Science

AbstractAfrica harbors the richest diversity of mitochondrial DNA lineages, reflecting its central role in human evolutionary history. Early studies of mtDNA variation provided the first genetic evidence for the African origin of modern humans. With complete mitochondrial genome sequencing, we can now reconstruct maternal lineages with high resolution, yet large parts of the continent remain underrepresented. Using a newly developed long-range sequencing assay, we generated 1,288 complete mitochondrial genomes from 14 countries across sub-Saharan Africa, focusing on previously understudied regions. We combined these with over 3,600 publicly available African mitogenomes to produce a comprehensive dataset and updated overview of maternal genetic diversity across the continent. We contextualized this diversity with autosomal structure and information on major human expansions, integrating archaeological and linguistic evidence. Our analyses reveal a demographic expansion of Niger-Congo speakers around 17 thousand years ago (kya), followed by a second expansion associated with Bantuspeaking groups around 6 kya. We identify haplogroup L3e as a key marker of this early Bantu expansion, tracking its spread across sub-Saharan Africa. Distinct demographic signatures also emerge for different geographic sub-branches of Bantu speakers. These findings highlight the power of mitochondrial DNA to trace maternal ancestry and demographic history in Africa, while also acknowledging its limitations for phylogeographic reconstruction.

Lassa fever is classically defined as a rural zoonosis constrained by the agricultural niche of its reservoir, Mastomys natalensis. However, current risk models rely on historical sampling heavily biased toward rural settings (>67%). Here, I reconstruct the realised niche of M. natalensis using an Integrated Multi-Species Occupancy Model (IMSOM) accounting for biotic interactions with invasive rodents. Contrary to climatic predictions of urban exclusion, I identify a cryptic reservoir niche in West African peri-urban fringes. While the reservoir and pathogen are urban-tolerant, analysis reveals a non-linear Socio-economic Shield proxied by infrastructure quality, dampening spillover in city cores. This creates an urban paradox displacing transmission from the shielded centre to hyper-endemic peri-urban fringes. Accounting for this shield and antibody waning ({lambda}=0.03), I estimate 2.6 million annual infections (Range: 0.9-4.4 million). This challenges conservative estimates based on lifelong immunity and aligns with the high force of infection required to sustain observed seroprevalence. Spatially, the model identifies widespread silent districts, where ecological conditions are primed for transmission but clinical reporting is absent. These findings suggest Lassa fever has the potential to emerge as a peri-urban disease, necessitating a paradigm shift in surveillance to address the blind spots of rapid urbanisation.

Ancient DNA has revolutionized our understanding of human history, and is now yielding important insights into evolution and natural selection. However, studies of selection using ancient DNA have largely been limited to Europe, excluding populations in other parts of the world. While many selective pressures were local to specific populations others, for example those related to the development of agriculture, may have been universal. By studying a broader range of global populations, we can identify examples of local adaption but also more general principles of adaptation to climatic, social and technological changes. We therefore leverage ancient DNA to test for selection in 7244 individuals from 13 ancient and 19 present-day populations across five regions: Europe, East Asia, South Asia, Africa and the Americas. In each region, we tested for selection using multiple approaches that account for complex demographic histories. We identify 31 genome-wide significant signals of selection, including both known and novel loci. We find a high degree of shared signal across regions, suggesting extensive parallel or shared adaptation. Using a novel admixture-aware time series method, we find that the strength of selection on many variants changed over time, for example decreasing selection at LCT in Europe and increasing selection at ADH1B in East Asia over the past few thousand years. Finally, we developed a test for polygenic selection on complex traits by modeling the frequencies of trait-associated alleles identified in GWAS. We tested for selection jointly across regions, avoiding the confounding effect of population stratification by excluding the European or East Asian GWAS population from the selection test. We find evidence for directional selection on pigmentation and immune traits, and that strong stabilizing selection on female waist-hip ratio was universal across human populations suggesting a fundamental constraint on human morphology.

Estimation of evolutionary relationships among lineages that rapidly diversified can be challenging, and, in such instances, inaccurate or unresolved phylogenetic estimates can lead to erroneous conclusions regarding historical geographical ranges of lineages. One example underscoring this issue has been the historical challenge posed by untangling the biogeographic origin of elapoid snakes, which includes numerous dangerously venomous species as well as species not known to be dangerous to humans. The worldwide distribution of this lineage makes it an ideal group for testing hypotheses related to historical faunal exchanges among the many continents and other landmasses occupied by contemporary elapoid species. We developed a novel suite of genomic resources, included worldwide sampling, and inferred a robust estimate of evolutionary relationships, which we leveraged to quantitatively estimate geographical range evolution through the deep-time history of this remarkable radiation. Our phylogenetic and biogeographical estimates of historical ranges definitively reject a lingering former Out of Africa hypothesis and support an Out of Asia scenario involving multiple faunal exchanges between Asia, Africa, Australasia, the Americas, and Europe.

Genetic diversity within species is the basis for evolutionary adaptive capacity and has recently been included as a target for protection in the United Nations Global Biodiversity Framework (GBF). However, we lack large-scale mathematical frameworks to quantify how much genetic diversity has already been lost, let alone to predict future losses under 21st century conservation scenarios. To fill this gap, we developed an area-based spatio-temporal predictive framework of genetic diversity calibrated with population-scale genomic data of 29 plant and animal species. To estimate present genetic diversity loss with our framework, we used species habitat area and population sizes losses reported in the Living Planet Index, the Red List, and new GBF indicators across 13,808 species for the last 5 decades. Applying our evolutionary framework across these species, we estimate genetic diversity loss lags behind population and habitat area declines, with an estimated current 13-22% {pi} genetic diversity loss. However, we forecast future genetic diversity losses will reach 41-76% even if populations are not further contracted. These results highlight that safeguarding existing habitats is insufficient to maintain the genetic health of species and relying solely on continuous genetic monitoring underestimates lagging long term impacts. Significance statementGenetic diversity is crucial for both species adaptation and survival. Recently, it has been included as a target for protection in the United Nations Global Biodiversity Framework. However, we lack large-scale predictive methods to quantify current and future losses of genetic diversity across species. Here, we develop an area-based spatio-temporal predictive framework trained with high-quality genome-wide data from 29 plant and animal species to enable quantitative predictions of genetic biodiversity at global scales. We infer global genetic diversity losses are beyond the preliminary UN targets to protect 90% of genetic diversity of species, evolutionary models dramatic genetic losses will occur in the future even with habitat protection if populations across species are not recovered.

Quantifying the sequestration potential of biologically driven carbon fluxes in the ocean depends critically on residence times - how long carbon remains stored in reservoirs before being re-exposed to the atmosphere. Simple mass balance provides estimates for many of the major ocean biogenic carbon reservoirs. For vegetated coastal ecosystems (mangroves, sea grass meadows, salt marshes) that globally store 20 to 40 PgC, this is 200 to 500 years, while for the biological carbon pump, a reservoir of about 2000 PgC, it is between 200 to 800 years. Over these time scales respective reservoirs reach equilibrium if left undisturbed. Importantly, near equilibrium of ocean reservoirs during the Holocene can be inferred from the near steady atmospheric concentrations during this period. The degradation of habitats and the over-exploitation of living marine resources particularly in the last 75 years have tipped these natural processes out of balance, to the extent where many are now net emitters of legacy carbon back to the atmosphere. The analysis exposes a conflict between how sequestration is reported in oceanographic literature and how it is understood with regards durable carbon capture and storage. Nature-based solutions can be sought to address parts of the climate crisis, by improving ecosystem health and biodiversity, but are unlikely to provide solutions to carbon management on a scale commensurate with anthropogenic emissions. The best we can do is to limit net emissions by restoring what we can, and to ensure that future practices do not further tip ocean carbon reservoirs out of balance. Significance StatementMarine animals and plants maintain large pools of carbon in the ocean and coastal areas that have been laid down by generations past. This legacy carbon is continuously being recycled on time scales of 100s of years. Left undisturbed, as they were for most of the last 10000 years, these carbon pools tend to equilibrium; flux in equals flux out. Human activities such as over fishing and coastal construction, particularly in the past 75 years, have tipped these natural cycles out of balance to the extent where many pools are now net emitters of carbon. Conservation and restoration of marine habitats can bring these cycles back into balance but cannot be counted as offsetting fossil fuel emissions.

COVID-19 prevalence and mortality remain uncertain. For all 86 countries with reliable testing data we estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral responses to risk shape pandemic dynamics. Estimated cumulative cases and deaths through 10 July 2020 are 10.5 and 1.47 times official reports, yielding an infection fatality rate (IFR) of 0.65%, with wide variation across nations. Despite underestimation, herd immunity remains distant. Sufficient early testing could have averted 39.7 (35.3-45.3) million cases and 218 (191-257) thousand deaths. Responses to perceived risk cause the reproduction number to settle near 1, but with very different steady-state incidence, while some nations experience endogenous rebounds. Scenarios through March 2021 show modest enhancements in responsiveness could reduce cumulative cases {approx}80%, to 271 (254-412) million across these nations. One Sentence SummaryCOVID-19 under-reporting is large, varies widely across nations, and strongly conditions projected outbreak dynamics.

Have European gray wolves recovered? Despite an increase to [~]21,000 wolves (Canis lupus), our genomic analyses reveal significant risks to their long-term viability. We analyzed over 200 whole-genomes spanning five major European populations. Rather than a single recovering population, European wolves form a mosaic of isolated, independently evolving lineages, mostly diverging in the late Pleistocene. All lineages have contemporary effective population sizes below the threshold for long-term viability (Ne [≥] 500) and show extensive inbreeding. Runs of homozygosity reveal population-specific inbreeding histories spanning recent to deep timeframes. Most lineages exhibit higher realized than masked genetic load, indicating emerging inbreeding depression. These findings challenge claims that downlisting European wolves is biologically warranted: none of these populations currently meets thresholds associated with favorable conservation status.

Genetic introgression from Neanderthals and Denisovan has shaped modern human genomes; however, introgressed structural variants (SVs [≥]50 base pairs) remain challenging to discover. We integrated high-quality phased assemblies from four new Papua New Guinea (PNG) genomes with 94 published assemblies of diverse ancestry to infer an archaic introgressed SV map. Introgressed SVs are overall enriched in genes (44%, n=1,592), including critical genomic disorder regions, and most abundant in PNG. We identify 11 centromeres likely derived from archaic hominins, adding unexplored diversity to centromere genomics. Pangenome genotyping across 1,363 samples reveals 16 candidate adaptive SVs, many associated with immune-related genes and their expression, in the PNG. We hypothesize that archaic SV introgression contributed to reproductive success, underscoring introgression as a significant force in human adaptive evolution.

We report high-coverage whole-genome sequencing data from 46 Yemeni individuals as well as genome-wide genotyping data from 169 Yemenis from diverse locations. We use this dataset to define the genetic diversity in Yemen and how it relates to people elsewhere in the Near East. Yemen is a vast region with substantial cultural and geographic diversity, but we found little genetic structure correlating with geography among the Yemenis - probably reflecting continuous movement of people between the regions. African ancestry from admixture in the past 800 years is widespread in Yemen and is the main contributor to the countrys limited genetic structure, with some individuals in Hudayda and Hadramout having up to 20% of their genetic ancestry from Africa. In contrast, individuals from Maarib appear to have been genetically isolated from the African gene flow and thus have genomes likely to reflect Yemens ancestry before the admixture. This ancestry was comparable to the ancestry present during the Bronze Age in the distant Northern regions of the Near East. After the Bronze Age, the South and North of the Near East therefore followed different genetic trajectories: in the North the Levantines admixed with a Eurasian population carrying steppe ancestry whose impact never reached as far south as the Yemen, where people instead admixed with Africans leading to the genetic structure observed in the Near East today.

When infections can be transmitted from hosts showing no symptoms, containing outbreaks requires distinct strategies like active surveillance. Yet it is rarely clear before-hand when such interventions are needed, especially for emerging pathogens. To investigate the within-host dynamics that enable pre-symptomatic transmission, we survey controlled human infection (CHI) trials with viral pathogens that follow symptoms and viral shedding after inoculation with a known dose. We find that many studies report average timing of symptom onset and shedding, but few report those data for individual participants. We fit a simple model to individual shedding time series from two CHI studies (using norovirus and SARS-CoV-2, respectively) to infer replication rates and the timing of peak shedding relative to symptom onset. We find that faster viral replication significantly hastens peak shedding with minimal impact on symptom onset and no evidence for a tradeoff between the rate and duration of transmission during the pre-symptomatic phase. We then develop and compare within-host models of pathogen replication, immune clearance, and symptom onset to identify plausible assumptions about the causes of pre-symptomatic transmission. We recover the empirical pattern that peak shedding can precede symptom onset when we assume that symptoms are triggered by immune responses rather than pathogen abundance. By incorporating resource limitation via a carrying capacity, we can recover the pattern that faster viral replication prolongs pre-symptomatic transmission. Thus, individual-level data from CHI trials--paired with models--can illuminate the within-host dynamics underpinning pre-symptomatic transmission, guiding efforts to improve control strategies. Significance statementThe COVID-19 pandemic was exacerbated by the potential for transmission before symptoms. Yet the causes of pre-symptomatic transmission--in some hosts but not others--remain unclear, hindering efforts to predict disease spread and tailor control efforts for novel pathogens. To identify patterns across viral taxa, we surveyed con-trolled human infection (CHI) trials, which rarely reported data on the onset of shedding and symptoms for individuals. Individual time series of shedding and symptoms were available from two CHI trials using norovirus and SARS-CoV-2. We fit models to those data to show that faster viral replication hastens shedding but not symptom onset and then used more detailed models to identify plausible assumptions about the within-host causes of underlying pre-symptomatic transmission.

The advent of generative machine learning models has revolutionized de novo design of protein binders. However, the wide adoption of this revolution is bottlenecked by computational cost. For many targets, binder design commonly requires computationally intensive sampling across structures, often wasting days of GPU time on unwanted or geometrically inviable regions. Here, IARA (Interface Analysis and Recognition Architecture) is introduced, a deep learning Graph Neural Network designed as a rapid structural filter to triage protein binder generative pipelines. IARA is trained entirely on BindCraft trajectories generated against s RFdiffusion-generated targets. Based on a slim network with only seven residue features, IARA maps the binder designability of input proteins in a matter of seconds. On validation runs using BindCraft, RFdiffusion and BoltzGen, IARA successfully identified the optimal binding interface for practically all targets. By instantly pinpointing the highest-probability binding pockets, IARA democratizes synthetic biology, drastically reducing the exploratory GPU compute required for successful de novo binder generation.

International wildlife trade is a major source of biodiversity loss, yet many species lie hidden within aggregated data that conceals trade impacts. We overcome this problem for the largest vertebrate wildlife trade globally - shark and ray meat - comprising 438 538 mt yr-1 across more than 150 species, 76% of which are Threatened. Revealed trade contains greater quantities of skates (+10%), hammerheads (+8%), and smoothhounds, dogfishes & tope (+5%), and fewer pelagic sharks (-38%) than previously known. Shorttail yellownose skate, smoothound, silky, mako, and blue sharks are the most underreported meat species, due to aggregated landings from China, Argentina, Japan, and Indonesia, demonstrating international trade in shark and ray meat as a diverse, pervasive, and previously hidden source of fishing mortality for many threatened species.

Dire wolves (Aenocyon dirus) are extinct predators of Pleistocene North America. Although phenotypically similar to living wolves (Canis lupus), dire wolves have yet to be placed confidently in the canid family tree. We generated 3.4x and 12.8x paleogenomes from two well-preserved dire wolves dating to > 13,000 and > 72,000 years ago, and estimated consensus species trees for these and 10 canid species. Our results revealed that [~]2/3 of dire wolf ancestry is derived from a lineage sister to the clade comprising the gray wolf, coyote, and dhole, and the remaining [~]1/3 from a lineage near the base of Canini diversity. We identified 80 genes evolving under diversifying selection in dire wolves. Our results underscore the power of paleogenomes to resolve long-standing taxonomic questions and contribute to growing evidence of the role of post-speciation gene flow as an evolutionary force.

Habitat modification is responsible for substantial biodiversity declines, but communities vary in their tolerance to land-use change. One infrequently queried possibility is that historical factors determine the sensitivity of contemporary communities. We use bird community data from 54 studies across the world to test the hypothesis that pre-historic human presence reduced community sensitivity to land-use change by eliminating sensitive species in natural habitats. We find that pre-historic human population size correlates with reduced sensitivity of communities. Primary vegetation in areas with larger pre-historic human populations contain fewer species today, while species richness in structurally simple agriculture is unimpacted. The greatest signal of humans impacts dates back to 12,000 YBP suggesting that early humans may have caused even more widespread extinctions, than previously appreciated. One-Sentence SummaryAreas with high human population 12,000 years ago have less biodiversity today, but are more tolerant of habitat modification

The colonization of our stomachs by Helicobacter pylori is believed to predate the oldest splits between extant human populations. We identify a "Hardy" ecospecies of H. pylori associated with indigenous groups, isolated from people in Siberia, Canada, USA and Chile. The ecospecies shares the ancestry of "Ubiquitous" H. pylori from the same geographical region in most of the genome but has nearly fixed SNP differences in 100 genes, many of which encode outer membrane proteins and host interaction factors. For these parts of the genome, the ecospecies has a separate, independently evolving gene pool with a distinct evolutionary history. H. acinonychis, found in big cats, and a newly identified primate-associated lineage both belong to the Hardy ecospecies and both represent human to animal host jumps. Most strains from the ecospecies encode an additional iron-dependent urease that is shared by Helicobacter from carnivorous hosts, as well as a tandem duplication of vacA, encoding the vacuolating toxin. We conclude that H. pylori split into two highly distinct ecospecies in Africa and that both dispersed around the globe with humans, but the Hardy ecospecies has gone extinct in most parts of the world. Our analysis also pushes back the likely length of the association between H. pylori and humans.

Orthogonal DNA replication systems uncouple the mutagenesis of target genes from host viability, enabling target gene hypermutation beyond the genomic critical error threshold and thereby unlocking access to greater sequence space for accelerated evolution. Here we introduce a series of upgrades to the E. coli orthogonal replication system, EcORep. We develop strategies to efficiently establish, engineer, and transform orthogonal replicons. We develop and utilize replicon-REXER to establish a 77 kb replicon, the largest orthogonal replicon reported to date. Directed evolution of the orthogonal DNA polymerase yielded variants with mutation rates of [~]10-4 substitutions per base per generation and best-in-class mutational spectra. These polymerases are three orders of magnitude more mutagenic than the first-generation EcORep system, enable mutagenesis at one million times the genomic levels, and straddle the evolutionary critical error threshold for the mutation of genes tested. Using the highly mutagenic EcORep system, we rapidly evolve an ethanol assimilation pathway for increased performance. Furthermore, we find that the three components sufficient to drive the minimal EcORep system enable O-replication systems to be established in other Gram-negative bacteria. Thus, we establish VinORep in Vibrio natriegens. VinORep combines O-replicon mutation, around the limit for molecular evolution of genes, with the fastest growing organism, to realize gene evolution approaching the biological speed limit. We exemplify the utility of this advance through the rapid evolution of new function - via the accumulation of tens of mutations, and selection - in 16 hours.

Strict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.

Nipah virus (NiV), a highly lethal virus in humans, circulates silently in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining genomes from bats means we have a poor understanding of NiV diversity, including how many lineages circulate within a roost and the spread of NiV over increasing spatial scales. Here we develop phylogenetic approaches applied to the most comprehensive collection of genomes to date (N=257, 175 from bats, 73 from humans) from six countries over 22 years (1999-2020). In Bangladesh, where most human infections occur, we find evidence of increased spillover risk from one of the two co-circulating sublineages. We divide the four major NiV sublineages into 15 genetic clusters (emerged 20-44 years ago). Within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1,500-2,000 km2. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate that each genetic cluster occupies an average area of 1.3 million km2 (95%CI: 0.6-2.3 million), with 14 clusters in an area of 100,000 km2 (95%CI: 6-24). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most of the genetic clusters have been identified, but only [~]15% of overall NiV diversity has been uncovered. Our findings are consistent with entrenched co-circulation of distinct lineages, even within individual roosts, coupled with slow migration over larger spatial scales.

From ancient nomadic movements to modern urbanization, migration has driven human history through mechanisms that remain poorly understood. We conducted a genome-wide association study of migration distance in 250,000 UK individuals, identifying 20 loci in neurodevelopmental genes with 5% heritability. Migration-related variants are associated with excitatory neuron gene expression and correlate with cognition, risk-tolerance, and reduced interpersonal attachment. Within-family analyses demonstrate genetic effects remain significant after controlling for shared environmental factors between siblings. Our polygenic score predicts inferred mobility in >1,000 ancient individuals spanning 10,000 years, revealing positive selection on migration alleles that increased substantially over millennia. At the population level, each standard deviation increase in county-level migration polygenic score predicts >$4,000 greater income growth per person in the US. These findings establish migration as a heritable trait and suggest biological pathways connecting individual neurodevelopment with regional prosperity across evolutionary and contemporary timescales.