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PubMed2026

Enhancing detection of polygenic adaptation: a comparative study of machine learning and statistical approaches using simulated evolve-and-resequence data.

BACKGROUND: Detecting signals of polygenic adaptation remains a significant challenge in population genomics, as traditional methods often struggle to identify the associated subtle, multi-locus allele-frequency shifts. Here, we introduced and tested several novel approaches combining machine learning techniques with traditional statistical tests to detect polygenic adaptation patterns in time-series of allele frequency changes from whole genome data. We implemented a Naive Bayesian Classifier (NBC) and One-Class Support Vector Machines (OCSVM), and compared their performance against the classical Fisher's Exact Test (FET). Furthermore, we combined machine learning and statistical models (OCSVM-FET and NBC-FET), resulting in 5 competing approaches. The framework is mainly designed and validated for evolve-and-resequence (EaR) experimental designs, where defined selection pressures and temporal sampling are feasible, but might be applicable for certain natural experiments as well. RESULTS: Using a simulated dataset based on empirical C. riparius Pool-Seq data, we evaluated methods across evolutionary scenarios varying in generation, selection strength, and number of loci under selection. Our results demonstrate that the combined OCSVM-FET approach consistently outperformed competing methods, achieving the lowest false positive rate, highest area under the curve, and high accuracy. The performance peak aligned with what we term the 'late dynamic phase' of adaptation - the period after initial selection has occurred but before fixation - highlighting the method's sensitivity to ongoing selective processes. CONCLUSIONS: Furthermore, we emphasize the critical role of parameter tuning, balancing biological assumptions with methodological rigor. While broader applicability remains an important direction for future work, the present benchmarking is intentionally scoped to EaR experimental contexts.

Machine Learning↗

PubMed2025

Evolutionary legacy of the "living fossil" genus Parrotia (Hamamelidaceae): genomic insights into species divergence and polygenic adaptation.

Despite their long evolutionary history, the genomic basis of adaptation and speciation in "living fossil" plants remain largely unexplored. Parrotia, a Tertiary relict tree genus with two extant species, P. subaequalis and P. persica, exhibits a disjunct distribution between East Asia and West Asia. Here, we present the first chromosome-level assemblies for both species, confirmed their sibling relationship, and dated the speciation event to the early Miocene. The recent proliferation of long-terminal repeat retrotransposons has driven the genome expansion in P. subaequalis. We detected widespread heterogeneous genomic differentiation between species. Extensive signals of divergent selection, local adaptation, and elevated Ka/Ks ratios in Parrotia indicate that this genus has undergone adaptive evolution in distinct refugia, challenging the notion of it as an "evolutionary dead end". Our findings provide new insights into the genomic evolution, environmental adaptation, and speciation of this "living fossil" tree genus.

Genome, Plant↗

PubMed2025

Genome sequencing and population genomics provide insights into the demographic history, genetic load, and local adaptation of an endangered Tertiary relict.

Endangered Tertiary relict trees represent an exceptional evolutionary heritage with small and isolated populations, yet little is known about how demographic history, local adaptation, and genetic load have affected their long-term survival and extinction risk. We performed whole-genome sequencing and population genomic analyses on Ulmus elongata L. K. Fu & C. S. Ding, an endangered Tertiary relict tree endemic to East Asia. By integrating genomes from U. elongata and seven other endangered trees from public databases, we identified rate-decelerated genes across endangered trees and genes under positive selection of U. elongata associated with tissue development, detoxification, and immune response, and signal transduction and regulation mechanisms potentially leading to endangered status. Demographic analyses revealed continuous population decline from the late Miocene to present, especially during the last glacial maximum (LGM) and last 10 000 years. Spearman correlation indicated a strong negative relationship between effective population size and human population density (rpopulation density = -0.90, P < 0.001) as well as cropland use (rcropland use = -0.89, P < 0.001). Genotype-environment association (GEA) analyses identified a set of candidate genes associated with temperature and precipitation, supporting a polygenic adaptation model in U. elongata. Overall, our findings underscore the severe population bottlenecks that have led to the fixation of strongly deleterious mutations and inbreeding, further compromising the adaptive potential and long-term viability of U. elongata. Furthermore, assessments of genomic vulnerability under future climate scenarios revealed higher genetic offsets in northern region of Fujian and Jiangxi populations, suggesting these regions require prioritized conservation efforts due to reduced adaptive capacity.

Endangered Species↗

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↗

PubMed2026

Polygenic Profiles Are Associated with Multidomain Biochemical Adaptations Across a Competitive Season in Professional Football Players: A Longitudinal Observational Study.

Background/Objectives: The physiological adaptations required to sustain elite football performance are influenced by both genetic background and dynamic biochemical responses, although their interaction across a full competitive season remains insufficiently characterized. This study aimed to examine the association between polygenic profiles and longitudinal biochemical adaptations in professional football players. Methods: Forty male professional football players competing in the Spanish league were monitored across two consecutive seasons. Blood samples were collected at six time points representing different phases of the competitive cycle. Biomarkers related to muscle metabolism, iron status, and hepatic function were analyzed. Polygenic profiles were calculated using Total Genotype Scores (TGS) for muscle performance, hepatic resilience, and metabolic efficiency. Associations were initially explored using Pearson correlations and subsequently evaluated using linear mixed-effects models accounting for repeated measurements within subjects. Results: Exploratory correlation analyses identified several associations between polygenic profiles and biochemical markers. Muscle performance TGS was inversely associated with serum iron (r = -0.36, p = 0.017) and positively associated with CK (r = 0.32, p = 0.041), Hb (r = 0.29, p = 0.046), and Hct (r = 0.33, p = 0.024). Hepatic resilience TGS showed inverse associations with ALT (r = -0.39, p = 0.012), urea (r = -0.51, p = 0.011), and BUN (r = -0.51, p = 0.011). Metabolic efficiency TGS was negatively associated with AST (r = -0.43, p = 0.044), ALT (r = -0.33, p = 0.025), and GGT across multiple time points (p = 0.001-0.013). However, although several nominal associations emerged in linear mixed-effects models accounting for repeated measurements, none remained statistically significant after false discovery rate correction. These findings should therefore be interpreted as exploratory and hypothesis-generating. Conclusions: Polygenic profiles may be associated with inter-individual variability in biochemical adaptations throughout a competitive season. These findings suggest the integration of genomic and biochemical data in precision athlete monitoring, while highlighting causal relationships and predictive applications require further investigation.

Humans↗

PubMed2026

Landscape Genomics Reveals Divergent Adaptation Modes and Predicts Climate Vulnerability in Xinjiang Indigenous Sheep.

Climate change increasingly endangers precious indigenous sheep germplasm resources distributed across diverse Chinese landscapes, and systematically decoding their polygenic climate-adaptive genetic mechanisms is essential for targeted breed conservation and long-term sustainable pastoral production. Whole-genome resequencing data from 93 individuals covering six representative local sheep breeds were analyzed in this work. After filtering highly collinear climate variables, three mature landscape genomic approaches were jointly applied to identify environment-linked gene variants, while two predictive metrics across ten CMIP6 future climate scenarios quantified each breed's long-term adaptive risks. Six temperature- and water-related environmental factors jointly drove sheep population genetic differentiation, with temperature fluctuation indices showing markedly stronger explanatory power. Detected adaptive genes were significantly enriched in ion transport, energy metabolism and cellular stress response pathways. Future projections indicated western breeds (Bayinbuluke, Cele Black, Xiahe) face severe maladaptation risks under high-emission SSP370 scenarios by 2100, whereas central and eastern breeds possess much broader climate tolerance. This study systematically reveals the core genomic basis of ovine climate adaptation and quantifies distinct breed-specific climate vulnerability, providing solid reliable theoretical support for precision germplasm conservation and selective breeding of climate-resilient sheep varieties.

adaptive loci↗

PubMed2026

Climate-Driven Niche Tracking and Genomic Resilience Shape Future Distribution of a Widespread Agricultural Weed.

Understanding how agriculturally important species respond to environmental change is critical for maintaining productivity, mitigating agroecosystem threats and sustaining resilience. While crops have traditionally been the focus in agroecosystems, agricultural weeds are integral components that often face even stronger selective pressures, making them powerful models for investigating ecological and evolutionary responses to climatic and human-mediated challenges. Insights from how weeds adapt rapidly under these pressures can inform strategies to improve agricultural outcomes, since both pests and crops evolve under the same multivariate selective pressures. Here, we integrate two centuries of distribution records with whole-genome sequencing from natural populations of the most damaging weed in Europe-Alopecurus myosuroides (blackgrass) - to examine its ecological and evolutionary responses in agroecosystems. Blackgrass largely maintained its historical climatic niche, expanding its range primarily by tracking environments analogous to those it historically occupied. Genome-wide analyses revealed a polygenic basis of environmental responses, with most loci linked to single environmental variables and a subset showing limited environmental pleiotropy, indicating modular adaptation to the complex selective pressures of managed agricultural landscapes. Coupling these genomic-environment relationships with projected climate change and genomic offset analyses indicated that most blackgrass populations will remain well aligned with future conditions. Our findings show that ecological niche tracking and polygenic adaptation allow agricultural weeds like blackgrass to persist under rapid environmental change, offering insights relevant not only for weed management but also for designing resilient cropping systems under future climates.

Plant Weeds↗

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

Identification and characterization of non-canonical azole antifungal resistance pathways in Aspergillus fumigatus.

UNLABELLED: Human fungal infections, especially those caused by Aspergillus fumigatus, pose a significant global health threat, particularly in immunocompromised individuals. Azole antifungals are the primary treatment for this pathogen; however, the prevalence of azole-resistant A. fumigatus strains is steadily increasing. Mutations in cyp51A, which encodes an enzyme involved in ergosterol biosynthesis and the molecular target of the azoles, are well established to confer resistance in this fungal species. However, additional mechanisms governing resistance to this antifungal class remain understudied and poorly characterized, despite growing recognition of their importance in clinical resistance. In this study, we investigated the genetic basis of azole resistance in A. fumigatus isolates from clinical settings worldwide, with a particular focus on mechanisms independent of cyp51A (non-canonical). Using a combination of genomic and functional approaches, including whole-genome sequencing and transcriptomic analysis, we identified novel genetic variants and characterized population structure, advancing our understanding of the genetic diversity and evolutionary dynamics of resistance in A. fumigatus. By expanding our understanding of the complex genetic and molecular factors underlying azole resistance in this important human fungal pathogen, this research is poised to inform the development of novel antifungal strategies and contribute to global efforts to combat fungal infections. IMPORTANCE: Azole antifungals are the frontline therapy for infections caused by the opportunistic mold Aspergillus fumigatus, yet resistance to these drugs is rapidly increasing worldwide. Most studies have focused on mutations in cyp51A, the canonical target of azoles; however, a growing proportion of resistant clinical isolates lack these mutations, indicating that alternative resistance mechanisms are emerging. Here, we integrate population genomics, transcriptomics, and functional analyses across a global collection of isolates to define the architecture of cyp51-independent (non-canonical) azole resistance. We show that this resistance phenotype is strongly associated with a distinct population lineage and is driven by a highly polygenic network of metabolic, mitochondrial, and regulatory adaptations rather than single target site mutations. These isolates exhibit extensive transcriptional rewiring and metabolic remodeling under azole stress, suggesting distinct survival strategies beyond canonical resistance. Our findings reveal that azole resistance in A. fumigatus can evolve through diverse evolutionary routes and emphasize the need to monitor and therapeutically target non-canonical pathways that may increasingly contribute to antifungal treatment failure.

Aspergillus fumigatus↗

PubMed2026

Intersecting experimental evolution and CRISPR screens to identify novel toxin resistance loci.

Understanding toxin resistance in insects is key to appreciating niche adaptations but remains challenging due to its often-polygenic basis. A well-known example is the specialized association of Drosophila sechellia with noni fruit (Morinda citrifolia), which is toxic to other insects, including Drosophila simulans and Drosophila melanogaster. The main noni toxin is octanoic acid (OA), but the mechanisms that determine sensitivity or resistance to OA in different species remain unclear. Here, we experimentally evolved D. simulans with increased OA resistance, identifying multiple loci under selection. Cross-referencing these with a genome-wide, OA resistance CRISPR screen in a D. melanogaster cell line highlighted two proteins: Kraken, a putative detoxification enzyme expressed in digestive and renal tissues, and Alkbh7, a mitochondrial protein linked to fatty acid metabolism. Both genes show elevated expression in D. sechellia and OA-resistant D. simulans. In D. melanogaster, kraken mutants are more OA-sensitive, while Alkbh7 overexpression increased OA resistance. Mutation of these genes in D. sechellia reduced OA tolerance. Our identification of genes contributing to OA resistance in laboratory and natural contexts demonstrates how complementary selection approaches can provide insights into complex mechanisms of toxin susceptibility and adaptation. Such methods could have practical applications in the characterization of natural and artificial insecticides.

Animals↗

PubMed2026

Intersecting experimental evolution and CRISPR screens to identify novel toxin resistance loci.

Understanding toxin resistance in insects is key to appreciate niche adaptations but remains challenging due to its often-polygenic basis. A well-known example is the specialized association of Drosophila sechellia with noni fruit ( Morinda citrifolia ), which is toxic to most other insects, including the closely-related Drosophila simulans and Drosophila melanogaster . Toxicity of noni is due to its high concentration of octanoic acid (OA), but the mechanisms that determine sensitivity or resistance to OA in different species remain poorly understood. Here, we experimentally-evolved D. simulans with increased OA resistance, identifying multiple loci under selection. Cross-referencing these with a genome-wide, OA-resistance CRISPR screen in a D. melanogaster cell line highlighted two proteins: Kraken, a putative detoxification enzyme expressed in digestive and renal tissues, and Alkbh7, a mitochondrial protein linked to fatty acid metabolism. Both genes show elevated expression in D. sechellia and OA-resistant D. simulans . In D. melanogaster , kraken mutants are more OA-sensitive, while Alkbh7 overexpression increased OA resistance. Importantly, mutation of these genes in D. sechellia reduced OA tolerance. Our identification of genes underlying OA resistance in laboratory and natural contexts demonstrates how complementary, cross-species selection approaches can provide insights into complex mechanisms of toxin susceptibility and adaptation; such methods could also have practical applications in the characterization of natural and artificial insecticides.

Journal Article↗

PubMed1979

The human chin and its relationship to mandibular morphology.

This study evaluated the proportion of the external chin (protuberantia mentalia) in relation to the total symphyseal area in normal jaws and those with a diverse morphology. A sample of 60 cases was randomly selected and divided into three groups of 20 each on the basis of normal growth, horizontal growth and vertical growth with an open bite. Tracings of lateral dn frontal radiographs were used to describe general mandibular form and to determine the percentage of external/total symphyseal area. Dental casts were also examined to determine a basal arch form ratio. The results of this study indicate that the amount of bony chin present is related to certain morphologic features of the mandible. The most significant findings illustrate: 1. The chin increases in size as the mandibular type varies from a vertical type, to a normal type, to a horizontal type of growth pattern. 2. With dental "hypofunction" in combination with an exaggerated vertical development of the mandible, a smaller proportion of the protruding chin is present. 3. The chin increases in size as the mandibular basal arch form varies from a tapered shape for the vertical cases to a more square form in the horizontal cases. 4. The degree of lateral ramal flair does not appear to influence the proportion of protruding chin present. Several models have been presented which attempt to explain protuberantia mentalia variation. The evidence in this study supports the concept that mandibular morphology is the result of the action of compensative adaption in a developing structure. There appears to be an implied polygenic influence on symphyseal morphology operating from the cartilaginous cranial base and mandibular basilar bone. This may be manifested in the relative proportion of mandibular basal bone to cranial base width, and to the vector of cranial base growth. The ultimate proportion of the bony chin is viewed to be the result of mandibular adaption to a functional musculoskeletal balance in the craniofacial complex. The extreme variability of chin form in man may be considered to be the result of compensative growth developing in response to the most structurally efficient jaw form, the contiguous soft and hard tissue environment, and the intrinsic genotype of the mandible.

Adolescent↗

PubMed2026

Shared candidate genes associated with variation in egg size in cold-adapted and artificially selected Drosophila melanogaster.

The development of most multicellular organisms begins with oogenesis, the production of the egg. In D. melanogaster, egg size is a highly polygenic trait closely related to fitness. Elements of shifts in egg size have been widely studied and modeled, but the genes underlying this variation are still poorly understood. This study aimed to identify candidate genes associated with processes underlying egg-size variation using D. melanogaster as a model. In selection experiments, we generated large-egg populations from a shared ancestral population using both cold-adaptation and artificial selection, and identified candidate genes for the large-egg phenotype. Using whole-genome DNA sequencing and strict computational filtering, we uncovered single-nucleotide polymorphisms in 10 genes. Characterization of these candidates revealed functions in cytoskeletal dynamics, DNA replication and repair, intracellular signaling, and stem cell maintenance and differentiation. RT-PCR and qPCR were used to validate gene expression differences between cold-adapted lines and the Oregon R control (OrR) in a subset of the candidates. In RT-PCR, stathmin demonstrated a modified expression pattern in all cold-adapted lines relative to OrR controls. In qPCR experiments, Pde1c had significantly higher expression (p < 0.05) in the cold-adapted flies compared to OrR controls for all three fly cages tested. For Ino80, significantly higher expression was observed for one of three cages while one cage showed lower expression. We have assembled a candidate list we hope will be a useful resource for researchers across specialties, from germ cells to cytoskeletal dynamics, to further investigate the genetic and developmental aspects of variation in egg size in D. melanogaster.

Animals↗

PubMed2024

Plasticity of Human Microglia and Brain Perivascular Macrophages in Aging and Alzheimer's Disease.

The complex roles of myeloid cells, including microglia and perivascular macrophages, are central to the neurobiology of Alzheimer's disease (AD), yet they remain incompletely understood. Here, we profiled 832,505 human myeloid cells from the prefrontal cortex of 1,607 unique donors covering the human lifespan and varying degrees of AD neuropathology. We delineated 13 transcriptionally distinct myeloid subtypes organized into 6 subclasses and identified AD-associated adaptive changes in myeloid cells over aging and disease progression. The GPNMB subtype, linked to phagocytosis, increased significantly with AD burden and correlated with polygenic AD risk scores. By organizing AD-risk genes into a regulatory hierarchy, we identified and validated MITF as an upstream transcriptional activator of GPNMB, critical for maintaining phagocytosis. Through cell-to-cell interaction networks, we prioritized APOE-SORL1 and APOE-TREM2 ligand-receptor pairs, associated with AD progression. In both human and mouse models, TREM2 deficiency disrupted GPNMB expansion and reduced phagocytic function, suggesting that GPNMB's role in neuroprotection was TREM2-dependent. Our findings clarify myeloid subtypes implicated in aging and AD, advancing the mechanistic understanding of their role in AD and aiding therapeutic discovery.

Journal Article↗

PubMed2026

Plasticity of human microglia and brain perivascular macrophages in aging and Alzheimer's disease.

Myeloid cells, including microglia and perivascular macrophages, are central to Alzheimer's disease (AD) neurobiology, yet their role remains incompletely understood. We profiled 832,505 human myeloid cells from the prefrontal cortex of 1,607 donors spanning the lifespan and showing varying degrees of AD neuropathology. We delineated six subclasses comprising 13 transcriptionally distinct subtypes and identified adaptive changes associated with aging and AD progression. Here we show that a disease-associated microglial subtype, characterized by elevated GPNMB expression and enriched for polygenic AD risk, expands with AD pathology and shows increased phagocytic activity. We identify MITF as an upstream regulator required to maintain this microglial state. Cell-cell interaction analyses prioritize APOE-SORL1 and APOE-TREM2 signaling pairs associated with disease progression. Using human and mouse models, we demonstrate that the neuroprotective effects of this microglial subtype depend on TREM2. These findings provide mechanistic insights into myeloid cell function in aging and AD, aiding therapeutic discovery.

Humans↗

PubMed2026

The reporting and handling of missing data in genetic epidemiological studies of mental health in childhood and adolescence: A systematic review.

BACKGROUND: Genetic epidemiological analyses of child and adolescent mental health often use data from prospective longitudinal cohorts. Missingness due to selective attrition is therefore an important potential source of bias in such analyses. Informatively reporting on missingness and taking appropriate steps to handle it in analyses can mitigate this potential bias. Here, we aim to systematically assess how researchers report and address missingness in genetic epidemiological studies of child and adolescent mental health-related outcomes using cohort data. METHODS: We systematically searched the Ovid Medline database for studies published between August 2012 and August 2025, reporting polygenic score, genome-wide association, or Mendelian randomization analyses, of data on children or adolescents participating in cohort studies. We extracted information from eligible studies based on criteria adapted from the strengthening and reporting of observational studies in epidemiology (STROBE) guidelines. RESULTS: A total of 133 eligible studies were included, of which 125 (93.98%) reported the number of complete cases in all waves, while 84 (63.16%) detailed the amount of missingness on all key variables. Most studies used complete case analysis, while 39 studies explicitly reported applying other methods to handle missingness, with multiple imputation (n = 20, 15.04%) being the most common, followed by full information maximum likelihood 10 (8.1%). Only 18 studies (13.53%) reported an assumed missing mechanism along with the method used to address missingness. Full reporting of both the extent and handling of missingness at the item level was rare, occurring in only 5 (3.76%) and 15 (11.28%) studies, respectively, among the 123 studies that used multi-item instruments. CONCLUSION: Best practice recommendations for reporting on missing data handling emphasize the importance of detailing the proportion of missingness, types of mechanisms underpinning missingness, and details of approaches used. Based on this review, these recommendations for proper reporting of missing data are rarely followed in full.

children and adolescents↗

PubMed2025

Factors underlying a latitudinal gradient in the S/G lignin monomer ratio in natural poplar variants.

The chemical composition of wood plays a pivotal role in the adaptability and structural integrity of trees. However, few studies have investigated the environmental factors that determine lignin composition and its biological significance in plants. Here, we examined the lignin syringyl-to-guaiacyl (S/G) ratio in members of a Populus trichocarpa population sourced from their native habitat and conducted a genome wide association study to identify genes linked to lignin formation. Our results revealed many significant associations, suggesting that lignin biosynthesis is a complex polygenic trait. Additionally, we found an increase in the S/G ratio from northern to southern geographic origin of the trees sampled, along with a corresponding metabolic and transcriptional reprogramming of xylem cell wall biosynthesis. Further molecular analysis identified a mutation in a cell wall laccase genetically associated with higher S/G ratios that predominate in trees from warmer lower latitudes. Collectively, our findings suggest that lignin heterogeneity arises from an evolutionary process enabling poplar adaptation to different climatic challenges.

Populus↗

PubMed2026

Beyond the salt barrier: CRISPR-mediated DNA reprogramming to uncouple yield from tolerance in Rice: A review.

Rice (Oryza sativa L.) feeds half of humanity, yet its cultivation is increasingly threatened by soil salinization, which now affects 1.4 billion hectares globally. Decades of breeding and engineering have focused on Na+ exclusion, principally through the Saltol QTL and the xylem-unloading transporter OsHKT1;5, yet this strategy has reached a physiological ceiling. Excluder genotypes survive salinity but fail to fill grain, because the ATP-intensive cost of continuous ion extrusion starves reproductive sinks, while ABA-mediated stomatal closure imposes chronic carbon limitation. The resulting "survival-yield gap" exposes a fundamental flaw in single-trait approaches to a polygenic stress. In this review, we argue that durable, yield-stable salt tolerance requires a coordinated systems-level intervention spanning five mechanistic tiers: (i) CRISPR/Cas9-mediated removal of negative regulatory brakes (OsRR22, RST1, PC1) that suppress plant's latent stress-adaptive capacity; (ii) reinforcement of actin-myosin cytoskeletal transport to sustain SOS1, NHX1, and HKT1;5 delivery under ionic stress; (iii) importation of halophyte design principles from Oryza coarctata, including salt gland architecture and superior Na+ compartmentalization; (iv) recalibration of the ROS-photosynthesis axis via the DHHC09-STRK1-CatC molecular switch and stomatal density engineering; and (v) pyramiding these modules into a "Salt-Shield Rice" genotype through multiplex editing, marker-assisted introgression, speed breeding, and genomic selection. We propose a phased ten-year roadmap that integrates synthetic biology circuit design with conventional breeding to deliver field-ready, multi-module varieties with greater than 70% yield stability at 8-10 dS m-1. This remains an aspirational design target rather than a demonstrated outcome, as three of the five tiers-halophyte-derived structural traits, cytoskeletal reinforcement, and full multi-module pyramiding-remain unvalidated in rice.

CRISPR/Cas9↗