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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

Branching plasticity and candidate gene-hormone networks associated with shade responses in soybean under relay strip intercropping.

BACKGROUND: Branching is a key determinant of high-yield plant architecture in soybean, particularly in maize- soybean relay strip intercropping where plants experience an "initially shaded-then fully illuminated" light regime. However, the genetic regulation of branching responses to shading remains poorly understood. METHODS: We evaluated 11 branching-related traits across 202 soybean accessions grown under monoculture (SS) and relay strip intercropping (RI). Branch number (BN), branching incidence (BI), and total branch length (TBL) were assessed together with stress tolerance indices (STI) and relative distance plasticity index (RDPI). Genome-wide association studies (GWAS) using mixed linear model (MLM) and three-variance-component MLM (3VmrMLM) were combined with haplotype and protein structural analyses to refine candidate genes. RESULTS: Based on Pearson correlation analysis of all 11 traits, BN, BI, and TBL measured before maize harvest showed the strongest and most consistent associations with branch seed weight within the corresponding cropping system (BSW_SS under SS and BSW_RI under RI), whereas other traits showed weaker or environment-dependent associations. Higher STI values calculated from these traits during the co-growth phase were negatively associated with BSW_RI, suggesting weaker compensatory recovery after light restoration in genotypes with more stable early branching patterns between SS and RI. In contrast, mediation analysis indicated that RDPI was positively associated with BSW_RI mainly through improved mature branching architecture (MB_index), which accounted for approximately 70% of the total positive effect. GWAS identified 57 and 74 significant QTNs using MLM and 3VmrMLM, respectively, and LD-window genes were filtered for exonic nonsynonymous or premature stop-codon variants, yielding 883 genes with putative functional variants. Two high-confidence genes emerged: Glyma.02G058600 (PP2C55), exhibiting shading-specific haplotype effects likely linked to GA-mediated branch-stem balance, and Glyma.02G059900 (DA1-related protein), showing stable effects across environments and implicated in ABA-mediated suppression of axillary meristems. CONCLUSIONS: These results provide insight into the genetic and physiological basis of soybean branching responses under relay strip intercropping, clarify that branching plasticity and relative shade tolerance represent distinct response dimensions in this system, and identify putative loci that may be useful for breeding soybean cultivars with improved shade adaptation and yield stability.

Glycine max

ClearDepthIAS enables automated high-throughput quantification of roots in soil-grown taproot crops.

Understanding root system architecture is critical for improving crop productivity and resilience, yet phenotyping root traits such as root growth angle and rooting depth remains technically challenging, especially at high throughput. Here, we present ClearDepthIAS, a high-throughput imaging and analysis platform that enables nondestructive, automated quantification of root architecture traits in taproot system crops. By capturing and stitching 360° images of roots growing along the transparent walls of pots and applying deep learning-based segmentation (ClearDepth-WRT), we measured wall root shallowness (WRS)-a proxy for root growth angle-with high precision. We demonstrated for the tap root systems of soybean and canola that the system accurately detects root tips, quantifies their vertical distribution, and extracts biologically meaningful traits such as root area, distribution indices, and growth angles. Validation experiments in canola and soybean demonstrated that WRS can correlate with root crown architecture in mature plants, both in greenhouse and field settings. Furthermore, WRS and root distribution indices derived from ClearDepthIAS are predictors of early root architecture and can be correlated with root biomass distribution across soil depths under field conditions; however, environmental interactions may influence these relationships and weaken or even negate such correlations, as observed when comparing field to field variation in root system architecture. Our system enables efficient phenotyping of genetically diverse populations, with medium to high trait heritability, supporting its utility for genome-wide association studies and breeding. ClearDepthIAS accelerates the development of root ideotypes for improved resource acquisition and carbon sequestration, offering a scalable tool for supporting climate-resilient agriculture.

Plant Roots

PGPR inoculation and growth enhancement of crops cultivated in hydroponic systems.

Plant growth-promoting rhizobacteria (PGPR) are ubiquitous rhizosphere microorganisms that promote plant health through various mechanisms. Although the study of PGPR inoculants in soil has been done for ages, their application in hydroponic systems has received relatively limited attention. This review identifies PGPR inoculants that are commonly used in hydroponics, methods of application, and their effects on plant growth and nutrient use efficiency. Literature shows that PGPR inoculants improve plant performance in controlled hydroponic systems through the production of growth-stimulating substances, nitrogen fixation, and improved nutrient acquisition. However, the plant growth responses are highly variable depending on the composition of nutrient solutions, environmental factors, crop and microbe species, and the type of hydroponic system. The review identifies various challenges of PGPR inoculation in hydroponic systems and future research directions to address the current gaps. Generally, the productivity of hydroponic systems can be enhanced through advanced inoculation strategies and the development of suitable carrier materials to improve inoculant survival, viability, and functions. Emphasis should also be placed on designing system-specific microbial consortia and Synthetic communities that are tailored to the unique ecological conditions of hydroponic systems.

Hydroponics

Genetic legacy effects in a mungbean-wheat rotation reveal potential to breed for system-level yield gains.

Legume crops provide protein-rich food, serve as critical disease breaks in cereal rotations, and contribute to soil fertility through symbiotic nitrogen fixation. However, crop improvement programs typically focus on within-crop performance rather than system-level benefits. We hypothesize that legacy effects (the influence of one crop's genotype on subsequent crop performance) are under genetic control and could be targeted in breeding programs. To test this, we evaluated how 309 genetically diverse mungbean genotypes influenced subsequent wheat performance. The mungbean panel was grown, followed by a single wheat cultivar sown in the same plots. Remarkably, wheat yield varied by nearly 1 t ha-1 (2.52-3.49 t ha-1), depending solely on the preceding mungbean genotype. Legacy effects showed moderate heritability (H2: 0.43-0.65), suggesting untapped genetic potential for breeding. However, these estimates were derived from a single site and season and require validation across environments. Analyses of mungbean traits, soil properties, and volatile organic compounds identified root architecture, symbiotic nitrogen fixation, and the soil microbiome as potential contributors to legacy effects, although these mechanisms remain to be tested directly. Haplotype mapping identified genomic regions in mungbean associated with wheat yield and, to a lesser extent, grain protein, revealing trade-offs between within-crop performance and legacy effects. Genetic simulations based on empirically derived marker effects compared genomic selection strategies targeting mungbean yield, wheat yield, or both simultaneously. A selection strategy placing equal weight on mungbean yield and subsequent wheat yield (50:50 weighting) achieved simultaneous gains in both crops (19.5% and 7.6%), highlighting the potential to breed for system-level productivity with reduced input requirements.

crop rotations

Holistic approaches for improvement of maize resistance against lodging stress: current status and future perspective.

Lodging is a major constraint in maize production, causing significant yield losses, reduced grain quality, and harvesting inefficiencies, thereby posing a serious challenge to global food security and climate-resilient agriculture. This review synthesizes current knowledge on the genetic, physiological, and agronomic determinants of maize lodging resistance and evaluates holistic strategies for improving tolerance to lodging stress. Recent advances in quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), functional gene characterization, genome editing, high-throughput phenotyping, and precision agronomy have provided powerful tools to enhance stalk biomechanics, root anchorage, and adaptive plant architecture. Integrating genomic discovery with advanced phenomics and optimized agronomic management offers a scalable framework for accelerating the development of high-yielding, lodging-resilient maize cultivars. However, critical gaps remain in understanding the genetic coordination between stalk strength and root system architecture, integrating multi-omics approaches to unravel regulatory networks, validating genome-editing interventions across diverse agro-ecologies, and developing environment-responsive predictive breeding models and cost-effective phenotyping tools, particularly for stress-prone regions. Addressing these challenges through coordinated multi-environment trials and integrative molecular-agronomic strategies will facilitate the translation of genomic discoveries into climate-resilient, high-performing maize cultivars. By consolidating molecular insights with applied breeding and management practices, this review provides a comprehensive framework that guides researchers in designing genome-informed and field-validated approaches to improve maize resistance to lodging stress and support sustainable crop production systems.

Zea mays

Multimodal Deep Learning and Foundation Models for Early Detection and Forecasting of Plant Diseases.

Plant diseases destroy 20-40% of global food production annually, posing a critical threat to food security for a projected population of 9.7 billion by 2050. Conventional diagnostic approaches relying on expert visual assessment are slow, costly, and unsuitable for modern agricultural scales. While deep convolutional neural networks demonstrated early promise, single-modality, image-centric systems consistently fail under real-world field conditions characterized by variable lighting, co-occurring infections, and cultivar diversity. This review synthesizes a decade of progress across four interconnected frontiers: the evolution of deep learning architectures for plant disease detection; the adaptation of foundation models including CLIP, SAM, and DINOv2 to agricultural contexts; the development of multimodal fusion frameworks integrating imagery, environmental, genomic, and hyperspectral data; and the transition from static disease diagnosis to descriptive comparison of reported metrics, which suggested that multimodal approaches frequently reported improved diagnostic performance relative to corresponding single-modality baselines, although direct cross-study comparison was limited by methodological heterogeneity. A systematic review following PRISMA guidelines identifies eligible comparative studies. Descriptive comparison of reported performance metrics across these studies indicated that multimodal approaches generally achieved higher accuracy and sensitivity than single-modality models, particularly for pre-symptomatic disease detection. Eight critical research gaps are identified, including the absence of a unified agricultural foundation model and limited climate-aware forecasting under non-stationary climate projections. A structured research agenda is proposed to accelerate translation from laboratory performance to globally equitable, field-deployable crop protection systems.

convolutional neural networks

Disruption of HaVipR1 confers Vip3Aa resistance in the moth crop pest Helicoverpa armigera.

The global reliance on Bacillus thuringiensis (Bt) proteins for controlling lepidopteran pests in cotton, corn, and soybean crops underscores the critical need to understand resistance mechanisms. Vip3Aa, one of the most widely deployed and currently effective Bt proteins in genetically modified crops, plays a pivotal role in pest management. This study investigates the molecular basis of Vip3Aa resistance in Australian Helicoverpa armigera through genetic crosses, and integrated genomic and transcriptomic analyses. We identified a previously uncharacterized gene, LOC110373801 (designated HaVipR1), as potentially important in Vip3Aa resistance in two field-derived resistant lines. Functional validation using CRISPR/Cas9 knockout in susceptible lines confirmed the gene's role in conferring high-level resistance to Vip3Aa. Despite extensive laboratory selection of Vip3Aa-resistant colonies in Lepidoptera, the biochemical mechanisms underlying resistance have remained elusive. Our research identifies HaVipR1 as a potential contributor to resistance, adding to our understanding of how insects may develop resistance to this important Bt protein. The identification of HaVipR1 contributes to our understanding of potential resistance mechanisms and may inform future resistance management strategies. Future work should explore the biochemical pathways influenced by HaVipR1 and assess its interactions with other resistance mechanisms. The approach utilized here underscores the value of field-derived resistant lines for understanding resistance in agricultural pests and highlights the need for targeted approaches to manage resistance sustainably.

Animals

Recurrent and niche-specific functional bacteriome of maize hybrid revealed by integrated metabarcoding and culturomics.

The plant microbiome plays a pivotal role in plant survival in natural habitats by facilitating nutrient acquisition, stress adaptation, and disease suppression, while also offering opportunities to enhance crop productivity and climate resilience. However, the distribution of persistent and culturable bacteriome across maize-associated niches and their functional potential remain poorly resolved. This study integrated metagenomic next-generation sequencing (mNGS-based metabarcoding) and culturomics to characterise the maize-associated bacteriome of bulk soil, rhizoplane, phylloplane, and cob of the maize hybrid PHM-1 under contrasting cropping and tillage systems, and to identify recurrent and agriculturally promising bacteriome components. The bacteriome exhibited pronounced niche-specific structuring, whereas overall bacterial community composition did not differ significantly across cropping and tillage treatments (ANOSIM, R = 0.038, p = 0.306). Proteobacteria predominated in the culturable bacteriome (69-84%; mean, 76.2%) but accounted for only 1% of the total bacteriome, whereas Patescibacteria and Firmicutes were relatively enriched. Niche-specific dominance was evident, with Pantoea accounting for 40.79% of the total and 56.27% of the culturable phylloplane bacteriome under cereal monocropping, while Serratia represented 31.59% and 59.40% of the total and culturable cob bacteriomes, respectively. Across niches, mNGS captured substantially greater bacteriome diversity, particularly uncultured and unidentified taxa in soil-associated compartments, whereas culturomics recovered a narrower but functionally accessible fraction. Culturomics yielded 99 isolates representing 32 species across 12 genera, including six genera shared with the mNGS-derived recurrent bacteriome: Bacillus, Enterobacter, Pantoea, Pseudomonas, Serratia, and Stenotrophomonas. Functional screening identified strong biocontrol and plant-beneficial traits among core-associated isolates. Pseudomonas oryzihabitans ZM-DL-PA10 inhibited Rhizoctonia solani, Macrophomina phaseolina, and Bipolaris maydis by up to 40.6%, 43.9%, and 45.2%, respectively, through secreted and volatile metabolites; exhibited P, K, and Zn solubilisation; and produced IAA and siderophores. It also recorded the lowest B. maydis disease index (ADI) of 1.00. Pantoea ananatis ZM-BH-EA4 showed 52.4% and 68.5% inhibition of R. solani and B. maydis, respectively, through volatile metabolites. Collectively, the integration of mNGS and culturomics revealed a strongly compartmentalised maize bacteriome and identified recurrent, culturable, and functionally promising bacterial taxa, providing a targeted resource for microbiome-based crop protection and climate-resilient maize production.

Zea mays

CasY7: An optimized Cas12i system for enhanced genome editing in monocot crops.

The CRISPR-Cas12 family nucleases, particularly the Cas12i subtypes, are considered promising alternatives to Cas9 for genome editing in plants. We previously developed a new Cas12i variant, CasY7, which has been successfully applied in clinical trials; its performance in plants remains to be investigated. Initial testing in stable transgenic maize and rice showed that the codon-optimized CasY7 (pCasY7e1) achieved average editing efficiencies of 58.7% and 62.3% across five target sites, respectively, outperforming the typical Cpf1 (pCpf1) control that targets the same sites. To further enhance activity, we fused T5 exonuclease to CasY7 (pCasY7e2), which shifted mutation profiles toward larger deletions, and subsequently integrated an MS2 aptamer into the crRNA scaffold (pCasY7e3). The optimized pCasY7e3 system increased editing efficiencies to 87.7% in maize and 82.9% in rice-approximately 2.7-fold higher than pCpf1. We further demonstrated multiplexed editing in maize, generating biallelic dwarf mutants, and validated functionality in hexaploid wheat with editing efficiencies up to 58.8%. Overall, our comprehensive validation across 942 transgenic plants confirmed robust editing in maize, rice, and wheat, establishing CasY7 as a high-efficiency addition to the CRISPR toolkit.

Zea mays

Soil management practices shape the abundance, diversity, and spread of antimicrobial resistance.

Agricultural soils are critical hotspots of antimicrobial resistance genes (ARGs). Yet, the environmental factors shaping these reservoirs and the hazards they pose to humans and livestock remain poorly understood. Because management practices introduce antibiotics, heavy metals, and nonantibiotic biocides, they can rapidly select for resistance. Most studies have examined components of management practices in isolation, overlooking the multiple stressors of modern industrial agriculture. Here, we used a large-scale field experiment to examine how multiple stressors from soil and crop management interact to shape antimicrobial resistance. We combined shotgun metagenomics, phylogenomics, and risk-score analyses to quantify the diversity of ARGs, mobile genetic elements (MGEs), and the transmission potential of drug-resistant pathogens. Relative to other management systems, intensive, chemically reliant monoculture systems, typical of the US Corn Belt, create strong selective pressures promoting more abundant and diverse ARGs and MGEs. These systems therefore carry greater potential to transmit ARGs, including those with relevance to both livestock and public health such as tetA and blaPAM, likely mediated by integration and excision. In contrast, less-intensive, lower-input systems with diverse crop rotations maintained resistomes with lower abundance, diversity, and transmission potential. Our results suggest that these patterns could arise due to the divergent effects of management practices on overall soil microbial diversity, an ecological barrier that can suppress ARGs. This study highlights the need to understand the combined stressors of agricultural practices, beyond antimicrobial use, to design effective strategies to mitigate antimicrobial resistance.

Soil Microbiology

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

A Novel Approach to Engineering Tomato Spotted Wilt Virus Infectious Clones by Disarming Key Nodes in Antiviral Defenses.

Tomato spotted wilt virus (TSWV) is an economically devastating pathogen that rapidly overcomes genetic resistance in major crops. Reverse genetic systems are crucial for investigating plant-virus interactions and resistance-breaking mechanisms, and developing these tools for segmented ambisense RNA viruses remains a crucial challenge. Current TSWV clones rely on extensively modified Asian isolates requiring co-delivery of multiple replication helpers and viral silencing suppressors. Streamlining these systems for regionally significant strains with minimal genetic alterations is essential. Here, we developed the first infectious clone of a U.S. TSWV isolate (PA01). Three binary plasmids contain cDNAs for the antigenomic L and S segments, as well as the genomic M segment, with enhanced GFP replacing NSs on the S segment. Co-delivery of the cucumovirus 2b alone or in combination with tombusvirus P19 or begomovirus AL2 achieved a high proportion of systemically infected Nicotiana benthamiana and Capsicum annuum plants. In N. tabacum, co-delivering the Caenorhabditis elegans cell death suppressor CED-9 or using NahG transgenic plants produced 30 to 33% systemically infected plants. Co-delivery of 2b boosted infection levels in NahG plants to 62%. These data indicate that in addition to the antiviral RNA-silencing machinery, additional host defense pathways influence TSWV rescue and systemic infection from cDNA. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Tospovirus

Integrated agronomy of pea (Pisum sativum L.): a review on cultivation, harvesting, and storage for sustainable agriculture.

Peas (Pisum sativum L.) are a cornerstone of sustainable agriculture, yet their potential is limited by fragmented agronomic practices. This review provides an integrated synthesis of advancements across cultivation, mechanized harvesting, and post-harvest storage. Key findings reveal that optimal growth conditions and nanotechnology interventions can significantly enhance abiotic stress tolerance. Mechanized harvesting innovations reduce yield losses by up to 40%, but smallholder adoption and terrain compatibility remain critical challenges. Effective post-harvest strategies, including low-temperature storage and hermetic bags, are crucial for preserving quality. Despite progress, systemic barriers persist. Future research must prioritize interdisciplinary solutions-combining genomics, precision engineering, and farmer training-to unlock the full potential of peas as a keystone crop for sustainable food systems.

climate resilience

Genome editing research initiatives and regulatory landscape of genome edited crops in India.

Food and nutritional security are the top priorities in Indian agriculture. Exponential population growth coupled with climate change effects has become a serious challenge for sustainable agriculture. Genome editing has revolutionized the agricultural sector because of its ability to create precise, stable and predictable modifications in the genome and therefore, offers great opportunities for crop improvement in India. However, for harvesting the real benefits of this technology in agriculture sector, there is a strong need of creating awareness among the end users and development of suitable policies for regularization of genome edited products. Many regulatory agencies around the world have been modernizing their regulatory approaches to be more risk proportionate and to reflect a more science-based approach. In this article, recent research initiatives and developments undertaken by different Indian institutes/organizations for the genetic improvement of agricultural and horticultural crops via genome editing technologies are summarized. Furthermore, to benefit from this potential technology in our country, regulatory policies must be clear, science-based and proportionate. Therefore, in the present review, the regulatory policies related to the genome editing of crop products in India are discussed in detail. This review will sensitize researchers and stakeholders to the application of genome editing techniques in crop improvement and various biosafety committees involved in the development and regulation of genome edited crops.

Crops, Agricultural

The emerging impact of CRISPR and gene editing on global crop improvement.

The advent of CRISPR-based genome editing has revolutionized crop improvement, offering unprecedented precision and efficiency in modifying key agronomic traits. This review comprehensively examines the mechanisms, applications, and future potential of CRISPR technology in enhancing global crop production. CRISPR-Cas systems, originally identified as adaptive immune mechanisms in bacteria and archaea, have been repurposed for targeted genome editing in plants. The CRISPR-Cas9 system, in particular, has emerged as a powerful tool for introducing site-specific double-strand breaks, enabling precise genetic modifications. The three-stage process of adaptation, expression, and interference underlies the CRISPR mechanism, with guide RNAs directing Cas endonucleases to specific genomic loci. Advances in CRISPR technology have expanded its applications beyond gene knockouts, encompassing base editing, prime editing, and epigenome editing. These innovations have facilitated the development of crops with enhanced yield, stress tolerance, disease resistance, nutritional content, and post-harvest quality. However, challenges related to off-target effects, regulatory hurdles, ethical concerns, and public acceptance must be addressed to fully harness the potential of CRISPR in agriculture. Integration of CRISPR with other cutting-edge technologies, such as synthetic biology, artificial intelligence, and high-throughput phenotyping, holds immense promise for accelerating crop improvement efforts. As research continues to refine CRISPR tools and expand their applicability across diverse plant species, this transformative technology is poised to play a pivotal role in shaping a sustainable, resilient, and productive global food system for future generations.

Gene Editing

Zea mays Meiotic Spindle Ultrastructure Reveals Kinetochore-Microtubule Interface and Embedded Membrane Components.

UNLABELLED: Introduction: Spindles are microtubules-based machines whose primary function is to accurately segregate chromosomes in both mitotic and meiotic cell division. The structure of spindles is critical for their function; errors in morphology or attachment to chromosomes lead to aneuploidy, potentially resulting in disease, infertility, and lethality. Electron microscopy studies have yielded fine-detail spindle ultrastructures in many plant and animal species, but no studies have investigated the spindle of Zea mays, a critical crop, and cytogenetic model system. METHODS: Here we use electron tomography (ET), reconstruction, and modeling to obtain three-dimensional, nanometer-resolution of the Z. mays meiotic spindle. Structures such as microtubules, kinetochores, vesicles, membrane channels, and nuclear envelope were modeled through a partial spindle reconstruction, and confirmed using immunostaining and live fluorescence microscopy. RESULTS: ET revealed that maize spindles contain 8-18 kinetochore microtubules (kMTs) per kinetochore, which are approximately 776 nm in diameter and 316 nm in depth. Small ∼37 nm vesicles were identified, as well as larger (∼5 µm long, 800 nm wide) membrane structures with channels that allow spindle microtubules to pass through. These membrane channels stain positively for the ER-marker protein disulfide isomerase. Imaging of prophase meiotic cells revealed a cross-hatch microtubule arrangement in the perinuclear ring on the external surface of the nuclear envelope, which also contained type II nuclear grooves with transnuclear microtubules passing from the nucleus to the cytoplasm. CONCLUSIONS: Z. mays meiotic spindles are similar to animal counterparts with a comparable number of kMTs and pre-spindle transnuclear microtubules but also plant-specific features such as Golgi-derived vesicles to assist cell plate formation, internal ER membrane channels, and a perinuclear microtubule ring that aids spindle assembly. Maize kinetochores have an electron-diffuse ball in cup morphology that is comparable in size to Drosophila kinetochores and larger than mammalian kinetochores. .

Zea mays

Advances in Cytoplasmic Male Sterility in Sugar Beet from Mitochondrial Genome Structural Dynamics and Nuclear-Cytoplasmic Coordination.

Sugar beet (Beta vulgaris L.) is a globally important sugar crop whose hybrid breeding system relies heavily on cytoplasmic male sterility (CMS) lines. Recent advances in sugar beet genomics, particularly the release of high-quality reference genomes and the characterization of organellar genomes, have provided a foundation for elucidating the molecular genetic mechanisms of CMS. Furthermore, innovations in gene editing technologies are enabling transformative functional studies in this field. The precise targeting of CMS-associated mitochondrial genes and nuclear restorer-of-fertility genes not only allows for direct investigation of theoretical models governing fertility regulation through nuclear-cytoplasmic interactions but also holds promise for the targeted development of sterile and restorer lines. This review systematically summarizes progresses in sugar beet genomics, the development of gene editing tools, and the current understanding of the molecular genetics of CMS and fertility restoration in sugar beet. Although challenges remain-such as efficient delivery of editing tools into mitochondria and coordinated editing of multiple genes-the integration of genomic and gene editing technologies is expected to accelerate multi-omics-guided dissection of CMS mechanisms. These advances will facilitate the precise design of high-yield, high-sugar, and stress-resistant sugar beet hybrids, thereby providing core scientific and technological support for the sustainable development of the global sugar industry.

Beta vulgaris