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PubMed2026

Molecular and Physiological Insights into CAT- and SOD-Associated Redox Homeostasis Under Salt Stress in Artemisia argyi.

Soil salinity disrupts redox homeostasis and limits plant growth and development. Although catalase (CAT) and superoxide dismutase (SOD) are key enzymatic antioxidants, the CAT and SOD gene families have not been characterized in Artemisia argyi (A. argyi), a species of medicinal and ecological importance. While SOD and CAT serve as the primary enzymatic scavengers for reactive oxygen species (ROS) detoxification, their genomic architecture and stress-responsive regulatory networks in A. argyi have remained uncharacterized. In this study, we conducted the first comprehensive genome-wide analysis of these gene families in A. argyi, identifying 22 structurally conserved members (8 AarCATs and 14 AarSODs). Collinearity and synteny analyses revealed strict lineage-specific evolutionary conservation, while tertiary protein modeling and subcellular localization illustrated a highly organized multi-organelle defense compartmentalization. High salinity (up to 200 mM NaCl) reduced the stomatal conductance and net photosynthetic rate. Salt stress reduced growth and increased osmoprotectant and antioxidant accumulation in A. argyi. Furthermore, histochemical staining using nitroblue tetrazolium (NBT) and 3,3'-Diaminobenzidine (DAB) provided comprehensive evidence of significant accumulation of ROS in leaves, which indicates the intense oxidative stress triggered by ionic stress. Tissue-specific analysis revealed that AarCAT1, AarCSD1, and AarFSD2 were 3.9-, 7.9-, and 12.7-fold higher in leaves than in roots, respectively. Under stress, AarCAT6 and AarCSD1 were strongly repressed in leaves by ~50% and ~46-70%, respectively, whereas AarMSD2 and AarMSD3 were significantly induced in roots by ~2.2- and ~1.8-fold. These distinct expression patterns suggest their potential involvement in tissue-specific stress adaptation and ROS homeostasis. These findings uncover the evolutionary and physiological basis of salt tolerance in A. argyi, providing genetic targets for climate-resilient breeding.

Artemisia↗

PubMed2026

Whole-genome sequencing reveals divergent and shared selection signatures of heat stress adaptation in indigenous Ethiopian zebu cattle from dry-hot and humid-hot environments.

African zebu cattle (Bos indicus) exhibit remarkable adaptations to extreme thermal conditions, yet the genomic basis of this resilience remains incompletely characterized. Ethiopia provides a unique natural setting in which closely related zebu populations have adapted divergently to dry-hot (DHETZ) and humid-hot (HHETZ) climates. In this study, we reanalyzed publicly available whole-genome sequencing datasets from 46 Ethiopian zebu cattle from five populations and compared them with Asian zebu, Sudanese zebu, African taurine, and European taurine breeds. By integrating genome-wide SNP analysis, population genetic structure assessment, and multiple selection scans (iHS, Hp, XP-EHH, and XP-CLR), we identified distinct and shared selection signatures between DHETZ and HHETZ. We detected 33.7 million and 34.2 million biallelic autosomal SNPs in DHETZ and HHETZ, respectively. Ethiopian zebu clustered closely with Sudanese zebu but showed clear divergence from Asian zebu and taurine breeds. DHETZ and HHETZ exhibited very low genetic differentiation (FST = 0.0063), consistent with their shared ancestry; however, each group displayed unique selection signals. In DHETZ, iHS and Hp detected 298 and 113 candidate regions, respectively, whereas in HHETZ, they detected 244 and 138 regions, respectively. Cross-population XP-EHH and XP-CLR analyses identified 163 and 227 divergent regions between DHETZ and HHETZ, respectively. Integration of the four selection scans identified 19 high-confidence candidate regions in DHETZ and 13 in HHETZ. DHETZ showed strong selection in genes involved in oxidative stress regulation, protein folding, mitochondrial function, and vascular remodeling, including SESN2, DNAJC8, GRPEL2, ABLIM3, and AFAP1L1. In contrast, HHETZ displayed signatures in genes associated with immune responses, energy metabolism, and angiogenesis inhibition, including MYD88, PRKACA, PRKACB, and WIF1. Several genes, including VEGFC, TNIP3, and DMXL2, were under selection in both groups, suggesting conserved mechanisms of thermotolerance and reproductive adaptation. The shared VEGFC signal and the HHETZ-specific WIF1 signal may indicate a distinct vascular regulatory mechanism in the dry-hot and humid-hot environments. Our results reveal a dual pattern of genomic adaptation in Ethiopian zebu cattle and provide candidate loci for future validation and climate-resilient livestock breeding.

Animals↗

PubMed2026

Identification of the BrSK gene family in flowering Chinese cabbage and functional characterization of BrSK2 subfamily involvement in heat stress.

Glycogen synthase kinase 3 (GSK3) kinases are evolutionarily conserved regulators of plant development and stress signaling, yet their contributions to thermotolerance in cool-adapted Brassica crops remain poorly understood. Here, we identified 16 BrSK genes in the Caixin (Brassica rapa ssp. chinensis var. parachinensis) genome, all harboring intact catalytic motifs indicative of functional kinase activity. Spatiotemporal expression profiling revealed preferential accumulation of BrSK transcripts in stem apices and floral organs during reproductive transition, while promoter analysis identified abundant heat- and abiotic stress-responsive cis-elements. Under heat stress, BrSK21, BrSK22, and BrSK23 displayed striking genotype-specific expression dynamics. BrSK21/22/23 transcripts were stably suppressed in the heat-tolerant cultivar '49-19' but transiently declined before rapidly rebounding in the heat-sensitive 'Liuye 50', mirroring RNA-seq profiles. Protein-protein interaction assays (Y2H, BiFC, and LCI) demonstrated specific associations between BrSK kinases and BrHSFA1. Functional validation via VIGS revealed that silencing of BrSK21 significantly enhanced thermotolerance, with triple silencing of BrSK21/22/23 conferring additive protection, indicating functional redundancy within the BrSK2 subfamily. Collectively, these findings establish the BrSK2 subfamily as negative regulators of heat tolerance in Caixin, likely via modulation of BrHSFA1 expression. This work identifies high-priority targets for molecular breeding of climate-resilient Brassica vegetables.

Plant Proteins↗

PubMed2026

Allelic variation in UVR8 modulates thermotolerance-yield tradeoffs in plants.

Industrial activities have driven stratospheric ozone depletion, increasing surface UV-B radiation while exacerbating global warming. These changes limit crop productivity, alter species distributions, and disrupt plant metabolic processes, but the mechanisms linking energy signaling to heat-stress responses remain unclear. Here, we identify the photoreceptor UV RESISTANCE LOCUS 8b (OsUVR8b) as a substrate of SNF1-related protein kinase 1 (SnRK1) in rice and reveal a natural variation at its SnRK1-mediated phosphorylation site (Ser177) that is correlated with adaptation to tropical climates. The thermotolerant OsUVR8bAla177 accessions show geographic enrichment in low-latitude regions with elevated temperatures. Functional validation through prime editing demonstrated that a Ser177-to-Ala177 substitution enhances heat tolerance, whereas the reverse edit compromises it. Mechanistically, OsUVR8bSer177 exhibits reduced stability and an impaired capacity for scavenging reactive oxygen species under heat stress. The regulatory function of the OsUVR8b Ser177 phosphorylation site, a molecular switch that governs UVR8 stability and thermotolerance, can be functionally re-established across rice, Arabidopsis, tobacco, and soybean, indicating its preservation during domestication. Notably, OsUVR8bSer177 maintains higher fertility and yield under non-stress conditions, indicating a tradeoff between heat adaptation and productivity. Our findings thus establish this switch as a key regulator of the yield-resilience balance and a promising target for breeding of climate-resilient crops.

Thermotolerance↗

PubMed2026

Low-pass whole-genome sequencing reveals genomic diversity and ecotype-specific adaptation in indigenous Tigrayan chickens.

Indigenous chickens play a critical role in food security and climate resilience in smallholder systems, yet their genomic diversity and adaptive potential remain insufficiently characterised. This study employed low-pass whole-genome sequencing (LP-WGS; 0.2-1.99×) to investigate genomic diversity, population structure, inbreeding and candidate environment-associated genomic variation in 33 chickens from highland, midland, and lowland agroecologies in the Tigray region of northern Ethiopia. After imputation and stringent filtering, 23.4 million high-confidence SNPs were retained, including ~ 17% novel variants, indicating substantial uncharacterised genetic diversity in these populations. SNP density (13.8 ± 8.6 SNPs/kb) was comparable to values reported from high-coverage Ethiopian chicken datasets, demonstrating the suitability of LP-WGS for population genomics in resource-limited settings. Marked differences in genomic diversity were observed among ecotypes: midland chickens showed the highest nucleotide diversity (π = 0.00267), followed by lowland (π = 0.00233), whereas highland chickens showed the lowest diversity (π = 0.00203) and elevated genomic inbreeding (FROH and FHOM ≈ 0.18). Population structure analyses revealed clear genetic separation among ecotypes. PCA (13.91% variation explained) distinguished lowland chickens along PC1 and separated highland from midland along PC2, while ADMIXTURE and FST patterns supported three major ancestral genomic backgrounds. Functional annotation of private missense variants uncovered distinct adaptive signatures reflecting the contrasting agroecological conditions. Highland chickens showed enrichment of candidate genes potentially involved in physiological processes relevant to high-altitude environments, including cold response, angiogenesis, cardiovascular regulation and metabolic homeostasis (eg., PARP1, ACOX2, ITGB3, EDNRB, SOX8, and SOX10). Midland chickens exhibited candidate signals of selection in genes with known roles in innate antiviral immunity, bacterial defence and inflammatory regulation (eg., BAK1, CLSTN1, CYSLTR1, CYSLTR2, CXCR7, GIPR, DSCAM, GDAP1, TLR3, TLR4, TLR7, IFIH1, ADORA1, EPHB1, and TMPRSS2). Lowland chickens displayed candidate variants associated with heat-stress response, DNA damage repair, oxidative balance and cardiovascular support under extreme temperatures (e.g., MLH1, BDKRB1, GPR19, FLT1, CCL18, TGM2, and RAMP3). Overall, the results indicate substantial genomic differentiation among ecotypes and suggest candidate environment-associated genetic divergence across Tigray's diverse agroecological zones. These populations may represent important reservoirs of adaptive genetic variation for climate-resilient poultry breeding, warranting further functional validation and conservation-oriented management.

Animals↗

PubMed2026

Hormone priming and metabolic engineering of phytohormone crosstalk in rice under combined biotic and abiotic stresses: a multi-omics perspective for climate-resilient crop development.

Rice (Oryza sativa L.) is the caloric backbone for more than half of humanity, yet it remains one of the most vulnerable crops to the simultaneous biotic and abiotic stresses exacerbated by climate change. Phytohormone priming and the complex crosstalk networks governed by transcription factor hubs like WRKY, MYB, and NAC serve as the central adaptive mechanism for stress resilience. This review synthesizes how multi-omics integration, including spatial and single-cell transcriptomics, is resolving the molecular architecture of hormonal priming and epigenetic stress memory. We critically evaluate advanced metabolic engineering and genome-editing strategies such as CRISPR-Cas9, base/prime editing, and synthetic gene circuits that enable precision modifications to decouple stress tolerance from historical yield penalties. Furthermore, we discuss the emerging roles of microbiome-assisted priming via synthetic consortia and the application of artificial intelligence and digital twins (continuously updated computational models of crop physiology) for predictive stress management. By integrating these diverse technological pillars, we propose a systems-level roadmap for developing climate-resilient rice cultivars capable of maintaining yield stability across a volatile combinatorial stress landscape. This synthesis provides a framework for translating mechanistic hormonal insights into field-applicable cultivars to ensure global food security.

CRISPR↗

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

Application of Omics Technologies for Cowpea Improvement.

Cowpea (Vigna unguiculata) is a vital crop for food security, nutrition, and climate resilience in sub-Saharan African and other semi-arid regions. However, its improvement is constrained by the complexity of polygenic traits such as drought tolerance, pest resistance, and seed quality. Conventional breeding, while foundational, remains insufficient to address these challenges at the required pace. Recent advances in multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, provide new opportunities to dissect complex traits, identify candidate genes, and accelerate the development of resilient, high-yielding cultivars. This review presents a critical synthesis of current applications of omics technologies in cowpea improvement, highlighting their contributions to stress adaptation, nutritional enhancement, and precision breeding. The review also examines key technical and institutional constraints limiting the adoption of omics-assisted breeding in cowpea, including inadequate research infrastructure, challenges in multi-omics data integration, and limited technical capacity across breeding programs in sub-Saharan Africa. It discusses strategies to address these barriers through regional collaboration, investment in bioinformatics capacity, and the integration of computational approaches into breeding pipelines. Overall, the review concludes that combining multi-omics technologies with artificial intelligence and machine learning has strong potential to improve genotype-phenotype prediction, accelerate breeding decisions, and support the development of climate-resilient and nutritionally enhanced cowpea cultivars.

cowpea↗

PubMed2026

Translating Flood-Tolerance Biology into Breeding: A 5D Framework for Next-Generation Rice Varieties.

Flooding is among the most devastating abiotic stresses limiting rice productivity. Although SUB1A introgression conferred submergence tolerance in several mega-varieties, this single-gene approach is insufficient for the diverse flood types-flash floods, stagnant floods, anaerobic germination, and deepwater inundation-progressively intensifying with climate change. Here, we review the physiological mechanisms and genetic architecture underlying tolerance to each flood type, emphasizing the dual role of reactive oxygen species (ROS) in signalling and damage, the management of elemental toxicities (Fe2+, Mn2+) under altered soil redox, and lessons from wetland species and lowland rice. We then examine why marker-assisted selection has failed for polygenic, multi-stress tolerance and identify persistent breeding bottlenecks. Building on this biological foundation, we outline an integrated 5D framework (Demand, Discovery, Design, Development, Deployment) that links gene-bank diversity, multi-omics discovery, predictive breeding and on-farm validation through continuous feedback. We discuss how connected breeding, the transition-from-trait-to-environment (TTE) strategy, and speed breeding can accelerate genetic gain, and we close with research priorities centred on the biology of multi-flood tolerance to develop climate-resilient rice.

5D breeding framework↗

PubMed2026

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↗

PubMed2026

Genome-wide variation analysis of two Salvia hispanica L. genotypes and implication for associations with metabolic and adaptive traits.

BACKGROUND: Advances in next-generation sequencing have accelerated genome-wide exploration of genetic diversity in underutilized oilseed crops. Salvia hispanica L. (chia), a high-nutrient pseudocereal rich in omega-3 fatty acids, is increasingly valued for its health benefits and commercial potential, yet it remains poorly characterized at the genomic level. Understanding the scale and nature of genomic variation is essential for improving complex traits such as oil yield, stress tolerance, and seed quality. METHODS: Two contrasting chia genotypes, Black-chia (CACH-B) and White- chia (CACH-W), were resequenced using the Bio-Resequencing Toolkit (BRT) pipeline. High-coverage sequencing, with a mapping rate exceeding 99% and an average depth of approximately 28×, facilitated the detection and annotation of single-nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy-number variations (CNVs), and structural variants (SVs). The functional classification of variant impacts enabled the identification of genes potentially linked to metabolic and adaptive traits. RESULTS: A total of 1.97 million SNPs, 401,493 InDels, 836 CNVs, and 15,288 SVs were identified across the chia genome. Notably, approximately 53% of exonic SNPs were non-synonymous (dN/dS ≈ 1.28), predominantly affecting lipid metabolism, transcriptional regulation, and stress response pathways, potentially altering key agronomic traits. In addition, CNV hotspots were concentrated in chromosomes 3 and 6, overlapping MYB, WRKY, and bZIP transcription factor loci, may potentially be involved in stress tolerance and yield. Furthermore, structural rearrangements, including inversions and duplications within the FAD2, FAD3, and CYP450 gene clusters, were potentially associated with seed pigmentation and omega-3 biosynthesis, pointing to their potential breeding relevance. Observed heterozygosity (Hₒ ≈ 0.71) and nucleotide diversity (π ≈ 7 × 10-3) indicated moderate to high allelic richness. In addition, the low FST value (0.038) indicates substantial genomic similarity between the two genotypes. CONCLUSION: This study presents the first comprehensive map integrating SNPs, CNVs, and SVs in S. hispanica L. The results reveal a structurally dynamic genome characterized by substantial sequence and structural variation, providing valuable insights into genomic diversity and potential adaptive mechanisms in chia. The coexistence of high SNP diversity and abundant structural variation underpins chia's nutritional specialization and environmental resilience. These results deliver a foundational genomic resource for marker-assisted breeding, genome-wide association studies, and the development of climate-resilient chia cultivars.

Copy-number variation, structural variation↗

PubMed2026

Current landscape of Cys-OxiPTMs in plants: from hormone signaling to phenotypic control and their potential in sustainable agriculture.

The integration of environmental and developmental cues into coherent physiological responses is fundamental to plant survival. Reactive oxygen, nitrogen, and sulfur species (ROS/RNS/RSS) are now recognized as essential signaling molecules, not merely cytotoxic byproducts. Their specificity is largely achieved through reversible, site-specific cysteine oxidative post-translational modifications (Cys-OxiPTMs), which constitute a dynamic and sophisticated "redox code". This review provides a systematic synthesis of the current landscape of Cys-OxiPTMs in plants, bridging chemistry, hormone biology, agronomy, detection, and engineering. The chemical and enzymatic basis of major Cys-OxiPTMs is detailed, along with a discussion of how their spatiotemporal interplay orchestrates signaling specificity. A critical examination is then presented on how these modifications decode and integrate plant hormone signaling networks to regulate key agronomic traits. Cutting-edge proteomic technologies that have revolutionized the identification of redox-sensitive cysteines are also evaluated. Finally, forward-looking strategies to "write" the redox code are explored. By moving the field from descriptive cataloging to predictive "redox breeding", this review establishes a foundational framework for manipulating Cys-OxiPTMs to develop climate-resilient, high-yielding crops for sustainable agriculture.

Agronomic traits↗

PubMed2026

Engineering cold stress resilience in capsicum annuum through functional genomics and precision breeding.

This review synthesizes the molecular mechanisms of cold tolerance in pepper, integrating multi-omics data,genome editing, and precision breeding strategies to accelerate the development of cold-resilient cultivars. Cold stress is a significant environmental factor that affects the growth, productivity, and fruit quality of Capsicum annuum by impairing membrane integrity photosynthesis and cellular redox homeostasis. Although pepper has several endogenous cold-responsive regulators such as CaNAC035 and CabHLH035, along with antioxidant defense systems, its cold tolerance remains limited due to low transcriptional activation of key regulators, functional redundancy among cold-responsive genes, and the polygenicity of cold tolerance. These complexities, combined with low genetic diversity and linkage drag, have hindered the improvement of cold-resistant cultivars through conventional breeding. This review brings together the recent progress in understanding the molecular mechanisms of cold stress perception, signal transduction, transcriptional regulation, metabolic reprogramming, and phytohormone interactions in pepper. Precision Breeding 2.0 is a new innovation that combines the integration of multi-omics-based target identification with next-generation genome-editing techniques, allowing precise and multiplex engineering of complex and interconnected regulatory networks instead of single genes. We cover new approaches such as engineering the DREB/CBF pathway, allele-specific editing and targeted disruption of negative regulators to enhance the pathway(s) involved in cold response. Moreover, we propose a roadmap for integration of transcriptomics, proteomics, metabolomics, high-throughput phenomics, and speed breeding to accelerate the identification, validation, and deployment of superior alleles to boost cold tolerance. This review provides a foundation for developing climate-resilient pepper cultivars by connecting functional genomics with precision genome engineering approaches to maintain productivity under variable environmental conditions.

Capsicum↗

PubMed2026

Combining ability and gene action for grain yield and biofortification traits in pearl millet [Pennisetum glaucum (L.) R. Br.]: implications for breeding high-yielding biofortified hybrids in arid regions.

Hybrid RIB-9184 × RIB-15131 combines high yield (18.84 g plant⁻¹) with iron (46.16 mg kg⁻¹), zinc (38.86 mg kg⁻¹), and protein (11.91%); Fe-Zn correlation (rg = 0.82) permits simultaneous biofortification. Pearl millet [Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) Morrone] is a climate-resilient cereal with inherently high micronutrient levels, making it a priority crop for biofortification. Understanding gene action for yield and nutritional traits is essential for designing effective breeding strategies. Ten diverse inbred lines were crossed in a half-diallel design (Griffing's Method 2, Model 1), and the 55 entries (45 F1 hybrids + 10 parents) were evaluated across two sowing-date environments in a randomised complete block design with three replications at Jaipur, Rajasthan, India. Biofortification traits (Fe, Zn, protein) showed predominantly additive gene action (Baker's ratio 0.71-0.91) with high heritability (0.90-0.94). G×E interaction was significant for Fe and Zn but genotypic variance was substantially larger, maintaining high heritability; protein showed no G×E interaction. Grain yield was governed largely by non-additive effects (Baker's ratio 0.54) with significant G×E interaction, favouring hybrid breeding. Among parents, RIB-9205 had the highest GCA for Fe (6.65, P < 0.001), RIB-9184 for Zn (3.85, P < 0.001) and protein (0.78, P < 0.001), and RIB-9185 was a balanced combiner for yield (1.39, P < 0.001) and micronutrients. The hybrid RIB-9184 × RIB-15131 ranked first across all five weighting schemes of the multi-trait performance index (1.31), combining grain yield of 18.84 g plant⁻1 with Fe of 46.16 mg kg⁻1, Zn of 38.86 mg kg⁻1, and protein of 11.91%. The strong Fe-Zn correlation (rg = 0.82, P < 0.01) permits simultaneous micronutrient improvement. An integrated approach combining hybrid development for yield with population improvement for micronutrient density is recommended for biofortified pearl millet cultivars in arid regions.

Pennisetum↗

PubMed2026

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↗

PubMed2026

CRISPR-Cas technologies for precision genome editing in plants: advances, applications, and future perspectives.

Developing climate-smart crops with enhanced crop productivity, nutritional quality, resistance to biological and environmental stressors is vital for global food security. While hybrid breeding forms the cornerstone of modern crop improvement, conventional breeding approaches are limited by genetic barriers and prolonged breeding cycles. CRISPR-Cas based genome editing has revolutionized plant biology by allowing precise, efficient, and multiplex genetic modifications. This review provides a comprehensive synthesis of a recent advances in CRISPR-Cas technologies and their strategic applications in crop genetics and hybrid breeding. We summarize major genome-editing strategies, including gene knock-out, base editing (BE), knock-in, gene replacement, epigenome editing, and transcriptional regulation. Furthermore, we contrast stable, transient, and DNA-free delivery systems, highlighting ribonucleoprotein (RNP)-mediated delivery for minimizing off-target effects and avoiding transgene integration. We showcase how these technologies accelerate hybrid breeding by engineering male sterility systems, fixing heterosis, and generating high-throughput mutant libraries for trait discovery. Finally, we synthesize major bottlenecks in tissue culture-independent transformation and delivery systems, while outlining how emerging paradigms like de novo domestication and synthetic biology will shape the future of climate-resilient agriculture.

CRISPR/Cas↗

PubMed2026

Rhizosphere Dialogue: Microorganisms Mediated by Root Exudates Alleviate Drought Stress in Grasses.

Drought stress threatens the ecological functions and economic value of grasses, posing a major challenge to their sustainable production. Plants co-evolve with rhizosphere microbial communities, sometimes described as the plant's second genome, that can contribute to drought adaptation. Drought alters root architecture, hormonal and redox regulation and belowground carbon allocation, thereby modifying the quantity and composition of root exudation and reshaping the rhizosphere environment. This review uses the rhizosphere dialogue as an integrative framework to link these plant responses with microbial recruitment and subsequent feedback to the host. We summarise three linked stages of this dialogue: drought-induced changes in root exudation; microbial recruitment and colonisation through chemotaxis, attachment, biofilm formation, and root colonisation; and microbiome-mediated feedback that improves plant water relations, hormonal and redox homoeostasis, nutrient acquisition, and root function. We highlight microbial extracellular polymeric substances, 1-aminocyclopropane-1-carboxylate deaminase, and microbial volatile organic compounds as key mediators of drought alleviation. We then discuss how this framework may inform rational synthetic microbial community (SynCom) design, microbiome-informed breeding, artificial intelligence and machine-learning assisted strain prioritisation, rhizosphere legacy effects, and real-time monitoring. Future work should distinguish active exudate-mediated recruitment from drought-driven environmental filtering and integrate multi-omics, plant genetics, functional validation, and multi-location field trials to determine whether rhizosphere dialogue can become a predictive framework for climate-resilient grass production.

drought stress↗

PubMed2026

Seed shattering habit in millets and the secrets of the abscission layer - a comprehensive review.

Though seed shattering continues to be a significant barrier affecting yield stability and harvesting efficiency in millets and other grasses, millets are increasingly acknowledged as climate-resilient, nutrient-rich 2007cereal crops with the potential to strengthen global nutritional and food security under the combined pressures of climate change, population growth, and limited natural resources. Since strong artificial selection favoured non-shattering phenotypes during domestication, seed shattering, an adaptive trait in wild species that promotes seed dispersal through the formation and activation of specialised abscission layers, became a distinguishing feature of cultivated cereals. With a focus on the morphological, physiological, hormonal, and genetic modulation of the abscission zone, this article summarizes the state of the art regarding seed shattering in millets. Abscission layer morphology, location, and lignification vary greatly among grasses, from well-defined lignified zones in rice and sorghum to non-lignified and anatomically subtle zones in Setaria and Panicum species. Cell wall-modifying enzymes like polygalacturonases, cellulases, expansins, and pectin methylesterases that mediate middle lamella degradation are modulated by coordinated hormonal signalling involving auxin, ethylene, and abscisic acid, which controls the timing and progression of cell separation at the physiological level. Domestication-related genes, including SH1, qSH1, SH4, and LES1, demonstrate convergent evolutionary mechanisms controlling abscission layer development in a variety of grass lineages at the molecular level. Understanding these regulatory networks has been greatly enhanced by recent developments in transcriptomics, functional genomics, and genome sequencing in both model species and underused millets. The role of millets as climate-smart cereals for sustainable future agriculture is reinforced by the integration of anatomical, physiological, and genetic insights, which offer a solid basis for targeted breeding and genome-editing strategies intended to improve seed retention, enhance yield stability, and increase harvest efficiency.

Abscission Layer↗