66 research outputs found

    Exploring the nano-wonders: unveiling the role of Nanoparticles in enhancing salinity and drought tolerance in plants

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    Plants experience diverse abiotic stresses, encompassing low or high temperature, drought, water logging and salinity. The challenge of maintaining worldwide crop cultivation and food sustenance becomes particularly serious due to drought and salinity stress. Sustainable agriculture has significant promise with the use of nano-biotechnology. Nanoparticles (NPs) have evolved into remarkable assets to improve agricultural productivity under the robust climate alteration and increasing drought and salinity stress severity. Drought and salinity stress adversely impact plant development, and physiological and metabolic pathways, leading to disturbances in cell membranes, antioxidant activities, photosynthetic system, and nutrient uptake. NPs protect the membrane and photosynthetic apparatus, enhance photosynthetic efficiency, optimize hormone and phenolic levels, boost nutrient intake and antioxidant activities, and regulate gene expression, thereby strengthening plant’s resilience to drought and salinity stress. In this paper, we explored the classification of NPs and their biological effects, nanoparticle absorption, plant toxicity, the relationship between NPs and genetic engineering, their molecular pathways, impact of NPs in salinity and drought stress tolerance because the effects of NPs vary with size, shape, structure, and concentration. We emphasized several areas of research that need to be addressed in future investigations. This comprehensive review will be a valuable resource for upcoming researchers who wish to embrace nanotechnology as an environmentally friendly approach for enhancing drought and salinity tolerance

    iTRAQ-Based Comparative Proteomic Analysis of Seedling Leaves of Two Upland Cotton Genotypes Differing in Salt Tolerance

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    Cotton yields are greatly reduced under high salinity stress conditions, although cotton is considered a moderately salt-tolerant crop. Understanding at the molecular level how cotton responds to salt stress will help in developing salt tolerant varieties. Here, we combined physiological analysis with isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics of seedling leaves of 2 genotypes differing in salinity tolerance to 200 mM (18.3 dS/m) NaCl stress. Salt stress produced significant stress symptoms in the sensitive genotype Nan Dan Ba Di Da Hua (N), including lower relative water and chlorophyll contents and higher relative electrolyte leakage and Na+/K+ ratio in leaf samples, compared with those in the tolerant genotype Earlistaple 7 (Z). A total of 58 differentially abundant salt-responsive proteins were identified. Asp-Glu-Ala-Asp (DEAD)-box ATP-dependent RNA helicase 3 and protochlorophyllide reductase were markedly suppressed after salt treatment, whereas the phosphate-related differentially abundant proteins (DAPs) phosphoethanolamine N-methyltransferase 1 and 14-3-3-like protein E were induced, and all these proteins may play significant roles in salt stress. Twenty-nine salt-responsive proteins were also genotype specific, and 62.1 and 27.6% of these were related to chloroplast and defense responses, respectively. Based on the Arabidopsis thaliana protein interaction database, orthologs of 25 proteins showed interactions in Arabidopsis, and among these, a calmodulin protein was predicted to have 212 functional partners. In addition, the Golgi apparatus and calcium may be important for salt secretion in cotton. Through integrative proteome and transcriptome analysis, 16 DAPs were matched to differentially expressed genes and verified using qRT-PCR. On the basis of these findings, we proposed that some proteins related to chloroplast, ATP, ribosomal, and phosphate metabolism as well as to the Golgi apparatus and calcium may play key roles in the short-term salt stress response of cotton seedling leaves

    Association Analysis of Salt Tolerance in Asiatic cotton (<em>Gossypium arboretum</em>) with SNP Markers

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    Salinity is not only a major environmental factor which limits plant growth and productivity, but it has also become a worldwide problem. However, little is known about the genetic basis underlying salt tolerance in cotton. This study was carried out to identify marker-trait association signals of seven salt-tolerance-related traits and one salt tolerance index using association analysis for 215 accessions of Asiatic cotton. According to a comprehensive index of salt tolerance (CIST), 215 accessions were mainly categorized into four groups, and 11 accessions with high salinity tolerance were selected for breeding. Genome-wide association studies (GWAS) revealed nine SNP rich regions significantly associated with relative fresh weight (RFW), relative stem length (RSL), relative water content (RWC) and CIST. The nine SNP rich regions analysis revealed 143 polymorphisms that distributed 40 candidate genes and significantly associated with salt tolerance. Notably, two SNP rich regions on chromosome 7 were found to be significantly associated with two salinity related traits, RFW and RSL, by the threshold of −log10P ≥ 6.0, and two candidate genes (Cotton_A_37775 and Cotton_A_35901) related to two key SNPs (Ca7_33607751 and Ca7_77004962) were possibly associated with salt tolerance in G. arboreum. These can provide fundamental information which will be useful for future molecular breeding of cotton, in order to release novel salt tolerant cultivars

    A Genome-Wide Association Study Revealed Key SNPs/Genes Associated With Salinity Stress Tolerance In Upland Cotton

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    Millions of hectares of land are too saline to produce economically valuable crop yields. Salt tolerance in cotton is an imperative approach for improvement in response to ever-increasing soil salinization. Little is known about the genetic basis of salt tolerance in cotton at the seedling stage. To address this issue, a genome-wide association study (GWAS) was conducted on a core collection of a genetically diverse population of upland cotton (Gossypium hirsutum L.) comprising of 419 accessions, representing various geographic origins, including China, USA, Pakistan, the former Soviet Union, Chad, Australia, Brazil, Mexico, Sudan, and Uganda. Phenotypic evaluation of 7 traits under control (0 mM) and treatment (150 mM) NaCl conditions depicted the presence of broad natural variation in the studied population. The association study was carried out with the efficient mixed-model association eXpedited software package. A total of 17,264 single-nucleotide polymorphisms (SNPs) associated with different salinity stress tolerance related traits were found. Twenty-three candidate SNPs related to salinity stress-related traits were selected. Final key SNPs were selected based on the r2 value with nearby SNPs in a linkage disequilibrium (LD) block. Twenty putative candidate genes surrounding SNPs, A10_95330133 and D10_61258588, associated with leaf relative water content, RWC_150, and leaf fresh weight, FW_150, were identified, respectively. We further validated the expression patterns of twelve candidate genes with qRT-PCR, which revealed different expression levels in salt-tolerant and salt-sensitive genotypes. The results of our GWAS provide useful knowledge about the genetic control of salt tolerance at the seedling stage, which could assist in elucidating the genetic and molecular mechanisms of salinity stress tolerance in cotton plants

    Integration of proteomic and transcriptomic profiles reveals multiple levels of genetic regulation of salt tolerance in cotton

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    Abstract Background Salinity is a major abiotic stress that limits upland cotton growth and reduces fibre production worldwide. To reveal genetic regulation via transcript and protein levels after salt stress, we comprehensively analysed the global changes in mRNA, miRNA, and protein profiles in response to salt stress in two contrasting salt-tolerant cotton genotypes. Results In the current study, proteomic and mRNA-seq data were combined to reveal that some genes are differentially expressed at both the proteomic and mRNA levels. However, we observed no significant change in mRNA corresponding to most of the strongly differentially abundant proteins. This finding may have resulted from global changes in alternative splicing events and miRNA levels under salt stress conditions. Evidence was provided indicating that several salt stress-responsive proteins can alter miRNAs and modulate alternative splicing events in upland cotton. The results of the stringent screening of the mRNA-seq and proteomic data between the salt-tolerant and salt-sensitive genotypes identified 63 and 85 candidate genes/proteins related to salt tolerance after 4 and 24 h of salt stress, respectively, between the tolerant and sensitive genotype. Finally, we predicted an interaction network comprising 158 genes/proteins and then discovered that two main clusters in the network were composed of ATP synthase (CotAD_74681) and cytochrome oxidase (CotAD_46197) in mitochondria. The results revealed that mitochondria, as important organelles involved in energy metabolism, play an essential role in the synthesis of resistance proteins during the process of salt exposure. Conclusion We provided a plausible schematic for the systematic salt tolerance model; this schematic reveals multiple levels of gene regulation in response to salt stress in cotton and provides a list of salt tolerance-related genes/proteins. The information here will facilitate candidate gene discovery and molecular marker development for salt tolerance breeding in cotton

    The Negative Correlation between Fiber Color and Quality Traits Revealed by QTL Analysis.

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    Naturally existing colored cotton was far from perfection due to having genetic factors for lower yield, poor fiber quality and monotonous color. These factors posed a challenge to colored cotton breeding and innovation. To identify novel quantitative trait loci (QTL) for fiber color along with understanding of correlation between fiber color and quality in colored cotton, a RIL and two F2 populations were generated from crosses among Zong128 (Brown fiber cotton) and two white fiber cotton lines which were then analyzed in four environments. Two stable and major QTLs (qLC-7-1, qFC-7-1) for fiber lint and fuzz color were detected accounting for 16.01%-59.85% of the phenotypic variation across multiple generations and environments. Meanwhile, some minor QTLs were also identified on chromosomes 5, 14, 21 and 24 providing low phenotypic variation (<5%) from only F2 populations, not from the RILs population. Especially, a multiple-effect locus for fiber color and quality has been detected between flanking markers NAU1043 and NAU3654 on chromosome 7 (A genome) over multiple environments. Of which, qLC-7-1, qFC-7-1 were responsible for positive effects and improved fiber color in offsprings. Meanwhile, the QTLs (qFL-7-1, qFU-7-1, qFF-7-1, qFE-7-1, and qFS-7-1) for fiber quality had negative effects and explained 2.19%-8.78% of the phenotypic variation. This multiple-effect locus for fiber color and quality may reveal the negative correlation between the two types of above traits, so paving the way towards cotton genetic improvement

    Genotype × Environment Interaction Analysis for Yield Stability of Hybrid Cotton Across Production Environments Through Multiple Biometrical Tools

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    The expected gains in the productivity and sustainability of cotton cultivars across environmental spectra may face many challenges. To address this issue, a set of 572 cotton accessions, including 284 F1 hybrids along with their parental lines and checks, were evaluated and compared across multiple test environments. Popular biometrical tools viz; best linear unbiased prediction (BLUP), additive main effects and multiplicative interaction (AMMI) and genotype main effects and genotype × environment interaction effects (GGE) were utilized for reliable estimation graphical depiction of GEI effects. The first two interaction coordinates as principal components in BLUP, AMMI, and GGE biplots explained the maximum proportion of GEI regarding seed cotton yield. The contrasting environments did not cluster together, thus revealing their varying influences on the genotypes. A set of 44 F1 hybrids featuring higher stability, 46 with higher adaptability, and 5 F1 hybrids exhibited higher stability, adaptability, and highest seed cotton yield across the investigated environments simultaneously. F1 hybrids of cotton were concluded as more stable and adaptable regarding seed cotton yield across environments. Accordingly, switching from line to hybrid breeding could enable a cotton breeding program to address the broader issue of growing this crop in a wide range of target environments
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