Language is a defining feature of our species, yet the genomic changes enabling it remain poorly understood. Despite decades of work since FOXP2’s discovery, we still lack a clear picture of which regions shaped language evolution and how variation contributes to present-day phenotypic differences. Using an evolutionary stratified polygenic score approach, we find that human ancestor quickly evolved regions (HAQERs) are associated with spoken language abilities (discovery N = 350, total replication N > 100,000). HAQERs evolved before the human-Neanderthal split, giving hominins increased binding of Forkhead and Homeobox transcription factors, and show evidence of balancing selection across the past 20,000 years. Language-associated variants in HAQERs appear more prevalent in Neanderthals, and HAQER-like sequences show convergent evolution across vocal-learning mammals. Our results reveal how ancient innovations continue shaping human language.

Directional cues are essential for orienting cells during tissue morphogenesis and repair. In peripheral nerve regeneration, Schwann cells (SCs) align longitudinally in the nerve bridge to guide axonal pathfinding, but the mechanisms are not fully understood. We show here that after nerve injury, activated SCs up-regulate the guidance receptor Plexin-B1, enabling membrane plasticity required for SC polarization and longitudinal alignment along the axons. Aligned axon-SC provides positional cues to orient macrophages and extracellular matrix. Loss of Plexin-B1 disrupts SC morphological transformation, contact inhibition of locomotion between SCs, and axon-SC alignment, leading to SC misorientation, excessive inflammation, and delayed axon regeneration and functional recovery. These findings identify Plexin-B1 as a key orchestrator to orient SCs by regulating both SC-SC and axon-SC interactions during nerve repair. Elucidating the mechanisms of spatial guidance in nerve repair after injury has potential implications for therapeutic strategies to enhance neural regeneration.

Diagnosing rare genetic diseases remains a major challenge despite widespread clinical testing. Long-read RNA sequencing (RNA-seq) offers a powerful approach to capturing the effects of genetic variants on the transcriptome, yet challenges with sequencing coverage, cost, tissue selection, and scalability have limited its clinical adoption. To address this, we developed STRIPE (Sequencing Targeted RNAs Identifies Pathogenic Events), a targeted long-read RNA-seq-based strategy for rare disease diagnosis and variant interpretation. STRIPE enables deep sequencing of full-length transcripts for any customized disease-specific gene panel such that a wide range of clinically informative readouts, including transcript aberrations and sequence variants, can be detected at haplotype-level resolution. Applying STRIPE to 88 individuals spanning two major rare disease groups, we accurately reidentified known pathogenic variants and revealed their transcript consequences, including many unexpected ones. For 8 of 15 splice site region variants, we observed more complex RNA processing defects beyond single exon skipping or cryptic splice site activation. Notably, we find that donor splice site variants frequently activate cryptic intronic polyadenylation sites, leading to premature transcript termination. Leveraging unique strengths of long-read RNA-seq, STRIPE also resolved variants of uncertain significance and uncovered disease-causing variants in five previously undiagnosed individuals. Overall, STRIPE is a powerful, adaptable, and scalable strategy with broad potential to improve clinical variant interpretation and advance genetic diagnosis of rare diseases.

Determining the high-resolution structure of the widely expressed nonmuscle myosin 2A (NM2A), in its dephosphorylated shutdown state, is important in understanding its regulation and disease roles. In shutdown molecules, the coiled-coil tail wraps around the myosin heads, preventing them from forming filaments and binding to actin. We have solved the shutdown structure of NM2A to a global resolution of 3.0 angstroms in the head region and 6.3 angstroms for the whole molecule. This reveals specific ionic interactions that explain why the path of the coiled coil and the shutdown mechanism for NM2A differ from those of β-cardiac myosin and provides key insight into how specific mutations likely destabilize the shutdown state, leading to disease.

Scientists have long been fascinated by magnetoreception, the innate capacity of many animals to sense and use Earth's magnetic field for navigation. In eusocial insects like honey bees, magnetoreception has been linked to communication and foraging. However, little is known about magnetoreception's phylogenetic patterns and relationship to species traits and natural history. Here, we demonstrate that putative magnetoreception based on ferromagnetic particles is widespread across a diversity of bee species (74 of 96 species tested), with no phylogenetic signal. We also detected such putative magnetoreception in non-bee outgroups, suggesting that this magnetic capacity predates the evolution of the Anthophila. Although magnetic signals were found across a diversity of life history traits, the strength of the magnetic signal varied within and between species and increased with body size and social behavior.

A challenge in Earth and space sciences is the capability to continuously monitor the key parameters of space systems that frequently experience complex, multiscale dynamics. The ionosphere-thermosphere (I-T) system is a region where the direct measurement of essential quantities such as electric fields, neutral winds, and temperatures remain largely inaccessible. Here, we present a generalizable inverse modeling framework that bridges sparse observations with physics-based simulation to recover these hidden state variables. By leveraging high-resolution, data-driven reconstructions of electron density in combination with the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM), our approach enables end-to-end inference of latent I-T parameters without relying on explicit forward models. Through supervised neural networks trained on large-scale simulation data, the system autonomously learns the intrinsic couplings among I-T variables, enabling fast, robust, and physically informed parameter estimation. This fusion of physical modeling and machine learning transcends traditional retrieval methods, offering a scalable pathway toward real-time geospace monitoring and improved representation of upper-atmosphere dynamics in Earth system models.

The water-energy nexus demands membranes with subångström ion-sieving precision, a capability hindered by the intrinsic selectivity limits of conventional materials. We fabricated ultrathin covalent organic network (CON) membranes via interfacial polymerization of 1,4,7,10-tetraazacyclododecane (cyclen) with either terephthaloyl chloride or isophthaloyl chloride. The resulting architectures demonstrate narrow pore size distribution and subångström-level ion resolution. CON-T membranes exhibit exceptional water permeance (22.2 liters per square meter per hour per bar) along with Li+/Mg2+ and Cl-/SO42- selectivities of 82.6 and 118.1, respectively. Monomer conformation engineering yielded CON-I membranes that set high benchmarks for Li+/Mg2+ (326.7) and Cl-/SO42- (376.9) selectivity. At the process scale, CON-T membranes facilitate highly efficient lithium resource extraction (97.4% recovery with 99.3% purity), while CON-I membranes enable Cl- production at ~99.9% purity from industrial wastewater. This methodology establishes a paradigm for high-resolution ion-sieving membranes that is fully compatible with industrial-scale polymeric membrane manufacturing, offering a viable solution for next-generation water-energy systems.

The response regulator CheY is an intracellular signaling molecule that plays a central role in chemotaxis signaling in E. coli cells. Here, we show that changes in CheY-P concentration and flagellar motor rotation are highly correlated within a single cell after stimulation by the attractant l-serine. To monitor the CheY-P concentration and cellular behavior, FRET between CheY-YFP and CheZ-CFP and flagellar rotation were monitored simultaneously. The time required for recovery of the CheY-P concentration (FRET recovery time) and the duration of highly counterclockwise-biased flagellar rotation (CCW duration) were similar and depended on the strength of the stimulus. Both the FRET recovery time and the CCW duration varied from cell to cell, even at the same serine concentration. In cells adapted to serine, the sensitivity of the motor to CheY-P concentration shifted toward lower CheY-P levels relative to prestimulation cells. Thus, we could correlate the changes in CheY-P concentration with motor behavior during attractant adaptation.

Emerging static aqueous Zn─Br batteries offer substantial cost and energy density advantages but suffer from toxic Br2 formation and polybromide shuttling. Here, we report a universal electrode engineering for advanced Zn─Br battery via incorporating layered materials into the cathode, reshaping the working mechanism from conversion to intercalation-conversion. Findings confirm that Br- intercalate-converts to Br-0.14 within unsaturated N-rich g-C3N4, effectively avoiding liquid Br2 formation and suppressing its toxicity and diffusion. Consequently, the self-discharge of cell remarkably decreases from 96.5 to 9.5% following 12 hours resting. Through controlling 48.7% Zn depth-of-discharge and industrial-level mass loading 40 mg(KBr) cm-2, the multilevel pouch cell with ampere hour-level capacity exhibits 750 cycles, outperforming aqueous counterparts at high mass loadings. This electrode engineering is applicable to other layered materials, underscoring its practical universality. These findings not only unlock the full potential of aqueous Zn─Br batteries but also enrich the chemistry landscape of aqueous battery family.

Linker histone H1, the most abundant chromatin protein, condenses chromatin, modulates DNA transactions such as transcription and DNA replication/repair, and participates in differentiation, development, and tumorigenesis. While recent studies indicate that nucleosomes are clustered as condensed chromatin domains in higher eukaryotic cells, how histone H1 mechanically condenses chromatin remains unclear. Here, using a combination of direct visualization of single-H1 molecules in living human cells and multiscale molecular dynamics simulations, we demonstrate that the majority of H1 behaves like a liquid inside chromatin domains, rather than binding stably to nucleosomes as suggested by the traditional model. H1 functions as a liquid-like "glue," mediating dynamic multivalent electrostatic interactions between nucleosomes within chromatin domains. Consistently, rapid depletion of H1.2 leads to decondensed chromatin domains both in cells and in silico. Our findings suggest that the H1 "glue" condenses chromatin domains while keeping them fluid and accessible, thereby supporting essential DNA transactions.