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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↗

PubMed2025

Genomic Insights Into Local Adaptation Across Heterogeneous Understory Habitats and Climate Change Vulnerability.

Understanding adaptive evolution and survival risks in understory herbs is crucial for the effective conservation of biodiversity. How environmental gradients shape species local adaptation patterns is not well understood, nor is how populations of understory herbs respond to a changing climate. In this study, we conducted population genomic analyses of Adenocaulon himalaicum (Asteraceae) with a pan-East Asian distribution, representing a good model for dominant understory herbs to elucidate adaptation mechanisms in heterogeneous forest ecosystems. Based on 34,398 putatively neutral single nucleotide polymorphisms (SNPs) across 27 populations, we identified three genetic lineages accompanied by high levels of genetic differentiation between populations. Our isolation by environment results (IBE) indicated a significant effect of environmental gradients on genomic variation of A. himalaicum (r = 0.18, p = 0.03). To decompose the relative contributions of climate, geography and population structure in explaining genetic variance, our partial RDA found that the prominent contribution of environmental effects (climatic and soil variables) explained 29% and 36% of the neutral and adaptive genetic variation, respectively. Using two genotype-environment association (GEA) methods, we identified 13 SNPs as candidates for core climate-related adaptation loci, with two of these loci further validated by qRT-PCR experiments. Projections of spatiotemporal genomic vulnerability under different future climate scenarios revealed that populations in the southeastern edge of the Himalayas, near the Sichuan Basin, the southernmost region of Northeast China and the northern Korean Peninsula, as well as northern Japan, were identified as the most vulnerable and should be prioritised for conservation. Therefore, our current study provides the genomic foundations for conservation and management strategies to elucidate how these understory herbs cope with future climate changes.

Climate Change↗

PubMed2026

Population and landscape genomics provide insights into the adaptive genetic variation and future climate-induced vulnerability of the endangered tree species Phoebe bournei.

Elucidating the genomic underpinnings of adaptive variation is highly important for the conservation, landscape application, and management of ornamental trees against the backdrop of global climate change. However, research on the genetic mechanisms underlying climate adaptation in Phoebe bournei-a near-threatened subtropical tree species endemic to China, which is endowed with exceptionally high ornamental and ecological value-remains scarce. Whole-genome resequencing was conducted on 362 individuals from 27 natural populations across the geographical range of the species. Genome-environment association analyses were employed to identify 1556 climate-associated variants and 167 candidate genes associated with temperature and precipitation variables. Through functional annotation and expression profiling, pivotal genes, including TRX-M4 and FBD1, were identified as integral to drought and heat stress responses, with adaptive alleles displaying distinct geographic frequency distributions and significant phenotypic differentiation. Divergent evolutionary trajectories were deduced among populations, with southeastern populations distinguished by elevated genetic diversity and strong signatures of local adaptation. Nevertheless, projections derived from the Risk of Non-Adaptedness and gradient forest models suggest that these southeastern populations will face substantial genomic offset under future climate scenarios, signaling heightened vulnerability and the need for prioritized conservation and management. This study provides the first genome-wide perspective into the adaptive evolution of P. bournei and offers a robust foundation for its conservation and climate-resilient management.

Journal Article↗

PubMed2025

Harnessing Landscape Genomics to Evaluate Genomic Vulnerability and Future Climate Resilience in an East Asia Perennial.

In this era of rapid climate change, understanding the adaptive potential of organisms is imperative for buffering biodiversity loss. Genomic forecasting provides invaluable insights into population vulnerability and adaptive potential under diverse climatic conditions, thereby facilitating management interventions and bolstering shaping species-specific germplasm conservation strategies. We primarily employed landscape genomics approaches, leveraging single-nucleotide polymorphisms obtained through whole-genome resequencing of 201 individuals across 43 Rheum palmatum complex populations, to pinpoint adaptive variation and its significance in the context of future climates, delineate seed zones, and establish guidelines for ex situ germplasm conservation. The species complex exhibited strong signatures of local adaptation and differential genomic vulnerabilities across its distribution range, with eastern lineage populations facing significant maladaptation risks under future climate scenarios. Using diverse datasets of putatively adaptive loci and climate change scenarios, we delineated three distinct seed zones within the species' range, estimated varying sample sizes per zone to capture most adaptive diversity, and predicted shifts in seed zone centroids ranging from 48.3 to 359.3 km from historical distributions to mitigate climate change impacts. Collectively, our findings underscore the importance of integrating genomic and environmental data to forecast the adaptive trajectory of an East Asian perennial under anticipated climate changes, guide seed zone delineation for germplasm conservation and enhance population resilience. These results provide a blueprint for designing targeted conservation strategies and restoration plans in other imperilled species.

Climate Change↗

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↗

PubMed2025

Comparative genomic analysis of Acer tsinglingense and A. davidii provides insights into nervonic acid biosynthesis, population evolution and genome vulnerability of endangered A. tsinglingense.

Global biodiversity is facing threats from climate change, habitat fragmentation, and anthropogenic activities-pressures that particularly endanger endemic and narrowly distributed species. In this study, the high-quality chromosome-level genomes of two ecologically divergent maples were assembled: the endangered and range-restricted Acer tsinglingense (791.40 Mb) and its widespread congener Acer davidii (1291.99 Mb). Phylogenomic analysis indicates that the two species diverged ~16.3 million years ago, with A. tsinglingense showing notable gene family expansions in secondary metabolite pathways. Notably, the 3-ketoacyl-CoA synthase gene family, which is involved in nervonic acid biosynthesis, underwent significant expansion and tandem duplication in A. tsinglingense, exhibiting high expression in buds. Population genomic analysis revealed that, compared with the widely distributed A. davidii, A. tsinglingense possesses lower genetic diversity, higher harmful mutation load, and signatures of a severe population bottleneck during the Late Pleistocene. Genome-environment association analysis further identified climate-adaptive genomic variations linked to five key environmental factors and projected potential genomic offsets under future climate scenarios. The southern lineage of A. tsinglingense exhibited greater climate sensitivity and genomic vulnerability under strong selective pressures, underscoring its importance as a conservation priority. Our research reveals that metabolic specializations in A. tsinglingense (such as the synthesis of nervonic acid) may confer competitive advantages in specific habitats. However, factors including its restricted distribution, historical population bottlenecks, and accumulated genetic load severely constrain its evolutionary potential to cope with rapid climate change. These findings emphasize the importance of elucidating the genomic basis and mechanisms of endangerment in metabolically specialized and threatened plant species to inform effective conservation strategies.

Genome, Plant↗

PubMed2026

Reduced legacy precipitation decreases microbial community growth efficiency and alters soil organic carbon in a California grassland.

BACKGROUND: Changes in global patterns can leave a lasting legacy in semiarid grasslands by reshaping microbial growth dynamics and carbon cycling during the first wet-up in the autumn-a period known for intense microbial activity and significant carbon emissions. To study the lasting impacts of decreased winter rain, we implemented two precipitation regimes (100% vs. 50% mean annual precipitation) in California Mediterranean-climate grassland field plots. After the dry season, soils were rewetted in the laboratory with H218O and sampled at 0 h, 3 h, 24 h, 48 h, 72 h, and 168 h post rewet. We quantified CO2 efflux, measured microbial growth and mortality via quantitative 18O stable isotope probing and 16S rRNA gene amplicon sequencing, and characterized the soil organic carbon chemical composition, metagenomes, and metatranscriptomes. RESULTS: We found that reduced winter precipitation imposed a strong legacy effect on microbial turnover; despite maintaining similar respiration rates, microbial growth declined by ~1 order of magnitude, yielding decreased community growth efficiency (CGE = new biomass growth/respiration), and microbial mortality declined by ~2 orders of magnitude. Soil organic carbon also shifted from lipid-like, amino-sugar-like, and protein-like compounds (indicative of microbial necromass) to more oxidized lignin-like and tannin-like compounds (indicative of decomposing plant-derived compounds). Meta-omics revealed distinct metabolic strategies linked to CGE. At high-CGE, microbes appeared to consume more energetically favorable N-rich necromass (released via high microbial turnover); this allowed for increased amino acids and peptidoglycan biosynthesis and greater aromatic compound degradation, fueling further energy production and growth efficiency. At low CGE, communities had elevated carbohydrate metabolism and lipid turnover, consistent with increased investment in plant detritus degradation and membrane repair and maintenance rather than growth. CONCLUSIONS: Together, our findings demonstrate that reduced winter rainfall decreases microbial turnover following rewetting without a concurrent reduction in CO2 emissions. This shift results in persistently lower CGE, which has the potential to increase soil carbon loss as CO2. If such conditions are maintained over multiple years, these changes could reshape soil organic carbon stocks and alter the balance of grassland ecosystems under future climate scenarios. While our data suggest that sustained reductions in CGE may drive SOC decline, the magnitude and persistence of these effects depend on long-term environmental dynamics and warrant further investigation. Video Abstract.

Soil Microbiology↗

PubMed2026

Impacts of climate-driven yield changes on the affordability of healthy diets: a modelling study.

BACKGROUND: Food security is central to global nutrition improvement and public health goals, and healthy diets represent a higher-level aspiration beyond merely avoiding hunger. Climate change poses an increasing threat to food systems by affecting crop yields and food prices. Although climate change-driven risks to hunger have been widely studied, the extent to which climate change undermines the affordability of healthy diets while accounting for socioeconomic responses and regional inequalities remains insufficiently understood. This study aimed to quantify the effects of climate change on the future affordability of healthy diets under alternative socioeconomic and climate scenarios. METHODS: We developed an integrated modelling framework that explicitly couples multimodel crop-yield projections with an integrated assessment model (Global Change Analysis Model [GCAM]). Yield responses from six global gridded crop models driven by four climate models were integrated into GCAM, allowing endogenous socioeconomic adjustments such as land-use shifts, production reallocation, and price responses to emerge under shared socioeconomic pathways (SSPs). Diet affordability was then assessed using the Food and Agriculture Organization of the UN's Cost and Affordability of a Healthy Diet framework across three socioeconomic-climate scenarios (SSP1-2.6, SSP2-4.5, and SSP3-6.0). FINDINGS: Under a high-emissions pathway (ie, SSP3-6.0), climate change was projected to render healthy diets unaffordable for a model-mean of 119 million people globally by 2100, even when CO2 fertilisation effects are included, with the upper end of the model ensemble reaching about 1·6 billion people. In contrast, climate-induced affordability losses were found to be negligible under both a low-emissions pathway (ie, SSP1-2.6; -0·3 million) and a medium-emission pathway (SSP2-4.5; +0·2 million). Under a high-emission pathway, model-mean projections indicated that diet costs could increase by up to 12% in the most affected regions by the end of the century. Under medium emissions, cost increases were projected to remain below 4%, whereas under low emissions, affordability changes were projected to be minimum across regions (within approximately 0·5%). Substantial regional disparities emerged, with the largest and most consistent affordability losses concentrated in low-income regions that contributed least to historical greenhouse gas emissions. Under SSP3-6.0, these disparities persisted particularly in regions of Africa and Asia despite projected three-to-five-fold increases in income over the century, with climate-induced disruptions to food systems increasing the number of people unable to afford a healthy diet through mid-century. INTERPRETATION: Climate change is likely to exacerbate global nutritional inequalities by disproportionately increasing the affordability risks of healthy diets in regions that have contributed least to historical greenhouse gas emissions. Under high-warming scenarios, socioeconomic development alone is insufficient to fully offset these risks, highlighting the structural vulnerability of low-income food systems to climate-driven price shocks. These findings suggest that in the absence of targeted interventions, climate change could continue to undermine progress towards equitable and health-oriented nutrition outcomes. FUNDING: Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China; National Aeronautics and Space Administration Goddard Institute for Space Studies Climate Impacts Group; Future of Life Institute; and Global Alliance for Improved Nutrition.

Journal Article↗

PubMed2025

Intraspecific divergence within Microcystis aeruginosa mediates the dynamics of freshwater harmful algal blooms under climate warming scenarios.

Intraspecific biodiversity can have ecosystem-level consequences and may affect the accuracy of ecological forecasting. For example, rare genetic variants may have traits that prove beneficial under future environmental conditions. The cyanobacterium responsible for most freshwater harmful algal blooms worldwide, Microcystis aeruginosa, occurs in at least three types. While the dominant type occurs in eutrophic environments and is adapted to thrive in nutrient-rich conditions, two additional types have recently been discovered that inhabit oligotrophic and eutrophic environments and have genomic adaptations for survival under nutrient limitation. Here, we show that these oligotrophic types are widespread throughout the Eastern USA. By pairing an experimental warming study with gene expression analyses, we found that the eutrophic type may be most susceptible to climate warming. In comparison, oligotrophic types maintained their growth better and persisted longer under warming. As a mechanistic explanation for these patterns, we found that oligotrophic types responded to warming by widespread elevated expression of heat shock protein genes. Reduction of nutrient loading has been a historically effective mitigation strategy for controlling harmful algal blooms. Our results suggest that climate warming may benefit oligotrophic types of M. aeruginosa, potentially reducing the effectiveness of such mitigation efforts. In-depth study of intraspecific variation may therefore improve forecasting for understanding future whole ecosystem dynamics.

Microcystis↗

PubMed2025

A decentralized future for the open-science databases.

The continuous and reliable open access to curated biological data repositories is indispensable for accelerating rigorous scientific inquiry and fostering reproducible research outcomes. However, the current paradigm, which relies heavily on centralized infrastructure for the storage and distribution of foundational biomedical datasets, inherently introduces significant vulnerabilities. This centralized model is susceptible to single points of failure, including cyberattacks, technical malfunctions, natural disasters, and even political or funding uncertainties. Such disruptions can lead to widespread data unavailability, data loss, integrity compromises, and substantial delays in critical research, ultimately impeding scientific progress. The downstream effect of such interruptions can be the widespread paralysis of diverse research activities, including computational, clinical, molecular, and climate studies. This scenario vividly illustrates the inherent dangers of consolidating essential scientific resources within a single geopolitical or institutional locus. As data generation is accelerating and the global landscape continues to fluctuate, the sustainability of centralized models must be critically re-evaluated. A shift toward federated and decentralized architectures may offer a robust and forward-looking approach to enhancing the resilience of scientific data infrastructures by reducing exposure to governance instability, infrastructural fragility, and funding volatility, while also promoting equity and global accessibility. Inspired by established models such as ELIXIR's federated infrastructure and the policy and funding frameworks developed by CODATA and the Global Biodata Coalition (GBC), emerging Decentralized Science (DeSci) initiatives can contribute to building more resilient, fair, and incentive-aligned data ecosystems. The future of open science depends on integrating these complementary approaches to establish a globally distributed, economically sustainable, and institutionally robust infrastructure that safeguards scientific data as a public good, further ensuring continued accessibility, interoperability, and preservation for generations to come. Here, we examine the structural limitations of centralized repositories, evaluate federated and decentralized models, and propose a hybrid framework for resilient, fair, and sustainable scientific data stewardship.

data accessibility↗

PubMed2025

Smarter stomata: emergent technologies unlocking yield potential in a changing climate.

Stomata, the gatekeepers of leaf gas exchange, regulate carbon dioxide uptake and water loss, functions increasingly critical as crops face more frequent, intense heat and drought. Under dry conditions, stomatal conductance (g s) typically decreases, limiting carbon assimilation and yield. Heat stress, in contrast, elicits variable g S responses: sometimes increasing to facilitate transpirational cooling, while at other times decreasing, especially when combined with drought. Heat and drought also induce complex, context-dependent shifts in stomatal anatomy. Smaller, denser stomata improve drought resilience in some cases, while reduced density confers greater tolerance in others. The optimal stomatal ideotype remains unknown, and different or even opposing traits may confer resilience dependent on the environmental scenario. Substantial genotypic variation in g s and stomatal anatomy, high heritability and co-localized quantitative trait loci for stomatal traits and yield highlight their untapped potential as breeding targets for climate-resilient crops. However, stomatal traits remain largely absent from breeding pipelines due to challenges of phenotyping at scale. This is changing rapidly. Advances in deep learning, porometry, digital microscopy, and remote sensing now enable high-throughput measurement of stomatal physiology and anatomy. Next-generation breeding technologies including clustered regularly interspaced short palindromic repeats (CRISPR), multi-omics approaches, and artificial intelligence-driven ideotype selection models could revolutionize breeding, allowing precise engineering of stomatal traits for resilience to environmental stress. The time has come to move beyond characterizing stomatal traits and start actively incorporating them into breeding strategies. By leveraging these technologies, stomatal traits can become high value targets, unlocking their potential to enhance crop performance in a hotter, drier future.

abiotic stress↗