Drought is among the most significant environmental factors that frequently limits the growth and productivity of terrestrial plants, making them susceptible to various diseases and resulting in the death of many species each year. Because the plants could not relocate to avoid environmental stresses (i.e., drought, cold temperatures, and high salinity), they developed specific adaptive mechanisms at the root-soil interface to cope with these stresses, especially drought. For instance, under drought conditions, plants change the composition of root exudates by increasing the concentrations of abscisic acid (ABA). This hormone is transported through the xylem transport system to plant leaves, signalling the leaf stomata to regulate stomatal activity. It reduces water loss in plants and enhances their resistance to drought conditions. This review examines the role of soil-root-microbe interactions under drought stress and highlights how this interaction influences nutrient cycling, osmotic pressure adjustment, signalling pathways, and microbial recruitment to enhance plant resilience under drought stress. Furthermore, the mechanisms by which root exudates enhance plant resilience through nitrogen and phosphorus cycling, detoxification of aluminium toxicity, and regulation of stomatal activity are discussed. Understanding these processes and mechanisms provides new insights into developing sustainable forest and agricultural management practices that enhance plant productivity under drought conditions by increasing their resilience in a changing environment.
{"title":"Drought mitigation in plants through root exudate-mediated rhizosphere interactions: Opportunities for future research","authors":"Salam Suresh Singh, Ngangbam Somen Singh, Emilynruwaka Lamare, Ningthoujam Ranjana Devi, Shadokpam Anjali Devi, Remei Kaguijenliu, Biki Takum, Keshav Kumar Upadhyay, Shri Kant Tripathi","doi":"10.1016/j.cpb.2025.100504","DOIUrl":"10.1016/j.cpb.2025.100504","url":null,"abstract":"<div><div>Drought is among the most significant environmental factors that frequently limits the growth and productivity of terrestrial plants, making them susceptible to various diseases and resulting in the death of many species each year. Because the plants could not relocate to avoid environmental stresses (i.e., drought, cold temperatures, and high salinity), they developed specific adaptive mechanisms at the root-soil interface to cope with these stresses, especially drought. For instance, under drought conditions, plants change the composition of root exudates by increasing the concentrations of abscisic acid (ABA). This hormone is transported through the xylem transport system to plant leaves, signalling the leaf stomata to regulate stomatal activity. It reduces water loss in plants and enhances their resistance to drought conditions. This review examines the role of soil-root-microbe interactions under drought stress and highlights how this interaction influences nutrient cycling, osmotic pressure adjustment, signalling pathways, and microbial recruitment to enhance plant resilience under drought stress. Furthermore, the mechanisms by which root exudates enhance plant resilience through nitrogen and phosphorus cycling, detoxification of aluminium toxicity, and regulation of stomatal activity are discussed. Understanding these processes and mechanisms provides new insights into developing sustainable forest and agricultural management practices that enhance plant productivity under drought conditions by increasing their resilience in a changing environment.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100504"},"PeriodicalIF":5.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-03DOI: 10.1016/j.cpb.2025.100505
S. Tamil Selvan , Pallavi , Karishma Seem , Venkata Y. Amara , V. Prathap , K.K. Vinod , Archana Singh , Trilochan Mohapatra , Suresh Kumar
Phosphorus (P) is a vital macronutrient for various physiological/biochemical activities like ATP production through respiration/photosynthesis, carbohydrate metabolism, nucleic acid/membrane synthesis, intracellular signalling, and functioning of enzymes. To deal with P-starvation/deficiency, plant modulates gene expression for adjusting metabolic/signaling pathways. For P homeostasis, metabolic activities are reoriented by transcriptional as well as post-transcriptional/post-translational modulations to integrate physio-biochemical, (epi)genomic, proteomic, and metabolomic processes. Despite the advances in understanding P-starvation/deficiency responses of plants, the genes/regulatory processes for resilience to low-P stress in plants remain enigmatic. To unravel the genes/pathways and regulatory actions of Pup1 QTL on P-starvation in rice, integrative multi-omics analysis of a near-isogenic line-23 (NIL-23, harboring Pup1) and its parental high-yielding rice variety was performed. The multi-omics analysis indicated adoption of multifaceted tolerance mechanisms, integrated nutrient acquisition/transport, hormone signaling, cell wall modification, metabolic modulations, and epigenetic modifications, controlled by Pup1 in NIL-23. Transcriptomic and proteomic analyses highlighted up-regulation of genes/proteins involved in starch/sucrose/nucleotide-sugars metabolism, biosynthesis of secondary metabolites, energy metabolism, and phytohormone signaling in NIL-23. As Pup1 does not carry many protein-coding genes, regulatory functions of the QTL through transcriptomic/epigenetic cascades (via key regulators like transcription factors, chromatin remodelers, and epigenetic factors) modulate gene expression on P-starvation. These affect crucial processes like adaptive changes in plant’s morphology, nutrient acquisition, and metabolic reprogramming in NIL-23. The present study provides a better understanding on Pup1-mediated regulatory complex for resilience to nutrient/phosphorus deficiency, which might help improving P utilization efficiency of crop plants for enhanced productivity in P-scarce soils.
{"title":"Integrative multi-omics analysis of rice grown continuously under P-starvation stress unravels Pup1-mediated regulatory complex for resilience to phosphorus deficiency","authors":"S. Tamil Selvan , Pallavi , Karishma Seem , Venkata Y. Amara , V. Prathap , K.K. Vinod , Archana Singh , Trilochan Mohapatra , Suresh Kumar","doi":"10.1016/j.cpb.2025.100505","DOIUrl":"10.1016/j.cpb.2025.100505","url":null,"abstract":"<div><div>Phosphorus (P) is a vital macronutrient for various physiological/biochemical activities like ATP production through respiration/photosynthesis, carbohydrate metabolism, nucleic acid/membrane synthesis, intracellular signalling, and functioning of enzymes. To deal with P-starvation/deficiency, plant modulates gene expression for adjusting metabolic/signaling pathways. For P homeostasis, metabolic activities are reoriented by transcriptional as well as post-transcriptional/post-translational modulations to integrate physio-biochemical, (epi)genomic, proteomic, and metabolomic processes. Despite the advances in understanding P-starvation/deficiency responses of plants, the genes/regulatory processes for resilience to low-P stress in plants remain enigmatic. To unravel the genes/pathways and regulatory actions of <em>Pup1</em> QTL on P-starvation in rice, integrative multi-omics analysis of a near-isogenic line-23 (NIL-23, harboring <em>Pup1</em>) and its parental high-yielding rice variety was performed. The multi-omics analysis indicated adoption of multifaceted tolerance mechanisms, integrated nutrient acquisition/transport, hormone signaling, cell wall modification, metabolic modulations, and epigenetic modifications, controlled by <em>Pup1</em> in NIL-23. Transcriptomic and proteomic analyses highlighted up-regulation of genes/proteins involved in starch/sucrose/nucleotide-sugars metabolism, biosynthesis of secondary metabolites, energy metabolism, and phytohormone signaling in NIL-23. As <em>Pup1</em> does not carry many protein-coding genes, regulatory functions of the QTL through transcriptomic/epigenetic cascades (via key regulators like transcription factors, chromatin remodelers, and epigenetic factors) modulate gene expression on P-starvation. These affect crucial processes like adaptive changes in plant’s morphology, nutrient acquisition, and metabolic reprogramming in NIL-23. The present study provides a better understanding on <em>Pup1</em>-mediated regulatory complex for resilience to nutrient/phosphorus deficiency, which might help improving P utilization efficiency of crop plants for enhanced productivity in P-scarce soils.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100505"},"PeriodicalIF":5.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144261520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.cpb.2025.100503
Bahman Panahi , Rasmieh Hamid
Drought, salinity and alkaline conditions are the major constraints to cotton (Gossypium spp.) productivity and require the development of genotypes with increased resilience for sustainable cultivation. Abiotic stress tolerance in cotton involves complex gene networks and regulatory pathways. Transcriptome meta-analysis provides a robust approach to elucidate these mechanisms by integrating diverse data sets and identifying consistently responding genes. In this study, RNA-seq meta-analysis using p-value combination approach was harnessed to elucidate the core molecular mechanisms involved in adaptation to drought, salinity and alkaline stress in root and leaf tissues. Moreover, functional analysis of identified core genes were performed using GO and KEGG enrichment and protein-protein interaction network analysis. Prioritization of core genes was further performed using topological analysis of core gene networks and machine learning approach. Key genes identified as central regulatory hubs, such as Gh_A01G1844.1 (aquaporin PIP2–2), Gh_D03G1591.1 (ethylene-responsive transcription factor 5) and Gh_A05G1554.1 (dehydrin COR47), play a central role in adaptive responses, including osmotic adjustment, oxidative stress management and tissue-specific functionality. Enrichment analysis revealed that critical processes such as transcriptional regulation, macromolecular metabolism and cellular signaling pathways are crucial for stress resilience. In addition, the prediction of transcription factor (TF) networks identified the major TF families bHLH, WRKY, NAC, ERF and MYB, which integrate different regulatory mechanisms. In addition, the network analysis revealed important signaling pathways such as ethylene and nodulation, with genes such as Dehydration-Responsive Element 1 D (DRE1D) and Cycling DOF Factor 1 (CDF1) contributing to adaptive responses. This study provides a valuable resource for breeding programs aimed at improving abiotic stress tolerance in cotton and offers insights into the genetic and functional basis of adaptation in different environmental contexts.
{"title":"Decoding core molecular mechanisms related to multiple abiotic stress adaptation in cotton: Insights from RNA-seq data meta-analysis in combination with machine learning approach","authors":"Bahman Panahi , Rasmieh Hamid","doi":"10.1016/j.cpb.2025.100503","DOIUrl":"10.1016/j.cpb.2025.100503","url":null,"abstract":"<div><div>Drought, salinity and alkaline conditions are the major constraints to cotton (Gossypium spp.) productivity and require the development of genotypes with increased resilience for sustainable cultivation. Abiotic stress tolerance in cotton involves complex gene networks and regulatory pathways. Transcriptome meta-analysis provides a robust approach to elucidate these mechanisms by integrating diverse data sets and identifying consistently responding genes. In this study, RNA-seq meta-analysis using p-value combination approach was harnessed to elucidate the core molecular mechanisms involved in adaptation to drought, salinity and alkaline stress in root and leaf tissues. Moreover, functional analysis of identified core genes were performed using GO and KEGG enrichment and protein-protein interaction network analysis. Prioritization of core genes was further performed using topological analysis of core gene networks and machine learning approach. Key genes identified as central regulatory hubs, such as <em>Gh_A01G1844.1</em> (aquaporin PIP2–2), <em>Gh_D03G1591.1</em> (ethylene-responsive transcription factor 5) and <em>Gh_A05G1554.1</em> (dehydrin COR47), play a central role in adaptive responses, including osmotic adjustment, oxidative stress management and tissue-specific functionality. Enrichment analysis revealed that critical processes such as transcriptional regulation, macromolecular metabolism and cellular signaling pathways are crucial for stress resilience. In addition, the prediction of transcription factor (TF) networks identified the major TF families bHLH, WRKY, NAC, ERF and MYB, which integrate different regulatory mechanisms. In addition, the network analysis revealed important signaling pathways such as ethylene and nodulation, with genes such as Dehydration-Responsive Element 1 D (DRE1D) and Cycling DOF Factor 1 (CDF1) contributing to adaptive responses. This study provides a valuable resource for breeding programs aimed at improving abiotic stress tolerance in cotton and offers insights into the genetic and functional basis of adaptation in different environmental contexts.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100503"},"PeriodicalIF":5.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-29DOI: 10.1016/j.cpb.2025.100502
Armida A. Gil-Salido , Carmen A. Contreras-Vergara , Ana Paulina Sortillón-Sortillón , Mitzuko Dautt-Castro , Agustín Rascón-Chu , Miguel A. Martínez-Téllez , Adriana Sañudo-Barajas , Sergio Casas-Flores , Rosalba Contreras-Martínez , Rosabel Velez-de la Rocha , Manuel A. Báez-Sañudo , Jugpreet Singh , María A. Islas-Osuna
Mango is consumed worldwide for its sweet flavor, pleasant aroma, high commercial value, and rich source of L-ascorbic acid (AA), an essential human micronutrient. AA is primarily synthesized in plants via the Smirnoff-Wheeler (SW) pathway. Alternative routes for AA synthesis, such as gulose, myo-inositol, and galacturonic acid, are proposed in some species alongside a recycling pathway that helps maintain AA homeostasis in plant cells. However, a formal genetic demonstration of the alternative routes for AA synthesis and recycling in mangoes remains. In this study, 165 genes associated with AA metabolism were identified in the “Tommy Atkins” mango genome; some of them were previously identified in mango “Ataulfo” and “Kent” transcriptomes. Physical-chemical parameters, AA content, and carbohydrate levels were measured in collected “Ataulfo” mangoes. The expression of SW key genes involved in AA synthesis from alternative and recycling pathways, was evaluated during postharvest ripening, and promoter regions of these genes were analyzed in silico for the presence of regulatory cis-elements. During ripening, transcript accumulation of MiGME-3, MiGGP-1, MiGalLDH, MiGALUR-1, MiPME-1, MIMDHAR-4, and MiAPX-4 from the SW, alternative and recycling pathways showed a significant increase of 3- to 10-fold. However, AA content remained relatively stable throughout ripening, averaging 124 mg/100 g fresh weight, suggesting additional regulatory factors that may counterbalance the increased synthesis. Promoter analysis revealed the presence of seven cis-elements associated with stress and ripening regulation, indicating potential regulatory mechanisms for the identified genes. More than one route could be active in mango fruits, contributing to AA biosynthesis and maintenance during ripening.
{"title":"The “Ataulfo” mango (Mangifera indica L.) maintains its L- ascorbic acid content during fruit ripening: Insights into synthesis and recycling pathways","authors":"Armida A. Gil-Salido , Carmen A. Contreras-Vergara , Ana Paulina Sortillón-Sortillón , Mitzuko Dautt-Castro , Agustín Rascón-Chu , Miguel A. Martínez-Téllez , Adriana Sañudo-Barajas , Sergio Casas-Flores , Rosalba Contreras-Martínez , Rosabel Velez-de la Rocha , Manuel A. Báez-Sañudo , Jugpreet Singh , María A. Islas-Osuna","doi":"10.1016/j.cpb.2025.100502","DOIUrl":"10.1016/j.cpb.2025.100502","url":null,"abstract":"<div><div>Mango is consumed worldwide for its sweet flavor, pleasant aroma, high commercial value, and rich source of L-ascorbic acid (AA), an essential human micronutrient. AA is primarily synthesized in plants via the Smirnoff-Wheeler (SW) pathway. Alternative routes for AA synthesis, such as gulose, myo-inositol, and galacturonic acid, are proposed in some species alongside a recycling pathway that helps maintain AA homeostasis in plant cells. However, a formal genetic demonstration of the alternative routes for AA synthesis and recycling in mangoes remains. In this study, 165 genes associated with AA metabolism were identified in the “Tommy Atkins” mango genome; some of them were previously identified in mango “Ataulfo” and “Kent” transcriptomes. Physical-chemical parameters, AA content, and carbohydrate levels were measured in collected “Ataulfo” mangoes. The expression of SW key genes involved in AA synthesis from alternative and recycling pathways, was evaluated during postharvest ripening, and promoter regions of these genes were analyzed <em>in silico</em> for the presence of regulatory <em>cis</em>-elements. During ripening, transcript accumulation of <em>MiGME-3, MiGGP-1, MiGalLDH, MiGALUR-1, MiPME-1, MIMDHAR-4,</em> and <em>MiAPX-4</em> from the SW, alternative and recycling pathways showed a significant increase of 3- to 10-fold. However, AA content remained relatively stable throughout ripening, averaging 124 mg/100 g fresh weight, suggesting additional regulatory factors that may counterbalance the increased synthesis. Promoter analysis revealed the presence of seven <em>cis</em>-elements associated with stress and ripening regulation, indicating potential regulatory mechanisms for the identified genes. More than one route could be active in mango fruits, contributing to AA biosynthesis and maintenance during ripening.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100502"},"PeriodicalIF":5.4,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-26DOI: 10.1016/j.cpb.2025.100501
Helong Yu , Zhenyang Chen , Xiaoyan Liu , Shaozhong Song , Mojun Chen
Rice is one of the important crops for food supply, and there are multiple differences in the quality of rice grown in different geographic environments, which have an important impact on subsequent yield, economic efficiency, and food processing. Most of the current computer vision-based rice kernel classification focuses only on different varieties. In this study, we propose a method based on deep learning and image processing to recognize rice from different origins. First, Ji-Japonica 830 rice was collected from ten different regions, and a total of 30,000 images were obtained through image segmentation and data enhancement to participate in the training and testing of the model. Four lightweight networks and four classical networks were compared and tested in the pre-training phase, where EfficientNet_b0 obtained the highest accuracy of 93.38 %, and then EfficientNet_b0 was improved by introducing a dynamic adjustment strategy for the learning rate, removing the Dropout layer, and introducing a grouped convolution, which resulted in 96.80 % accuracy. The experimental results show that the method performs well in terms of classification accuracy, parameters, time, and robustness, and can effectively distinguish rice kernels from different geographic environments.
{"title":"Improving EfficientNet_b0 for distinguishing rice from different origins: A deep learning method for geographical traceability in precision agriculture","authors":"Helong Yu , Zhenyang Chen , Xiaoyan Liu , Shaozhong Song , Mojun Chen","doi":"10.1016/j.cpb.2025.100501","DOIUrl":"10.1016/j.cpb.2025.100501","url":null,"abstract":"<div><div>Rice is one of the important crops for food supply, and there are multiple differences in the quality of rice grown in different geographic environments, which have an important impact on subsequent yield, economic efficiency, and food processing. Most of the current computer vision-based rice kernel classification focuses only on different varieties. In this study, we propose a method based on deep learning and image processing to recognize rice from different origins. First, Ji-Japonica 830 rice was collected from ten different regions, and a total of 30,000 images were obtained through image segmentation and data enhancement to participate in the training and testing of the model. Four lightweight networks and four classical networks were compared and tested in the pre-training phase, where EfficientNet_b0 obtained the highest accuracy of 93.38 %, and then EfficientNet_b0 was improved by introducing a dynamic adjustment strategy for the learning rate, removing the Dropout layer, and introducing a grouped convolution, which resulted in 96.80 % accuracy. The experimental results show that the method performs well in terms of classification accuracy, parameters, time, and robustness, and can effectively distinguish rice kernels from different geographic environments.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100501"},"PeriodicalIF":5.4,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-23DOI: 10.1016/j.cpb.2025.100500
Fengchao Jiang , Li Yang , Junhuan Zhang , Meiling Zhang , Wenjian Yu , Haoyuan Sun
Apricot is a commercially vital stone fruit prized for its distinctive organoleptic characteristics and nutritional value. We developed an F1 population from ‘Chuanzhihong’ × ‘Luotuohuang’ to investigate the genetic basis of sugar metabolism. Whole-genome resequencing identified 63,162 high-quality InDel markers, while metabolomic profiling quantified soluble sugars (sucrose, glucose, fructose) across fruit developmental stages. Continuous variation in sugar accumulation patterns indicated polygenic inheritance. A high-density genetic map (601.5 cM, 0.44 cM average interval) revealed 20 stable QTLs across 8 linkage groups, explaining 8.0–16.2 % phenotypic variance for individual and total sugars. WGCNA identified sugar component-specific modules showing strong correlations (r = 0.57–0.95). Integrative analysis prioritized PA08G27233 as a hub gene within QTL intervals, encoding a SWEET transporter (designated PaSWEET1) with evolutionary conservation to AtSWEET1. This study elucidates molecular mechanisms of photoassimilate partitioning in apricot and provides genomic resources (high-resolution map, candidate genes) for marker-assisted breeding. The findings advance functional characterization of sugar metabolism pathways in Prunus species.
{"title":"Integrated QTL mapping and transcriptomic profiling elucidate molecular determinants of sucrose accumulation in apricot (Prunus armeniaca L)","authors":"Fengchao Jiang , Li Yang , Junhuan Zhang , Meiling Zhang , Wenjian Yu , Haoyuan Sun","doi":"10.1016/j.cpb.2025.100500","DOIUrl":"10.1016/j.cpb.2025.100500","url":null,"abstract":"<div><div>Apricot is a commercially vital stone fruit prized for its distinctive organoleptic characteristics and nutritional value. We developed an F1 population from ‘Chuanzhihong’ × ‘Luotuohuang’ to investigate the genetic basis of sugar metabolism. Whole-genome resequencing identified 63,162 high-quality InDel markers, while metabolomic profiling quantified soluble sugars (sucrose, glucose, fructose) across fruit developmental stages. Continuous variation in sugar accumulation patterns indicated polygenic inheritance. A high-density genetic map (601.5 cM, 0.44 cM average interval) revealed 20 stable QTLs across 8 linkage groups, explaining 8.0–16.2 % phenotypic variance for individual and total sugars. WGCNA identified sugar component-specific modules showing strong correlations (r = 0.57–0.95). Integrative analysis prioritized <em>PA08G27233</em> as a hub gene within QTL intervals, encoding a SWEET transporter (designated <em>PaSWEET1</em>) with evolutionary conservation to AtSWEET1. This study elucidates molecular mechanisms of photoassimilate partitioning in apricot and provides genomic resources (high-resolution map, candidate genes) for marker-assisted breeding. The findings advance functional characterization of sugar metabolism pathways in <em>Prunus</em> species.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100500"},"PeriodicalIF":5.4,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-22DOI: 10.1016/j.cpb.2025.100493
Yanru Wang , Ying Zhang , Anran Song , Minkun Guo , Changyu Zhang , Chuanyu Wang , Yanxin Zhao , Guanmin Huang , Qingmei Men , Chunjiang Zhao , Xinyu Guo
The seed coat serves as a protective barrier between seeds and their environment. This structure plays fundamental roles in protection, environmental sensing, and germination regulation. Current phenotypic characterization methods typically measure the seed coat together with adjacent structures, including the aleurone layer and endosperm. Such combined measurements hinder accurate assessment of seed coat-specific traits. This study presents an integrated analytical approach for phenotyping isolated maize seed coats. The method combines microscopic hyperspectral imaging with atomic force microscopy (AFM), enabling quantitative assessment of 24 phenotypic indicators spanning roughness, light transmittance, color, and texture parameters. The investigation of phenotypic diversity focused on inbred lines from natural association populations. The analytical workflow involved kernel contour extraction from RGB images followed by detailed phenotypic mapping. Population-wide analysis revealed substantial phenotypic variation. Coefficients of variation ranged from 30 % to 45 % for light transmittance and color texture phenotypes, while exceeding 60 % for roughness parameters. A phenotypic interaction network was constructed to elucidate trait relationships, identifying VLD as key characteristic phenotypes in seed coat morphology. Dimensional reduction analysis highlighted 12 critical indicators: Rp, Ra, Rv, Rz, LAQ, VLI, LAD, TRGSD, TSGSH, TRGSE, CBAve, and SCAve. Germination studies demonstrated significant correlations between seed emergence rate (SER) and multiple seed coat traits, including light transmittance, color, and texture characteristics (R: −0.204 to −0.194, P < 0.05). Notable inbred lines, including Ry737, Dong46, CML486, and CML426, exhibited superior germination rates characterized by low seed coat roughness, high light transmittance, enhanced texture roughness, and increased color saturation and brightness. The methodological advances presented here provide novel insights into maize seed coat characteristics. These findings have significant implications for precise germplasm identification and the development of high-quality, high-vigor maize varieties.
{"title":"Precision profiling of seed coat phenotypes in maize: 3D surface morphology, color, texture traits for the construction of phenotyping interaction networks","authors":"Yanru Wang , Ying Zhang , Anran Song , Minkun Guo , Changyu Zhang , Chuanyu Wang , Yanxin Zhao , Guanmin Huang , Qingmei Men , Chunjiang Zhao , Xinyu Guo","doi":"10.1016/j.cpb.2025.100493","DOIUrl":"10.1016/j.cpb.2025.100493","url":null,"abstract":"<div><div>The seed coat serves as a protective barrier between seeds and their environment. This structure plays fundamental roles in protection, environmental sensing, and germination regulation. Current phenotypic characterization methods typically measure the seed coat together with adjacent structures, including the aleurone layer and endosperm. Such combined measurements hinder accurate assessment of seed coat-specific traits. This study presents an integrated analytical approach for phenotyping isolated maize seed coats. The method combines microscopic hyperspectral imaging with atomic force microscopy (AFM), enabling quantitative assessment of 24 phenotypic indicators spanning roughness, light transmittance, color, and texture parameters. The investigation of phenotypic diversity focused on inbred lines from natural association populations. The analytical workflow involved kernel contour extraction from RGB images followed by detailed phenotypic mapping. Population-wide analysis revealed substantial phenotypic variation. Coefficients of variation ranged from 30 % to 45 % for light transmittance and color texture phenotypes, while exceeding 60 % for roughness parameters. A phenotypic interaction network was constructed to elucidate trait relationships, identifying VLD as key characteristic phenotypes in seed coat morphology. Dimensional reduction analysis highlighted 12 critical indicators: Rp, Ra, Rv, Rz, LAQ, VLI, LAD, TRGSD, TSGSH, TRGSE, CBAve, and SCAve. Germination studies demonstrated significant correlations between seed emergence rate (SER) and multiple seed coat traits, including light transmittance, color, and texture characteristics (R: −0.204 to −0.194, P < 0.05). Notable inbred lines, including Ry737, Dong46, CML486, and CML426, exhibited superior germination rates characterized by low seed coat roughness, high light transmittance, enhanced texture roughness, and increased color saturation and brightness. The methodological advances presented here provide novel insights into maize seed coat characteristics. These findings have significant implications for precise germplasm identification and the development of high-quality, high-vigor maize varieties.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100493"},"PeriodicalIF":5.4,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-22DOI: 10.1016/j.cpb.2025.100498
Xue Kong , Jiangtao Zhao , Yirou Liu , Bo Bai , Juntao Yang , Yangyang Fan , Guowei Li , Zhenhai Li , Shubo Wan
Accurate estimation of leaf biochemical parameters is crucial for understanding crop physiology and monitoring nutritional status. Remote sensing algorithms perform well on limited germplasm, but the transferability to high-throughput phenotyping with diverse genotypes remains unclear. This study estimated leaf chlorophyll content (Cab), equivalent water thickness (Cw), and dry matter content (Cm) using the single vegetation index (SVI), random forest (RF), and the PROSPECT model to evaluate the performance and transferability of these models under diverse peanut germplasm conditions. Results showed that Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Water Index (WI), and Modified Simple Ratio (mSR) were strongly correlated with Cab, Cw, and Cm, respectively, highlighting their importance in the inversion models. Comparative analysis revealed that the RF model achieved the highest accuracy for Cab (R2 = 0.77, RMSE = 8.14 µg cm−2), Cw (R2 = 0.67, RMSE = 1.1 × 10−3 g cm−2), and Cm (R2 = 0.50, RMSE = 6.2 × 10−4 g cm−2), followed by the PROSPECT model, with R2 and RMSE of 0.76 and 8.21 µg cm−2 for Cab, 0.61 and 1.2 × 10−3 g cm−2 for Cw, and 0.38 and 7.7 × 10−4 g cm−2 for Cm, respectively. However, the PROSPECT model was most effective in Cab inversion across diverse germplasm resources (R2 = 0.58, RMSE = 7.68 µg cm−2), demonstrating its superior transferability and stability. These results underscore its value in high-throughput phenotyping and improving the accuracy and generalizability of crop biochemical parameter estimation.
{"title":"The PROSPECT model in high-throughput phenotyping for peanut leaf parameter estimation: Comparative performance of hyperspectral inversion models","authors":"Xue Kong , Jiangtao Zhao , Yirou Liu , Bo Bai , Juntao Yang , Yangyang Fan , Guowei Li , Zhenhai Li , Shubo Wan","doi":"10.1016/j.cpb.2025.100498","DOIUrl":"10.1016/j.cpb.2025.100498","url":null,"abstract":"<div><div>Accurate estimation of leaf biochemical parameters is crucial for understanding crop physiology and monitoring nutritional status. Remote sensing algorithms perform well on limited germplasm, but the transferability to high-throughput phenotyping with diverse genotypes remains unclear. This study estimated leaf chlorophyll content (Cab), equivalent water thickness (Cw), and dry matter content (Cm) using the single vegetation index (SVI), random forest (RF), and the PROSPECT model to evaluate the performance and transferability of these models under diverse peanut germplasm conditions. Results showed that Transformed Chlorophyll Absorption in Reflectance Index (TCARI), Water Index (WI), and Modified Simple Ratio (mSR) were strongly correlated with Cab, Cw, and Cm, respectively, highlighting their importance in the inversion models. Comparative analysis revealed that the RF model achieved the highest accuracy for Cab (R<sup>2</sup> = 0.77, RMSE = 8.14 µg cm<sup>−2</sup>), Cw (R<sup>2</sup> = 0.67, RMSE = 1.1 × 10<sup>−3</sup> g cm<sup>−2</sup>), and Cm (R<sup>2</sup> = 0.50, RMSE = 6.2 × 10<sup>−4</sup> g cm<sup>−2</sup>), followed by the PROSPECT model, with R<sup>2</sup> and RMSE of 0.76 and 8.21 µg cm<sup>−2</sup> for Cab, 0.61 and 1.2 × 10<sup>−3</sup> g cm<sup>−2</sup> for Cw, and 0.38 and 7.7 × 10<sup>−4</sup> g cm<sup>−2</sup> for Cm, respectively. However, the PROSPECT model was most effective in Cab inversion across diverse germplasm resources (R<sup>2</sup> = 0.58, RMSE = 7.68 µg cm<sup>−2</sup>), demonstrating its superior transferability and stability. These results underscore its value in high-throughput phenotyping and improving the accuracy and generalizability of crop biochemical parameter estimation.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100498"},"PeriodicalIF":5.4,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-22DOI: 10.1016/j.cpb.2025.100497
Qian Wu , Chunyu Wu , Ziying Wu , Shibo Chen , Hong-Bin Wang , Hong-Lei Jin , Kewei Zhao
Plant-derived vesicle-like nanoparticles (PDVLNs) contain various biomolecules and metabolites that aid in material conversion, signal transduction, cross-species information communication, and gene expression regulation. Despite their potential, there have been no prior reports on Andrographis paniculata-derived vesicle-like nanoparticles (ApDVLNs) and their biological components. In this study, ApDVLNs were identified through physical and biochemical characterization, and their cargoes were analyzed using multi-omics (microRNA omics, proteomics, non-targeted metabolomics). Joint analysis revealed that both fresh and dry ApDVLNs were rich in miRNAs involved in regulating plant growth, development, and environmental adaptation. Target genes of specific miRNAs in fresh ApDVLNs were related to photosynthesis and hormone signal transduction, at the same time, those in dry ApDVLNs were involved in secondary metabolite accumulation and nucleic acid repair. miRNAs like miR396-x and miR166-y may also regulate infections, cancer, cardiovascular diseases, immune disorders, and metabolic diseases in Homo sapiens. Both fresh and dry ApDVLNs contained numerous proteins primarily associated with catalytic activity, binding, transporter activity, and other functions. They included proteins involved in endocytosis, ABC transporters, vesicles, aquaporins, tetraspanins, and membrane proteins, which support ApDVLNs functionality. Interestingly, many miRNAs and proteins were present in both fresh and dry ApDVLNs, but dry ApDVLNs contain more of these miRNAs and proteins. Additionally, dry ApDVLNs were metabolite-rich, identifying 23,760 metabolites, with 53.06 % of the annotated ones belonging to lipids and lipid-like molecules. The results of these works demonstrate that ApDVLNs are abundant in miRNAs, proteins and metabolites. Enhancing the concentration of these substances during the drying process is crucial for their biological function. These components form the material basis for their biological activities.
{"title":"Multi-omics analyses reveal the differentiation of biochemical constituents from fresh and dry Andrographis paniculata-derived vesicle-like nanoparticles","authors":"Qian Wu , Chunyu Wu , Ziying Wu , Shibo Chen , Hong-Bin Wang , Hong-Lei Jin , Kewei Zhao","doi":"10.1016/j.cpb.2025.100497","DOIUrl":"10.1016/j.cpb.2025.100497","url":null,"abstract":"<div><div>Plant-derived vesicle-like nanoparticles (PDVLNs) contain various biomolecules and metabolites that aid in material conversion, signal transduction, cross-species information communication, and gene expression regulation. Despite their potential, there have been no prior reports on <em>Andrographis paniculata</em>-derived vesicle-like nanoparticles (ApDVLNs) and their biological components. In this study, ApDVLNs were identified through physical and biochemical characterization, and their cargoes were analyzed using multi-omics (microRNA omics, proteomics, non-targeted metabolomics). Joint analysis revealed that both fresh and dry ApDVLNs were rich in miRNAs involved in regulating plant growth, development, and environmental adaptation. Target genes of specific miRNAs in fresh ApDVLNs were related to photosynthesis and hormone signal transduction, at the same time, those in dry ApDVLNs were involved in secondary metabolite accumulation and nucleic acid repair. miRNAs like miR396-x and miR166-y may also regulate infections, cancer, cardiovascular diseases, immune disorders, and metabolic diseases in <em>Homo sapiens</em>. Both fresh and dry ApDVLNs contained numerous proteins primarily associated with catalytic activity, binding, transporter activity, and other functions. They included proteins involved in endocytosis, ABC transporters, vesicles, aquaporins, tetraspanins, and membrane proteins, which support ApDVLNs functionality. Interestingly, many miRNAs and proteins were present in both fresh and dry ApDVLNs, but dry ApDVLNs contain more of these miRNAs and proteins. Additionally, dry ApDVLNs were metabolite-rich, identifying 23,760 metabolites, with 53.06 % of the annotated ones belonging to lipids and lipid-like molecules. The results of these works demonstrate that ApDVLNs are abundant in miRNAs, proteins and metabolites. Enhancing the concentration of these substances during the drying process is crucial for their biological function. These components form the material basis for their biological activities.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100497"},"PeriodicalIF":5.4,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-19DOI: 10.1016/j.cpb.2025.100496
Zonaira Qaiser , Noreen Khalid , Adeel Mahmood , Shiou Yih Lee , Zarrin Fatima Rizvi , Muhammad Kashif Irshad , Ujala Ejaz , Muhammad Aqeel
This study was carried out to evaluate the interaction between terrestrial food crop plants and microplastics (MPs) with a focus on understanding their uptake, effects on growth, physiological, biochemical, and yield characteristics of two different cultivars of Solanum tuberosum L. i.e., Variety-1, Astrix (AL-4) and Variety-2, Harmes (WA-4). Polyethylene (PE), polystyrene (PS), and polypropylene (PP) spheres of size 5 μm were applied to the soil at concentrations of 0 %, 1 %, and 5 %. Morphological parameters, including seed germination rate, shoot and root lengths, leaf area, and fresh and dry biomass of plants, got reduced significantly with the increase in MP concentration. PS MPs caused the most negative impact, particularly at 5 %, leading to the greatest decline in growth and Na, Mg, Zn, Cu, Ni, and Mn nutrient content. The highest DPPH scavenging activity was observed in the 5 % PS MPs treatment with approximately a 45.34 % increase from the control, indicating its potential to enhance antioxidant activity in response to stress caused by PS MPs. Both reducing and non-reducing sugar contents and total proteins were also decreased significantly. Vitamin C content exhibited a significant increase in response to MPs, with the highest levels recorded under 5 % PS MPs treatments. This suggests an adaptive antioxidant response to mitigate oxidative damage induced by MPs. SEM analysis revealed tissue infiltration of MP particles in shoots, leaves, and tubers of both varieties. Among MPs, PS had the most detrimental effects, followed by PP and PE, with higher concentrations increasing the negative impact.
{"title":"Tissue infiltration of polyethylene, polypropylene, and polystyrene microplastics in Solanum tuberosum L. influences plant growth and yield","authors":"Zonaira Qaiser , Noreen Khalid , Adeel Mahmood , Shiou Yih Lee , Zarrin Fatima Rizvi , Muhammad Kashif Irshad , Ujala Ejaz , Muhammad Aqeel","doi":"10.1016/j.cpb.2025.100496","DOIUrl":"10.1016/j.cpb.2025.100496","url":null,"abstract":"<div><div>This study was carried out to evaluate the interaction between terrestrial food crop plants and microplastics (MPs) with a focus on understanding their uptake, effects on growth, physiological, biochemical, and yield characteristics of two different cultivars of <em>Solanum tuberosum</em> L. i.e., Variety-1, Astrix (AL-4) and Variety-2, Harmes (WA-4). Polyethylene (PE), polystyrene (PS), and polypropylene (PP) spheres of size 5 μm were applied to the soil at concentrations of 0 %, 1 %, and 5 %. Morphological parameters, including seed germination rate, shoot and root lengths, leaf area, and fresh and dry biomass of plants, got reduced significantly with the increase in MP concentration. PS MPs caused the most negative impact, particularly at 5 %, leading to the greatest decline in growth and Na, Mg, Zn, Cu, Ni, and Mn nutrient content. The highest DPPH scavenging activity was observed in the 5 % PS MPs treatment with approximately a 45.34 % increase from the control, indicating its potential to enhance antioxidant activity in response to stress caused by PS MPs. Both reducing and non-reducing sugar contents and total proteins were also decreased significantly. Vitamin C content exhibited a significant increase in response to MPs, with the highest levels recorded under 5 % PS MPs treatments. This suggests an adaptive antioxidant response to mitigate oxidative damage induced by MPs. SEM analysis revealed tissue infiltration of MP particles in shoots, leaves, and tubers of both varieties. Among MPs, PS had the most detrimental effects, followed by PP and PE, with higher concentrations increasing the negative impact.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"43 ","pages":"Article 100496"},"PeriodicalIF":5.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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