Distant-acting enhancers are central to human development1. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease2. Here we determined the functional sensitivity to mutagenesis of human developmental enhancers in vivo. Focusing on seven enhancers that are active in the developing brain, heart, limb and face, we created over 1,700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-base-pair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal in vivo activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modelling, we annotated critical nucleotides at the base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes in in vivo function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features that are required for their normal in vivo function and provide a rich resource for further exploration of human enhancer logic.

The pursuit of strong yet ductile alloys has been ongoing for centuries. However, for all alloys developed thus far, including recent high-entropy alloys, those possessing good tensile ductility rarely approach 2-GPa yield strength at room temperature. The few that do are mostly ultra-strong steels1-3; however, their stress-strain curves exhibit plateaus and serrations because their tensile flow suffers from plastic instability (such as Lüders strains)1-4, and the elongation is pseudo-uniform at best. Here we report that a group of carefully engineered multi-principal-element alloys, with a composition of Fe35Ni29Co21Al12Ta3 designed by means of domain knowledge-informed machine learning, can be processed to reach an unprecedented range of simultaneously high strength and ductility. An example of this synergy delivers 1.8-GPa yield strength combined with 25% truly uniform elongation. We achieved strengthening by pushing microstructural heterogeneities to the extreme through unusually large volume fractions of not only coherent L12 nanoprecipitates but also incoherent B2 microparticles. The latter, being multicomponent with a reduced chemical ordering energy, is a deformable phase that accumulates dislocations inside to help sustain a high strain hardening rate that prolongs uniform elongation.

Sexual reproduction relies on meiotic chromosome pairing to form bivalents, a process that is complicated in polyploids owing to the presence of multiple subgenomes1. Uneven ploidy mostly results in sterility due to unbalanced chromosome pairing and segregation during meiosis. However, pentaploid dogroses (Rosa sect. Caninae; 2n = 5x = 35) achieve stable sexual reproduction through a unique mechanism: 14 chromosomes form bivalents and are transmitted biparentally, while the remaining 21 chromosomes are maternally inherited as univalents2,3. Despite being studied for over a century, the role of centromeres in this process has remained unclear. Here we analyse haplotype-resolved chromosome-level genome assemblies for three pentaploid dogroses. Subgenome phasing revealed a bivalent-forming subgenome with two highly homozygous chromosome sets and three divergent subgenomes lacking homologous partners, therefore explaining their meiotic behaviour. Comparative analyses of chromosome synteny, phylogenetic relationships and centromere composition indicate that the subgenomes originated from two divergent clades of the genus Rosa. Pollen genome analysis shows that subgenomes from different evolutionary origins form bivalents, supporting multiple origins of dogroses and highlighting variation in subgenome contributions. We reveal that bivalent-forming centromeres are enriched with ATHILA retrotransposons, contrasting with larger tandem-repeat-based centromeres mainly found in univalents. This centromere structural bimodality possibly contributes to univalent drive during female meiosis. Our findings provide insights into the unique reproductive strategies of dogroses, advancing our understanding of genome evolution, centromere diversity and meiotic mechanisms in organisms with asymmetrical inheritance systems.

Until now, computationally designed enzymes exhibited low catalytic rates1-5 and required intensive experimental optimization to reach activity levels observed in comparable natural enzymes5-9. These results exposed limitations in design methodology and suggested critical gaps in our understanding of the fundamentals of biocatalysis10,11. We present a fully computational workflow for designing efficient enzymes in TIM-barrel folds using backbone fragments from natural proteins and without requiring optimization by mutant-library screening. Three Kemp eliminase designs exhibit efficiencies greater than 2,000 M-1 s-1. The most efficient shows more than 140 mutations from any natural protein, including a novel active site. It exhibits high stability (greater than 85 °C) and remarkable catalytic efficiency (12,700 M-1 s-1) and rate (2.8 s-1), surpassing previous computational designs by two orders of magnitude1-5. Furthermore, designing a residue considered essential in all previous Kemp eliminase designs increases efficiency to more than 105 M-1 s-1 and rate to 30 s-1, achieving catalytic parameters comparable to natural enzymes and challenging fundamental biocatalytic assumptions. By overcoming limitations in design methodology11, our strategy enables programming stable, high-efficiency, new-to-nature enzymes through a minimal experimental effort.

Post-traumatic stress disorder (PTSD) is a polygenic disorder occurring after extreme trauma exposure. Recent studies have begun to detail the molecular biology of PTSD. However, given the array of PTSD-perturbed molecular pathways identified so far1, it is implausible that a single cell type is responsible. Here we profile the molecular responses in over two million nuclei from the dorsolateral prefrontal cortex of 111 human brains, collected post-mortem from individuals with and without PTSD and major depressive disorder. We identify neuronal and non-neuronal cell-type clusters, gene expression changes and transcriptional regulators, and map the epigenomic regulome of PTSD in a cell-type-specific manner. Our analysis revealed PTSD-associated gene alterations in inhibitory neurons, endothelial cells and microglia and uncovered genes and pathways associated with glucocorticoid signalling, GABAergic transmission and neuroinflammation. We further validated these findings using cell-type-specific spatial transcriptomics, confirming disruption of key genes such as SST and FKBP5. By integrating genetic, transcriptomic and epigenetic data, we uncovered the regulatory mechanisms of credible variants that disrupt PTSD genes, including ELFN1, MAD1L1 and KCNIP4, in a cell-type-specific context. Together, these findings provide a comprehensive characterization of the cell-specific molecular regulatory mechanisms that underlie the persisting effects of traumatic stress response on the human prefrontal cortex.

Each spring, billions of Bogong moths escape hot conditions across southeast Australia by migrating up to 1,000 km to a place that they have never previously visited-a limited number of cool caves in the Australian Alps, historically used for aestivating over summer1,2. At the beginning of autumn, the same individuals make a return migration to their breeding grounds to reproduce and die. Here we show that Bogong moths use the starry night sky as a compass to distinguish between specific geographical directions, thereby navigating in their inherited migratory direction towards their distant goal. By tethering spring and autumn migratory moths in a flight simulator3-5, we found that, under naturalistic moonless night skies and in a nulled geomagnetic field (disabling the moth's known magnetic sense4), moths flew in their seasonally appropriate migratory directions. Visual interneurons in different regions of the moth's brain responded specifically to rotations of the night sky and were tuned to a common sky orientation, firing maximally when the moth was headed southwards. Our results suggest that Bogong moths use stellar cues and the Earth's magnetic field to create a robust compass system for long-distance nocturnal navigation towards a specific destination.

Climate change threatens global food systems1, but the extent to which adaptation will reduce losses remains unknown and controversial2. Even within the well-studied context of US agriculture, some analyses argue that adaptation will be widespread and climate damages small3,4, whereas others conclude that adaptation will be limited and losses severe5,6. Scenario-based analyses indicate that adaptation should have notable consequences on global agricultural productivity7-9, but there has been no systematic study of how extensively real-world producers actually adapt at the global scale. Here we empirically estimate the impact of global producer adaptations using longitudinal data on six staple crops spanning 12,658 regions, capturing two-thirds of global crop calories. We estimate that global production declines 5.5 × 1014 kcal annually per 1 °C global mean surface temperature (GMST) rise (120 kcal per person per day or 4.4% of recommended consumption per 1 °C; P < 0.001). We project that adaptation and income growth alleviate 23% of global losses in 2050 and 34% at the end of the century (6% and 12%, respectively; moderate-emissions scenario), but substantial residual losses remain for all staples except rice. In contrast to analyses of other outcomes that project the greatest damages to the global poor10,11, we find that global impacts are dominated by losses to modern-day breadbaskets with favourable climates and limited present adaptation, although losses in low-income regions losses are also substantial. These results indicate a scale of innovation, cropland expansion or further adaptation that might be necessary to ensure food security in a changing climate.

Modern colour image sensors face challenges in further improving sensitivity and image quality because of inherent limitations in light utilization efficiency1. A major factor contributing to these limitations is the use of passive optical filters, which absorb and dissipate a substantial amount of light, thereby reducing the efficiency of light capture2. On the contrary, active optical filtering in Foveon-type vertically stacked architectures still struggles to deliver optimal performance owing to their lack of colour selectivity, making them inefficient for precise colour imaging3. Here we introduce an innovative architecture for colour sensor arrays that uses multilayer monolithically stacked lead halide perovskite thin-film photodetectors. Perovskite bandgap tunability4 is utilized to selectively absorb the visible light spectrum's red, green and blue regions, eliminating the need for colour filters. External quantum efficiencies of 50%, 47% and 53% are demonstrated for the red, green and blue channels, respectively, as well as a colour accuracy of 3.8% in ΔELab outperforming the state-of-the-art colour-filter array and Foveon-type photosensors. The image sensor design improves light utilization in colour sensors and paves the way for the next generation of highly sensitive, artefact-free images with enhanced colour fidelity.

Climate change may amplify the frequency and severity of supply-demand mismatches in future power systems with high shares of wind and solar energy1,2. Here we use a dispatch optimization model to assess potential increases in hourly costs associated with the climate-intensified gaps under fixed, high penetrations of wind and solar energy generation. We further explore various strategies to enhance system resilience in the face of future climate change. We find that extreme periods-defined as hours in the upper decile of hourly costs (that is, the most costly 10% of hours)-are likely to become more costly in the future in most countries, mainly because of the increased need for investments in flexible energy capacity. For example, under the Shared Socioeconomic Pathway SSP1-2.6 scenario, 47 countries that together account for approximately 43.5% of global future electricity generation are projected to experience more than a 5% increase in average hourly costs during extreme periods, with the largest reaching up to 23.7%. The risk of rising costs could be substantially mitigated through tailored, country-specific strategies involving the coordinated implementation of multiple measures to address supply-demand imbalances and enhance system flexibility. Our findings provide important insights for building future climate-resilient power systems while reducing system costs.