European beech (Fagus sylvatica L.) spans a wide range of European climates and exhibits evidence of local adaptation, which supports its persistence under diverse conditions. We analysed 18 populations-distributed across an altitude gradient on the southwestern geographic range edge of the species-using landscape genomics to assess their adaptive variation and vulnerability to future climatic conditions. We uncovered weak but structured genetic differentiation, revealing three main climate-tied genetic groups. Combining multiple Genotype-Environment Association (GEA) approaches-linear, such as Latent Factor Mixed Models (LFMM) or Redundancy Analyses (RDA), and non-linear (Gradient Forest)-we identified 373 Single Nucleotide Polymorphisms (SNPs) detected by all GEA methods as being putatively associated with climate gradients. Using the Gradient Forest model, we mapped genetic offset across all 21st century periods under a key climate scenario: Shared Socioeconomic Pathway (SSP) 5, forcing 8.5 W/m2 (SSP585) and across all SSPs for 2061-2080, identifying Pyrenean and pre-Pyrenean regions as maladaptation hotspots. To capture temporal dynamics, we introduce a novel approach to interpret genetic offset. The Required Evolutionary Rate (REvoRate) quantifies the minimum genetic change per year needed to keep pace with projected climates. Joint interpretation of offset and REvoRate revealed that some stands with moderate offsets face high short-term adaptive demands, while others with larger offsets are required to evolve more gradually. The drought-temperature gradient emerged as the main driver of allele frequency turnover, with geography contributing through isolation by distance. Together, genetic offset and REvoRate provide a dynamic framework to assess temporal maladaptation risk. Our results highlight the need to integrate standing genetic variation and evolutionary potential into forest management and conservation planning to ensure the persistence of F. sylvatica in one of its most climate-vulnerable range margins.

The application of in-field and aerial spectroscopy to assess functional and phylogenetic variation in plants has led to novel ecological insights and supports global assessments of plant biodiversity. Understanding how plant genetic variation influences reflectance spectra will help harness this potential for biodiversity monitoring and improve understanding of why plants differ in functional responses to environmental change. Here, we use a well-resolved genetic mapping population derived from Multiparent Advanced Generation Inter-cross (MAGIC) lines of Nicotiana attenuata to associate genetic differences with differences in leaf spectra between plants in a field experiment in their natural environment. We analyzed the leaf reflectance spectra using a hand-held spectroradiometer (350-2500 nm) on 616 fully genotyped plants of N. attenuata grown in a randomized block design. We tested three approaches to conducting genome-wide association studies on spectral variants. We introduce a new hierarchical spectral clustering with parallel analysis (HSC-PA) method. This method efficiently captured the variation in our high-dimensional dataset and allowed us to discover a novel association, between a locus on chromosome 1 and the 734-1143 nm spectral range, spanning the red-edge and near-infrared regions that are sensitive to leaf structure and photosynthetic activity. This locus contains a candidate gene annotated as carbonic anhydrase, an enzyme involved in CO₂ hydration and regulation of photosynthetic efficiency, suggesting a physiological link between variation in leaf optical properties and carbon assimilation. In contrast, an approach treating single wavelengths as phenotypes identified genetic signals highly consistent with HSC-PA, but suffered from massive statistical redundancy without pinpointing significant, interpretable features. An index-based approach, which reduces complex spectra to a few dimensionless variables, detected two significant associations for (a water-content-related index) with loci on chromosome 1 near genes annotated as a Zeta toxin domain-containing protein, and an Exocyst subunit Exo70 family protein. While these findings are biologically plausible, they represent a very narrow subset of the spectral variation captured by HSC-PA. The HSC-PA approach supports a comprehensive understanding of the genetic determinants of leaf spectral variation that is data-driven but human-interpretable and is thus a tool to discover genetic differences underlying intraspecific variation, a foundation of biodiversity.

Deflecting the parasitic paradigm: new insights into mutualistic transposons in plant genomes.

Cotranslational subunit assembly is thought to be a prominent feature throughout the proteome, but, in bacteria, there are only a limited number of experimentally confirmed examples and most involve the addition of extraneous tag sequences for experimental convenience. Toxin CcdA and Antitoxin CcdB are components of the ccdAB operon. They assemble in a hetero-multimeric complex in vivo. Building on a previously characterised saturation mutagenesis dataset of CcdB, we investigated how operonic gene organisation influences the cotranslational folding and assembly of the toxin-antitoxin complex. We compared the phenotypic effects of CcdB mutations when expressed alone versus in the native operonic context downstream of CcdA. Although several charged and polar mutations in the CcdB core result in loss of function in the absence of CcdA, many of these are functionally rescued in the operonic context. Furthermore, we show that the efficiency of rescue is substantially reduced when ccdA and ccdB are expressed from separate mRNAs rather than from a single polycistronic transcript. Our results highlight a direct role for cotranslational interactions in enabling correct folding of CcdB and suggest that bacterial operon structure may have evolved, in part, to facilitate such chaperone-like rescue of unstable protein variants. Gene organisation in operons in bacteria may thus reflect a fundamental cotranslational mechanism that is important for the effective assembly of protein complexes and can potentially buffer substantial genetic variation.

Genetic evidence for fluctuating selection has begun to accumulate for different species over the past few decades, especially for the Drosophila genus where studies have reported hundreds of loci undergoing putatively adaptive oscillations across successive seasons. However, most theoretical and simulation studies of fluctuating selection have relied on abstract or weakly parameterized models, making it difficult to assess their relevance for natural populations. In this study, we simulate multilocus seasonally fluctuating selection under a recently developed model and examine its effect on the variance effective population size (Ne ) at a genome-wide scale. By recapitulating genomic, demographic, and evolutionary parameters from natural Drosophila populations in our simulations, we were able to reproduce allele frequency oscillations reported in recent studies and show that these lead to ~50% genome-wide reductions in Ne . We also demonstrate that Ne reductions are well predicted by the maximum frequency amplitude among all adaptively fluctuating loci, and that the frequency amplitudes are largely determined by the number of adaptively fluctuating loci and the strength of their epistatic interactions. Our results demonstrate that fluctuating selection can substantially reduce effective population size and underscore the importance of temporally variable selection in shaping genome-wide patterns of variation beyond classical models.

Decoding metabolic reprogramming heterogeneity across bladder cancer stages using single-cell and spatial multi-omics approaches.

Cell-type-specific genetic architecture of postpartum depression: A single-cell Mendelian randomization framework for causal gene discovery.

Global warming is altering spring phenology in temperate forests, with important consequences for tree survival, growth, and ecological interactions. However, temperature requirements for dormancy release and budburst vary among populations adapted to different climatic conditions, complicating predictions of spring phenology across broad geographic regions. Here, we quantified the chilling and forcing requirements of three deciduous tree species (Fagus sylvatica, Quercus robur, and Tilia cordata) using four provenances per species spanning a latitudinal gradient from Spain to Poland. Saplings were overwintered under either ambient or warmed open-top chambers and were transferred monthly from November to February to a climate chamber under constant forcing conditions. We found that reduced chilling due to earlier transfer substantially delayed budburst, with T. cordata showing the highest chilling requirement, followed by F. sylvatica, whereas Q. robur exhibited the lowest. We detected both co- and counter-gradient patterns of genetic variation in budburst timing. In Q. robur and, to a lower extent, in T. cordata, Polish provenances budburst later than Spanish ones, while German and Swiss populations were intermediate (co-gradient). In contrast, F. sylvatica showed the opposite pattern with the Spanish provenance tending to budburst latest and the Polish one earliest (counter-gradient). These differences likely reflect genetic differentiation in chilling and forcing requirements among provenances, likely driven by variation in frost risk at their sites of origin. Importantly, insufficient chilling significantly reduced budburst success by 25%-85% across species, with the strongest effect in T. cordata, where success fell below 10% in saplings transferred in November or December across all provenances, potentially constraining canopy development and impairing growth and reproduction. These findings underscore the critical role of winter chilling in regulating budburst timing and canopy development, as well as provenance-specific adaptation, suggesting that species adapted to low chilling might be candidates for assisted migration under rapid climate warming.

This case report describes the use of doxazosin (Cardura) as a treatment for a patient with an autosomal dominant KCNT1, single-nucleotide R398Q pathogenic variant, which has not previously been described in the literature. The patient has KCNT1 gain-of-function pathogenic genetic variant. Because of the patient's continued seizure burden with the use of traditional antiseizure medications and failed invasive antiseizure interventions, an oocyte cell line with the specific genetic variant was created to test efficacy of various medications. Doxazosin was found to have a high degree of inhibitory activity in both wild-type and mutant cell lines and, as a result, was trialed with this patient. The patient experienced a decrease in unplanned hospitalizations in addition to a dramatic decrease in seizure burden with the initiation of doxazosin with minimal side effects.

Rapid evolution of marine phytoplankton under global change: mechanisms, constraints, and ecological consequences.

ABSTRACTHeat tolerance is an important trait in cowpea, a crop that is the primary protein source for a large portion of the human population in sub‐Saharan Africa. Cultivated, landrace, semi‐wild, and wild cowpea grow across the region in diverse climatic conditions. This study used environmental association (envGWAS) and allele‐frequency outlier approaches across a panel of 580 gene bank accessions to identify genomic regions associated with adaptation to heat and limited precipitation. Allele frequency outliers are detected independent of potential selective factors driving differentiation; we used a ranking‐based approach to identify the climate variables most associated with variants among outliers. Precipitation‐related variables dominated the signals we identified for envGWAS and allele frequency outliers. We identified variants on all 11 chromosomes that are putatively associated with cowpea adaptation to higher‐temperature environments. The overlap between variants associated with low precipitation and high temperature suggests that these traits may be inextricably linked in cowpea. The Sahel region is the source of many accessions with derived variants associated with high temperatures, suggesting that accessions from this region could contribute heat tolerance alleles for cowpea improvement.

Pharmacogenomics enables precision pharmacotherapy by linking genetic variation to drug response, yet Arab populations are underrepresented in global reference datasets. We systematically synthesized pharmacogenomic allele-frequency evidence across Arab countries, focusing on clinically actionable genes, to describe population variation, identify high-priority variants, and highlight research gaps. We analyzed 295 studies including 94,346 individuals from 19 countries, pooled country-level allele counts for frequently tested variants, and compared pooled estimates with Middle Eastern reference frequencies. Across most loci, allele-frequency profiles were broadly similar between countries, but several variants showed marked, locus-specific differences with direct relevance to anticoagulants, statins, thiopurines, antidepressants, and fluoropyrimidines. Evidence was uneven across countries and often limited by inconsistent genotyping and incomplete reporting of haplotypes and structural variation. These findings support variant-focused implementation, underscore the need for better population coverage and standardized reporting, and motivate development of a regional pharmacogenomics resource to improve the safety and effectiveness of therapy.

Pangenomes are revolutionizing our ability to resolve genomic regions with complex variations1. However, existing human pangenomes2,3, constrained by small sample sizes, provide limited utility for medical and population genetic applications. Here we generated 1,116 diploid genome assemblies (55 de novo and 1,061 pangenome-informed) with an average size of 2.98 Gb and a mean quality value of 46 as part of the 1000 Chinese Pangenome (1KCP) project. On the basis of these assemblies, we constructed a pangenome comprising 405.3 million base pairs of sequences absent from the current references GRCh38 and CHM13, including 26.2 million base pairs of functional genic and predicted regulatory elements. We catalogued a full spectrum of genetic variation, including 35.4 million small variants, 110,530 structural variants (SVs), 485,575 tandem repeats (TRs) and 0.86 million nested variants embedded in non-reference sequences. This extensive dataset enabled detailed characterization of multiscale genic variations relevant to medical genetics, including gene-altering SVs, TR expansions, gene cluster variations and HLA gene haplotypes. Coupled with the 1KCP gene expression data, we conducted pan-variant expression quantitative trait locus (eQTL)mapping to analyse diverse variant types. We identified 3,256 eQTLs involving complex variants (SVs, TRs and nested variants) and elucidated their regulatory complexity. Finally, we developed a 1KCP pan-variant imputation reference panel, which provides multitype genetic markers to enhance the resolution of future association studies. This resource advances our understanding of complex variants and their functional implications to provide new insights into human health.

• Genomic selection and reproductive biotechnologies have reversed historical declines in fertility, yet fertility remains underemphasized in most breeding objectives. • Emerging tools—including novel phenotypes, functional genomics, male-fertility evaluations and genome editing—expand the scope for sustainable genetic improvement of fertility. • The review highlights the delicate balance among genetic gain, biological constraints and management practices, stressing the need for continuous monitoring to ensure long-term sustainability. Fertility and genetic improvement are fundamentally interdependent in dairy cattle breeding: reproductive success determines the realization of genetic gain, while selection decisions shape the genetic capacity for reproduction. Historically, fertility declined because breeding objectives prioritised milk production, trait definitions captured only a narrow portion of reproductive biology, heritability was suppressed by strong environmental influences, and phenotypic data were often incomplete or imprecise, a limitation that still affects fertility evaluations in many systems. Although genomic selection (GS) has reversed long-standing negative trends and enabled more balanced breeding goals, fertility traits still receive comparatively low emphasis in selection indices. This underrepresentation is further sustained by extensive reliance on management interventions—particularly hormonal synchronisation—that improve phenotypic fertility in the short term but risk obscuring genetic variation, biasing evaluations and conflicting with societal expectations for sustainable livestock systems. This review synthesises fertility within three complementary domains: the biological mechanisms underlying reproduction, the genetic architecture and evaluation systems used to improve it, and the management practices that shape the phenotypes on which selection depends. Across these domains, recent progress has been considerable. Genomic selection has increased the accuracy of breeding values for low-heritability traits, reproductive biotechnologies have intensified selection and shortened generation intervals, and emerging indicator traits, high-throughput phenotyping and richer genomic resources offer new opportunities to align fertility evaluations more closely with underlying biology. Developing evaluations for male fertility, meanwhile, represents an accessible additional avenue for strengthening genetic improvement. Looking ahead, genome editing and advanced reproductive interventions offer unprecedented potential to overcome genetic constraints, yet their practical use remains limited by current evaluation methodologies, the need for robust and biologically meaningful fertility phenotypes and societal acceptance of biotechnological innovation. Taken together, the evidence underscores that progress in fertility will depend not on individual technologies alone, but on maintaining alignment across the biological, genetic and management domains. Only when these dimensions operate synergistically—supported by coordinated strategies among key stakeholders including breeding organisations, AI companies, producers and laboratories—can selection act effectively on fertility, ensuring long-term reproductive resilience and the sustainability of dairy cattle breeding.

Limited pangenome and ambiguous genomic architecture constrain comprehensive genetic variation discovery and cotton improvement. Here we assembled a telomere-to-telomere (T2T) genome for elite cultivar NDM13 and near-T2T genomes for 27 additional representatives of Gossypium hirsutum over the recent century, with transcriptomic profiling of 15 distinct tissues from each. We uncovered 51,551 one-to-one conserved orthologs across all genomes and landscapes of telomere, centromere, 45S rDNA, segmental duplication and copy number variant. We revealed hotspots of structural variation (SV) and impacts of SV, segmental duplication and copy number variant on gene expression or content alteration, as well as adversity resistances. We identified thousands of divergent SVs and genes implicated in modern breeding evolution. Combining T2T-reference-based pangenome construction and 761,536 SVs identified across 1,671 worldwide accessions with phenotypic data from 22 environments, we captured a number of hidden SVs that potentially influence critical breeding traits. These will boost genetic study and biotechnological improvement of the crop.

Glioblastoma (GB), defined as IDH-wildtype CNS WHO grade 4 tumour according to the 2021 WHO classification of CNS tumours, remains a uniformly lethal malignancy in which the efficacy of temozolomide (TMZ) continues to be constrained by both intrinsic tumur biology and the pharmacological barrier imposed by the blood-brain barrier (BBB). Given the central role of the ABCB1 (MDR1/P-glycoprotein) efflux transporter in regulating CNS drug disposition, germline variation in ABCB1 has been proposed as a potential determinant of interindividual variability in TMZ response. This systematic review synthesised clinical evidence from four independent studies, encompassing more than 400 GB patients, evaluating the association between ABCB1 polymorphisms and TMZ efficacy and patients' survival. Across the available literature, the influence of ABCB1 genetic variation emerged as limited and inconsistent. An early study reported a marked survival advantage for carriers of the ABCB1 C1236T C/C genotype treated with TMZ, suggesting reduced efflux and enhanced drug exposure. However, subsequent investigations, including epigenetic analyses, high-quality multivariate survival modelling and a pharmacokinetic study demonstrating genotype-dependent differences in plasma TMZ concentrations, did not replicate a corresponding survival effect. Across the remaining cohorts, common variants such as 1236C>T, 2677G>T/A, 3435C>T and 1199G>A showed no robust association with clinical outcome, indicating that transporter-mediated modulation is likely overshadowed by dominant prognostic drivers, including MGMT methylation, IDH status and tumour heterogeneity. Collectively, current evidence does not support ABCB1 polymorphisms as reliable predictive biomarkers of TMZ response in GB. Nonetheless, the pharmacokinetic signals observed, together with emerging technologies capable of selectively modulating efflux activity at the tumour-BBB interface, point to a continued role for ABCB1 in future therapeutic strategies. Integration of transporter genomics with spatial pharmacokinetics and molecular stratification will be essential to refine drug delivery and improve outcomes in GB.

Identification of CsAK as a critical caffeine-related upstream gene in tea accessions through genome-wide association study

Molecular epidemiology of Streptococcus pneumoniae serotypes 6A and 6B: A systematic review of circulating clones and clonal clusters.

Environmental DNA (eDNA) tools are increasingly used for biodiversity monitoring, with most existing assays targeting species-level identification. However, the use of eDNA to resolve intraspecific genetic variation remains rare and methodologically underdeveloped. This study presents the development and laboratory validation of a novel molecular assay capable of detecting specific phylogeographic lineages, advancing eDNA applications by enabling resolution below the species level. The assay combines Recombinase Polymerase Amplification (RPA) and CRISPR-Cas12a technologies with a lateral flow platform for field-ready, on-site detection. Irish Arctic char (Salvelinus alpinus) was selected as the model due to its conservation relevance and post-glacial lineage diversity in Ireland. Mitochondrial genome sequencing of known Irish lineages identified a Protospacer Adjacent Motif (PAM) site unique to the Atlantic Subclade 1 lineage, allowing clear discrimination from co-occurring lineages. Two assays were optimised: a species-specific assay detecting all Arctic char lineages and a lineage-specific assay targeting Lineage 1. Both showed high sensitivity and specificity under laboratory conditions, with LbCas12a outperforming AsCas12a at optimised buffer concentrations. The lateral flow adaptation, utilising a dual-labelled FAM-Biotin probe, enabled portable and rapid detection with minimal equipment. Field validation using eDNA from Irish lakes highlighted the need for improved sampling protocols, as lake-edge surface samples failed to yield detections. This assay represents the first reported example of a CRISPR-based eDNA tool for phylogeographic lineage detection in the field. It offers a novel, non-invasive, and scalable approach to fine-scale ecological monitoring and establishes a foundation for future conservation tools targeting intraspecific diversity.

Microsatellite-based assessment of genetic variation, bottleneck signatures and population structure in Omani and exotic goats