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At least 19 recordsLinked to original sources
PubMed2025

Largest-Scale Genomic Resource Reconstructing the Genetic Origin, Population Structure, and Biological Adaptations of the Hui People.

Historical and archaeological records indicate that the Maritime and Land Silk Roads played a pivotal role in facilitating Trans-Eurasian migrations and cultural exchanges. However, the extent to which population movements or the spread of ideas shape Chinese Hui populations remains debated. We present the largest genomic resource to date, including 2,280 Hui individuals sequenced or genotyped from 30 diverse regions, to examine the genetic origins, population structure, and biological adaptations of this underrepresented group in global human genome research. We identified a detailed population structure characterized by five distinct genetic lineages of the Hui, influenced by geography and varying gene flow. The admixture history and demographic events suggest that the northwestern and northern Hui lineages emerged from demic diffusion during the Tang and Yuan Dynasties via the Land Silk Road. In contrast, the southern and island Hui lineages reflect cultural diffusion along the Maritime Silk Road, while the mixed southern-northern lineage likely developed through a combination of demic and cultural diffusion. Our findings support a hybrid model for Hui formation, indicating that both demographic processes and sociocultural transmissions contributed to their population history. We identified east-west highly differentiated variants and pre- and post-admixture adaptations in Hui genomes, demonstrating that admixture-driven adaptive or neutral variants impacted susceptibility to cardiovascular diseases and immune- and diet-related traits. These adaptive signatures include post-admixture signals of SLC24A5 and ECHDC1 in the Hui, as well as pre-admixture signals of the HLA region, BCL2A1, and KCNH8 in the East Asian source. Overall, our study suggests that Han-related genetic components helped the Hui population rapidly adapt to new local environments. Additionally, the frequency spectrum of clinically essential variants differed significantly between Hui and Han individuals, emphasizing the importance of including underrepresented populations in genomic research to promote health equity.

Humans↗
PubMed2025

Adapting systems biology to address the complexity of human disease in the single-cell era.

Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent experimental and computational advances - from single-cell and spatial profiling to CRISPR genome editing and machine learning - have raised the exciting possibility of leveraging such strategies to prevent, diagnose and treat human diseases. However, adapting systems-inspired approaches to dissect human disease complexity is challenging, given that discrepancies between the biological features of human tissues and the experimental models typically used to probe function (which we term 'translational distance') can confound insight. Here we review how samples, measurements and analyses can be contextualized within overall multiscale human disease processes to mitigate data and representation gaps. We then examine ways to bridge the translational distance between systems-inspired human discovery loops and model system validation loops to empower precision interventions in the era of single-cell genomics.

Humans↗
PubMed2026

Beyond Earth: Recent Advancements in Microgravity Biomedical and Genetic Research in Saudi Arabia.

Microgravity research has emerged as a rapidly evolving field at the intersection of space medicine, genomics, biotechnology, and precision medicine. Exposure to the space environment induces complex physiological and molecular adaptations that affect multiple biological systems, including immune regulation, metabolism, musculoskeletal function, and gene expression. Recent advances in genomics, multi-omics technologies, artificial intelligence, and bioengineering have substantially improved our understanding of biological adaptation to spaceflight and expanded opportunities for translational biomedical research. This review summarizes recent advances in genetic and biomedical research under microgravity conditions, with particular emphasis on molecular mechanisms, omics technologies, genome editing, microbiome research, regenerative medicine, and personalized healthcare approaches. Major experimental platforms, landmark spaceflight studies, and translational applications in infectious diseases, cancer biology, aging, tissue engineering, and pharmaceutical development are discussed. The review also highlights Saudi Arabia's emerging contributions to genomic medicine and space biosciences through initiatives such as the Saudi Human Genome Program, the Saudi Pangenome Project, the Saudi Space Agency, and the BioGravity Initiative. Recent Saudi participation in human spaceflight and microgravity-associated biomedical research is discussed within the context of Vision 2030 and national investments in biotechnology and precision medicine. Collectively, advances in microgravity research are expected to contribute to the advancement of precision medicine and facilitate the development of innovative diagnostic and therapeutic strategies with significant implications for both human space exploration and terrestrial healthcare.

Humans↗
PubMed2026

Museum genomics links MC1R alleles to adaptive winter coat color polymorphism in the long-tailed weasel.

Understanding the architecture of biological adaptations is a major endeavor of evolutionary biology. Using Natural History collections, we study the genetic basis and evolution of white/brown winter coat color variation in the long-tailed weasel (Neogale frenata), a crucial phenological adaptation for camouflage in habitats with seasonal snow. We produced whole-genome sequencing data for museum specimens, along two winter color morph transition areas in North America, at the West and East coasts. Genome-wide association scans identified a single genomic region linked to color variation polymorphism with approximately 300 kb and 200 kb in the West and East regions, respectively, which included the pigmentation gene MC1R. We identified three MC1R alleles, two of which with deletions of nine or eight amino acids, alternatively associated with the winter brown morphs in the West and East, respectively. These deletions affect the second transmembrane domain, and in one case also the first extracellular loop, which in silico analyses predicted to impact the protein's function. Our findings show alternative intraspecific evolutionary solutions for environmental adaptation in long-tailed weasels, building on the evidence that major genes of the melanin production pathway are hotspots for recurrent and independent evolution of winter camouflage adaptation. This adaptive variation may be crucial to anchor adaptive responses facing future environmental change.

Receptor, Melanocortin, Type 1↗
PubMed2025

Laboratory Evolution Reveals Transcriptional Mechanisms Underlying Thermal Adaptation of Escherichia coli.

Adaptive laboratory evolution is able to generate microbial strains, which exhibit extreme phenotypes, revealing fundamental biological adaptation mechanisms. Here, we use adaptive laboratory evolution to evolve Escherichia coli strains that grow at temperatures as high as 45.3 °C, a temperature lethal to wild-type cells. The strains adopted a hypermutator phenotype and employed multiple systems-level adaptations that made global analysis of the DNA mutations difficult. Given the challenge at the genomic level, we were motivated to uncover high-temperature tolerance adaptation mechanisms at the transcriptomic level. We employed independently modulated gene set (iModulon) analysis to reveal five transcriptional mechanisms underlying growth at high temperatures. These mechanisms were connected to acquired mutations, changes in transcriptome composition, sensory inputs, phenotypes, and protein structures. They are as follows: (i) downregulation of general stress responses while upregulating the specific heat stress responses, (ii) upregulation of flagellar basal bodies without upregulating motility and upregulation fimbriae, (iii) shift toward anaerobic metabolism, (iv) shift in regulation of iron uptake away from siderophore production, and (v) upregulation of yjfIJKL, a novel heat tolerance operon whose structures we predicted with AlphaFold. iModulons associated with these five mechanisms explain nearly half of all variance in the gene expression in the adapted strains. These thermotolerance strategies reveal that optimal coordination of known stress responses and metabolism can be achieved with a small number of regulatory mutations and may suggest a new role for large protein export systems. Adaptive laboratory evolution with transcriptomic characterization is a productive approach for elucidating and interpreting adaptation to otherwise lethal stresses.

Escherichia coli↗
PubMed2026

An international framework for clinical translation of molecular classifiers in osteosarcoma.

Despite well-recognized biological heterogeneity, osteosarcoma has been treated as a single disease for over four decades with minimal improvement in survival. Clinical features are inadequate for risk stratification, and no molecular classifiers guide therapy. An international working group evaluated candidate prognostic biomarkers for clinical translation. Pre-treatment circulating tumor DNA is positioned for clinical implementation, while additional classifiers warrant prospective validation. This work establishes a path to risk-adapted, biologically informed treatment.

Journal Article↗
PubMed2025

Resource presentation dictates genetic and phenotypic adaptation in yeast.

BACKGROUND: Environments shape adaptive trajectories of populations, often leading to adaptive parallelism in identical, and divergence in different environments. However, how does the likelihood of these possibilities change with minute changes in the environment remain unclear. RESULTS: In this study, we evolved Saccharomyces cerevisiae in environments which differed only in the manner in which the sugar source is presented to the population. In one set of populations, carbon was presented as a mixture of glucose-galactose, and in the other, as melibiose, a glucose-galactose disaccharide. Since the two environments differed in how the two monosaccharides are packaged, we call these environments 'synonymous'. Our results show that even subtle environmental differences can lead to differing phenotypic responses between the two sets of evolved populations. However, despite different adaptive responses, pleiotropic effects of adaptation are largely predictable. We also show that distinct genomic targets of adaptation between the two sets of evolved populations are functionally convergent. CONCLUSION: This study highlights how subtle environmental differences dictate phenotypic and genetic adaptation of populations. Additionally, these results also suggest the predictive potential of ancestor's fitness in understanding pleiotropic responses. Our work underscores the importance of studying more such environments to understand the generality of adaptive responses in populations.

Saccharomyces cerevisiae↗
PubMed2026

DPAS-Graph: adaptive spatial-feature relation learning for spatial RNA-to-protein prediction and virtual protein profiling.

Paired spatial multi-omics provides a supervised basis for learning RNA-protein correspondence in situ, but predicting protein abundance from spatial transcriptomic data alone remains challenging across tissue contexts and protein panels. Here, we present DPAS-Graph, an adaptive relation-learning framework for spatial RNA-to-protein prediction. Rather than directly merging spatial proximity and transcriptomic similarity as fixed graph priors, DPAS-Graph represents them as two relation channels on a shared edge support and updates their contributions during representation learning for protein prediction. Its Niche-Coupled Field Encoder combines layer-wise edge-relation modeling, intra-branch relation refinement, and cross-branch residual correction to learn spot representations for protein abundance prediction. In a leave-one-dataset-out benchmark across seven paired spatial multi-omics datasets, DPAS-Graph achieved lower aggregate prediction errors and improved spot-level agreement of protein expression profiles, with gains mainly reflected in error-based metrics and PCC-Spot. Spatial autocorrelation and protein-derived domain agreement analyses were further used to characterize the spatial behavior of the predicted protein maps. When applied to external RNA-only spatial sections, DPAS-Graph generated qualitatively interpretable marker-level virtual protein maps, illustrating its use as a complementary tool for protein-level interpretation of transcriptomics-only spatial data.

RNA↗
PubMed2015

Evolutionary genomics of Culex pipiens: global and local adaptations associated with climate, life-history traits and anthropogenic factors.

We present the first genome-wide study of recent evolution in Culex pipiens species complex focusing on the genomic extent, functional targets and likely causes of global and local adaptations. We resequenced pooled samples of six populations of C. pipiens and two populations of the outgroup Culex torrentium. We used principal component analysis to systematically study differential natural selection across populations and developed a phylogenetic scanning method to analyse admixture without haplotype data. We found evidence for the prominent role of geographical distribution in shaping population structure and specifying patterns of genomic selection. Multiple adaptive events, involving genes implicated with autogeny, diapause and insecticide resistance were limited to specific populations. We estimate that about 5-20% of the genes (including several histone genes) and almost half of the annotated pathways were undergoing selective sweeps in each population. The high occurrence of sweeps in non-genic regions and in chromatin remodelling genes indicated the adaptive importance of gene expression changes. We hypothesize that global adaptive processes in the C. pipiens complex are potentially associated with South to North range expansion, requiring adjustments in chromatin conformation. Strong local signature of adaptation and emergence of hybrid bridge vectors necessitate genomic assessment of populations before specifying control agents.

Adaptation, Biological↗
PubMed2026

Polygenic and monogenic adaptation drive evolutionary rescue at different magnitudes of environmental change.

Understanding the genetic basis of rapid adaptation is key to predicting species' evolutionary responses to environmental change. However, it is still debatable whether many small-effect mutations or a few large-effect mutations underlie rapid adaptation, and how this knowledge can predict population survival or extinction. To address this question, we performed a series of ecologically grounded forward-in-time genetic simulations to study rapid adaptation and extinction with increasing magnitudes of environmental change. These simulations were seeded with genomic variation of the plant Arabidopsis thaliana to have a realistic genomic structure, with one (monogenic) to 1,000 (polygenic) variants with varying heritabilities contributing to an environmental adaptive trait. Our results revealed two distinct scenarios of rapid adaptation and population rescue. Under small-to-moderate environmental shifts, high polygenic traits increased evolutionary rescue probability. Under extreme environmental shifts, high polygenic traits lead predictably to extinction, yet monogenic traits sometimes produce one-off winning adaptive genotypes. We interpret our rapid evolutionary rescue findings in terms of the fundamental theorem of natural selection, where trait polygenicity shapes the distribution of genetic variance in fitness across replicates and, in turn, the probability of population survival, with polygenic architectures producing more stable and predictable fitness variance and monogenic architectures generating highly skewed and variable outcomes. These results highlight the insights genomics gives us into the (un)predictability of species' evolutionary responses to global change, with management implications for assisted adaptation and conservation.

Arabidopsis↗
PubMed2025

Harnessing fern stress adaptations: From evolution and ecophysiology to molecular biology.

Ferns are the second most diverse vascular plant lineage after angiosperms and have been a key ecological component of Earth's biodiversity for more than 380 million years. Importantly, ferns are sister to seed plants, providing a critical outgroup for understanding the evolution of seed plant features. Ferns are remarkably resilient to abiotic and biotic stresses due to a long evolutionary history with adaptations to diverse habitats, stresses, and herbivores. As a result, ferns produce a multitude of secondary metabolites with unique bioactivities; these chemicals are potentially linked to the adaptation of ferns to herbivory, various abiotic and biotic stresses, and changing environments. Assembled reference genomes and the identification of key metabolic compounds of multiple ferns have already made significant contributions to human health and well-being. Here, we review the recent scientific advances in fern research, including evolution, stress resistance, metabolites and medicinal utilization, and comparative multi-omics applications. We propose that integrated investigations involving ecological, physiological, and molecular techniques will facilitate the future research translation of fern resources in diverse areas including soil remediation, biopesticides, and medicine. Advances in our understanding of fern molecular biology will provide new insights into the evolution of land plants and promote the utilization of ferns for heightened environmental restoration, crop protection and human health.

Ferns↗
PubMed2026

Overcoming cancer resistance in pancreatic cancer: toward dynamic precision oncology.

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal malignancy, largely because of its profound and evolving therapeutic resistance. Resistance is not determined by a single molecular alteration but arises from interconnected mechanisms, including intrinsic resistance, treatment-induced adaptive resistance, acquired resistance, genomic evolution, clonal selection, cancer stemness, phenotypic plasticity, metabolic adaptation, and tumor microenvironment-mediated effects. Emerging therapeutic approaches targeting KRAS/RAS signaling, stromal and immune components, metabolic dependencies, and DNA damage repair pathways offer opportunities to address these mechanisms, although durable efficacy remains limited by biological heterogeneity and adaptive responses. In this review, we examine therapeutic resistance as an evolutionary and multidimensional process and summarize emerging strategies for overcoming resistance. We further propose a Dynamic Precision Oncology (DPO) framework that extends conventional precision oncology beyond baseline molecular profiling by integrating longitudinal assessment of tumor genomics, circulating tumor DNA, CA19-9, imaging, radiomics, and clinical characteristics. This framework emphasizes iterative detection and characterization of emerging resistance, mechanism-informed treatment adaptation, and subsequent reassessment rather than automatic treatment modification based on a single biomarker. DPO may provide a conceptual framework for integrating evolving tumor biology into treatment decision-making, while prospective studies are needed to validate biomarkers, define actionable thresholds, and determine whether longitudinal resistance-guided strategies improve clinical outcomes in PDAC.

Humans↗
PubMed2025

Genome-wide Parallelism Underlies Rapid Freshwater Adaptation Fueled by Standing Genetic Variation in a Wild Fish.

A fundamental focus of ecological and evolutionary biology is determining how natural populations adapt to environmental changes. Rapid parallel phenotypic evolution can be leveraged to uncover the genetics of adaptation. Using population genomic approaches, we investigated the genetic architecture underlying rapid parallel freshwater adaptation of Neosalanx brevirostris by comparing four freshwater-resident populations with their common ancestral anadromous population. We demonstrated that the rapid parallel adaptation to freshwater followed a complex polygenic architecture and was characterized by genomic-level parallelism, which proceeded predominantly through repeated selection on the preexisting standing genetic variations. Frequencies of the genome-wide adaptive standing variations were moderate in the ancestral anadromous population, which had pre-adapted to fluctuating salinities. Relatively large allele frequency shifts were observed at some adaptive single-nucleotide polymorphisms (SNPs) during parallel adaptation to freshwater environments, with a large fraction of freshwater-favored alleles being fixed or nearly fixed. These adaptive SNPs were involved in multiple biological functions associated with osmoregulation, immunoregulation, locomotion, metabolism, etc., which were highly consistent with the polygenic architecture of adaptive divergence between the two ecotypes involving multiple complex physiological and behavioral traits. This work provides insight into the mechanisms by which natural populations rapidly evolve to changes in the environment and highlights the importance of standing genetic variation for the evolutionary potential of populations facing global environmental changes.

Animals↗
PubMed2026

Repair and regeneration across the lifespan: an ontogenetic perspective.

The capacity for tissue repair and regeneration undergoes a profound and progressive decline across the human lifespan, representing a fundamental driver of aging and chronic disease. This review establishes a comprehensive ontogenetic framework by mapping the continuous biological transition from the flawless, scarless regenerative plasticity of embryonic development to the irreversible fibrotic scarring and organ failure characteristic of senescence. We synthesize the hierarchical collapse of reparative networks across multiple biological scales. Importantly, this ontogenetic decline should not be interpreted as a purely degenerative trajectory but rather as a dynamic systems-level reprogramming in which evolutionary trade-offs prioritize tumor suppression, immune surveillance, and reproductive fitness over long-term regenerative fidelity. Recognizing this adaptive reallocation of biological resources reframes aging not simply as failure but as a predictable recalibration of repair hierarchies. At the molecular and cellular levels, the accumulation of genomic instability, unresolvable DNA damage, and mitochondrial dysfunction gradually overwhelms intracellular quality-control mechanisms. Concurrently, epigenetic drift and chronic, low-grade systemic inflammation ("inflammaging") dismantle the stem cell niche, driving adult stem cell exhaustion and shifting wound healing away from functional tissue replacement toward maladaptive fibrosis. Furthermore, we examine divergent, organ-specific repair trajectories. By contrasting the severe regenerative restrictions of the adult central nervous system and myocardium with the persistent, yet exhaustible, resilience of the liver, we elucidate the unique intrinsic and microenvironmental barriers that impede structural and functional recovery. Finally, we evaluate the clinical paradigm shift from passive management of age-related degeneration to active restoration of tissue integrity. By integrating systemic geroscience-which addresses the global hallmarks of aging-with targeted bioengineering and in vivo epigenetic modulation, contemporary regenerative medicine seeks to recreate permissive, youthful microenvironments. Ultimately, mastering these ontogenetic principles holds unprecedented potential to reactivate endogenous repair pathways, mitigate multi-organ collapse, and significantly extend human functional healthspan.

DNA repair↗
PubMed2026

T2T Genome Assembly and Multi-Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte).

Laevichaulis alte is a slug in the order Systellommatophora that evolved from aquatic ancestors and now faces strong challenges from desiccation, respiration on land, and novel pathogens. Its mucus is essential for water retention, locomotion, and defense. To link terrestrial adaptation with mucus biosynthesis, we generated a gap-free genome assembly of L. alte using PacBio HiFi reads, Oxford Nanopore ultra-long reads, and Hi-C data. The genome shows low heterozygosity and holocentromeric chromosomes. Functional metabolomics revealed marked metabolic shifts between L. alte and the closely related aquatic species Peronia verruculata. In L. alte, differential metabolites were enriched in lipid metabolism, immune regulation, and stress response pathways, consistent with life in a dry and microbe-rich terrestrial environment. Comparative genomics and transcriptomics identified candidate genes linked to mucus secretion and physiological adaptation, including VEGF, ASGR2, and COL6A6. Further analyses highlighted the vascular endothelial growth factor (VEGF) gene family as a key regulator connecting angiogenesis, tissue remodeling, and mucus production pathways in L. alte. Together, this gap-free genome and multi-omics dataset establish a molecular framework that links genomic innovation, mucus biology, and terrestrial adaptation in Systellommatophora, and they offer a basis for understanding ecological niche specialization in land molluscs.

Animals↗
PubMed2026

Stress-driven strategic games in cancer.

Tumor cells face chronic genotoxic, metabolic, hypoxic, and immune stress that shapes their evolution. While stress-response molecular pathways are well characterized, cancer biology lacks a predictive framework for how cells select among alternative adaptive strategies and how these selections interact to produce tumor-level behavior. We propose that evolutionary game theory, previously applied to cooperation in cancer, should be extended to position stress adaptation itself as the organizing principle of tumor evolution. In this framework, stress-adaptive strategies constitute frequency-dependent games whose payoffs depend on population composition. We introduce a three-level distinction between cell states (transcriptional snapshots), game states (local configurations of stress and neighbor composition that define the active payoff structure), and cell strategies (conditional behavioral policies mapping game states to fitness-relevant outputs). This perspective explains the maintenance of intratumor heterogeneity through frequency-dependent selection, the reversibility of resistance through bet-hedging dynamics, and therapy resistance as an equilibrium outcome rather than genetic inevitability. Integrating insights from single-cell genomics, spatial profiling, and lineage tracing, we outline testable predictions and experimental approaches for measuring payoff structures. Therapeutically, the framework suggests exploiting adaptive trade-offs, restricting phenotypic plasticity, and reshaping competitive landscapes. Re-framing cancer as an evolving game of stress adaptation provides a unifying structure for predictive oncology.

Animals↗
PubMed2025

ATAC-seq for Characterizing Host and Pathogen Genome Accessibility During Virus Infection.

Chromatin regulation provides a mechanism through which cells dynamically and rapidly regulate their gene expression profiles, playing a pivotal role in diverse biological processes and disease states. The Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method that enables genome-wide detection of accessible chromatin regions, providing information on nucleosome positioning and the epigenetic regulation of the chromatin structure. ATAC-seq has been used in various biological contexts, and several reports have demonstrated its application to studying infections with viral or bacterial pathogens. The ability to characterize changes in viral or bacterial genome accessibility during infections provides insights into both pathogen replication and host defense mechanisms. Viral genomes undergo dynamic changes in their structural landscape to facilitate replication and evade host immune responses. Additionally, host cells encode DNA sensors, which are specialized proteins that bind to viral genomes to initiate innate immune responses and sometimes, to suppress viral gene expression. ATAC-seq enables the systematic detection of key structural changes on the viral genome mediated by either viral or host proteins, offering mechanistic insights into virus-host interactions. Here, we describe an ATAC-seq method optimized for studying changes in chromatin accessibility in both host and viral genomes. We have previously applied this method to demonstrate a systematic decrease in the genome accessibility of herpes simplex virus type I (HSV-1) enabled by a host antiviral factor, the interferon-gamma inducible protein 16 (IFI16) during infection of human fibroblasts. This protocol can be adapted to various biological contexts involving the introduction of foreign DNA, making it a valuable tool for a broad range of research endeavors.

Humans↗
PubMed2026

Chromosome level genome assembly and full-length transcriptome of blacktip trevally (Caranx heberi).

Caranx heberi (Bennett, 1830) commonly known as the blacktip trevally belongs to the family Carangidae and is a potential brackishwater aquaculture species. However, the limited genomic resources are hindering the efforts to study its genetic traits and their molecular basis. To bridge this gap, we generated a high-quality reference genome employing multiple sequencing strategies including PacBio Hifi reads (135x), Illumina short reads (150x), and Hi-C chromosome conformation capturing (180x). The high-quality genome assembly consisted of 159 scaffolds summing to 618.71 Mb and an N50 value of 26.72 Mb. Among these, 24 chromosome level scaffolds covered 97.5% of the total assembly. The genome contained 20.94% of repeat elements and 30,354 protein encoding genes. In addition, full-length transcriptomes were generated using the PacBio IsoSeq approach from seven tissues (gill, kidney, liver, muscle, heart, spleen, and intestine). The comprehensive genomic and transcriptomic resources developed in this study will facilitate the domestication and aquaculture development of C. heberi, as well as support research on its nutritional potential, ecological adaptations, and evolutionary biology.

Animals↗