Cotton, the world's most widely cultivated fiber crop, faces increasing challenges from climate change across many production regions. Optimizing cotton production requires aligning cultivar selection, irrigation, and planting dates, yet evidence and decision-support tools are lacking. The study aimed to evaluate the DSSAT-CSMCROPGRO-Cotton to identify promising combinations of cultivars, irrigation regimes, and planting dates for core and non-core cotton growing areas of Pakistan. The model was calibrated and validated using an extensive dataset from twelve (short, medium, and long duration) cultivars and eleven sites across core and non-core cotton growing areas of Pakistan over two seasons. The model was then used to assess cotton production for 30 years on these sites, under three planting dates (25-Apr, 10-May, and 25-May) and four irrigation regimes (30 %, 50 %, 70 %, and 90 % plant available water). Calibration results showed satisfactory model performance for simulating phenology, biomass, and yield across cultivars and sites, with normalized root mean square error remaining below 20 %. Long-term simulations demonstrated superior performance with the highest biomass, yield, harvest index, water use efficiency (WUE), and WUE irrigation (WUE_irri) in core areas. Long-duration cultivars excelled in the harvest index, whereas medium-duration cultivars showed the maximum biomass, yield, WUE, and WUE_irri. 70 % and 90 % irrigation produced similar maximum biomass and yield, and WUE was highest at 50 % irrigation. Planting dates had no significant impact on yield. The findings offer useful insights to guide cotton growers to make informed decisions and improve productivity across Pakistan.

Sustainable crop development aims to maintain or increase yields while reducing environmental impact and managing the challenges imposed by climate change. As the global population grows and arable land becomes scarcer, the integration of molecular breeding with bioinformatics has emerged as an effective strategy for long-term crop improvement. Bioinformatics enables researchers to analyze and interpret the vast quantities of genetic data generated by high-throughput sequencing, making it possible to identify molecular markers, candidate genes, and regulatory networks linked to specific agronomic traits, which breeders then translate into focused, ecologically sustainable breeding programs. This approach has enabled major progress across several fronts: the identification of genes conferring resistance to biotic stressors (pests, pathogens) and abiotic stressors (drought, salinity, heat); the development of nutrient-efficient, low-input crop varieties; the improvement of agronomic performance and nutritional quality through identification of yield- and quality-related genes; and the conservation and deployment of genetic diversity to safeguard long-term breeding sustainability. By combining genomic data with precision breeding techniques, researchers are developing crops that are better adapted to a growing population and a changing climate, positioning the integration of molecular breeding and bioinformatics as a central pillar of future global food security.

Irrigation water quality markedly shapes plant growth and physiological functioning, particularly under integrated biotic and abiotic stresses. This study evaluated the influence of irrigation water types, tap water (TW), domestic wastewater (DWW), Lyari wastewater (LWW), and Malir wastewater (MWW), interacting with wastewater-isolated bioprotectant Trichoderma viride on Abelmoschus esculentus infected with soil-borne pathogens Fusarium oxysporum and Rhizoctonia solani. Morphological traits, together with ITS amplicon sequencing and BLAST analysis, confirmed T. viride (PZ212855). Plants treated with LWW and T. viride showed pronounced enhancements in agronomic and physiological traits, i.e., enhanced plant height (101.25 ± 2.87 cm), fresh biomass (24.04 ± 0.86 g), dry biomass (8.45 ± 0.32 g), leaf number (20.25 ± 0.75), fruit fresh biomass (14.33 ± 0.55 g), chlorophyll a (2.12 ± 0.0 4 mg/g F.wt), chlorophyll b (1.30 ± 0.02 mg/g F.wt), total chlorophyll (3.42 ± 0.02 mg/g F.wt), carotenoids (0.75 ± 0.02 mg/g F.wt), and total soluble proteins (1.66 ± 0.02 mg/g F.wt). These increases corresponded with the greater nutrient content of LWW and DWW, which met FAO irrigation standards. DWW upgraded plant functioning, but its slightly higher arsenic concentration required mitigation using T. viride in the rhizosphere. MWW, exhibiting greater physicochemical loads and higher arsenic, generated oxidative stress, increased H2O2 (2.74 ± 0.01 nm/g F.wt) and MDA (0.97 ± 0.03 nm/g F.wt), and reduced growth. T. viride partially mitigated these effects by regulating antioxidant enzyme activity. Overall, integrating nutrient-rich wastewater with T. viride improved plant growth, yield, and stress resilience under challenging conditions.

Ensuring food security and solving the issues brought on by climate change require breeding and engineering of climate-resilient crops. Despite its contributions to reducing agricultural diseases, genetic engineering has several limitations, including high labor costs, lengthy processing times, and poor productivity. Genome editing has become a potential method to provide notable opportunities to explain complex biological processes, genetically solve the causes of diseases, and improve crops for disease resistance by effectively modifying multiple traits. Genome editing techniques including TALENs, ZFNs, and CRISPR/Cas9 increase agricultural productivity by developing climate-resistant crops and promoting climate-resilient agriculture. Among these approaches, CRISPR/Cas9 shows exceptional efficacy, minimal chance of off-target effects, and improved traits such as drought tolerance and disease resistance. This study explores advanced gene editing techniques for improving disease resistance in crops and developing climate-resilient varieties to reduce food insecurity and hunger. It demonstrates that these techniques have enhanced the nutritional content and resilience of many crops by fighting abiotic and biotic stresses. Future agricultural practices could alter the genes and improve disease-resistant crops by genome editing techniques.

IntroductionNitrogen limitation is a critical abiotic stressor that disrupts the balance between plants and their environment, imposing trade-offs in biomass allocation that threaten crop productivity and food security. While modern breeding programs often focus on improving shoot performance, the genetic mechanisms that coordinate root-shoot responses under nitrogen stress remain poorly understood. This study aimed to dissect the molecular and physiological foundations of nitrogen-driven resilience in wheat, leveraging the genetically diverse Watkins wheat landraces as a source of adaptive alleles.MethodsA total of 308 Watkins wheat landraces were phenotyped under low nitrogen (LN) and normal nitrogen (NN) conditions to assess root-shoot allocation strategies. Genome-wide association studies (GWAS) were conducted to identify candidate genes governing nitrogen-responsive traits. Functional annotation and transcriptomic validation were used to elucidate gene networks, and haplotype mapping was employed to link allelic variation to geographic adaptation. Multivariate analysis was performed to classify biomass allocation strategies among the landraces.ResultsPhenotypic analysis revealed stark differences in root-shoot allocation strategies under LN and NN conditions. GWAS identified 130 candidate genes, including root-specific RALF33 and shoot-prioritizing TaNAR1, involved in nitrogen-responsive traits. Functional studies highlighted antagonistic gene networks, such as TAF6 and TaAPY6, balancing root meristem activity and stress adaptation. Adaptive alleles of RALF33 in European landraces optimized root proliferation under LN, while Eurasian landraces exhibited shoot-root coordination under NN through TaNAR1 variants. Multivariate analysis classified landraces into four distinct biomass allocation strategies, identifying elite genotypes resilient to nitrogen limitation.DiscussionBy integrating genomics, phenomics, and haplotype mapping, this study connects molecular mechanisms underlying nutrient stress with ecophysiological adaptation. Key genes, such as RALF33 and TaAPY6, emerged as actionable targets for marker-assisted breeding to develop nitrogen-efficient wheat varieties. These findings highlight the potential of evolutionary-informed genetics in the Watkins landraces to enhance stress resilience, providing a roadmap for sustainable crop design in the context of global nutrient scarcity.

Historical landrace collections, such as the Watkins Wheat Collection, harbor immense genetic diversity that holds the potential to transform our understanding of crop resilience and adaptation. This study employs a novel integrative phenotyping approach to dissect regional adaptation and nitrogen stress resilience in Watkins wheat landraces under contrasting nitrogen regimes. By leveraging a multidimensional framework, including stress indices, geographic analyses, and multivariate clustering, this work identifies 48 landraces with contrasting responses to nitrogen limitation. High-performing genotypes, such as WATDE0013 and WATDE0020, exhibited superior biomass partitioning under stress, reflecting historical adaptation to low-input agroecosystems spanning Europe, Asia, and North Africa. These findings emphasize the value of phenotypic plasticity in nitrogen use efficiency (NUE) improvement. In contrast, low-performing accessions, such as WATDE1055, highlighted vulnerabilities to nitrogen limitation, illustrating the importance of comprehensive phenotypic screening for gene-bank prioritization. Regional adaptation patterns, elucidated through geographic analyses, uncovered stress-resilient genotypes clustered in historically marginal agricultural regions, revealing adaptive traits shaped by environmental selection pressures. Principal component analysis (PCA) and hierarchical clustering delineated five distinct phenotypic groups, enhancing our understanding of evolutionary trajectories within this collection. This integrative approach transcends traditional phenotyping methods by linking phenotype, genotype, and geographic context to uncover nuanced adaptive traits. By bridging gene bank conservation with a systems-level understanding of crop evolution, this study provides actionable insights and a robust framework for breeding climate-resilient wheat varieties. These findings underscore the critical role of preserving genetic diversity in landraces to address global challenges in nitrogen stress and climate resilience.

The challenge of feeding the world's growing population is impaired by declining arable land, water quality and erratic weather patterns due to climate change. Abiotic stresses such as drought, heat, salinity and cold disrupt plant growth, reducing crop yields and quality. Modern biotechnological tools including high‐throughput sequencing and bioinformatics have enabled the characterization of plant stress responses through advanced “omics” technologies. Genomics, transcriptomics, proteomics, metabolomics and epigenomics describe molecular mechanisms underlying plant stress tolerance. Integrating multi‐omics approaches provides a deeper understanding of these mechanisms, addressing the limitations of single‐omics studies. The combination of multi‐omics data (genomics, transcriptomics, proteomics and metabolomics) identifies important biomarkers, regulatory networks and genetic targets that enhance plant stress resilience. This multi‐omics information regarding plants is crucial for genome‐assisted breeding (GAB) to improve crop traits and the development of climate‐resilient crops to withstand environmental challenges. Therefore, researchers use multi‐omics pipelines to enhance productive crops, quality and stress tolerance, solving global food security challenges caused by climate change and environmental stressors. This review discusses the role of omics technologies in describing the genetic mechanisms of plant stress responses and explores how this information is applied to enhance crop resilience and productivity, which leads to improved crops. The application of combining omics approaches to develop next‐generation crops that are capable of thriving under adverse environmental conditions, ensuring reliable and safe food supply for the future under stress conditions.

Plants, as sessile organisms, rely on sophisticated gene regulatory networks (GRNs) to adapt to dynamic environmental conditions. Among the central components of these networks are the interconnected pathways of light signaling and circadian rhythms, which together optimize growth, development, and stress resilience. While light and circadian pathways have been extensively investigated independently, their integrative coordination in mediating climate change adaptation responses remains a critical knowledge gap. Light perception via photoreceptors initiates transcriptional reprogramming, while the circadian clock generates endogenous rhythms that anticipate daily and seasonal changes. This review explores the molecular integration of light and circadian signaling, emphasizing how their crosstalk fine-tunes GRNs to balance resource allocation, photomorphogenesis, and stress adaptation. We highlight recent advances in systems biology tools, e.g., single-cell omics, CRISPR screens that unravel spatiotemporal regulation of shared hubs like phytochrome-interacting factors (PIFs), ELONGATED HYPOCOTYL 5 (HY5), and CIRCADIAN CLOCK ASSOCIATED 1 (CCA1). Here, we synthesize mechanistic insights across model and crop species to bridge fundamental molecular crosstalk with actionable strategies for enhancing cropresilience. Moreover, we have tried to discuss agricultural implications in engineering light–clock interactions for the enhancement in crop productivity under climate change scenarios. Through synthesizing mechanistic insights and translational applications, this work will help underscore the potential for manipulating light–circadian networks to promote sustainability in agriculture.

Soil salinity is a growing global concern, necessitating the development of salt-tolerant cotton cultivars to enhance the utilization of salt-affected soils and boost crop productivity. Salt tolerance is regulated by a complex interplay of genetic and physiological factors involving multiple genes. To investigate the genetic basis of salt stress tolerance, eight parental genotypes (four lines and four testers) and their 16 hybrid combinations were evaluated under normal and salt stress conditions (15 dS m-1). Data were collected on various traits including the plant height (PH), number of bolls per plant (NBP), boll weight (BW), lint percentage (LP), seed cotton yield (SCY), fiber length (FL), fiber strength (FS), fiber fineness (FF), chlorophyll a and b, carotenoids (CAR), total soluble proteins (TSP), hydrogen peroxide (H2O2), catalase (CAT), peroxidase (POD), superoxide dismutase (SOD), potassium ions (K+), sodium ions (Na+), and K+ to Na+ ratio (K+/Na+). The box plot analysis indicated that the median values of the morphological and fiber traits were reduced under salt stress, with the exception of the FF and Na+, which increased. Antioxidant molecule levels were significantly elevated against salt stress, while the ionic and physiological traits decreased. The line x tester analysis revealed significant genetic variation among the genotypes for all the traits, with the testers contributing more to the variation than the lines and their interactions. Nonadditive gene action predominated for most of the morphological, physiochemical, and ionic traits, as indicated by the higher specific combining ability (SCA) effects compared to the general combining ability(GCA) effects under both conditions. Notably, the genotypes, Barani-333 and JSQ-White Hold, were identified as good general combiners. Cross combinations FBG-222 x Barani-222, Hatf-3 x CCB-17, and CCB-22 x JSQ-White Hold, exhibited desirable SCA effects and superior parent heterosis for most of the traits under both conditions. The identified parents and cross combinations showed potential for breeding programs aimed at developing salt-tolerant cultivars.

Creating salt-tolerant genotypes is crucial for maximizing the productivity under salinized land. To evaluate genetic diversity for salt tolerance, 35 diverse cotton accessions were screened under 17 dS m-1 salt stress conditions using 20 agronomic and physiological traits relevant to salt tolerance. The general linear model analysis indicated significant salinity impacts across the studied accessions, and genotype x treatment effects were also significant for all parameters examined. Among all 35 studied accessions; the genotypes CCB-1, CCB-2, CCB-28, CCB-3, CCB-4, Ghauri-1, JSQ-70, and JSQ-71 showed considerably higher performance for plant height, boll per plant, boll weight, lint percentage, seed cotton yield and fiber quality traits under salt stress. Physiological traits, chlorophyll and carotenoid contents, total soluble proteins, K+, and K+/Na+ were reduced under saline conditions, while biochemical traits such as catalase, superoxide dismutase, peroxidase, H2O2 and MDA level increased. The genotypes CCB-17, CCB-18, CCB-19, CCB-20, CCB-21, CCB-22, Hatf-3, Badar-1, Eagle-2, Eagle-4, CCB-23, CCB-24, CCB-25, CCB-26 and CCB-28 exhibited lower values for agro-physiological and fiber quality character respectively, signifying their sensitivity to salt stress. Under salinity, these genotypes showed reduced antioxidant levels and increased values for K+/Na+, Na+, H2O2, and MDA contents. Whereas the genotypes CCB-5, CCB-6, CCB-7, CCB-8, CCB-9, CCB-10, CCB-11, CCB-12, CCB-13, CCB-14, CCB-15, and CCB-16 demonstrated moderate performance for these traits under salt stress conditions respectively. Utilizing multivariate analysis techniques (cluster and PCA), 35 genotypes have been categorized into three groups based on studied traits: tolerant (cluster-1), moderately tolerant (cluster-2), and susceptible (cluster-3) under saline conditions.

Plant phenotype assessment approaches have facilitated crop improvement in recent years by providing opportunities for the dissection of complex nature quantitative traits. Fiber quality and yield are significant economic traits with a complex nature mainly due to interactions between its genetic architecture and the surrounding environment. These economic traits showed stagnant performance in recent decades due to eroded genetic diversity via the selection process. It necessitates exploiting conserved germplasm resources to rebuild genetic diversity within cotton cultivars. Compared to the conventional univariate selection methods using a single trait at a time, the multivariate analysis extends its selection to multiple variables for the selection of genotypes. In evaluating a core collection of cotton over two years using various phenotyping methods, multivariate analysis, particularly principal component analysis (PCA), was employed to assess genetic diversity. The PCA analysis demonstrated substantial variability of 39.83% and 45.37% across two years, highlighting a significant impact on yield and fiber quality attributes. The cumulative eigenvalues of principal components exceeding 80% supported the classification of accessions into six distinct groups based on their trait variability. Both PCA and cluster analysis successfully categorized accessions into six groups, indicating high diversity and suggesting their potential utility in breeding programs. The diverse genotypes identified in this study would be potential resources for variety development and accelerated breeding programs, particularly focusing on stress resilience under climate change scenarios. By utilizing these diverse genotypes, there is an opportunity to enhance breeding strategies and accelerate the development of improved cotton varieties with enhanced yield and fiber quality attributes. The significance of our study lies in its demonstration of the importance of genetic diversity in improving yield and fiber quality attributes, thus underscoring its relevance to cotton breeding programs.

CPSF30, a key polyadenylation factor, also serves as an m6A reader, playing a crucial role in determining RNA fate post-transcription. While its homologs mammals are known to be vital for viral replication and immune evasion, the full scope of CPSF30 in plant, particular in viral regulation, remains less explored. Our study demonstrates that CPSF30 significantly facilitates the infection of turnip mosaic virus (TuMV) in Arabidopsis thaliana, as evidenced by infection experiments on the engineered cpsf30 mutant. Among the two isoforms, CPSF30-L, which were characterized with m6A binding activity, emerged as the primary isoform responding to TuMV infection. Analysis of m6A components revealed potential involvement of the m6A machinery in regulating TuMV infection. In contrast, CPSF30-S exhibited distinct subcellular localization, coalescing with P-body markers (AtDCP1 and AtDCP2) in cytoplasmic granules, suggesting divergent regulatory mechanisms between the isoforms. Furthermore, comprehensive mRNA-Seq and miRNA-Seq analysis of Col-0 and cpsf30 mutants revealed global transcriptional reprogramming, highlighting CPSF30’s role in selectively modulating gene expression during TuMV infection. In conclusion, this research underscores CPSF30’s critical role in the TuMV lifecycle and sets the stage for further exploration of its function in plant viral regulation.

Cotton fiber quality is a persistent concern that determines planting benefits and the quality of finished textile products. However, the limitations of measurement instruments have hindered the accurate evaluation of some important fiber characteristics such as fiber maturity, fineness, and neps, which in turn has impeded the genetic improvement and industrial utilization of cotton fiber. Here, 12 single fiber quality traits were measured using Advanced Fiber Information System (AFIS) equipment among 383 accessions of upland cotton (Gossypium hirsutum L.). In addition, eight conventional fiber quality traits were assessed by the High Volume Instrument (HVI) System. Genome-wide association study (GWAS), linkage disequilibrium (LD) block genotyping and functional identification were conducted sequentially to uncover the associated elite loci and candidate genes of fiber quality traits. As a result, the previously reported pleiotropic locus FL_D11 regulating fiber length-related traits was identified in this study. More importantly, three novel pleiotropic loci (FM_A03, FF_A05, and FN_A07) regulating fiber maturity, fineness and neps, respectively, were detected based on AFIS traits. Numerous highly promising candidate genes were screened out by integrating RNA-seq and qRT-PCR analyses, including the reported GhKRP6 for fiber length, the newly identified GhMAP8 for maturity and GhDFR for fineness. The origin and evolutionary analysis of pleiotropic loci indicated that the selection pressure on FL_D11, FM_A03 and FF_A05 increased as the breeding period approached the present and the origins of FM_A03 and FF_A05 were traced back to cotton landraces. These findings reveal the genetic basis underlying fiber quality and provide insight into the genetic improvement and textile utilization of fiber in G. hirsutum.

The increased land salinization threatens land productivity, food security, and economic losses. The study used a comprehensive set of morpho-physiological, biochemical, and fiber quality parameters to examine the genetic variability of 24 cotton genotypes against 15 dSm-1 salt stress. The general linear model (GLM) effect revealed significant effects of salinity for studied accessions except for lint percentage and fiber strength. The genotype × treatment effects were also significant for all studied traits, while non-significant effects were observed for seed number per boll (SNB), potassium to sodium ratio (K+/Na+), K+, peroxidase (POD), and catalase (CAT). A notable reduction for all traits was observed except for fiber fineness, superoxide (SOD), CAT, POD, carotenoid contents, and hydrogen peroxide (H2O2), which were increased under saline conditions. Based on multivariate analyses, hybrids viz. MS-71× KAHKASHAN, followed by MS-71× CRS-2007 and NS-131× CRS-2007, performed well under both normal stressed conditions. Moreover, biochemical and agronomical traits in PCA validate that the MS-71× KAHKASHAN is the most desirable genotype under both conditions. Better hybrid performance under normal and 15 dSm-1 salt stress conditions supports the hybrid adaptability under salinity stress environments. The outcome would assist breeders in developing salt-tolerant cotton varieties under climate change scenarios.

The boll weight (BW) is the most decisive yield component character and is utilized as a key index for selection in various cotton improvement programs. In the current study, 1260 accessions of cotton with a diverse genetic background were assessed for boll weight across four different environments (two locations for each environment) in China. A genome-wide association study (GWAS) was performed to mine novel single nucleotide polymorphisms (SNPs) controlling boll weight characteristics. A total of 1,122,352 SNPs were identified in association with boll weight across multiple environments, of which 138 were designated as key SNPs, harboring significantly higher association peaks for the all chromosomes on the basis of log10 P value (− log10 ≥ 6). Among 53 significant associations related to BW development across environments were identified. Six genes in the vicinity of these key SNPs (Pentatricopeptide repeat-containing protein PCMP-E76 ) , Trihelix transcription factor ASIL2, Auxin-responsive protein SAUR50, Floral homeotic protein AGAMOUS ( AG ) , Piriformospora indica-insensitive protein 2 ( PII-2 ) , and LOB domain-containing protein 16 ( LBD16 ) exhibited higher expression patterns. These identified BW-related key SNPs and candidate genes could prove to have potential for influencing BW development in upland cotton. The outcome of the current study will serve as a base for further mechanistic research focused on the exploitation of BW for accelerated cotton improvement.

Priming-mediated stress tolerance in plants stimulates defense mechanisms and enables plants to cope with future stresses. Seed priming has been proven effective for tolerance against abiotic stresses; however, underlying genetic mechanisms are still unknown. We aimed to assess upland cotton genotypes and their transcriptional behaviors under salt priming and successive induced salt stress. We pre-selected 16 genotypes based on previous studies and performed morpho-physiological characterization, from which we selected three genotypes, representing different tolerance levels, for transcriptomic analysis. We subjected these genotypes to four different treatments: salt priming (P0), salt priming with salinity dose at 3-true-leaf stage (PD), salinity dose at 3-true-leaf stage without salt priming (0D), and control (CK). Although the three genotypes displayed distinct expression patterns, we identified common differentially expressed genes (DEGs) under PD enriched in pathways related to transferase activity, terpene synthase activity, lipid biosynthesis, and regulation of acquired resistance, indicating the beneficial role of salt priming in enhancing salt stress resistance. Moreover, the number of unique DEGs associated with G. hirsutum purpurascens was significantly higher compared to other genotypes. Coexpression network analysis identified 16 hub genes involved in cell wall biogenesis, glucan metabolic processes, and ribosomal RNA binding. Functional characterization of XTH6 (XYLOGLUCAN ENDOTRANSGLUCOSYLASE/HYDROLASE) using virus-induced gene silencing revealed that suppressing its expression improves plant growth under salt stress. Overall, findings provide insights into the regulation of candidate genes in response to salt stress and the beneficial effects of salt priming on enhancing defense responses in upland cotton.

While genetically modified (GM) crops bring economic benefits to human beings, their impact on non-target organisms has become an important part of environmental safety assessments. Symbiotic bacteria play an important role in eukaryotic biological functions and can adjust host communities to adapt to new environments. Therefore, this study examined the effects of Cry1B protein on the growth and development of non-target natural enemies of Pardosa astrigera (L. Koch) from the perspective of symbiotic bacteria. Cry1B protein had no significant effect on the health indicators of P. astrigera (adults and 2nd instar spiderlings). 16S rRNA sequencing results revealed that Cry1B protein did not change the symbiotic bacteria species composition of P. astrigera, but did reduce the number of OTU and species diversity. In 2nd instar spiderlings, neither the dominant phylum (Proteobacteria) nor the dominant genus (Acinetobacter) changed, but the relative abundance of Corynebacterium-1 decreased significantly; in adult spiders, the dominant bacteria genera of females and males were different. The dominant bacterial genera were Brevibacterium in females and Corynebacterium-1 in males, but Corynebacterium-1 was the dominant bacteria in both females and males feeding on Cry1B. The relative abundance of Wolbachia also increased significantly. In addition, bacteria in other genera varied significantly by sex. KEGG results showed that Cry1B protein only altered the significant enrichment of metabolic pathways in female spiders. In conclusion, the effects of Cry1B protein on symbiotic bacteria vary by growth and development stage and sex.

Background The cotton crop is universally considered as protein and edible oil source besides the major contributor of natural fiber and is grown in tropical and subtropical regions around the world Unpredicted environmental stresses are becoming significant threats to sustainable cotton production, ultimately leading to a substantial irreversible economic loss. Mitogen-activated protein kinase (MAPK) is generally considered essential for recognizing environmental stresses through phosphorylating downstream signal pathways and plays a vital role in numerous biological processes. Results We have identified 74 MAPK genes across cotton, 41 from G. hirsutum , 19 from G. raimondii, whereas 14 have been identified from G. arboreum . The MAPK gene-proteins have been further studied to determine their physicochemical characteristics and other essential features. In this perspective, characterization, phylogenetic relationship, chromosomal mapping, gene motif, cis -regulatory element, and subcellular localization were carried out. Based on phylogenetic analysis, the MAPK family in cotton is usually categorized as A, B, C, D, and E clade. According to the results of the phylogenic relationship, cotton has more MAPKS genes in Clade A than Clade B . The cis -elements identified were classified into five groups (hormone responsiveness, light responsiveness, stress responsiveness, cellular development, and binding site). The prevalence of such elements across the promoter region of these genes signifies their role in the growth and development of plants. Seven GHMAPK genes ( GH_A07G1527, GH_D02G1138, GH_D03G0121, GH_D03G1517, GH_D05G1003, GH_D11G0040, and GH_D12G2528) were selected, and specific tissue expression and profiling were performed across drought and salt stresses. Results expressed that six genes were upregulated under drought treatment except for GH_D11G0040 which is downregulated. Whereas all the seven genes have been upregulated at various hours of salt stress treatment. Conclusions RNA sequence and qPCR results showed that genes as differentially expressed across both vegetative and reproductive plant parts. Similarly, the qPCR analysis showed that six genes had been upregulated substantially through drought treatment while all the seven genes were upregulated across salt treatments. The results of this study showed that cotton GHMPK3 genes play an important role in improving cotton resistance to drought and salt stresses. MAPKs are thought to play a significant regulatory function in plants' responses to abiotic stresses according to various studies. MAPKs' involvement in abiotic stress signaling and innovation is a key goal for crop species research, especially in crop breeding.

The ever-changing global environment currently includes an increasing ambient temperature that can be a devastating stress for organisms. Plants, being sessile, are adversely affected by heat stress in their physiology, development, growth, and ultimately yield. Since little is known about the response of biochemical traits to high-temperature ambiance, we evaluated eight parental lines (five lines and three testers) and their 15 F 1 hybrids under normal and high-temperature stress to assess the impact of these conditions over 2 consecutive years. The research was performed under a triplicate randomized complete block design including a split-plot arrangement. Data were recorded for agronomic, biochemical, and fiber quality traits. Mean values of agronomic traits were significantly reduced under heat stress conditions, while hydrogen peroxide, peroxidase, total soluble protein, superoxide dismutase, catalase (CAT), carotenoids, and fiber strength displayed higher mean values under heat stress conditions. Under both conditions, high genetic advance and high heritability were observed for seed cotton yield (SCY), CAT, micronaire value, plant height, and chlorophyll-a and b content, indicating that an additive type of gene action controls these traits under both the conditions. For more insights into variation, Pearson correlation analysis and principal component analysis (PCA) were performed. Significant positive associations were observed among agronomic, biochemical, and fiber quality-related traits. The multivariate analyses involving hierarchical clustering and PCA classified the 23 experimental genotypes into four groups under normal and high-temperature stress conditions. Under both conditions, the F 1 hybrid genotype FB-SHAHEEN × JSQ WHITE GOLD followed by Ghuari-1, CCRI-24, Eagle-2 × FB-Falcon, Ghuari-1 × JSQ White Gold, and Eagle-2 exhibited better performance in response to high-temperature stress regarding the agronomic and fiber quality-related traits. The mentioned genotypes could be utilized in future cotton breeding programs to enhance heat tolerance and improve cotton yield and productivity through resistance to environmental stressors.