Neurodevelopmental disorders that cause cognitive, behavioural or motor impairments affect around 15% of children and adolescents worldwide1, with diagnoses of profound autism and attention deficit hyperactivity disorder increasing in the USA and contributing to a major economic burden2,3. Yet the origins and mechanisms of these conditions remain poorly understood, limiting progress in therapies. Comprehensive cell atlases of the developing human brain, alongside those of model organisms such as mice and non-human primates, are now providing high-resolution measures of gene expression, cell-type abundance and spatial distribution. In this Perspective, we highlight recent studies that have identified novel developmental cell populations, revealed conserved and divergent patterns of cell genesis, migration and maturation across species, and begun testing hypotheses that link them to processes ranging from transcriptional control of cell fate specification to the emergence of complex behaviours. We present remaining conceptual and technical challenges and provide an outlook on how further studies of human and mammalian brain development can empower a deeper understanding of neurodevelopmental and neuropsychiatric disorders. Future efforts expanding to additional developmental stages, including adolescence, as well as whole-brain, multimodal and cross-species integration, will yield new insights into how development shapes the brain. These atlases promise to serve as essential references for unravelling mechanisms of brain function and disease vulnerability, and for advancing precision medicine.

The mammalian cortex is composed of a highly diverse set of cell types and develops through a series of temporally regulated events1-3. Single-cell transcriptomics enables a systematic study of cell types across the entire timeline of cortical development. Here we present a comprehensive and high-resolution transcriptomic and epigenomic cell-type atlas of the developing mouse visual cortex. The atlas is built from a single-cell RNA sequencing dataset of 568,654 high-quality single-cell transcriptomes and a single-nucleus Multiome dataset of 200,061 high-quality nuclei, which were densely sampled across the embryonic and postnatal developmental stages (from embryonic day 11.5 to postnatal day 56). We computationally reconstructed a transcriptomic developmental trajectory map of all excitatory, inhibitory and non-neuronal cell types in the visual cortex. Branching points that mark the emergence of new cell types at specific developmental ages and molecular signatures of cellular diversification are identified. The trajectory map shows that neurogenesis, gliogenesis and early postmitotic maturation in the embryonic stage give rise to all cell classes and nearly all subclasses in a staggered parallel manner. Increasingly refined cell types emerge throughout the postnatal differentiation process, including the late emergence of many cell types during the eye-opening stage and the onset of critical period, suggesting that there is continuous cell-type diversification at different stages of cortical development. Throughout development, there are cooperative dynamic changes in gene expression and chromatin accessibility in specific cell types. We identify cell-type-specific and temporally resolved gene regulatory networks that link transcription factors and downstream target genes through accessible chromatin motifs. Collectively, our study provides a detailed dynamic molecular map directly associated with individual cell types and specific temporal events that can reveal the molecular logic underlying the complex and multifaceted cortical cell type and circuit development.

The telencephalon of the mammalian brain contains multiple regions and circuits that have adaptive and integrative roles in a variety of brain functions. GABAergic neurons in the telencephalon are diverse; they have many circuit functions, and dysfunction of these neurons has been implicated in various brain disorders1-3. Here we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished using 611,423 young adult single-cell transcriptomes and 614,569 single-cell transcriptomes collected from multiple prenatal and postnatal developmental timepoints. We present a hierarchically organized adult telencephalic GABAergic neuronal cell-type taxonomy of 7 classes, 52 subclasses, 284 supertypes and 1,051 clusters, as well as a corresponding developmental taxonomy of 1,688 clusters across ages from embryonic day 7 to postnatal day 14. Detailed charting efforts reveal extraordinary complexity whereby relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types are often found in distant and diverse brain regions, indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Moreover, we find various spatial dimensions of both discrete and continuous variation among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal, preoptic and most pallidal GABAergic neuronal types emerge in a burst during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell-type taxonomy will serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community.

The human neocortex is composed of diverse cell types1 that are generated during development according to spatially and temporally organized programmes initiated by neural stem cells2-5. Despite the growing number of studies that have captured snapshots of gene expression of single cells along the axis of differentiation and maturation, the underlying map of lineage relationships that link individual progenitor cells to specific subtypes of neurons and glia remains unknown, especially in humans. Here we applied prospective lineage tracing to map the manifold of human neural stem and progenitor cell differentiation across the developmental window encompassing neurogenesis and gliogenesis in human primary tissue. By profiling the clonal output of 6,402 progenitor cells, we created a lineage-resolved map of human cortical development. Here we show that cortical progenitors switch from glutamatergic to GABAergic (involving γ-aminobutyric acid) neurogenesis around midgestation, which coincides with an onset of oligodendrocyte generation. Additionally, we find that truncated radial glia maintain a glutamatergic neurogenic potential for a protracted period during human cortical development. Unexpectedly, we find that late-born glutamatergic neurons derived from truncated radial glia exhibit molecular features of deep cortical layer neurons and may contribute to the expansion of the subplate region during midgestation.

Mammalian brains vary in size, structure and function, but the extent to which evolutionarily novel cell types contribute to this variation remains unresolved1-4. Previous studies suggest that there is a primate-specific population of striatal inhibitory interneurons-the TAC3 interneurons5. However, broader taxonomic and developmental characterization is required to address novelty in cell-type evolution. Here we examine gene expression in inhibitory neurons across 10 mammalian species, spanning 160 million years of divergence from primates. We find that the initial class of newborn TAC3 interneurons specified during development represents an ancestral, medial ganglionic eminence (MGE)-derived striatal population that is also present in pig and ferret cortex. This discovery prompted a re-examination of Glires, including mice, which are thought to lack the TAC3 type5,6. Targeted enrichment of MGE precursors in mice revealed conservation of the TAC3 initial class, camouflaged by reduced expression of Tac2 (the mouse orthologue of TAC3) and a gain of Th expression. Extending our analysis to the adult striatum further supported the homology of primate TAC3 and mouse Th striatal interneurons, and also uncovered a rare Tac2 subpopulation in the mouse ventromedial striatum. This study suggests that initial classes of telencephalic inhibitory neurons are largely conserved, and that during evolution, neuronal types in the mammalian brain change through redistribution and fate refinement, rather than by derivation of novel precursors early in development.

The endoplasmic reticulum (ER) is a highly interconnected membrane network that serves as a central site for protein synthesis and maturation1. A crucial subset of ER-associated transcripts, termed secretome mRNAs, encode secretory, lumenal and integral membrane proteins, representing nearly one-third of human protein-coding genes1. Unlike cytosolic mRNAs, secretome mRNAs undergo co-translational translocation, and thus require precise coordination between translation and protein insertion2,3. Disruption of this process, such as through altered elongation rates4, activates stress response pathways that impede cellular growth, raising the question of whether secretome translation is spatially organized to ensure fidelity. Here, using live-cell single-molecule imaging, we demonstrate that secretome mRNA translation is preferentially localized to ER junctions that are enriched with the structural protein lunapark and in close proximity to lysosomes. Lunapark depletion reduced ribosome density and translation efficiency of secretome mRNAs near lysosomes, an effect that was dependent on eIF2-mediated initiation and was reversed by the integrated stress response inhibitor ISRIB. Lysosome-associated translation was further modulated by nutrient status: amino acid deprivation enhanced lysosome-proximal translation, whereas lysosomal pH neutralization suppressed it. These findings identify a mechanism by which ER junctional proteins and lysosomal activity cooperatively pattern secretome mRNA translation, linking ER architecture and nutrient sensing to the production of secretory and membrane proteins.

Fibrous materials that provide reversible actuation1,2 or adapt mechanical properties3,4 in response to external stimuli hold great promise for smart textiles5, soft robotics6 and wearable technologies7. Although considerable progress has been made in creating fibrous materials responsive to scalar stimuli such as voltage8, temperature6, humidity2 and ion concentration9, these technologies often lack directional controllability and functional diversity10-14. Here we report a class of vector-stimuli-responsive magnetorheological fibrous materials, guided by our engineering model integrating the structural mechanics of textiles with the magnetics of soft magnetic materials. We mass-produced soft magnetic polymer composite fibres with optimized mechanical and magnetic properties, which we then assembled into concentric helical yarns. These yarns exhibited pronounced bending and stiffening properties controlled by the direction and magnitude of magnetic fields, allowing for customized fabrics with various actuation and stiffening functionalities. We demonstrated innovative smart textiles derived from those fabrics, including an active ventilation fabric for personal moisture management, an integrated conformable gripper for handling objects of varying shapes and stiffness, and a compact remote-controllable haptic finger glove that replicates the sensation of fabric hardness and smoothness. Our work provides insights into stimuli-responsive fibrous materials, elevating them from scalar to sophisticated vector control, heralding an era of smart textile innovation.

Densely substituted aromatic rings are ubiquitous in pharmaceuticals and agrochemicals1. For making aromatic molecules, aryne intermediates have synthetic potential that rivals most functional groups2. They readily react with nucleophiles, participate in pericyclic reactions, and activate inert σ-bonds. Despite their potential, arynes are currently used by a specialized community for mainly niche applications. The lack of widespread adoption of arynes is due to the undesirable means to generate them. Here, we report the design of an aryne precursor to overcome this prohibitive barrier. Readily available carboxylic acids are derivatized in a single step to a make a precursor which is then activated by blue light or by heat. Dozens of previously unknown aminated arynes, including pyridynes, are generated in this work, opening the door to drug discovery using aryne intermediates. We envision that future development of this precursor platform will allow even more decorated arynes to be accessed, further expanding the reach of aryne chemistry.

Computer vision is central to many artificial intelligence (AI) applications, from autonomous vehicles to consumer devices. However, the data behind such technical innovations are often collected with insufficient consideration of ethical concerns1-3. This has led to a reliance on datasets that lack diversity, perpetuate biases and are collected without the consent of data rights holders. These datasets compromise the fairness and accuracy of AI models and disenfranchise stakeholders4-8. Although awareness of the problems of bias in computer vision technologies, particularly facial recognition, has become widespread9, the field lacks publicly available, consensually collected datasets for evaluating bias for most tasks3,10,11. In response, we introduce the Fair Human-Centric Image Benchmark (FHIBE, pronounced 'Feebee'), a publicly available human image dataset implementing best practices for consent, privacy, compensation, safety, diversity and utility. FHIBE can be used responsibly as a fairness evaluation dataset for many human-centric computer vision tasks, including pose estimation, person segmentation, face detection and verification, and visual question answering. By leveraging comprehensive annotations capturing demographic and physical attributes, environmental factors, instrument and pixel-level annotations, FHIBE can identify a wide variety of biases. The annotations also enable more nuanced and granular bias diagnoses, enabling practitioners to better understand sources of bias and mitigate potential downstream harms. FHIBE therefore represents an important step forward towards trustworthy AI, raising the bar for fairness benchmarks and providing a road map for responsible data curation in AI.

Microglia, the innate immune cells of the brain, play a defining role in the progression of Alzheimer's disease (AD)1. The microglial response to amyloid plaques in AD can range from neuroprotective to neurotoxic2. Here we show that the protective function of microglia is governed by the transcription factor PU.1, which becomes downregulated following microglial contact with plaques. Lowering PU.1 expression in microglia reduces the severity of amyloid disease pathology in mice and is linked to the expression of immunoregulatory lymphoid receptor proteins, particularly CD28, a surface receptor that is critical for T cell activation3,4. Microglia-specific deficiency in CD28, which is expressed by a small subset of plaque-associated PU.1low microglia, promotes a broad inflammatory microglial state that is associated with increased amyloid plaque load. Our findings indicate that PU.1low CD28-expressing microglia may operate as suppressive microglia that mitigate the progression of AD by reducing the severity of neuroinflammation. This role of CD28 and potentially other lymphoid co-stimulatory and co-inhibitory receptor proteins in governing microglial responses in AD points to possible immunotherapy approaches for treating the disease by promoting protective microglial functions.

Materials improvement is a powerful approach to reducing loss and decoherence in superconducting qubits, because such improvements can be readily translated to large-scale processors. Recent work improved transmon coherence by using tantalum as a base layer and sapphire as a substrate1. The losses in these devices are dominated by two-level systems with comparable contributions from both the surface and bulk dielectrics2, indicating that both must be tackled to achieve substantial improvements in the state of the art. Here we show that replacing the substrate with high-resistivity silicon markedly decreases the bulk substrate loss, enabling 2D transmons with time-averaged quality factors (Qavg) of 9.7 × 106 across 45 qubits. For our best qubit, we achieve a Qavg of 1.5 × 107, reaching a maximum Q of 2.5 × 107, corresponding to a lifetime (T1) up to 1.68 ms. This low loss also allows us to observe decoherence effects related to the Josephson junction, and we use an improved, low-contamination junction deposition to achieve Hahn echo coherence times (T2E) exceeding T1. We achieve these materials improvements without any modifications to the qubit architecture, allowing us to readily incorporate standard quantum control gates. We demonstrate single-qubit gates with 99.994% fidelity. The tantalum-on-silicon platform comprises a simple material stack that can potentially be fabricated at the wafer scale and therefore can be readily translated to large-scale quantum processors.

As a member of the G protein-coupled receptor superfamily, the μ-opioid receptor (MOR) activates heterotrimeric G proteins by opening the Gα α-helical domain (AHD) to enable GDP-GTP exchange, with GDP release representing the rate-limiting step1,2. Here, using pharmacological assays, we show that agonist efficacy correlates with decreased GDP affinity, promoting GTP exchange, whereas antagonists increase GDP affinity, dampening activation. Further investigating this phenomenon, we provide 8 unique structural models and 16 cryogenic electron microscopy maps of MOR with naloxone or loperamide, capturing several intermediate conformations along the activation pathway. These include four GDP-bound states with previously undescribed receptor-G protein interfaces, AHD arrangements and transitions in the nucleotide-binding pocket required for GDP release. Naloxone stalls MOR in a 'latent' state, whereas loperamide promotes an 'engaged' state, which is structurally poised for opening of the AHD domain and subsequent GDP release. These findings, supported by molecular dynamics simulations, identify GDP-bound intermediates and AHD conformations as key determinants of nucleotide exchange rates, providing structural and mechanistic insights into G protein activation and ligand efficacy with broad implications for G protein-coupled receptor pharmacology.

Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes1. Although these methods are conceptually similar, by analysing association studies of 209 quantitative traits in the UK Biobank2-4, we show that they systematically prioritize different genes. This raises the question of how genes should ideally be prioritized. We propose two prioritization criteria: (1) trait importance - how much a gene quantitatively affects a trait; and (2) trait specificity - the importance of a gene for the trait under study relative to its importance across all traits. We find that GWAS prioritize genes near trait-specific variants, whereas burden tests prioritize trait-specific genes. Because non-coding variants can be context specific, GWAS can prioritize highly pleiotropic genes, whereas burden tests generally cannot. Both study designs are also affected by distinct trait-irrelevant factors, complicating their interpretation. Our results illustrate that burden tests and GWAS reveal different aspects of trait biology and suggest ways to improve their interpretation and usage.

The central Southern Cone of South America was one of the last regions of the globe to become inhabited by people1, and remains under-represented in studies of ancient DNA. Here we report genome-wide data from 238 ancient individuals spanning ten millennia. The oldest, from the Pampas region and dating to 10,000 years before present (BP), had distinct genetic affinity to Middle Holocene Southern Cone individuals, showing that differentiation from the central Andes and central east Brazil had begun by this time. Individuals dating to 4,600-150 BP primarily descended from a previously unsampled deep lineage of which the earliest representative is an individual dating to around 8,500 BP. This central Argentina lineage co-existed with two other lineages during the Mid-Holocene and, within central Argentina, this ancestry persisted for thousands of years with little evidence of inter-regional migration. Central Argentina ancestry was involved in three distinct gene flows: it mixed into the Pampas by 3,300 BP and seemingly became the main component there after 800 BP, with central Andes ancestry in northwest Argentina, and with tropical and subtropical forest ancestry in the Gran Chaco. In northwest Argentina, there was an increased rate of close-kin unions by 1,000 BP, paralleling the pattern in the central Andes. In the Paraná River region, a 400 BP individual with a Guaraní archaeological association clusters with Brazilian groups, consistent with Guaraní presence by this time.

Breast cancer is the leading cause of cancer-related death in women worldwide1. Here, in the Breast Cancer-Anti-Progestin Prevention Study 1 (BC-APPS1; NCT02408770 ), we assessed whether progesterone receptor antagonism with ulipristal acetate for 12 weeks reduces surrogate markers of breast cancer risk in 24 premenopausal women. We used multilayered OMICs and live-cell approaches as readouts for molecular features alongside clinical imaging and tissue micromechanics correlates. Ulipristal acetate reduced epithelial proliferation (Ki67) and the proportion, proliferation and colony formation capacity of luminal progenitor cells, the putative cell of origin of aggressive breast cancers2. MRI scans showed reduction in fibroglandular volume with treatment, whereas single-cell RNA sequencing, proteomics, histology and atomic force microscopy identified extracellular matrix remodelling with reduced collagen organization and tissue stiffness. Collagen VI was the most significantly downregulated protein after ulipristal acetate treatment, and we uncovered an unanticipated spatial association between collagen VI and SOX9high luminal progenitor cell localization, establishing a link between collagen organization and luminal progenitor activity. Culture of primary human breast epithelial cells in a stiff environment increased luminal progenitor activity, which was antagonized by anti-progestin therapy, strengthening this mechanistic link. This study offers a template for biologically informed early-phase therapeutic cancer prevention trials and demonstrates the potential for premenopausal breast cancer prevention with progesterone receptor antagonists through stromal remodelling and luminal progenitor suppression.

Ketamine and electroconvulsive therapy (ECT) achieve rapid remission in treatment-resistant depression. However, their mechanisms of action-the understanding of which is essential for refining therapeutic precision-remain unclear1-3. Here, using mouse models, we identify adenosine signalling as a central pathway that underlies the antidepressant effects of these interventions. Results from genetically encoded adenosine sensor experiments and real-time optical recordings reveal that both therapies induce strong adenosine surges in key mood-regulatory regions, including the medial prefrontal cortex and the hippocampus. Genetic or pharmacological disruption of A1 and A2A adenosine receptors abolishes their therapeutic effects, which establishes the essential role of adenosine signalling in antidepressant efficacy. Notably, adenosine signalling specifically in the medial prefrontal cortex drives antidepressant actions. Ketamine increases adenosine by modulating cellular metabolism to increase intracellular adenosine levels without causing neuronal hyperactivity. Leveraging this mechanism, we develop ketamine derivatives that enhance adenosine signalling and exhibit improved antidepressant efficacy with reduced side effects at therapeutic doses. Furthermore, acute intermittent hypoxia, a non-pharmacological intervention involving controlled reductions in oxygen levels, increases brain adenosine levels and produces antidepressant effects, paralleling the actions of ketamine and ECT. Our findings establish adenosine as a pivotal mediator of rapid-acting antidepressants and a tractable target for scalable, noninvasive therapeutics in major depressive disorder.

Despite the central role of antibodies in modern medicine, no method currently exists to design novel, epitope-specific antibodies entirely in silico. Instead, antibody discovery currently relies on immunization, random library screening or the isolation of antibodies directly from patients1. Here we demonstrate that combining computational protein design using a fine-tuned RFdiffusion2 network with yeast display screening enables the de novo generation of antibody variable heavy chains (VHHs), single-chain variable fragments (scFvs) and full antibodies that bind to user-specified epitopes with atomic-level precision. We experimentally characterize VHH binders to four disease-relevant epitopes. Cryo-electron microscopy confirms the binding pose of designed VHHs targeting influenza haemagglutinin and Clostridium difficile toxin B (TcdB). A high-resolution structure of the influenza-targeting VHH confirms atomic accuracy of the designed complementarity-determining regions (CDRs). Although initial computational designs exhibit modest affinity (tens to hundreds of nanomolar Kd), affinity maturation using OrthoRep3 enables production of single-digit nanomolar binders that maintain the intended epitope selectivity. We further demonstrate the de novo design of scFvs to TcdB and a PHOX2B peptide-MHC complex by combining designed heavy-chain and light-chain CDRs. Cryo-electron microscopy confirms the binding pose for two distinct TcdB scFvs, with high-resolution data for one design verifying the atomically accurate design of the conformations of all six CDR loops. Our approach establishes a framework for the computational design, screening and characterization of fully de novo antibodies with atomic-level precision in both structure and epitope targeting.

Multiple-system atrophy (MSA) is a rapidly progressive neurodegenerative disease of unknown cause, typically affecting individuals aged 50-60 years and leading to death within a decade1-3. It is characterized by glial cytoplasmic inclusions (GCIs) composed of fibrillar α-synuclein (aSyn)4-8, the formation of which shows parallels with prion propagation9,10. While fibrils extracted from brains of individuals with MSA have been structurally characterized11, their ability to replicate in a protein-only manner has been questioned12, and their ability to induce GCIs in vivo remains unexplored. By contrast, the synthetic fibril strain 1B13,14, assembled from recombinant human aSyn, self-replicates in vitro and induces GCIs in mice15-suggesting direct relevance to MSA-but lacks scrutiny at the atomic scale. Here we report high-resolution structural analyses of 1B fibrils and of fibrils extracted from diseased mice injected with 1B that developed GCIs (1BP). We show in vivo that conformational templating enables fibril strain replication, resulting in MSA-like inclusion pathology. Notably, the structures of 1B and 1BP are highly similar and mimic the fold of aSyn observed in one protofilament of fibrils isolated from patients with MSA11. Moreover, reinjection of crude mouse brain homogenates containing 1BP into new mice reproduces the same MSA-like pathology induced by the parent synthetic seed 1B. Our findings identify 1B as a synthetic pathogen capable of self-replication in vivo and reveal structural features of 1B and 1BP that may underlie MSA pathology, offering insights for therapeutic strategies.

Receptor signalling determines cellular responses and is crucial for defining specific biological outcomes. In legume root cells, highly similar and structurally conserved chitin and Nod factor receptor kinases activate immune or symbiotic pathways, respectively, when chitinous ligands are perceived1. Here we show that specific amino acid residues in the intracellular part of the Nod factor receptor NFR1 control signalling specificity and enable the distinction of immune and symbiotic responses. Functional investigation of CERK6, NFR1 and receptor variants thereof revealed a conserved motif that we term Symbiosis Determinant 1 in the juxtamembrane region of the kinase domain, which is key for symbiotic signalling. We show that two residues in Symbiosis Determinant 1 are indispensable hallmarks of NFR1-type receptors and are sufficient to convert Lotus CERK6 and barley RLK4 kinase outputs to enable symbiotic signalling in Lotus japonicus.

Methane is a potent but short-lived greenhouse gas and rapid reductions of its anthropogenic emissions could help decrease near-term warming1. Solid waste emits methane through the decay of organic material, which amounts to about 10% of total anthropogenic methane emissions2. Satellite instruments3 enable monitoring of strong methane hotspots4, including many strongly emitting urban areas that include solid waste disposal sites as most prominent sources5. Here we present a survey of methane emissions from 151 individual waste disposal sites across six continents using high-resolution satellite observations that can detect localized methane emissions above 100 kg h-1. Within this dataset, we find that our satellite-based estimates generally show no correlation with reported or modelled emission estimates at facility scale. This reveals major uncertainties in the current understanding of methane emissions from waste disposal sites, warranting further investigations to reconcile bottom-up and top-down approaches. We also observe that managed landfills show lower emission per area than dumping sites, and that detected emission sources often align with the open non-covered parts of the facility where waste is added. Our results highlight the potential of high-resolution satellite observations to detect and monitor methane emissions from the waste sector globally, providing actionable insights to help improve emission estimates and focus mitigation efforts.