Mycorrhizal fungi are ecosystem engineers that sustain plant life and help regulate Earth's biogeochemical cycles1-3. However, in contrast to plants and animals, the global distribution of mycorrhizal fungal biodiversity is largely unknown, which limits our ability to monitor and protect key underground ecosystems4,5. Here we trained machine-learning algorithms on a global dataset of 25,000 geolocated soil samples comprising >2.8 billion fungal DNA sequences. We predicted arbuscular mycorrhizal and ectomycorrhizal fungal richness and rarity across terrestrial ecosystems. On the basis of these predictions, we generated high-resolution, global-scale maps and identified key reservoirs of highly diverse and endemic mycorrhizal communities. Intersecting protected areas with mycorrhizal hotspots indicated that less than 10% of predicted mycorrhizal richness hotspots currently exist in protected areas. Our results describe a largely hidden component of Earth's underground ecosystems and can help identify conservation priorities, set monitoring benchmarks and create specific restoration plans and land-management strategies.

Since the advent of computing, humans have sought computer input technologies that are expressive, intuitive and universal. While diverse modalities have been developed, including keyboards, mice and touchscreens, they require interaction with a device that can be limiting, especially in on-the-go scenarios. Gesture-based systems use cameras or inertial sensors to avoid an intermediary device, but tend to perform well only for unobscured movements. By contrast, brain-computer or neuromotor interfaces that directly interface with the body's electrical signalling have been imagined to solve the interface problem1, but high-bandwidth communication has been demonstrated only using invasive interfaces with bespoke decoders designed for single individuals2-4. Here, we describe the development of a generic non-invasive neuromotor interface that enables computer input decoded from surface electromyography (sEMG). We developed a highly sensitive, easily donned sEMG wristband and a scalable infrastructure for collecting training data from thousands of consenting participants. Together, these data enabled us to develop generic sEMG decoding models that generalize across people. Test users demonstrate a closed-loop median performance of gesture decoding of 0.66 target acquisitions per second in a continuous navigation task, 0.88 gesture detections per second in a discrete-gesture task and handwriting at 20.9 words per minute. We demonstrate that the decoding performance of handwriting models can be further improved by 16% by personalizing sEMG decoding models. To our knowledge, this is the first high-bandwidth neuromotor interface with performant out-of-the-box generalization across people.

Our knowledge of biogeographic patterns and processes in the deep sea has been limited by the lack of integrated datasets that cover its vast extent1. Here we analyse a new global dataset of genomic DNA sequences, spanning an entire taxonomic class of benthic invertebrates (Ophiuroidea), to obtain a broad understanding of phylogenetic divergence and biotic movement across all oceans, from coastal margins down to the abyssal plains. We show that regional faunas on the continental shelf are phylogenetically divergent, particularly at temperate and tropical latitudes. By contrast, assemblages in the deep sea are much more connected. Many temperate deep-sea lineages have achieved distribution ranges across the planet, including over the Quaternary period. A close relationship exists between deep-sea faunas of the northern Atlantic and, on the opposite side of the globe, southern Australia. Bathymetric interchange is not only reliant on vertical migration through isothermal polar waters but also occurs across the thermal depth gradients of tropical regions. The connected nature of deep-sea life should be an important consideration in marine conservation assessments.

Genetic studies have identified thousands of individual disease-associated non-coding alleles, but the identification of the causal alleles and their functions remains a critical bottleneck1. CRISPR-Cas editing has enabled targeted modification of DNA to introduce and test disease alleles. However, the combination of inefficient editing, heterogeneous editing outcomes in individual cells and nonspecific transcriptional changes caused by editing and culturing conditions limits the ability to detect the functional consequences of disease alleles2,3. To overcome these challenges, we present a multi-omic single-cell sequencing approach that directly identifies genomic DNA edits, assays the transcriptome and measures cell-surface protein expression. We apply this approach to investigate the effects of gene disruption, deletions in regulatory regions, non-coding single-nucleotide polymorphism alleles and multiplexed editing. We identify the effects of individual single-nucleotide polymorphisms, including the state-specific effects of an IL2RA autoimmune variant in primary human T cells. Multimodal functional genomic single-cell assays, including DNA sequencing, enable the identification of causal variation in primary human cells and bridge a crucial gap in our understanding of complex human diseases.

Coherent quantum transition spectroscopy is a powerful tool in metrology1, quantum information processing2, magnetometry3 and precision tests of the standard model4. It was applied with great success in proton and deuteron magnetic moment measurements5, which culminated in maser spectroscopy with sub-parts-per-trillion resolution6 and many other experiments at the forefront of physics7. All of these experiments were performed on macroscopic ensembles of particles, whereas the coherent spectroscopy of a 'free' single nuclear spin has, to our knowledge, never been reported before. Here we demonstrate coherent quantum transition spectroscopy of the spin of a single antiproton stored in a cryogenic Penning-trap system. We apply a multi-trap technique8, detect the antiproton spin state using the continuous Stern-Gerlach effect9 and transport the particle to the homogeneous magnetic field of a precision trap (PT). Here we induce the coherent dynamics and analyse the result by quantum-projection measurements in the analysis trap (AT)10. We observe, for the first time, Rabi oscillations of an antiproton spin and achieve in time-series measurements spin-inversion probabilities greater than 80% at spin coherence times of about 50 s. Scans of single-particle spin resonances show inversions greater than 70%, at transition linewidths 16 times narrower than in previous measurements8, limited by cyclotron frequency measurement decoherence. This achievement marks a notable step towards at least tenfold improved tests of matter/antimatter symmetry using proton and antiproton magnetic moments.

Cancer-associated fibroblasts (CAFs) have a pivotal cancer-supportive role, yet CAF-targeted therapies are lacking1,2. Here, using spatial transcriptomics and single-cell RNA sequencing, we investigate the role of nicotinamide N-methyltransferase (NNMT) in high-grade serous ovarian cancer. Mechanistically, NNMT-induced H3K27me3 hypomethylation drives complement secretion from CAFs, attracting immunosuppressive myeloid-derived suppressor cells (MDSCs) to the tumour. Nnmt knockout in immunocompetent mice impairs tumour growth in syngeneic ovarian, breast and colon tumour models through enhanced CD8+ T cell activation. Using high-throughput screening, we develop a potent and specific NNMT inhibitor that reduces the tumour burden and metastasis in multiple mouse cancer models and restores immune checkpoint blockade efficacy by decreasing CAF-mediated recruitment of MDSCs and reinvigorating CD8+ T cell activation. Our findings establish NNMT as a central CAF regulator and a promising therapeutic target to mitigate immunosuppression in the tumour microenvironment.

Human history is born in writing. Inscriptions are among the earliest written forms, and offer direct insights into the thought, language and history of ancient civilizations. Historians capture these insights by identifying parallels-inscriptions with shared phrasing, function or cultural setting-to enable the contextualization of texts within broader historical frameworks, and perform key tasks such as restoration and geographical or chronological attribution1. However, current digital methods are restricted to literal matches and narrow historical scopes. Here we introduce Aeneas, a generative neural network for contextualizing ancient texts. Aeneas retrieves textual and contextual parallels, leverages visual inputs, handles arbitrary-length text restoration, and advances the state of the art in key tasks. To evaluate its impact, we conduct a large study with historians using outputs from Aeneas as research starting points. The historians find the parallels retrieved by Aeneas to be useful research starting points in 90% of cases, improving their confidence in key tasks by 44%. Restoration and geographical attribution tasks yielded superior results when historians were paired with Aeneas, outperforming both humans and artificial intelligence alone. For dating, Aeneas achieved a 13-year distance from ground-truth ranges. We demonstrate Aeneas' contribution to historical workflows through analysis of key traits in the renowned Roman inscription Res Gestae Divi Augusti, showing how integrating science and humanities can create transformative tools to assist historians and advance our understanding of the past.

There is an urgent need for efficient and innovative therapies to treat brain disorders such as psychiatric and neurodegenerative diseases. Immunotherapies have proved to be efficient in many medical areas, but have not been considered to treat brain diseases due to the poor brain penetration of immunoglobulins1,2. Here we developed a bivalent biparatopic antibody, made of two camelid heavy-chain antibodies (called nanobodies)3, one binding to, and the other potentiating the activity of, homodimeric metabotropic glutamate receptor 2. We show that this bivalent nanobody, given peripherally, reaches the brain and corrects cognitive deficits in two preclinical mouse models with endophenotypes resulting from NMDA receptor hypofunction. Notably, these in vivo effects last for at least 7 days after a single intraperitoneal injection and are maintained after subchronic treatment. Our results establish a proof of concept that nanobodies can target brain receptors, and pave the way for nanobody-based therapeutic strategies for the treatment of brain disorders.

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (median continuity of 130 Mb), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8 and AMY1/AMY2, and fully resolve 1,852 complex structural variants. In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in α-satellite higher-order repeat array length and characterize the pattern of mobile element insertions into α-satellite higher-order repeat arrays. Although most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value of 45. Using this approach, 26,115 structural variants per individual are detected, substantially increasing the number of structural variants now amenable to downstream disease association studies.

Genomic structural variants (SVs) contribute substantially to genetic diversity and human diseases1-4, yet remain under-characterized in population-scale cohorts5. Here we conducted long-read sequencing6 in 1,019 humans to construct an intermediate-coverage resource covering 26 populations from the 1000 Genomes Project. Integrating linear and graph genome-based analyses, we uncover over 100,000 sequence-resolved biallelic SVs and we genotype 300,000 multiallelic variable number of tandem repeats7, advancing SV characterization over short-read-based population-scale surveys3,4. We characterize deletions, duplications, insertions and inversions in distinct populations. Long interspersed nuclear element-1 (L1) and SINE-VNTR-Alu (SVA) retrotransposition activities mediate the transduction8,9 of unique sequence stretches in 5' or 3', depending on source mobile element class and locus. SV breakpoint analyses point to a spectrum of homology-mediated processes contributing to SV formation and recurrent deletion events. Our open-access resource underscores the value of long-read sequencing in advancing SV characterization and enables guiding variant prioritization in patient genomes.

Salicylic acid (SA) is a pivotal phytohormone for plant responses to biotic and abiotic stresses. Plants have evolved two pathways to produce SA: the isochorismate synthase and phenylalanine ammonia lyase (PAL) pathways1. Whereas the isochorismate synthase pathway has been fully identified2-4, the PAL pathway remains incomplete. Here we report the full characterization of the PAL pathway for SA biosynthesis via functional analysis of rice (Oryza sativa) SA-DEFICIENT GENE 1 (OSD1) to OSD4. The cinnamoyl-coenzyme A (CoA) ligase OSD1 catalyses the conversion of trans-cinnamic acid to cinnamoyl-CoA, which is subsequently transformed to benzoyl-CoA via the β-oxidative pathway in peroxisomes. The resulting benzoyl-CoA is further converted to benzyl benzoate by the peroxisomal benzoyltransferase OSD2. Benzyl benzoate is subsequently hydroxylated to benzyl salicylate by the endoplasmic reticulum membrane-resident cytochrome P450 OSD3, which is ultimately hydrolysed to salicylic acid by the cytoplasmic carboxylesterase OSD4. Evolutionary analyses reveal that the PAL pathway was first assembled before the divergence of gymnosperms and has been conserved in most seed plants. Activation of the PAL pathway in rice significantly enhances salicylic acid levels and plant immunity. Completion of the PAL pathway provides critical insights into the primary salicylic acid biosynthetic pathway across plant species and offers a precise target for modulating crop immunity.

Salicylic acid (SA) is a ubiquitous plant hormone with a long history in human civilization1,2. Because of the central role of SA in orchestrating plant pathogen defence, understanding SA biosynthesis is fundamental to plant immunity research and crop improvement. Isochorismate-derived SA biosynthesis has been well defined in Arabidopsis. However, increasing evidence suggests a crucial function for phenylalanine-derived SA biosynthesis in many other plant species1. Here we reveal the phenylalanine-derived SA biosynthetic pathway in rice by identifying three dedicated enzymes - peroxisomal benzoyl-CoA:benzyl alcohol benzoyltransferase (BEBT), the endoplasmic reticulum-associated cytochrome P450 enzyme benzylbenzoate hydroxylase (BBH), and cytosolic benzylsalicylate esterase (BSE) that sequentially convert benzoyl-CoA to benzylbenzoate, benzylsalicylate and SA. The pathogen-induced gene expression pattern and SA biosynthetic functions of this triple-enzyme module are conserved in diverse plants. This work fills a major knowledge gap in the biosynthesis of a key plant defence hormone, establishing a foundation for new strategies to create disease-resistant crops.

Malaria remains a substantial global health challenge, causing approximately half a million deaths each year1. The mosquito fibrinogen-related protein 1 (FREP1) is required for malaria parasites to infect the midgut epithelium2. The naturally occurring FREP1Q allele has been reported to prevent parasite infection, while supporting essential physiological functions in the mosquito3. Here we generate congenic strains of Anopheles stephensi, edited to carry either the parasite-susceptible FREP1L224 or the putative-refractory FREP1Q224 alleles. The FREP1Q224 allele confers robust resistance to infection by both human and rodent malaria parasites, with negligible fitness costs. The protective FREP1Q224 allele can be efficiently driven into FREP1L224 mosquito populations using a novel linked allelic-drive system that selectively replaces the L224 codon with the parasite-refractory Q224 allele, thereby rendering populations refractory to parasite infection. This antimalaria drive system provides a novel genetic approach to aid in malaria elimination efforts.

Salicylic acid (SA) is the active ingredient in willow bark that has been used for anti-inflammation and pain relief for centuries. Aspirin, a derivative of SA, is the most widely used medication in human history. SA also acts as a key plant defence hormone1-4. Although SA was known to be produced from chorismate in the model plant Arabidopsis5,6, how it is biosynthesized in plant families outside Brassicaceae remains unclear. Here we report the identification of a conserved pathway for SA biosynthesis in seed plants. Using Nicotiana benthamiana as a model, we identified three key steps for the biosynthesis of SA. First, ligation of benzoyl coenzyme A (CoA) and benzyl alcohol by benzoyl-CoA:benzyl alcohol benzoyl transferase (BEBT) gives rise to benzyl benzoate, which is then hydroxylated by benzyl benzoate oxidase (BBO) to produce benzyl salicylate. Subsequent cleavage of benzyl salicylate by benzyl salicylate hydrolase (BSH) yields SA. Notably, genes encoding these three enzymes are present in a broad range of plants, and the genes from dicots such as willow, poplar and soybean as well as the monocot rice can complement the phenotype of SA-deficient mutants of N. benthamiana. Moreover, knockout analysis of the Oryza sativa OsBEBT, OsBBO and OsBSH genes reveals that they are required for SA biosynthesis in rice. Our findings suggest that the SA biosynthesis pathway is highly conserved in plants.

Many animals use vision to navigate their environment. The pattern of changes that self-motion induces in the visual scene, referred to as optic flow1, is first estimated in local patches by directionally selective neurons2-4. However, how arrays of directionally selective neurons, each responsive to motion in a preferred direction at specific retinal positions, are organized to support robust decoding of optic flow by downstream circuits is unclear. Understanding this global organization requires mapping fine, local features of neurons across an animal's field of view3. In Drosophila, the asymmetrical dendrites of the T4 and T5 directionally selective neurons establish their preferred direction, which makes it possible to predict directional tuning from anatomy4,5. Here we show that the organization of the compound eye shapes the systematic variation in the preferred directions of directionally selective neurons across the entire visual field. To estimate the preferred directions across the visual field, we reconstructed hundreds of T4 neurons in an electron-microscopy volume of the full adult fly brain6, and discovered unexpectedly stereotypical dendritic arborizations. We then used whole-head micro-computed-tomography scans to map the viewing directions of all compound eye facets, and found a non-uniform sampling of visual space that explains the spatial variation in preferred directions. Our findings show that the global organization of the directionally selective neurons' preferred directions is determined mainly by the fly's compound eye, revealing the intimate connections between eye structure, functional properties of neurons and locomotion control.

Experiments that track hippocampal place cells in mice navigating the same real environment have found significant changes in neural representations over a period of days1,2. However, whether such 'representational drift' serves an intrinsic function, such as distinguishing similar experiences that occur at different times3,4, or is instead observed due to subtle differences in the sensory environment or behaviour5-7, remains unresolved. Here we used the experimental control offered by a multisensory virtual reality system to determine that differences in sensory environment or behaviour do not detectably change drift rate. We also found that the excitability of individual place cells was most predictive of their representational drift over subsequent days, with more excitable cells exhibiting less drift. These findings establish that representational drift occurs in mice even with highly reproducible environments and behaviour and highlight neuronal excitability as a key factor of long-term representational stability.

Evading imminent threat from predators is critical for animal survival. Effective defensive strategies can vary, even between closely related species. However, the neural basis of such species-specific behaviours remains poorly understood1-4. Here we find that two sister species of deer mice (genus Peromyscus)5 show different responses to the same looming stimulus: Peromyscus maniculatus, which occupies densely vegetated habitats, predominantly escapes, whereas the open field specialist, Peromyscus polionotus, briefly freezes. This difference arises from species-specific escape thresholds, is largely context-independent, and can be triggered by both visual and auditory threat stimuli. Using immunohistochemistry and electrophysiological recordings, we find that although visual threat activates the superior colliculus in both species, the role of the dorsal periaqueductal grey (dPAG) in driving behaviour differs. Whereas dPAG activity scales with running speed in P. maniculatus, neural activity in the dPAG of P. polionotus correlates poorly with movement, including during visually triggered escape. Moreover, optogenetic activation of dPAG neurons elicits acceleration in P. maniculatus but not in P. polionotus, and their chemogenetic inhibition during a looming stimulus delays escape onset in P. maniculatus to match that of P. polionotus. Together, we trace species-specific escape thresholds to a central circuit node, downstream of peripheral sensory neurons, localizing an ecologically relevant behavioural difference to a specific region of the mammalian brain.

Complex integumentary appendages such as avian feathers and mammalian hair play a principal role in tetrapod evolution, with critical functions in insulation, sensation, display and flight. Although feathers and hair originated in the stem-lineages of birds and mammals, respectively1,2, their underlying gene regulatory network has much deeper amniote roots3. The early evolution of amniote integumentary appendages, however, remains poorly understood because of the absence of fossil evidence. Here we present Mirasaura grauvogeli, a small-sized diapsid from the Middle Triassic epoch (about 247 million years ago) with a distinctive crest formed by elongate integumentary appendages extending serially along its back, similar to those of the poorly understood Triassic reptile Longisquama4-7. Despite its superficially bird-like skull, Mirasaura is not closely related to avemetatarsalians but instead belongs to the exclusively Triassic reptilian clade Drepanosauromorpha8. Melanosomes preserved in its integumentary appendages are consistent in geometry with melanosomes of feathers but not those of reptilian skin or mammalian hair. Nevertheless, the morphology of the integumentary appendages and phylogenetic placement of Mirasaura indicate that they are not structurally homologous to feathers or other integumentary appendages in living amniotes. Our findings show that complex integumentary appendages are not restricted to avemetatarsalians and mammaliaforms among amniotes and evolved in a lineage basal to all extant reptiles, challenging our understanding of the evolution of the reptilian integument.

Achieving long-term underwater adhesion to dynamic, regenerating soft substrates that undergo extreme fluctuations in pH and moisture remains a major unresolved challenge, with far-reaching implications for healthcare, manufacturing, robotics and marine applications1-16. Here, inspired by remoras-fish equipped with specialized adhesive discs-we developed the Mechanical Underwater Soft Adhesion System (MUSAS). Through detailed anatomical, behavioural, physical and biomimetic investigations of remora adhesion on soft substrates, we uncovered the key physical principles and evolutionary adaptations underlying their robust attachment. These insights guided the design of MUSAS, which shows extraordinary versatility, adhering securely to a wide range of soft substrates with varying roughness, stiffness and structural integrity. MUSAS achieves an adhesion-force-to-weight ratio of up to 1,391-fold and maintains performance under extreme pH and moisture conditions. We demonstrate its utility across highly translational models, including in vitro, ex vivo and in vivo settings, enabling applications such as ultraminiaturized aquatic kinetic temperature sensors, non-invasive gastroesophageal reflux monitoring, long-acting antiretroviral drug delivery and messenger RNA administration via the gastrointestinal tract.

Although the role of cellular immunity in checkpoint immunotherapy (CPI) for cancer is well established1,2, the effect of antibody-mediated humoral immunity is comparably underexplored. Here we used rapid extracellular antigen profiling3 to map the autoantibody reactome within a cohort of 374 patients with cancer treated with CPIs and 131 healthy control participants for autoantibodies to 6,172 extracellular and secreted proteins (the 'exoproteome'). Globally, patients with cancer treated with CPIs had diverse autoreactivities that were elevated relative to control individuals but changed minimally with treatment. Autoantibody signatures in patients treated with CPI strikingly distinguished them from healthy individuals. Although associations of specific autoantibodies with immune-related adverse events were sparse, we detected numerous individual autoantibodies that were associated with greatly altered odds ratios for response to therapy. These included autoantibodies to immunomodulatory proteins, such as cytokines, growth factors and immunoreceptors, as well as tumour surface proteins. Functional evaluation of several autoantibody responses indicated that they neutralized the activity of their target proteins, which included type I interferons (IFN-I), IL-6, OSM, TL1A, and BMPR1A and BMPR2. Modelling the effects of autoantibodies to IFN-I and TL1A in preclinical mouse tumour models resulted in enhanced CPI efficacy, consistent with their effects in patients. In conclusion, these findings indicate that autoantibodies to the exoproteome modify CPI responses and highlight therapeutically actionable pathways that can be exploited to augment immunotherapy.