresee the integration of single-cell and spatial omics platforms, data, and concepts into the future framework of defining and understanding in vivo drug-target interactions and mechanisms of actions.

STAB2: an updated spatio-temporal cell atlas of the human and mouse brain

The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.

Discovery and Validation of Novel Genes in a Large Chinese Autism Spectrum Disorder Cohort

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that causes impairments in social communication and stereotypical behaviors, often accompanied by developmental delay or intellectual disability. A growing body of evidence suggests that ASD is highly heritable, and genetic studies have defined numerous risk genes. However, most studies have been conducted with individuals of European and Hispanic ancestry, and there is a lack of genetic analyses of ASD in the East Asian population.

METHODS

We performed whole-exome sequencing on 772 Chinese ASD trios and combined the data with a previous study of 369 Chinese ASD trios, identifying de novo variants in 1141 ASD trios. We used single-cell RNA sequencing analysis to identify the cell types in which ASD-related genes were enriched. In addition, we validated the function of a candidate high-functioning autism gene in mouse models using genetic approaches.

RESULTS

Our findings showed that ASD without developmental delay or intellectual disability carried fewer disruptive de novo variants than ASD with developmental delay or intellectual disability. Moreover, we identified 9 novel ASD candidate genes that were not present in the current ASD gene database. We further validated one such novel ASD candidate gene, SLC35G1, by showing that mice harboring a heterozygous deletion of Slc35g1 exhibited defects in interactive social behaviors.

CONCLUSIONS

Our work nominates novel ASD candidate genes and emphasizes the importance of genome-wide genetic studies with ASD cohorts of different ancestries to reveal the comprehensive genetic architecture of ASD.

Nodal properties of the resting-state brain functional network in childhood and adolescence

BACKGROUND AND PURPOSE

Changes in the topological properties of brain functional network nodes during childhood and adolescence can provide more detailed and intuitive information on the rules of brain development. This study aims to explore the characteristics of nodal attributes in child and adolescent brain functional networks and analyze the correlation between nodal attributes in different brain regions and age.

METHODS

Forty-two healthy volunteers aged 6-18 years who were right-handed primary and middle school students were recruited, and the subgroup analysis included children (6-12 years, n = 19) and adolescents (13-18 years, n = 23). Resting-state functional magnetic resonance imaging data were collected using a 3.0 Tesla MRI scanner. The topological properties of the functional brain network were analyzed using graph theory.

RESULTS

Compared with the children group, the degree centrality and nodal efficiency of multiple brain regions in the adolescent group were significantly increased, and the nodal shortest path was reduced (q<0.05, false discovery rate corrected). These brain regions were widely distributed in the whole brain and significantly correlated with age. Compared with the children group, reduced degree centralities were observed in the left dorsolateral fusiform gyrus, left rostral cuneus gyrus, and right medial superior occipital gyrus.

CONCLUSION

The transmission efficiency of the brain's core network gradually increased, and the subnetwork function gradually improved in children and adolescents with age. The functional development of each brain area in the occipital visual cortex was uneven and there was functional differentiation within the occipital visual cortex.

Functional genomics and systems biology in human neuroscience

Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena.

Identification of de novo Mutations in the Chinese Autism Spectrum Disorder Cohort via Whole-Exome Sequencing Unveils Brain Regions Implicated in Autism

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts are still under-represented in genome-wide genetic studies. Here, we applied whole-exome sequencing to 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combined with single-cell sequencing data from the developing human brain, we found that the expression of genes with de novo mutations was specifically enriched in the pre-, post-central gyrus (PRC, PC) and banks of the superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and healthy controls, we found that the gray volume of the right BST in ASD patients was significantly decreased compared to healthy controls, suggesting the potential structural deficits associated with ASD. Finally, we found a decrease in the seed-based functional connectivity between BST/PC/PRC and sensory areas, the insula, as well as the frontal lobes in ASD patients. This work indicated that combinatorial analysis with genome-wide screening, single-cell sequencing, and brain imaging data reveal the brain regions contributing to the etiology of ASD.

A Meta-Atlas of the Developing Human Cortex Identifies Modules Driving Cell Subtype Specification

Human brain development requires the generation of hundreds of diverse cell types, a process targeted by recent single-cell transcriptomic profiling efforts. Through a meta-analysis of seven of these published datasets, we have generated 225 meta-modules - gene co-expression networks that can describe mechanisms underlying cortical development. Several meta-modules have potential roles in both establishing and refining cortical cell type identities, and we validated their spatiotemporal expression in primary human cortical tissues. These include meta-module 20, associated with FEZF2+ deep layer neurons. Half of meta-module 20 genes are putative FEZF2 targets, including TSHZ3, a transcription factor associated with neurodevelopmental disorders. Human cortical organoid experiments validated that both factors are necessary for deep layer neuron specification. Importantly, subtle manipulations of these factors drive slight changes in meta-module activity that cascade into strong differences in cell fate - demonstrating how of our meta-atlas can engender further mechanistic analyses of cortical fate specification.

Integrative Omics Reveals Rapidly Evolving Regulatory Sequences Driving Primate Brain Evolution

Although the continual expansion of the brain during primate evolution accounts for our enhanced cognitive capabilities, the drivers of brain evolution have scarcely been explored in these ancestral nodes. Here, we performed large-scale comparative genomic, transcriptomic, and epigenomic analyses to investigate the evolutionary alterations acquired by brain genes and provide comprehensive listings of innovatory genetic elements along the evolutionary path from ancestral primates to human. The regulatory sequences associated with brain-expressed genes experienced rapid change, particularly in the ancestor of the Simiiformes. Extensive comparisons of single-cell and bulk transcriptomic data between primate and nonprimate brains revealed that these regulatory sequences may drive the high expression of certain genes in primate brains. Employing in utero electroporation into mouse embryonic cortex, we show that the primate-specific brain-biased gene BMP7 was recruited, probably in the ancestor of the Simiiformes, to regulate neuronal proliferation in the primate ventricular zone. Our study provides a comprehensive listing of genes and regulatory changes along the brain evolution lineage of ancestral primates leading to human. These data should be invaluable for future functional studies that will deepen our understanding not only of the genetic basis of human brain evolution but also of inherited disease.

Identification of ligand-receptor pairs that drive human astrocyte development

Extrinsic signaling between diverse cell types is crucial for nervous system development. Ligand binding is a key driver of developmental processes. Nevertheless, it remains a significant challenge to disentangle which and how extrinsic signals act cooperatively to affect changes in recipient cells. In the developing human brain, cortical progenitors transition from neurogenesis to gliogenesis in a stereotyped sequence that is in part influenced by extrinsic ligands. Here we used published transcriptomic data to identify and functionally test five ligand-receptor pairs that synergistically drive human astrogenesis. We validate the synergistic contributions of TGFβ2, NLGN1, TSLP, DKK1 and BMP4 ligands on astrocyte development in both hCOs and primary fetal tissue. We confirm that the cooperative capabilities of these five ligands are greater than their individual capacities. Additionally, we discovered that their combinatorial effects converge in part on the mTORC1 signaling pathway, resulting in transcriptomic and morphological features of astrocyte development. Our data-driven framework can leverage single-cell and bulk genomic data to generate and test functional hypotheses surrounding cell-cell communication regulating neurodevelopmental processes.

Neuromorphological Atlas of Human Prenatal Brain Development: White Paper

Recent morphological data on human brain development are quite fragmentary. However, they are highly requested for a number of medical practices, educational programs, and fundamental research in the fields of embryology, cytology and histology, neurology, physiology, path anatomy, neonatology, and others. This paper provides the initial information on the new online Human Prenatal Brain Development Atlas (HBDA). The Atlas will start with forebrain annotated hemisphere maps, based on human fetal brain serial sections at the different stages of prenatal ontogenesis. Spatiotemporal changes in the regional-specific immunophenotype profiles will also be demonstrated on virtual serial sections. The HBDA can serve as a reference database for the neurological research, which provides opportunity to compare the data obtained by noninvasive techniques, such as neurosonography, X-ray computed tomography and magnetic resonance imaging, functional magnetic resonance imaging, 3D high-resolution phase-contrast computed tomography visualization techniques, as well as spatial transcriptomics data. It could also become a database for the qualitative and quantitative analysis of individual variability in the human brain. Systemized data on the mechanisms and pathways of prenatal human glio- and neurogenesis could also contribute to the search for new therapy methods for a large spectrum of neurological pathologies, including neurodegenerative and cancer diseases. The preliminary data are now accessible on the special HBDA website.

Promoting the Differentiation of Neural Progenitor Cells into Oligodendrocytes through the Induction of Olig2 Expression: A Transcriptomic Study Using RNA-seq Analysis

Oligodendrocytes are the myelinating cells of the central nervous system that facilitate efficient signal transduction. The loss of these cells and the associated myelin sheath can lead to profound functional deficits. Moreover, oligodendrocytes also play key roles in mediating glial-neuronal interactions, which further speaks to their importance in health and disease. Neural progenitor cells (NPCs) are a promising source of cells for the treatment of oligodendrocyte-related neurological diseases due to their ability to differentiate into a variety of cell types, including oligodendrocytes. However, the efficiency of oligodendrocyte differentiation is often low. In this study, we induced the expression of the Olig2 transcription factor in tripotent NPCs using a doxycycline-inducible promoter, such that the extent of oligodendrocyte differentiation could be carefully regulated. We characterized the differentiation profile and the transcriptome of these inducible oligodendrogenic NPCs (ioNPCs) using a combination of qRT-PCR, immunocytochemistry and RNA sequencing with gene ontology (GO) and gene set enrichment analysis (GSEA). Our results show that the ioNPCs differentiated into a significantly greater proportion of oligodendrocytes than the NPCs. The induction of Olig2 expression was also associated with the upregulation of genes involved in oligodendrocyte development and function, as well as the downregulation of genes involved in other cell lineages. The GO and GSEA analyses further corroborated the oligodendrocyte specification of the ioNPCs.

A custom-made AAV1 variant (AAV1-T593K) enables efficient transduction of Japanese quail neurons in vitro and in vivo

The widespread use of rodents in neuroscience has prompted the development of optimized viral variants for transduction of brain cells, in vivo. However, many of the viruses developed are less efficient in other model organisms, with birds being among the most resistant to transduction by current viral tools. Resultantly, the use of genetically-encoded tools and methods in avian species is markedly lower than in rodents; likely holding the field back. We sought to bridge this gap by developing custom viruses towards the transduction of brain cells of the Japanese quail. We first develop a protocol for culturing primary neurons and glia from quail embryos, followed by characterization of cultures via immunostaining, single cell mRNA sequencing, patch clamp electrophysiology and calcium imaging. We then leveraged the cultures for the rapid screening of various viruses, only to find that all yielded poor to no infection of cells in vitro. However, few infected neurons were obtained by AAV1 and AAV2. Scrutiny of the sequence of the AAV receptor found in quails led us to rationally design a custom-made AAV variant (AAV1-T593K; AAV1*) that exhibits improved transduction efficiencies in vitro and in vivo (14- and five-fold, respectively). Together, we present unique culturing method, transcriptomic profiles of quail's brain cells and a custom-tailored AAV1 for transduction of quail neurons in vitro and in vivo.

Human cortical spheroids with a high diversity of innately developing brain cell types

BACKGROUND

Three-dimensional (3D) human brain spheroids are instrumental to study central nervous system (CNS) development and (dys)function. Yet, in current brain spheroid models the limited variety of cell types hampers an integrated exploration of CNS (disease) mechanisms.

METHODS

Here we report a 5-month culture protocol that reproducibly generates H9 embryonic stem cell-derived human cortical spheroids (hCSs) with a large cell-type variety.

RESULTS

We established the presence of not only neuroectoderm-derived neural progenitor populations, mature excitatory and inhibitory neurons, astrocytes and oligodendrocyte (precursor) cells, but also mesoderm-derived microglia and endothelial cell populations in the hCSs via RNA-sequencing, qPCR, immunocytochemistry and transmission electron microscopy. Transcriptomic analysis revealed resemblance between the 5-months-old hCSs and dorsal frontal rather than inferior regions of human fetal brains of 19-26 weeks of gestational age. Pro-inflammatory stimulation of the generated hCSs induced a neuroinflammatory response, offering a proof-of-principle of the applicability of the spheroids.

CONCLUSIONS

Our protocol provides a 3D human brain cell model containing a wide variety of innately developing neuroectoderm- as well as mesoderm-derived cell types, furnishing a versatile platform for comprehensive examination of intercellular CNS communication and neurological disease mechanisms.

Identification of region-specific amino acid signatures for doxorubicin-induced chemo brain

Doxorubicin (DOX) is a cornerstone of chemotherapy for solid tumors and leukemias. DOX-induced cognitive impairment, termed chemo brain, has been reported in cancer survivors, whereas its mechanism remains poorly understood. Here we initially evaluated the cognitive impairments of mice treated with clinically relevant, long-term, low-dosage of DOX. Using HILIC-MS/MS-based targeted metabolomics, we presented the changes of 21 amino acids across six anatomical brain regions of mice with DOX-induced chemo brain. By mapping the altered amino acids to the human metabolic network, we constructed an amino acid-based network module for each brain region. We identified phenylalanine, tyrosine, methionine, and γ-aminobutyric acid as putative signatures of three regions (hippocampus, prefrontal cortex, and neocortex) highly associated with cognition. Relying on the reported mouse brain metabolome atlas, we found that DOX might perturb the amino acid homeostasis in multiple brain regions, similar to the changes in the aging brain. Correlation analysis suggested the possible indirect neurotoxicity of DOX that altered the brain levels of phenylalanine, tyrosine, and methionine by causing metabolic disorders in the liver and kidney. In summary, we revealed the region-specific amino acid signatures as actionable targets for DOX-induced chemo brain, which might provide safer treatment and improve the quality of life among cancer survivors.

Long non-coding RNA DLX6-AS1 is the key mediator of glomerular podocyte injury and albuminuria in diabetic nephropathy by targeting the miR-346/GSK-3β signaling pathway

Progressive albuminuria is the primary clinical symptom of diabetic nephropathy (DN), leading to a gradual decline in kidney function. DLX6-AS1 was the first reported long non-coding RNA (lncRNA) to participate in organogenesis and play crucial roles in the brain or neural cell development. Herein, we investigated the DLX6-AS1 (Dlx6-os1 in mice) role in DN pathogenesis. We found that DLX6-AS1 expression in DN patients correlated with the extent of albuminuria. Dlx6-os1 overexpression induced cellular damage and inflammatory responses in cultured podocytes through miR-346-mediated regulation of the GSK-3β pathway. In various established diabetic and newly developed knockout mouse models, Dlx6-os1 knockdown/knockout significantly reduced podocyte injury and albuminuria. The Dlx6-os1 effects were remarkably modulated by miR-346 mimics or mutants and significantly diminished in podocyte-specific GSK-3β-knockout mice. Thus, DLX6-AS1 (Dlx6-os1) promotes DN development by accelerating podocyte injury and inflammation through the upregulation of the GSK-3β pathway, providing a novel molecular target for DN therapy.

Tumor type and cell type-specific gene expression alterations in diverse pediatric central nervous system tumors identified using single nuclei RNA-seq

Central nervous system (CNS) tumors are the leading cause of pediatric cancer death, and these patients have an increased risk for developing secondary neoplasms. Due to the low prevalence of pediatric CNS tumors, major advances in targeted therapies have been lagging compared to other adult tumors. We collected single nuclei RNA-seq data from 35 pediatric CNS tumors and three non-tumoral pediatric brain tissues (84,700 nuclei) and characterized tumor heterogeneity and transcriptomic alterations. We distinguished cell subpopulations associated with specific tumor types including radial glial cells in ependymomas and oligodendrocyte precursor cells in astrocytomas. In tumors, we observed pathways important in neural stem cell-like populations, a cell type previously associated with therapy resistance. Lastly, we identified transcriptomic alterations among pediatric CNS tumor types compared to non-tumor tissues, while accounting for cell type effects on gene expression. Our results suggest potential tumor type and cell type-specific targets for pediatric CNS tumor treatment. In this study, we address current gaps in understanding single nuclei gene expression profiles of previously uninvestigated tumor types and enhance current knowledge of gene expression profiles of single cells of various pediatric CNS tumors.

Inositol pyrophosphate profiling reveals regulatory roles of IP6K2-dependent enhanced IP7 metabolism in the enteric nervous system

Inositol pyrophosphates regulate diverse physiological processes; to better understand their functional roles, assessing their tissue-specific distribution is important. Here, we profiled inositol pyrophosphate levels in mammalian organs using an originally designed liquid chromatography-mass spectrometry (LC-MS) protocol and discovered that the gastrointestinal tract (GIT) contained the highest levels of diphosphoinositol pentakisphosphate (IP₇) and its precursor inositol hexakisphosphate (IP₆). Although their absolute levels in the GIT are diet dependent, elevated IP₇ metabolism still exists under dietary regimens devoid of exogenous IP₇. Of the major GIT cells, enteric neurons selectively express the IP₇-synthesizing enzyme IP6K2. We found that IP6K2-knockout mice exhibited significantly impaired IP₇ metabolism in the various organs including the proximal GIT. In addition, our LC-MS analysis displayed that genetic ablation of IP6K2 significantly impaired IP₇ metabolism in the gut and duodenal muscularis externa containing myenteric plexus. Whole transcriptome analysis of duodenal muscularis externa further suggested that IP6K2 inhibition significantly altered expression levels of the gene sets associated with mature neurons, neural progenitor/stem cells, and glial cells, as well as of certain genes modulating neuronal differentiation and functioning, implying critical roles of the IP6K2-IP₇ axis in developmental and functional regulation of the enteric nervous system. These results collectively reveal an unexpected role of mammalian IP₇-a highly active IP6K2-IP₇ pathway is conducive to the enteric nervous system.

Investigation of early molecular alterations in tauopathy with generative adversarial networks

The recent advances in deep learning-based approaches hold great promise for unravelling biological mechanisms, discovering biomarkers, and predicting gene function. Here, we deployed a deep generative model for simulating the molecular progression of tauopathy and dissecting its early features. We applied generative adversarial networks (GANs) for bulk RNA-seq analysis in a mouse model of tauopathy (TPR50-P301S). The union set of differentially expressed genes from four comparisons (two phenotypes with two time points) was used as input training data. We devised four-way transition curves for a virtual simulation of disease progression, clustered and grouped the curves by patterns, and identified eight distinct pattern groups showing different biological features from Gene Ontology enrichment analyses. Genes that were upregulated in early tauopathy were associated with vasculature development, and these changes preceded immune responses. We confirmed significant disease-associated differences in the public human data for the genes of the different pattern groups. Validation with weighted gene co-expression network analysis suggested that our GAN-based approach can be used to detect distinct patterns of early molecular changes during disease progression, which may be extremely difficult in in vivo experiments. The generative model is a valid systematic approach for exploring the sequential cascades of mechanisms and targeting early molecular events related to dementia.

APOE3 Christchurch modulates tau phosphorylation and β-catenin/Wnt/Cadherin signaling in induced pluripotent stem cell-derived cerebral organoids from Alzheimer's cases

Alzheimer's disease (AD) is the most common cause of dementia among older adults. APOE3 Christchurch (R136S, APOE3Ch ) variant homozygosity was reported in an individual with extreme resistance to autosomal dominant AD due to the PSEN1 E280A mutation. This subject had a delayed clinical age at onset and resistance to tauopathy and neurodegeneration despite extremely high amyloid plaque burden. We established induced pluripotent stem (iPS) cell-derived cerebral organoids from this resistant case and from a non-protected kindred control (with PSEN1 E280A and APOE3/3 ). We used CRISPR/Cas9 gene editing to successfully remove the APOE3Ch to wild type in iPS cells from the protected case and to introduce the APOE3Ch as homozygote in iPS cells from the non-protected case to examine causality. We found significant reduction of tau phosphorylation (pTau 202/205 and pTau396) in cerebral organoids with the APOE3Ch variant, consistent with the strikingly reduced tau pathology found in the resistant case. We identified Cadherin and Wnt pathways as signaling mechanisms regulated by the APOE3Ch variant through single cell RNA sequencing in cerebral organoids. We also identified elevated β-catenin protein, a regulator of tau phosphorylation, as a candidate mediator of APOE3Ch resistance to tauopathy. Our findings show that APOE3Ch is necessary and sufficient to confer resistance to tauopathy in an experimental ex-vivo model establishing a foundation for the development of novel, protected case-inspired therapeutics for tauopathies, including Alzheimer's.

Transcriptional networks of transient cell states during human prefrontal cortex development

The human brain is divided into various anatomical regions that control and coordinate unique functions. The prefrontal cortex (PFC) is a large brain region that comprises a range of neuronal and non-neuronal cell types, sharing extensive interconnections with subcortical areas, and plays a critical role in cognition and memory. A timely appearance of distinct cell types through embryonic development is crucial for an anatomically perfect and functional brain. Direct tracing of cell fate development in the human brain is not possible, but single-cell transcriptome sequencing (scRNA-seq) datasets provide the opportunity to dissect cellular heterogeneity and its molecular regulators. Here, using scRNA-seq data of human PFC from fetal stages, we elucidate distinct transient cell states during PFC development and their underlying gene regulatory circuitry. We further identified that distinct intermediate cell states consist of specific gene regulatory modules essential to reach terminal fate using discrete developmental paths. Moreover, using in silico gene knock-out and over-expression analysis, we validated crucial gene regulatory components during the lineage specification of oligodendrocyte progenitor cells. Our study illustrates unique intermediate states and specific gene interaction networks that warrant further investigation for their functional contribution to typical brain development and discusses how this knowledge can be harvested for therapeutic intervention in challenging neurodevelopmental disorders.

An atlas of late prenatal human neurodevelopment resolved by single-nucleus transcriptomics

Late prenatal development of the human neocortex encompasses a critical period of gliogenesis and cortical expansion. However, systematic single-cell analyses to resolve cellular diversity and gliogenic lineages of the third trimester are lacking. Here, we present a comprehensive single-nucleus RNA sequencing atlas of over 200,000 nuclei derived from the proliferative germinal matrix and laminating cortical plate of 15 prenatal, non-pathological postmortem samples from 17 to 41 gestational weeks, and 3 adult controls. This dataset captures prenatal gliogenesis with high temporal resolution and is provided as a resource for further interrogation. Our computational analysis resolves greater complexity of glial progenitors, including transient glial intermediate progenitor cell (gIPC) and nascent astrocyte populations in the third trimester of human gestation. We use lineage trajectory and RNA velocity inference to further characterize specific gIPC subpopulations preceding both oligodendrocyte (gIPC-O) and astrocyte (gIPC-A) lineage differentiation. We infer unique transcriptional drivers and biological pathways associated with each developmental state, validate gIPC-A and gIPC-O presence within the human germinal matrix and cortical plate in situ, and demonstrate gIPC states being recapitulated across adult and pediatric glioblastoma tumors.

Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution

Human brain development is underpinned by cellular and molecular reconfigurations continuing into the third decade of life. To reveal cell dynamics orchestrating neural maturation, we profiled human prefrontal cortex gene expression and chromatin accessibility at single-cell resolution from gestation to adulthood. Integrative analyses define the dynamic trajectories of each cell type, revealing major gene expression reconfiguration at the prenatal-to-postnatal transition in all cell types followed by continuous reconfiguration into adulthood and identifying regulatory networks guiding cellular developmental programs, states, and functions. We uncover links between expression dynamics and developmental milestones, characterize the diverse timing of when cells acquire adult-like states, and identify molecular convergence from distinct developmental origins. We further reveal cellular dynamics and their regulators implicated in neurological disorders. Finally, using this reference, we benchmark cell identities and maturation states in organoid models. Together, this captures the dynamic regulatory landscape of human cortical development.

De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution

Uncovering the tissue molecular architecture at single-cell resolution could help better understand organisms' biological and pathological processes. However, bulk RNA-seq can only measure gene expression in cell mixtures, without revealing the transcriptional heterogeneity and spatial patterns of single cells. Herein, we introduce Bulk2Space ( https://github.com/ZJUFanLab/bulk2space ), a deep learning framework-based spatial deconvolution algorithm that can simultaneously disclose the spatial and cellular heterogeneity of bulk RNA-seq data using existing single-cell and spatial transcriptomics references. The use of bulk transcriptomics to validate Bulk2Space unveils, in particular, the spatial variance of immune cells in different tumor regions, the molecular and spatial heterogeneity of tissues during inflammation-induced tumorigenesis, and spatial patterns of novel genes in different cell types. Moreover, Bulk2Space is utilized to perform spatial deconvolution analysis on bulk transcriptome data from two different mouse brain regions derived from our in-house developed sequencing approach termed Spatial-seq. We have not only reconstructed the hierarchical structure of the mouse isocortex but also further annotated cell types that were not identified by original methods in the mouse hypothalamus.

Lineage Landscape: a comprehensive database that records lineage commitment across species

Commitment to specific cell lineages is critical for mammalian embryonic development. Lineage determination, differentiation, maintenance, and organogenesis result in diverse life forms composed of multiple cell types. To understand the formation and maintenance of living individuals, including human beings, a comprehensive database that integrates multi-omic information underlying lineage differentiation across multiple species is urgently needed. Here, we construct Lineage Landscape, a database that compiles, analyzes and visualizes transcriptomic and epigenomic information related to lineage development in a collection of species. This landscape draws together datasets that capture the ongoing changes in cell lineages from classic model organisms to human beings throughout embryonic, fetal, adult, and aged stages, providing comprehensive, open-access information that is useful to researchers of a broad spectrum of life science disciplines. Lineage Landscape contains single-cell gene expression and bulk transcriptomic, DNA methylation, histone modifications, and chromatin accessibility profiles. Using this database, users can explore genes of interest that exhibit dynamic expression patterns at the transcriptional or epigenetic levels at different stages of lineage development. Lineage Landscape currently includes over 6.6 million cells, 15 million differentially expressed genes and 36 million data entries across 10 species and 34 organs. Lineage Landscape is free to access, browse, search, and download at http://data.iscr.ac.cn/lineage/#/home.

Loss of non-motor kinesin KIF26A causes congenital brain malformations via dysregulated neuronal migration and axonal growth as well as apoptosis

Kinesins are canonical molecular motors but can also function as modulators of intracellular signaling. KIF26A, an unconventional kinesin that lacks motor activity, inhibits growth-factor-receptor-bound protein 2 (GRB2)- and focal adhesion kinase (FAK)-dependent signal transduction, but its functions in the brain have not been characterized. We report a patient cohort with biallelic loss-of-function variants in KIF26A, exhibiting a spectrum of congenital brain malformations. In the developing brain, KIF26A is preferentially expressed during early- and mid-gestation in excitatory neurons. Combining mice and human iPSC-derived organoid models, we discovered that loss of KIF26A causes excitatory neuron-specific defects in radial migration, localization, dendritic and axonal growth, and apoptosis, offering a convincing explanation of the disease etiology in patients. Single-cell RNA sequencing in KIF26A knockout organoids revealed transcriptional changes in MAPK, MYC, and E2F pathways. Our findings illustrate the pathogenesis of KIF26A loss-of-function variants and identify the surprising versatility of this non-motor kinesin.

Orchestrating human neocortex development across the scales; from micro to macro

How our brains have developed to perform the many complex functions that make us human has long remained a question of great interest. Over the last few decades, many scientists from a wide range of fields have tried to answer this question by aiming to uncover the mechanisms that regulate the development of the human neocortex. They have approached this on different scales, focusing microscopically on individual cells all the way up to macroscopically imaging entire brains within living patients. In this review we will summarise these key findings and how they fit together.

A single-nucleus transcriptomic atlas of the dog hippocampus reveals the potential relationship between specific cell types and domestication

The process of domestication has led to dramatic differences in behavioral traits between domestic dogs and gray wolves. Whole-genome research found that a class of putative positively selected genes were related to various aspects of learning and memory, such as long-term potentiation and long-term depression. In this study, we constructed a single-nucleus transcriptomic atlas of the dog hippocampus to illustrate its cell types, cell lineage and molecular features. Using the transcriptomes of 105 057 nuclei from the hippocampus of a Beagle dog, we identified 26 cell clusters and a putative trajectory of oligodendrocyte development. Comparative analysis revealed a significant convergence between dog differentially expressed genes (DEGs) and putative positively selected genes (PSGs). Forty putative PSGs were DEGs in glutamatergic neurons, especially in Cluster 14, which is related to the regulation of nervous system development. In summary, this study provides a blueprint to understand the cellular mechanism of dog domestication.

Allometry in the corpus callosum in neonates: Sexual dimorphism

The corpus callosum (CC) is the largest fiber tract in the human brain, allowing interhemispheric communication by connecting homologous areas of the two cerebral hemispheres. In adults, CC size shows a robust allometric relationship with brain size, with larger brains having larger callosa, but smaller brains having larger callosa relative to brain size. Such an allometric relationship has been shown in both males and females, with no significant difference between the sexes. But there is some evidence that there are alterations in these allometric relationships during development. However, it is currently not known whether there is sexual dimorphism in these allometric relationships from birth, or if it only develops later. We study this in neonate data. Our results indicate that there are already sex differences in these allometric relationships in neonates: male neonates show the adult‐like allometric relationship between CC size and brain size; however female neonates show a significantly more positive allometry between CC size and brain size than either male neonates or female adults. The underlying cause of this sexual dimorphism is unclear; but the existence of this sexual dimorphism in neonates suggests that sex‐differences in lateralization have prenatal origins.

Gene Coexpression Network Characterizing Microenvironmental Heterogeneity and Intercellular Communication in Pancreatic Ductal Adenocarcinoma: Implications of Prognostic Significance and Therapeutic Target

Background

Pancreatic ductal adenocarcinoma (PDAC) is characterized by intensive stromal involvement and heterogeneity. Pancreatic cancer cells interact with the surrounding tumor microenvironment (TME), leading to tumor development, unfavorable prognosis, and therapy resistance. Herein, we aim to clarify a gene network indicative of TME features and find a vulnerability for combating pancreatic cancer.

Methods

Single-cell RNA sequencing data processed by the Seurat package were used to retrieve cell component marker genes (CCMGs). The correlation networks/modules of CCMGs were determined by WGCNA. Neural network and risk score models were constructed for prognosis prediction. Cell–cell communication analysis was achieved by NATMI software. The effect of the ITGA2 inhibitor was evaluated in vivo by using a Kras^G12D-driven murine pancreatic cancer model.

Results

WGCNA categorized CCMGs into eight gene coexpression networks. TME genes derived from the significant networks were able to stratify PDAC samples into two main TME subclasses with diverse prognoses. Furthermore, we generated a neural network model and risk score model that robustly predicted the prognosis and therapeutic outcomes. A functional enrichment analysis of hub genes governing gene networks revealed a crucial role of cell junction molecule–mediated intercellular communication in PDAC malignancy. The pharmacological inhibition of ITGA2 counteracts the cancer-promoting microenvironment and ameliorates pancreatic lesions in vivo.

Conclusion

By utilizing single-cell data and WGCNA to deconvolute the bulk transcriptome, we exploited novel PDAC prognosis–predicting strategies. Targeting the hub gene ITGA2 attenuated tumor development in a PDAC mouse model. These findings may provide novel insights into PDAC therapy.

Genomics, convergent neuroscience and progress in understanding autism spectrum disorder

More than a hundred genes have been identified that, when disrupted, impart large risk for autism spectrum disorder (ASD). Current knowledge about the encoded proteins - although incomplete - points to a very wide range of developmentally dynamic and diverse biological processes. Moreover, the core symptoms of ASD involve distinctly human characteristics, presenting challenges to interpreting evolutionarily distant model systems. Indeed, despite a decade of striking progress in gene discovery, an actionable understanding of pathobiology remains elusive. Increasingly, convergent neuroscience approaches have been recognized as an important complement to traditional uses of genetics to illuminate the biology of human disorders. These methods seek to identify intersection among molecular-level, cellular-level and circuit-level functions across multiple risk genes and have highlighted developing excitatory neurons in the human mid-gestational prefrontal cortex as an important pathobiological nexus in ASD. In addition, neurogenesis, chromatin modification and synaptic function have emerged as key potential mediators of genetic vulnerability. The continued expansion of foundational 'omics' data sets, the application of higher-throughput model systems and incorporating developmental trajectories and sex differences into future analyses will refine and extend these results. Ultimately, a systems-level understanding of ASD genetic risk holds promise for clarifying pathobiology and advancing therapeutics.

Decoding Expression Dynamics of Protein and Transcriptome at the Single-Cell Level in Paired Picoliter Chambers

Simultaneous analysis of mRNAs and proteins at the single-cell level provides information about the dynamics and correlations of gene and protein expressions in individual cells, enabling a comprehensive study of cellular heterogeneity and expression patterns. Here, we present a platform for about 1000 cellular indexing of mRNAs and membrane proteins, named multi-Paired-seq, with high cell utilization, accurate molecular measurement, and low cost. Based on hydrodynamic differential flow resistance, multi-Paired-seq largely improves cell utilization in the percentage of cells measured in population (>95%). Combined with the pump/valve structure, cell-free antibodies and mRNAs can be removed completely for highly accurate detection (R = 0.96) of protein copies. The picoliter reaction chambers allow high detection sensitivity for both mRNA transcripts and protein copies and low sequencing cost. Using multi-Paired-seq, three clusters of known breast cancer cell types are identified according to multimodal measurements, and the expression correlations between mRNAs and proteins under altered conditions are quantified. Multi-Paired-seq provides multimodal measurements at the single-cell level, which offers a new tool for cell biology, developmental biology, drug discovery, and precision medicine.