Comparative cellular analysis of motor cortex in human, marmoset and mouse

Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys

Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.

Molecular and cellular mechanisms of human cortical connectivity

Comparative studies of the cerebral cortex have identified various human and primate-specific changes in both local and long-range connectivity, which are thought to underlie our advanced cognitive capabilities. These changes are likely mediated by the divergence of spatiotemporal regulation of gene expression, which is particularly prominent in the prenatal and early postnatal human and non-human primate cerebral cortex. In this review, we describe recent advances in characterizing human and primate genetic and cellular innovations including identification of novel species-specific, especially human-specific, genes, gene expression patterns, and cell types. Finally, we highlight three recent studies linking these molecular changes to reorganization of cortical connectivity.

Neuronal identity defines α-synuclein and tau toxicity

Pathogenic α-synuclein and tau are critical drivers of neurodegeneration, and their mutations cause neuronal loss in patients. Whether the underlying preferential neuronal vulnerability is a cell-type-intrinsic property or a consequence of increased expression levels remains elusive. Here, we explore cell-type-specific α-synuclein and tau expression in human brain datasets and use deep phenotyping as well as brain-wide single-cell RNA sequencing of >200 live neuron types in fruit flies to determine which cellular environments react most to α-synuclein or tau toxicity. We detect phenotypic and transcriptomic evidence of differential neuronal vulnerability independent of α-synuclein or tau expression levels. Comparing vulnerable with resilient neurons in Drosophila enabled us to predict numerous human neuron subtypes with increased intrinsic susceptibility to pathogenic α-synuclein or tau. By uncovering synapse- and Ca²⁺ homeostasis-related genes as tau toxicity modifiers, our work paves the way to leverage neuronal identity to uncover modifiers of neurodegeneration-associated toxic proteins.

Strong and reliable synaptic communication between pyramidal neurons in adult human cerebral cortex

Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3-4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.

Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements

Cell type-specific transcriptional differences between brain tissues from donors with Alzheimer's disease (AD) and unaffected controls have been well documented, but few studies have rigorously interrogated the regulatory mechanisms responsible for these alterations. We performed single nucleus multiomics (snRNA-seq plus snATAC-seq) on 105,332 nuclei isolated from cortical tissues from 7 AD and 8 unaffected donors to identify candidate cis-regulatory elements (CREs) involved in AD-associated transcriptional changes. We detected 319,861 significant correlations, or links, between gene expression and cell type-specific transposase accessible regions enriched for active CREs. Among these, 40,831 were unique to AD tissues. Validation experiments confirmed the activity of many regions, including several candidate regulators of APP expression. We identified ZEB1 and MAFB as candidate transcription factors playing important roles in AD-specific gene regulation in neurons and microglia, respectively. Microglia links were globally enriched for heritability of AD risk and previously identified active regulatory regions.

A molecularly defined and spatially resolved cell atlas of the whole mouse brain

In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in ~8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to ~300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

Astrocyte heterogeneity and interactions with local neural circuits

Astrocytes are ubiquitous within the central nervous system (CNS). These cells possess many individual processes which extend out into the neuropil, where they interact with a variety of other cell types, including neurons at synapses. Astrocytes are now known to be active players in all aspects of the synaptic life cycle, including synapse formation and elimination, synapse maturation, maintenance of synaptic homeostasis and modulation of synaptic transmission. Traditionally, astrocytes have been studied as a homogeneous group of cells. However, recent studies have uncovered a surprising degree of heterogeneity in their development and function, suggesting that astrocytes may be matched to neurons to support local circuits. Hence, a better understanding of astrocyte heterogeneity and its implications are needed to understand brain function.

Evolving characterization of the human hyperdirect pathway

The hyperdirect pathway (HDP) represents the main glutamatergic input to the subthalamic nucleus (STN), through which the motor and prefrontal cerebral cortex can modulate basal ganglia activity. Further, direct activation of the motor HDP is thought to be an important component of therapeutic deep brain stimulation (DBS), mediating the disruption of pathological oscillations. Alternatively, unintended recruitment of the prefrontal HDP may partly explain some cognitive side effects of DBS therapy. Previous work describing the HDP has focused on non-human primate (NHP) histological pathway tracings, diffusion-weighted MRI analysis of human white matter, and electrophysiology studies involving paired cortical recordings with DBS. However, none of these approaches alone yields a complete understanding of the complexities of the HDP. As such, we propose that generative modeling methods hold promise to bridge anatomy and physiology results, from both NHPs and humans, into a more detailed representation of the human HDP. Nonetheless, numerous features of the HDP remain to be experimentally described before model-based methods can simulate corticosubthalamic activity with a high degree of scientific detail. Therefore, the goals of this review are to examine the experimental evidence for HDP projections from across the primate neocortex and discuss new data which are required to improve the utility of anatomical and biophysical models of the human corticosubthalamic system.

Neurophysiological mechanisms of error monitoring in human and non-human primates

Performance monitoring is an important executive function that allows us to gain insight into our own behaviour. This remarkable ability relies on the frontal cortex, and its impairment is an aspect of many psychiatric diseases. In recent years, recordings from the macaque and human medial frontal cortex have offered a detailed understanding of the neurophysiological substrate that underlies performance monitoring. Here we review the discovery of single-neuron correlates of error monitoring, a key aspect of performance monitoring, in both species. These neurons are the generators of the error-related negativity, which is a non-invasive biomarker that indexes error detection. We evaluate a set of tasks that allows the synergistic elucidation of the mechanisms of cognitive control across the two species, consider differences in brain anatomy and testing conditions across species, and describe the clinical relevance of these findings for understanding psychopathology. Last, we integrate the body of experimental facts into a theoretical framework that offers a new perspective on how error signals are computed in both species and makes novel, testable predictions.

Differential effects of group III metabotropic glutamate receptors on spontaneous inhibitory synaptic currents in spine-innervating double bouquet and parvalbumin-expressing dendrite-targeting GABAergic interneurons in human neocortex

Diverse neocortical GABAergic neurons specialize in synaptic targeting and their effects are modulated by presynaptic metabotropic glutamate receptors (mGluRs) suppressing neurotransmitter release in rodents, but their effects in human neocortex are unknown. We tested whether activation of group III mGluRs by L-AP4 changes GABAA receptor-mediated spontaneous inhibitory postsynaptic currents (sIPSCs) in 2 distinct dendritic spine-innervating GABAergic interneurons recorded in vitro in human neocortex. Calbindin-positive double bouquet cells (DBCs) had columnar "horsetail" axons descending through layers II-V innervating dendritic spines (48%) and shafts, but not somata of pyramidal and nonpyramidal neurons. Parvalbumin-expressing dendrite-targeting cell (PV-DTC) axons extended in all directions innervating dendritic spines (22%), shafts (65%), and somata (13%). As measured, 20% of GABAergic neuropil synapses innervate spines, hence DBCs, but not PV-DTCs, preferentially select spine targets. Group III mGluR activation paradoxically increased the frequency of sIPSCs in DBCs (to median 137% of baseline) but suppressed it in PV-DTCs (median 92%), leaving the amplitude unchanged. The facilitation of sIPSCs in DBCs may result from their unique GABAergic input being disinhibited via network effect. We conclude that dendritic spines receive specialized, diverse GABAergic inputs, and group III mGluRs differentially regulate GABAergic synaptic transmission to distinct GABAergic cell types in human cortex.

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.

Developmental mechanisms underlying the evolution of human cortical circuits

The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.

The Development of Synapses in Mouse and Macaque Primary Sensory Cortices

We report that the rate of synapse development in primary sensory cortices of mice and macaques is unrelated to lifespan, as was previously thought. We analyzed 28,084 synapses over multiple developmental time points in both species and find, instead, that net excitatory synapse development of mouse and macaque neurons primarily increased at similar rates in the first few postnatal months, and then decreased over a span of 1-1.5 years of age. The development of inhibitory synapses differed qualitatively across species. In macaques, net inhibitory synapses first increase and then decrease on excitatory soma at similar ages as excitatory synapses. In mice, however, such synapses are added throughout life. These findings contradict the long-held belief that the cycle of synapse formation and pruning occurs earlier in shorter-lived animals. Instead, our results suggest more nuanced rules, with the development of different types of synapses following different timing rules or different trajectories across species.

Molecular and cellular evolution of the amygdala across species analyzed by single-nucleus transcriptome profiling

The amygdala, or an amygdala-like structure, is found in the brains of all vertebrates and plays a critical role in survival and reproduction. However, the cellular architecture of the amygdala and how it has evolved remain elusive. Here, we generated single-nucleus RNA-sequencing data for more than 200,000 cells in the amygdala of humans, macaques, mice, and chickens. Abundant neuronal cell types from different amygdala subnuclei were identified in all datasets. Cross-species analysis revealed that inhibitory neurons and inhibitory neuron-enriched subnuclei of the amygdala were well-conserved in cellular composition and marker gene expression, whereas excitatory neuron-enriched subnuclei were relatively divergent. Furthermore, LAMP5⁺ interneurons were much more abundant in primates, while DRD2⁺ inhibitory neurons and LAMP5⁺SATB2⁺ excitatory neurons were dominant in the human central amygdalar nucleus (CEA) and basolateral amygdalar complex (BLA), respectively. We also identified CEA-like neurons and their species-specific distribution patterns in chickens. This study highlights the extreme cell-type diversity in the amygdala and reveals the conservation and divergence of cell types and gene expression patterns across species that may contribute to species-specific adaptations.

HCN channels at the cell soma ensure the rapid electrical reactivity of fast-spiking interneurons in human neocortex

Accumulating evidence indicates that there are substantial species differences in the properties of mammalian neurons, yet theories on circuit activity and information processing in the human brain are based heavily on results obtained from rodents and other experimental animals. This knowledge gap may be particularly important for understanding the neocortex, the brain area responsible for the most complex neuronal operations and showing the greatest evolutionary divergence. Here, we examined differences in the electrophysiological properties of human and mouse fast-spiking GABAergic basket cells, among the most abundant inhibitory interneurons in cortex. Analyses of membrane potential responses to current input, pharmacologically isolated somatic leak currents, isolated soma outside-out patch recordings, and immunohistochemical staining revealed that human neocortical basket cells abundantly express hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channel isoforms HCN1 and HCN2 at the cell soma membrane, whereas these channels are sparse at the rodent basket cell soma membrane. Antagonist experiments showed that HCN channels in human neurons contribute to the resting membrane potential and cell excitability at the cell soma, accelerate somatic membrane potential kinetics, and shorten the lag between excitatory postsynaptic potentials and action potential generation. These effects are important because the soma of human fast-spiking neurons without HCN channels exhibit low persistent ion leak and slow membrane potential kinetics, compared with mouse fast-spiking neurons. HCN channels speed up human cell membrane potential kinetics and help attain an input-output rate close to that of rodent cells. Computational modeling demonstrated that HCN channel activity at the human fast-spiking cell soma membrane is sufficient to accelerate the input-output function as observed in cell recordings. Thus, human and mouse fast-spiking neurons exhibit functionally significant differences in ion channel composition at the cell soma membrane to set the speed and fidelity of their input-output function. These HCN channels ensure fast electrical reactivity of fast-spiking cells in human neocortex.

A cellular taxonomy of the adult human spinal cord

The mammalian spinal cord functions as a community of cell types for sensory processing, autonomic control, and movement. While animal models have advanced our understanding of spinal cellular diversity, characterizing human biology directly is important to uncover specialized features of basic function and human pathology. Here, we present a cellular taxonomy of the adult human spinal cord using single-nucleus RNA sequencing with spatial transcriptomics and antibody validation. We identified 29 glial clusters and 35 neuronal clusters, organized principally by anatomical location. To demonstrate the relevance of this resource to human disease, we analyzed spinal motoneurons, which degenerate in amyotrophic lateral sclerosis (ALS) and other diseases. We found that compared with other spinal neurons, human motoneurons are defined by genes related to cell size, cytoskeletal structure, and ALS, suggesting a specialized molecular repertoire underlying their selective vulnerability. We include a web resource to facilitate further investigations into human spinal cord biology.

scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data

The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.

scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data

The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.

Biophysical parameters control signal transfer in spiking network

Introduction

Information transmission and representation in both natural and artificial networks is dependent on connectivity between units. Biological neurons, in addition, modulate synaptic dynamics and post-synaptic membrane properties, but how these relate to information transmission in a population of neurons is still poorly understood. A recent study investigated local learning rules and showed how a spiking neural network can learn to represent continuous signals. Our study builds on their model to explore how basic membrane properties and synaptic delays affect information transfer.

Methods

The system consisted of three input and output units and a hidden layer of 300 excitatory and 75 inhibitory leaky integrate-and-fire (LIF) or adaptive integrate-and-fire (AdEx) units. After optimizing the connectivity to accurately replicate the input patterns in the output units, we transformed the model to more biologically accurate units and included synaptic delay and concurrent action potential generation in distinct neurons. We examined three different parameter regimes which comprised either identical physiological values for both excitatory and inhibitory units (Comrade), more biologically accurate values (Bacon), or the Comrade regime whose output units were optimized for low reconstruction error (HiFi). We evaluated information transmission and classification accuracy of the network with four distinct metrics: coherence, Granger causality, transfer entropy, and reconstruction error.

Results

Biophysical parameters showed a major impact on information transfer metrics. The classification was surprisingly robust, surviving very low firing and information rates, whereas information transmission overall and particularly low reconstruction error were more dependent on higher firing rates in LIF units. In AdEx units, the firing rates were lower and less information was transferred, but interestingly the highest information transmission rates were no longer overlapping with the highest firing rates.

Discussion

Our findings can be reflected on the predictive coding theory of the cerebral cortex and may suggest information transfer qualities as a phenomenological quality of biological cells.

Brain Data Standards - A method for building data-driven cell-type ontologies

Large-scale single-cell 'omics profiling is being used to define a complete catalogue of brain cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem: How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a partial solution to these problems, but no existing ontology schemas support the definition of cell types by direct reference to supporting data, classification of cell types using classifications derived directly from data, or links from cell types to marker sets along with confidence scores. Here we describe a generally applicable schema that solves these problems and its application in a semi-automated pipeline to build a data-linked extension to the Cell Ontology representing cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole-brain atlases currently in preparation.

Cross-species transcriptomic atlas of dorsal root ganglia reveals species-specific programs for sensory function

Sensory neurons of the dorsal root ganglion (DRG) are critical for maintaining tissue homeostasis by sensing and initiating responses to stimuli. While most preclinical studies of DRGs are conducted in rodents, much less is known about the mechanisms of sensory perception in primates. We generated a transcriptome atlas of mouse, guinea pig, cynomolgus monkey, and human DRGs by implementing a common laboratory workflow and multiple data-integration approaches to generate high-resolution cross-species mappings of sensory neuron subtypes. Using our atlas, we identified conserved core modules highlighting subtype-specific biological processes related to inflammatory response. We also identified divergent expression of key genes involved in DRG function, suggesting species-specific adaptations specifically in nociceptors that likely point to divergent function of nociceptors. Among these, we validated that TAFA4, a member of the druggable genome, was expressed in distinct populations of DRG neurons across species, highlighting species-specific programs that are critical for therapeutic development.

Identifying foetal forebrain interneurons as a target for monogenic autism risk factors and the polygenic 16p11.2 microdeletion

BACKGROUND

Autism spectrum condition or 'autism' is associated with numerous genetic risk factors including the polygenic 16p11.2 microdeletion. The balance between excitatory and inhibitory neurons in the cerebral cortex is hypothesised to be critical for the aetiology of autism making improved understanding of how risk factors impact on the development of these cells an important area of research. In the current study we aim to combine bioinformatics analysis of human foetal cerebral cortex gene expression data with anatomical and electrophysiological analysis of a 16p11.2^+/- rat model to investigate how genetic risk factors impact on inhibitory neuron development.

METHODS

We performed bioinformatics analysis of single cell transcriptomes from gestational week (GW) 8-26 human foetal prefrontal cortex and anatomical and electrophysiological analysis of 16p11.2^+/- rat cerebral cortex and hippocampus at post-natal day (P) 21.

RESULTS

We identified a subset of human interneurons (INs) first appearing at GW23 with enriched expression of a large fraction of risk factor transcripts including those expressed from the 16p11.2 locus. This suggests the hypothesis that these foetal INs are vulnerable to mutations causing autism. We investigated this in a rat model of the 16p11.2 microdeletion. We found no change in the numbers or position of either excitatory or inhibitory neurons in the somatosensory cortex or CA1 of 16p11.2^+/- rats but found that CA1 Sst INs were hyperexcitable with an enlarged axon initial segment, which was not the case for CA1 pyramidal cells.

LIMITATIONS

The human foetal gene expression data was acquired from cerebral cortex between gestational week (GW) 8 to 26. We cannot draw inferences about potential vulnerabilities to genetic autism risk factors for cells not present in the developing cerebral cortex at these stages. The analysis 16p11.2^+/- rat phenotypes reported in the current study was restricted to 3-week old (P21) animals around the time of weaning and to a single interneuron cell-type while in human 16p11.2 microdeletion carriers symptoms likely involve multiple cell types and manifest in the first few years of life and on into adulthood.

CONCLUSIONS

We have identified developing interneurons in human foetal cerebral cortex as potentially vulnerable to monogenic autism risk factors and the 16p11.2 microdeletion and report interneuron phenotypes in post-natal 16p11.2^+/- rats.

The Neuroscience Multi-Omic Archive: a BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain

Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org).

Mobility Coupled with Motivation Promotes Survival: The Evolution of Cognition as an Adaptive Strategy

Morphine plays a critical regulatory role in both simple and complex plant species. Dopamine is a critical chemical intermediate in the morphine biosynthetic pathway and may have served as a primordial agonist in developing catecholamine signaling pathways. While dopamine remains the preeminent catecholamine in invertebrate neural systems, epinephrine is the major product of catecholamine synthetic pathways in vertebrate species. Given that the enzymatic steps leading to the generation of morphine are similar to those constraining the evolutionary adaptation of the biosynthesis of catecholamines, we hypothesize that the emergence of these more advanced signaling pathways was based on conservation and selective "retrofitting" of pre-existing enzyme activities. This is consistent with observations that support the recruitment of enzymatically synthesized tetrahydrobiopterin (BH4), which is a cofactor for tyrosine hydroxylase, the enzyme responsible for dopamine production. BH4 is also an electron donor involved in the production of nitric oxide (NO). The links that coordinate BH4-mediated NO and catecholaminergic-mediated processes provide these systems with the capacity to regulate numerous downstream signaling pathways. We hypothesize that the evolution of catecholamine signaling pathways in animal species depends on the acquisition of a mobile lifestyle and motivationally driven feeding, sexual, and self-protective responses.

Neurodevelopmental disorders-high-resolution rethinking of disease modeling

Neurodevelopmental disorders arise due to various risk factors that can perturb different stages of brain development, and a combinatorial impact of these risk factors programs the phenotype in adulthood. While modeling the complete phenotype of a neurodevelopmental disorder is challenging, individual developmental perturbations can be successfully modeled in vivo in animals and in vitro in human cellular models. Nevertheless, our limited knowledge of human brain development restricts modeling strategies and has raised questions of how well a model corresponds to human in vivo brain development. Recent progress in high-resolution analysis of human tissue with single-cell and spatial omics techniques has enhanced our understanding of the complex events that govern the development of the human brain in health and disease. This new knowledge can be utilized to improve modeling of neurodevelopmental disorders and pave the way to more accurately portraying the relevant developmental perturbations in disease models.

Extraction and Purification of Single Nuclei from Frozen Human Brain Tissue

Resolving the complexity of the human brain at the level of single cells is essential to gaining an understanding of the immense diversity of cell types and functional states in both healthy and diseased brains. To exploit fully the technologies available for such studies, one must extract and isolate pure nuclei from unfixed postmortem tissue while preserving the molecules to be interrogated. Currently, nuclei are necessary substitutes for individual brain cells, since myriad cell types/sub-types constituting the human brain are embedded within the neuropil-a complex milieu of interconnected cells, processes, and synapses-which precludes intact and selective isolation of single brain cells. Here, we describe a protocol for the extraction and purification of intact single nuclei from frozen human brain tissue along with modifications to accommodate numerous downstream analyses, particularly for transcriptomic applications.

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.

The molecular evolution of spermatogenesis across mammals

The testis produces gametes through spermatogenesis and evolves rapidly at both the morphological and molecular level in mammals^1-6, probably owing to the evolutionary pressure on males to be reproductively successful⁷. However, the molecular evolution of individual spermatogenic cell types across mammals remains largely uncharacterized. Here we report evolutionary analyses of single-nucleus transcriptome data for testes from 11 species that cover the three main mammalian lineages (eutherians, marsupials and monotremes) and birds (the evolutionary outgroup), and include seven primates. We find that the rapid evolution of the testis was driven by accelerated fixation rates of gene expression changes, amino acid substitutions and new genes in late spermatogenic stages, probably facilitated by reduced pleiotropic constraints, haploid selection and transcriptionally permissive chromatin. We identify temporal expression changes of individual genes across species and conserved expression programs controlling ancestral spermatogenic processes. Genes predominantly expressed in spermatogonia (germ cells fuelling spermatogenesis) and Sertoli (somatic support) cells accumulated on X chromosomes during evolution, presumably owing to male-beneficial selective forces. Further work identified transcriptomal differences between X- and Y-bearing spermatids and uncovered that meiotic sex-chromosome inactivation (MSCI) also occurs in monotremes and hence is common to mammalian sex-chromosome systems. Thus, the mechanism of meiotic silencing of unsynapsed chromatin, which underlies MSCI, is an ancestral mammalian feature. Our study illuminates the molecular evolution of spermatogenesis and associated selective forces, and provides a resource for investigating the biology of the testis across mammals.

Characterizing cis-regulatory elements using single-cell epigenomics

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets

Ambient RNA contamination in single-cell and single-nuclei RNA sequencing (snRNA-seq) is a significant problem, but its consequences are poorly understood. Here, we show that ambient RNAs in brain snRNA-seq datasets have a nuclear or non-nuclear origin with distinct gene set signatures. Both ambient RNA signatures are predominantly neuronal, and we find that some previously annotated neuronal cell types are distinguished by ambient RNA contamination. We detect pervasive neuronal ambient RNA contamination in all glial cell types unless glia and neurons are physically separated prior to sequencing. We demonstrate that this contamination can be removed in silico and show that previous single-nuclei RNA-seq-based annotations of immature oligodendrocytes are glial nuclei contaminated with ambient RNAs. After ambient RNA removal, we detect rare, committed oligodendrocyte progenitor cells not annotated in most previous adult human brain datasets. Together, these results provide an in-depth analysis of ambient RNA contamination in brain single-nuclei datasets.

Defining the extent of gene function using ROC curvature

MOTIVATION

Interactions between proteins help us understand how genes are functionally related and how they contribute to phenotypes. Experiments provide imperfect 'ground truth' information about a small subset of potential interactions in a specific biological context, which can then be extended to the whole genome across different contexts, such as conditions, tissues or species, through machine learning methods. However, evaluating the performance of these methods remains a critical challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves.

RESULTS

We identify Functional Equivalence Classes (FECs), subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves built from gene-centric prediction tasks, such as function or interaction predictions. FECs are widespread across data types and methods, they can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10-50 genes), and tissue-specific secondary markers (100-500 genes). In addition, FECs suggest the existence of functional modules that span a wide range of the genome, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in the definition of functional gene sets.

AVAILABILITY AND IMPLEMENTATION

Code for analyses and figures is available at https://github.com/yexilein/pyroc.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multiregion transcriptomic profiling of the primate brain reveals signatures of aging and the social environment

Aging is accompanied by a host of social and biological changes that correlate with behavior, cognitive health and susceptibility to neurodegenerative disease. To understand trajectories of brain aging in a primate, we generated a multiregion bulk (N = 527 samples) and single-nucleus (N = 24 samples) brain transcriptional dataset encompassing 15 brain regions and both sexes in a unique population of free-ranging, behaviorally phenotyped rhesus macaques. We demonstrate that age-related changes in the level and variance of gene expression occur in genes associated with neural functions and neurological diseases, including Alzheimer's disease. Further, we show that higher social status in females is associated with younger relative transcriptional ages, providing a link between the social environment and aging in the brain. Our findings lend insight into biological mechanisms underlying brain aging in a nonhuman primate model of human behavior, cognition and health.

Molecular and spatial heterogeneity of microglia in Rasmussen encephalitis

Rasmussen encephalitis (RE) is a rare childhood neurological disease characterized by progressive unilateral loss of function, hemispheric atrophy and drug-resistant epilepsy. Affected brain tissue shows signs of infiltrating cytotoxic T-cells, microglial activation, and neuronal death, implicating an inflammatory disease process. Recent studies have identified molecular correlates of inflammation in RE, but cell-type-specific mechanisms remain unclear. We used single-nucleus RNA-sequencing (snRNA-seq) to assess gene expression across multiple cell types in brain tissue resected from two children with RE. We found transcriptionally distinct microglial populations enriched in RE compared to two age-matched individuals with unaffected brain tissue and two individuals with Type I focal cortical dysplasia (FCD). Specifically, microglia in RE tissues demonstrated increased expression of genes associated with cytokine signaling, interferon-mediated pathways, and T-cell activation. We extended these findings using spatial proteomic analysis of tissue from four surgical resections to examine expression profiles of microglia within their pathological context. Microglia that were spatially aggregated into nodules had increased expression of dynamic immune regulatory markers (PD-L1, CD14, CD11c), T-cell activation markers (CD40, CD80) and were physically located near distinct CD4+ and CD8+ lymphocyte populations. These findings help elucidate the complex immune microenvironment of RE.

Software Components and Product Variety in a Platform Ecosystem: A Dynamic Network Analysis of WordPress

Software components such as application programming interfaces (APIs) provided by external developers are vital to online digital platforms. Although APIs generally increase the variety of products according to anecdote, the precise relationship between the categories of APIs and product variety is not yet known. We find that APIs, regarding their use frequency, are categorized into three groups. The core is a group of frequently used APIs, whereas the periphery is a group of sparsely used APIs. In a large and mature platform ecosystem, an additional group of APIs, the regular core, mainly provided by third-party developers, emerges. APIs in the regular core are the main driver of product variety. However, we also find that the strength of this effect diminishes in a newly created product category when most of the new products are built by duplicating the usage of APIs from other products. A platform owner can stimulate developers’ creativity by acting as a bridge between digital product providers and third-party developers. It can collect functional needs from third-party developers and then share them with product providers. Therefore, the latter can build APIs that developers need.

Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material

Background

Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.

Results

We show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.

Conclusion

We present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.

Identification of visual cortex cell types and species differences using single-cell RNA sequencing

The primate neocortex exerts high cognitive ability and strong information processing capacity. Here, we establish a single-cell RNA sequencing dataset of 133,454 macaque visual cortical cells. It covers major cortical cell classes including 25 excitatory neuron types, 37 inhibitory neuron types and all glial cell types. We identified layer-specific markers including HPCAL1 and NXPH4, and also identified two cell types, an NPY-expressing excitatory neuron type that expresses the dopamine receptor D3 gene; and a primate specific activity-dependent OSTN + sensory neuron type. Comparisons of our dataset with humans and mice show that the gene expression profiles differ between species in relation to genes that are implicated in the synaptic plasticity and neuromodulation of excitatory neurons. The comparisons also revealed that glutamatergic neurons may be more diverse across species than GABAergic neurons and non-neuronal cells. These findings pave the way for understanding how the primary cortex fulfills the high-cognitive functions.

Integrative cross-species analysis of GABAergic neuron cell types and their functions in Alzheimer's disease

Understanding the phenotypic and functional diversity of cerebral cortical GABAergic neurons requires a comprehensive analysis of key transcriptional signatures and neuronal subtype identity. However, the diversity and conservation of GABAergic neurons across multiple mammals remain unclear. Here, we collected the single-nucleus RNA sequencing (snRNA-seq) datasets of cerebral cortex from human, macaque, mouse, and pig to identify the conserved neuronal cell types across species. After systematic analysis of the heterogeneity of GABAergic neurons, we defined four major conserved GABAergic neuron subclasses (Inc SST, Inc LAMP5, Inc PVALB, and Inc VIP) across species. We characterized the species-enriched subclasses of GABAergic neurons from four mammals, such as Inc Meis2 in mouse. Then, we depicted the genetic regulatory network (GRNs) of GABAergic neuron subclasses, which showed the conserved and species-specific GRNs for GABAergic neuron cell types. Finally, we investigated the GABAergic neuron subclass-specific expression modules of Alzheimer's disease (AD)-related genes in GABAergic neuron cell types. Overall, our study reveals the conserved and divergent GABAergic neuron subclasses and GRNs across multiple species and unravels the gene expression modules of AD-risk genes in GABAergic neuron subclasses, facilitating the GABAergic neurons research and clinical treatment.

The large numbers of minicolumns in the primary visual cortex of humans, chimpanzees and gorillas are related to high visual acuity

Minicolumns are thought to be a fundamental neural unit in the neocortex and their replication may have formed the basis of the rapid cortical expansion that occurred during primate evolution. We sought evidence of minicolumns in the primary visual cortex (V-1) of three great apes, three rodents and representatives from three other mammalian orders: Eulipotyphla (European hedgehog), Artiodactyla (domestic pig) and Carnivora (ferret). Minicolumns, identified by the presence of a long bundle of radial, myelinated fibers stretching from layer III to the white matter of silver-stained sections, were found in the human, chimpanzee, gorilla and guinea pig V-1. Shorter bundles confined to one or two layers were found in the other species but represent modules rather than minicolumns. The inter-bundle distance, and hence density of minicolumns, varied systematically both within a local area that might represent a hypercolumn but also across the whole visual field. The distance between all bundles had a similar range for human, chimpanzee, gorilla, ferret and guinea pig: most bundles were 20-45 μm apart. By contrast, the space between bundles was greater for the hedgehog and pig (20-140 μm). The mean density of minicolumns was greater in tangential sections of the gorilla and chimpanzee (1,243-1,287 bundles/mm2) than in human (314-422 bundles/mm2) or guinea pig (643 bundles/mm2). The minicolumnar bundles did not form a hexagonal lattice but were arranged in thin curving and branched bands separated by thicker bands of neuropil/somata. Estimates of the total number of modules/minicolumns within V-1 were strongly correlated with visual acuity.

What Does the Frontopolar Cortex Contribute to Goal-Directed Cognition and Action?

Understanding the unique functions of different subregions of primate prefrontal cortex has been a longstanding goal in cognitive neuroscience. Yet, the anatomy and function of one of its largest subregions (the frontopolar cortex) remain enigmatic and underspecified. Our Society for Neuroscience minisymposium Primate Frontopolar Cortex: From Circuits to Complex Behaviors will comprise a range of new anatomic and functional approaches that have helped to clarify the basic circuit anatomy of the frontal pole, its functional involvement during performance of cognitively demanding behavioral paradigms in monkeys and humans, and its clinical potential as a target for noninvasive brain stimulation in patients with brain disorders. This review consolidates knowledge about the anatomy and connectivity of frontopolar cortex and provides an integrative summary of its function in primates. We aim to answer the question: what, if anything, does frontopolar cortex contribute to goal-directed cognition and action?

Spatially resolved gene regulatory and disease-related vulnerability map of the adult Macaque cortex

Single cell approaches have increased our knowledge about the cell type composition of the non-human primate (NHP), but a detailed characterization of area-specific regulatory features remains outstanding. We generated single-cell transcriptomic and chromatin accessibility (single-cell ATAC) data of 358,237 cells from prefrontal cortex (PFC), primary motor cortex (M1) and primary visual cortex (V1) of adult female cynomolgus monkey brain, and integrated this dataset with Stereo-seq (spatial enhanced resolution omics-sequencing) of the corresponding cortical areas to assign topographic information to molecular states. We identified area-specific chromatin accessible sites and their targeted genes, including the cell type-specific transcriptional regulatory network associated with excitatory neurons heterogeneity. We reveal calcium ion transport and axon guidance genes related to specialized functions of PFC and M1, identified the similarities and differences between adult macaque and human oligodendrocyte trajectories, and mapped the genetic variants and gene perturbations of human diseases to NHP cortical cells. This resource establishes a transcriptomic and chromatin accessibility combinatory regulatory landscape at a single-cell and spatially resolved resolution in NHP cortex.

Evolution of cortical neurons supporting human cognition

Human cognitive abilities are generally thought to arise from cortical expansion over the course of human brain evolution. In addition to increased neuron numbers, this cortical expansion might be driven by adaptations in the properties of single neurons and their local circuits. We review recent findings on the distinct structural, functional, and transcriptomic features of human cortical neurons and their organization in cortical microstructure. We focus on the supragranular cortical layers, which showed the most prominent expansion during human brain evolution, and the properties of their principal cells: pyramidal neurons. We argue that the evolutionary adaptations in neuronal features that accompany the expansion of the human cortex partially underlie interindividual variability in human cognitive abilities.

Mechanisms of Action of the Peptide Toxins Targeting Human and Rodent Acid-Sensing Ion Channels and Relevance to Their In Vivo Analgesic Effects

Acid-sensing ion channels (ASICs) are voltage-independent H⁺-gated cation channels largely expressed in the nervous system of rodents and humans. At least six isoforms (ASIC1a, 1b, 2a, 2b, 3 and 4) associate into homotrimers or heterotrimers to form functional channels with highly pH-dependent gating properties. This review provides an update on the pharmacological profiles of animal peptide toxins targeting ASICs, including PcTx1 from tarantula and related spider toxins, APETx2 and APETx-like peptides from sea anemone, and mambalgin from snake, as well as the dimeric protein snake toxin MitTx that have all been instrumental to understanding the structure and the pH-dependent gating of rodent and human cloned ASICs and to study the physiological and pathological roles of native ASICs in vitro and in vivo. ASICs are expressed all along the pain pathways and the pharmacological data clearly support a role for these channels in pain. ASIC-targeting peptide toxins interfere with ASIC gating by complex and pH-dependent mechanisms sometimes leading to opposite effects. However, these dual pH-dependent effects of ASIC-inhibiting toxins (PcTx1, mambalgin and APETx2) are fully compatible with, and even support, their analgesic effects in vivo, both in the central and the peripheral nervous system, as well as potential effects in humans.

Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D

Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.

Upper cortical layer-driven network impairment in schizophrenia

Schizophrenia is one of the most widespread and complex mental disorders. To characterize the impact of schizophrenia, we performed single-nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. In addition, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most marked in upper-layer GABAergic neurons, including down-regulation in energy metabolism and up-regulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Last, Visium spatial transcriptomics further corroborated upper-layer neuron vulnerability in schizophrenia. Overall, our results point toward general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology.

Recent advances in deciphering oligodendrocyte heterogeneity with single-cell transcriptomics

Oligodendrocytes (OL) have been for decades considered a passive, homogenous population of cells that provide support to neurons, and show a limited response to pathological stimuli. This view has been dramatically changed by the introduction of powerful transcriptomic methods that have uncovered a broad spectrum of OL populations that co-exist within the healthy central nervous system (CNS) and also across a variety of diseases. Specifically, single-cell and single-nucleus RNA-sequencing (scRNA-seq, snRNA-seq) have been used to reveal OL variations in maturation, myelination and immune status. The newly discovered immunomodulatory role suggests that OL may serve as targets for future therapies. In this review, we summarize the current understanding of OL heterogeneity in mammalian CNS as revealed by scRNA-seq and snRNA-seq. We provide a list of key studies that identify consensus marker genes defining the currently known OL populations. This resource can be used to standardize analysis of OL related datasets and improve their interpretation, ultimately leading to a better understanding of OL functions in health and disease.

Riding brain "waves" to identify human memory genes

While there is extensive research on memory-related oscillations and brain gene expression, the relationship between oscillations and gene expression has rarely been studied. Recently, progress has been made to identify specific genes associated with oscillations that are correlated with episodic memory. Neocortical regions, in particular the temporal pole, have been examined in this line of research due to their accessibility during neurosurgical procedures. By harnessing this accessibility, a unique and powerful study design has allowed gene expression and intracranial oscillatory data to be sourced from the same human patients. These studies have identified a plethora of understudied gene targets that should be further characterized with respect to human brain function. Future work should extend to other brain regions to increase our understanding of the genetic signatures of oscillations and, ultimately, human cognition.

Maturation and circuit integration of transplanted human cortical organoids

Self-organizing neural organoids represent a promising in vitro platform with which to model human development and disease1-5. However, organoids lack the connectivity that exists in vivo, which limits maturation and makes integration with other circuits that control behaviour impossible. Here we show that human stem cell-derived cortical organoids transplanted into the somatosensory cortex of newborn athymic rats develop mature cell types that integrate into sensory and motivation-related circuits. MRI reveals post-transplantation organoid growth across multiple stem cell lines and animals, whereas single-nucleus profiling shows progression of corticogenesis and the emergence of activity-dependent transcriptional programs. Indeed, transplanted cortical neurons display more complex morphological, synaptic and intrinsic membrane properties than their in vitro counterparts, which enables the discovery of defects in neurons derived from individuals with Timothy syndrome. Anatomical and functional tracings show that transplanted organoids receive thalamocortical and corticocortical inputs, and in vivo recordings of neural activity demonstrate that these inputs can produce sensory responses in human cells. Finally, cortical organoids extend axons throughout the rat brain and their optogenetic activation can drive reward-seeking behaviour. Thus, transplanted human cortical neurons mature and engage host circuits that control behaviour. We anticipate that this approach will be useful for detecting circuit-level phenotypes in patient-derived cells that cannot otherwise be uncovered.

Molecular and cellular evolution of the primate dorsolateral prefrontal cortex

The granular dorsolateral prefrontal cortex (dlPFC) is an evolutionary specialization of primates that is centrally involved in cognition. We assessed more than 600,000 single-nucleus transcriptomes from adult human, chimpanzee, macaque, and marmoset dlPFC. Although most cell subtypes defined transcriptomically are conserved, we detected several that exist only in a subset of species as well as substantial species-specific molecular differences across homologous neuronal, glial, and non-neural subtypes. The latter are exemplified by human-specific switching between expression of the neuropeptide somatostatin and tyrosine hydroxylase, the rate-limiting enzyme in dopamine production in certain interneurons. The above molecular differences are also illustrated by expression of the neuropsychiatric risk gene FOXP2, which is human-specific in microglia and primate-specific in layer 4 granular neurons. We generated a comprehensive survey of the dlPFC cellular repertoire and its shared and divergent features in anthropoid primates.