Plant Biology Research Articles

Mycorrhizal fungi compromise production of endophytic alkaloids, increasing plant susceptibility to an aphid herbivore

Abstract Symbiosis plays a critical role in plant biology. Temperate grasses often associate with several symbiotic fungi simultaneously, including Epichloë endophytes and arbuscular mycorrhizal (AM) fungi, in shoots and roots, respectively. These symbionts often modulate plant–herbivore interactions by influencing nutritional traits (i.e. AM fungi‐mediated nutrient uptake) and/or the secondary chemistry (i.e. endophytic alkaloids) of their host plant. Moreover, such grasses also accumulate large amounts of silicon (Si) from the soil, which can be deposited in tissues to act as a physical anti‐herbivore defence. Recent evidence suggests that both endophytes and AM fungi independently facilitate Si uptake. However, the consequences of their interactions with piercing‐sucking insects (i.e. aphids), or whether Si supply, endophytes, and AM fungi interact in this regard, are currently unknown. While Si deposition may be less effective against aphids than other herbivores (i.e. chewing caterpillars), Si supply can also alter plant secondary metabolite defences, which could affect sucking insects. In a factorial greenhouse experiment, we evaluated whether these components, acting alone or in combination, altered (1) foliar primary chemistry, (2) Si and symbiont‐chemical (endophytic alkaloids) defences, as well as (3) performance of the bird cherry‐oat aphid (Rhopalosiphum padi) feeding on tall fescue (Festuca arundinacea). Endophytes decreased all aphid performance parameters, including population growth and reproduction by 40%, but their impact was reversed by the presence of AM fungi, leading to a 52% increase in aphid performance compared with plants solely hosting endophytes. This improvement in performance was associated with reduced loline alkaloid levels and higher shoot nitrogen in AM‐endophytic plants. Endophytes and AM fungi exhibited antagonism, with endophytes reducing AM colonization by 34% and AM presence decreasing endophyte loline alkaloids by 44%. While both fungi jointly increased Si accumulation by 39% under Si‐supplied conditions, Si had no noticeable effects on aphids. Moreover, although Si supply had no identifiable effects on AM colonization, it reduced endophyte peramine alkaloids by 24%. Synthesis. Our findings indicate that symbiotic fungal partnerships and silicon provision may benefit plants but could weaken anti‐herbivore defences when combined. Revealing the complex interactions among diverse fungal symbionts and showcasing their effects on different anti‐herbivore defences (chemical and physical) and herbivore performance for the first time.

Bioflavonoid Daidzein: Therapeutic Insights, Formulation Advances, and Future Directions.

Bioflavonoids, are a diverse group of phytonutrients that are widely distributed in fruits, vegetables, grains, teas, and certain medicinal herbs. They are characterized by their antioxidant properties and play essential roles in plant biology, such as providing color to fruits and flowers, protecting plants from environmental stresses. Daidzein, a bioflavonoid classified under natural products, is sourced from plants like soybeans and legumes. It exists in forms such as glycosides and aglycones, with equol and trihydroxy isoflavone being key metabolites formed by gut bacteria. Known for its wide-ranging therapeutic potential, daidzein has shown effects on cardiovascular health, cancer, diabetes, skin conditions, osteoporosis, and neurodegenerative disorders. Its mechanisms include interaction with estrogen receptors, antioxidative and anti-inflammatory properties, and modulation of apoptosis and cell cycles. Recent advances in formulation technologies aimed at enhancing daidzein's bioavailability and efficacy are critically evaluated, including nanoparticle-based delivery systems and encapsulation strategies. Researchers have developed advanced formulations like nanoparticles and liposomes to enhance daidzein's solubility, stability, bioavailability, and targeted delivery. Considered a promising nutraceutical, daidzein warrants further exploration into its molecular actions and safety profile to fully realize its clinical potential. This review offers a succinct overview encompassing therapeutic benefits, chemical characteristics, historical uses, toxicology insights, recent advancements in delivery systems, and future directions for daidzein research.

Endophytic bacteria with allelopathic potential regulate gene expression and metabolite production in host Casuarina equisetifolia.

Casuarina equisetifolia is a common protective forest in coastal areas. However, artificial C. equisetifolia forests cannot self-renew, mainly due to the accumulation of allelochemicals. Endophytic bacteria may alleviate the root growth inhibition caused by allelochemicals in C. equisetifolia seedlings. B. amyloliquefaciens and B. aryabhattai were endophytic bacteria with strong allelopathy in C. equisetifolia root. The allelopathy mechanism of these two endophytes and their interaction with C. equisetifolia remains to be studied. Whole-genome sequencing of B. amyloliquefaciens and B. aryabhattai isolated from the roots of allelochemical-accumulating C. equisetifolia was performed using Illumina Hiseq and PacBio single-molecule sequencing platforms. Sterile seedlings of C. equisetifolia were treated with either individual or mixed bacterial cultures through root drenching. Transcriptional and metabolomics analyses were conducted after 3 days of infection. Whole-genome sequencing of Bacillus aryabhattai and Bacillus amyloliquefaciens showed that the two strains contained various horizontal gene transfer elements such as insertion sequence, prophage and transposon. In addition, these two strains also contain numerous genes related to the synthesis and catabolism of allelochemicals. After these two strains of bacteria were individually or mixed infected with C. equisetifolia, metabolomics and transcriptomic analysis of C. equisetifolia showed the 11 important secondary metabolite biosynthesis among them alkaloids biosynthesis, phenylpropanoid and terpenes biosynthesis and related genes were putatively regulated. Correlation analysis revealed that 48 differentially expressed genes had strong positive correlations with 42 differential metabolites, and 48 differentially expressed genes had strong negative correlations with 36 differential metabolites. For example, CMBL gene showed positive correlations with the allelochemical (-)-Catechin gallate, while Bp10 gene showed negative correlations with (-)-Catechin gallate. The intergenerational accumulation of allelochemicals may induce horizontal gene transfer in endogenic bacteria of Casuarina equisetifolia root. Endophytic Bacillus plays an allelopathic role by assisting the host in regulating gene expression and the production and/or variety of allelochemicals. This comprehensive study sheds light on the intricate genetic and metabolic interactions between Bacillus endophytes and C. equisetifolia. These findings provide insights into endophyte-mediated allelopathy and its potential uses in plant biology and forest sustainability.

Retrospect and prospect of Nicotiana tabacum genome sequencing.

Investigating plant genomes offers crucial foundational resources for exploring various aspects of plant biology and applications, such as functional genomics and breeding practices. With the development in sequencing and assembly technology, several Nicotiana tabacum genomes have been published. In this paper, we reviewed the progress on N. tabacum genome assembly and quality, from the initial draft genomes to the recent high-quality chromosome-level assemblies. The application of long-read sequencing, optical mapping, and Hi-C technologies has significantly improved the contiguity and completeness of N. tabacum genome assemblies, with the latest assemblies having a contig N50 size over 50 Mb. Despite these advancements, further improvements are still required and possible, particularly on the development of pan-genome and telomere-to-telomere (T2T) genomes. These new genomes will capture the genomic diversity and variations among different N. tabacum cultivars and species, and provide a comprehensive view of the N. tabacum genome structure and gene content, so to deepen our understanding of the N. tabacum genome and facilitate precise breeding and functional genomics.

Current challenges for plant biology research in the Global South.

In an attempt to address the large inequities faced by the plant biology communities from the Global South (i.e. countries located around the tropics and the Southern Hemisphere) at international conferences, this Viewpoint is the reflexive thinking arising from the concurrent session titled 'Arabidopsis and its translational research in the Global South' organized at the International Conference of Arabidopsis Research 2023 (ICAR 2023) in Chiba, Japan in June 2023. Here, we highlight the main obstacles plant biology communities in the Global South face in terms of knowledge production, as measured by the unequal production and citation of publications, investigating and advancing local plant genomics and biodiversity, combating disparities in gender and diversity, and current initiatives to break isolation of scientists.

Fine-tuning plant valuable secondary metabolite biosynthesis via small RNA manipulation: strategies and potential.

Plants produce secondary metabolites that serve various functions, including defense against biotic and abiotic stimuli. Many of these secondary metabolites possess valuable applications in diverse fields, including medicine, cosmetic, agriculture, and food and beverage industries, exhibiting their importance in both plant biology and various human needs. Small RNAs (sRNA), such as microRNA (miRNA) and small interfering RNA (siRNA), have been shown to play significant roles in regulating the metabolic pathways post-transcriptionally by targeting specific key genes and transcription factors, thus offering a promising tool for enhancing plant secondary metabolite biosynthesis. In this review, we summarize current approaches for manipulating sRNAs to regulate secondary metabolite biosynthesis in plants. We provide an overview of the latest research strategies for sRNA manipulation across diverse plant species, including the identification of potential sRNAs involved in secondary metabolite biosynthesis in non-model plants. We also highlight the potential future research directions, focusing on the manipulation of sRNAs to produce high-value compounds with applications in pharmaceuticals, nutraceuticals, agriculture, cosmetics, and other industries. By exploring these advanced techniques, we aim to unlock new potentials for biotechnological applications, contributing to the production of high-value plant-derived products.

AScirRNA: A novel computational approach to discover abiotic stress-responsive circular RNAs in plant genome

In the realm of plant biology, understanding the intricate regulatory mechanisms governing stress responses stands as a pivotal pursuit. Circular RNAs (circRNAs), emerging as critical players in gene regulation, have garnered attention in recent days for their potential roles in abiotic stress adaptation. A comprehensive grasp of circRNAs' functions in stress response offers avenues for breeders to manipulating plants to develop abiotic stress resistant crop cultivars to thrive in challenging climates. This study pioneers a machine learning-based model for predicting abiotic stress-responsive circRNAs. The K-tuple nucleotide composition (KNC) and Pseudo KNC (PKNC) features were utilized to numerically represent circRNAs. Three different feature selection strategies were employed to select relevant and non-redundant features. Eight shallow and four deep learning algorithms were evaluated to build the final predictive model. Following five-fold cross-validation process, XGBoost learning algorithm demonstrated superior performance with LightGBM-chosen 260 KNC features (Accuracy: 74.55 %, auROC: 81.23 %, auPRC: 76.52 %) and 160 PKNC features (Accuracy: 74.32 %, auROC: 81.04 %, auPRC: 76.43 %), over other combinations of learning algorithms and feature selection techniques. Further, the robustness of the developed models were evaluated using an independent test dataset, where the overall accuracy, auROC and auPRC were found to be 73.13 %, 72.34 % and 72.68 % for KNC feature set and 73.52 %, 79.53 % and 73.09 % for PKNC feature set, respectively. This computational approach was also integrated into an online prediction tool, AScirRNA (https://iasri-sg.icar.gov.in/ascirna/) for easy prediction by the users. Both the proposed model and the developed tool are poised to augment ongoing efforts in identifying stress-responsive circRNAs in plants.

Diurnal.plant.tools in 2024: expanding to Marchantia polymorpha and four angiosperms.

Diurnal gene expression is a pervasive phenomenon occurring across all kingdoms of life, orchestrating adaptive responses to daily environmental fluctuations and thus enhancing organismal fitness. Our understanding of the plant circadian clock is primarily derived from studies in Arabidopsis and direct comparisons are difficult due to differences in gene family sizes. To this end, the identification of functional orthologs based on diurnal and tissue expression is necessary. The diurnal.plant.tools database constitutes a repository of gene expression profiles from 17 members of the Archaeplastida lineage, with built-in tools facilitating cross-species comparisons. In this database update, we expand the dataset with diurnal gene expression from 4 agriculturally significant crop species and Marchantia, a plant of evolutionary significance. Notably, the inclusion of diurnal gene expression data for Marchantia enables researchers to glean insights into the evolutionary trajectories of the circadian clock and other biological processes spanning from algae to angiosperms. Moreover, integrating diurnal gene expression data with datasets from related gene co-expression databases, such as CoNekt-Plants and CoNekt-Stress, which contain gene expression data for tissue and perturbation experiments, provides a comprehensive overview of gene functions across diverse biological contexts. This expanded database serves as a valuable resource for elucidating the intricacies of diurnal gene regulation and its evolutionary underpinnings in plant biology.

Use of image analysis in the evaluation of radicular nodules in chickpeas

The use of advanced computational systems facilitates the application of a wide range of statistical techniques, available in open-source format, to perform analyses of substantial complexity in biological systems, particularly in the field of plant biology. The aim of this study is to demonstrate the application of image analysis in the evaluation of root nodules in Cicer arietinum plants. The research was conducted in the field, where roots were collected, subjected to rigorous cleaning protocols and subsequently photographed under precisely controlled studio conditions. This photographic process was performed using equipment configured with meticulous parameter settings. Subsequently, image analyses were performed using the statistical software package, R. Parameters of interest were quantified, including metrics such as root area, nodule area, the proportional representation of nodules in relation to the total root mass and the absolute count of nodules present. A critical comparison between the proposed analytical methodology and conventional approaches evidenced a substantial improvement in efficiency, thus highlighting the robustness and validity of this analytical framework for the outlined research objectives. Therefore, the developed methodology has significant potential to facilitate accurate and comprehensive analyses of nodules and root systems, thus making a notable contribution to fostering a deeper understanding and exploration of plant-microorganism interactions. Furthermore, this methodological advancement has the potential to contribute to reducing operational costs and optimizing the time spent on such meticulous evaluative undertakings.

The Use of Flow Cytometry in the Analysis of Sows’ Colostrum and Milk

Abstract The flow cytometry method is used in many fields, not only scientific, but also clinical. In science, flow cytometry is used in immunology, molecular biology, microbiology or plant biology. In medicine, has its use, in the diagnosis of tumours, in reproductive and prenatal diagnosis, in transplants or in haematology. In our experimental work, we used this method to analyse colostrum and milk of sows. The aim of this study was to determine the number of somatic cells, the number of leukocytes and the number of T-lymphocytes. Colostrum samples were collected within 24 hours of delivery and then milk samples were collected at weekly intervals during 3 weeks. Statistical analysis revealed significant differences in the number of leukocytes (CD45+) in colostrum and milk. The most significant difference was noted between colostrum and milk in weeks 2 and 3 of the experiment (P < 0.0001), with the highest values found in colostrum. On the other hand, we found that the levels of helper T-cells (CD4+) and cytotoxic T-cells (CD8+) gradually increased over time (P > 0.05), with the highest values observed in the third week after farrowing. We can conclude that flow cytometry can be successfully used for the examination of somatic cells in sows’ milk.

The need for a strict delimitation of early tree life stages in vegetation ecology

AbstractAimFor practical and theoretical purposes, ecological studies commonly classify trees into five major life‐cycle stages: seed, seedling, sapling, juvenile and adult. Whereas the seed and adult stages are usually accurately delimited across studies, there are discrepancies and ambiguity in the categorization of seedlings, saplings and juveniles, which can significantly affect the conclusions of community ecology studies. Here we propose a standardized set of criteria intended for community‐level research for delimiting these three stages based on biological and ecological rationales.MethodsWe assessed the relevance of such standardization by conducting a meta‐analysis of the effects of two human‐caused disturbances (defaunation and logging) on each early tree life stage and examining differences in effect sizes and confidence intervals among: (1) studies that match our delimitation criteria, (2) studies that do not match these criteria, and (3) all studies grouped together regardless of the criteria they used.ResultsWe found stronger effects with narrower confidence intervals when considering only the studies that matched our standardized delimitation criteria. In fact, the proportion of significant effects was between 1.7 (defaunation) and 5.4 (logging) times higher in studies matching our delimitation criteria than in studies that do not match them, probably because confidence intervals were 2.3–3.1 times smaller in the former group than in the latter. For logging studies, the direction of the effects changed in 30%–50% of the cases when comparing the results from all data and studies not matching our criteria with the results of the studies matching our criteria, always from non‐significant to significant effects.ConclusionsThese findings underscore the need for an ecologically meaningful categorization of early tree life stages based on standardized measures to increase the confidence, accuracy, reproducibility and generalization in plant biology and community ecological research. Synthesis efforts will particularly benefit from this standardized protocol.

An unmanned ground vehicle phenotyping-based method to generate three-dimensional multispectral point clouds for deciphering spatial heterogeneity in plant traits

Fusing three-dimensional (3D) and multispectral (MS) imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge. Acquiring high-quality 3D MS point clouds (3DMPCs) of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure. Here, we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field (NeREF) for radiometric calibration. This approach was used to acquire 3DMPCs of perilla, tomato, and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness (EWT) estimation. The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6% compared with the fixed viewpoints alone. The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error (RMSE) of 58.93% for extracted reflectance spectra. The RMSE for chlorophyll content and EWT predictions decreased by 21.25% and 14.13% using partial least squares regression with the generated 3DMPCs. Collectively, our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions, which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits, and thus will facilitate plant biology and genetic studies as well as crop breeding.

THE TRANSFORMATIVE FUTURE OF METABOLOMICS FROM DIAGNOSTICS TO THERAPEUTICS

Metabolomics, or the study of metabolites produced during chemical reactions in living organisms, is a fast-growing topic within the "omics" sciences. It has proven valuable in various disciplines, including plant biology and medicine. However, there are still issues to be addressed. Metabolomics has already found biomarkers for multiple disorders, and the emphasis is now turning from diagnosis to treatment, resulting in "therapeutic metabolomics." This innovative approach seeks to comprehend and address the underlying pathophysiology of diseases. The next significant metabolomics hurdle will be identifying safe medicines that selectively target illness causes and demonstrate clinical utility. For example, current prostate cancer research has identified sarcosine pathway components as both disease progression biomarkers and possible therapeutic targets (1). Alongside concurrent brain imaging modalities, new data compilation approaches are needed for the metabolomics-based diagnosis of brain cancers. Furthermore, to expedite the measurement process, hyperpolarization techniques for the C12 isotope of metabolic substrates are required (2). Nowadays, the trend is shifting towards clinical studies. Within the next few years, it will become evident and apparent whether metabolomics can replace other studies that include genomics and proteomics in oncology. Even though metabolomics is increasingly used to determine the etiology of diseases in which metabolic changes play a role, several biomarkers have been identified for several diseases. However, metabolite profiling for many diseasesin adults has still not been focused on and studied (3). In the future, environmental metabolomics will be more concerned with understanding how organisms react to abiotic influences and interact with other organisms. This approach will expand our understanding of ecological interactions, allowing studies to go beyond individual individuals to entire populations. While closely related to ecophysiology and ecology, this research will eventually facilitate genetic adaptation studies, providing insights into how animals evolve and thrive in changing environments (2,3).

Genome wide identification of phenylalanine ammonia-lyase (PAL) gene family in Cucumis sativus (cucumber) against abiotic stress

Phenylalanine ammonia lyase (PAL) is a widely studied enzyme in plant biology due to its role in connecting primary metabolism to secondary phenylpropanoid metabolism, significantly influencing plant growth, development, and stress response. Although PAL genes have been extensively studied in various plant species but their exploration in cucumber has been limited. This study successfully identified 11 CsPAL genes in Cucumis sativus (cucumber). These CsPAL genes were categorized based on their conserved sequences revealing patterns through MEME analysis and multiple sequence alignment. Interestingly, cis-elements related to stress were found in the promoter regions of CsPAL genes, indicating their involvement in responding to abiotic stress. Furthermore, these gene’s promoters contained components associated with light, development and hormone responsiveness. This suggests that they may have roles in hormone developmental processes. MicroRNAs were identified as a key regulators for the CsPAL genes, playing a crucial role in modulating their expression. This discovery underscores the complex regulatory network involved in the plant’s response to various stress conditions. The influence of these microRNAs further highlights the complicated mechanisms that plants use to manage stress. Gene expression patterns were analyzed using RNA-seq data. The significant upregulation of CsPAL9 during HT3h (heat stress for 3 h) and the heightened upregulation of both CsPAL9 and CsPAL7 under HT6h (heat stress for 6 h) in the transcriptome study suggest a potential role for these genes in cucumber’s tolerance to heat stress. This comprehensive investigation aims to enhance our understanding of the PAL gene family’s versatility, offering valuable insights for advancements in cucumber genetics.

Nucleolar actions in plant development and stress responses.

The nucleolus is conventionally acknowledged for its role in ribosomal RNA (rRNA)synthesis and ribosome biogenesis. Recent research has revealed its multifaceted involvement in plant biology, encompassing regulation of the cell cycle, development, and responses to environmental stresses. This comprehensive review explores the diverse roles of the nucleolus in plant growth and responses to environmental stresses. The introduction delves into its traditional functions in rRNA synthesis and potential participation in nuclear liquid-liquid phase separation. By examining the multifaceted roles of nucleolar proteins in plant development, we highlight the impacts of various nucleolar mutants on growth, development, and embryogenesis. Additionally, we reviewed the involvement of nucleoli in responses to abiotic and biotic stresses. Under abiotic stress conditions, the nucleolar structure undergoes morphological changes. In the context of biotic stress, the nucleolus emerges as a common target for effectors of pathogens for manipulation of host immunity to enhance pathogenicity. The detailed exploration of how pathogens interact with nucleoli and manipulate host responses provides valuable insights into plant stress responses as well as plant growth and development. Understanding these processes may pave the way for promising strategies to enhance crop resilience and mitigate the impact of biotic and abiotic stresses in agricultural systems.

Expression of a mammalian RNA demethylase increases flower number and floral stem branching in Arabidopsis thaliana

AbstractRNA methylation plays a central regulatory role in plant biology and is a relatively new target for plant improvement efforts. In nearly all cases, perturbation of the RNA methylation machinery results in deleterious phenotypes. However, a recent landmark paper reported that transcriptome‐wide use of the human RNA demethylase FTO substantially increased the yield of rice and potatoes. Here, we have performed the first independent replication of those results and demonstrated broader transferability of the trait, finding increased flower and fruit count in the model species Arabidopsis thaliana. We also performed RNA‐seq of our FTO‐transgenic plants, which we analyzed in conjunction with previously published datasets to detect several previously unrecognized patterns in the functional and structural classification of the upregulated and downregulated genes. From these, we present mechanistic hypotheses to explain these surprising results with the goal of spurring more widespread interest in this promising new approach to plant engineering.

Inbreeding in Chinese fir: Insights into the adaptive growth traits of selfed progeny from mRNA, miRNA, and copy number variation.

The impact of inbreeding on biological processes is well documented in individuals with severe inbreeding depression. However, the biological processes influencing the adaptive growth of normal selfed individuals are unknown. Here, we aimed to investigate how inbreeding affects gene expression for adaptive growth of normal selfed seedlings from a self-fertilizing parent in Chinese fir (Cunninghamia lanceolata). Using RNA-seq data from above- and underground tissues of abnormal and normal selfed seedlings, we analyzed GO biological processes network. We also sequenced small RNAs in the aboveground tissues and measured the copy number variations (CNV) of the hub genes. Phenotypic fitness analysis revealed that the normal seedlings were better adapted than their abnormal counterparts. Upregulated differentially expressed genes (DEGs) were associated with development processes, and downregulated DEGs were mainly enriched in fundamental metabolism and stress response. Results of mRNA-miRNA parallel sequencing revealed that upregulated target genes were predominantly associated with development, highlighting their crucial role in phosphorylation in signal transduction networks. We also discovered a moderate correlation (0.1328 < R2 < 0.6257) between CNV and gene expression levels for three hub genes (TMKL1, GT2, and RHY1A). We uncovered the key biological processes underpinning the growth of normal selfed seedlings and established the relationship between CNV and the expression levels of hub genes in selfed seedlings. Understanding the candidate genes involved in the growth of selfed seedlings will help us comprehend the genetic mechanisms behind inbreeding depression in the evolutionary biology of plants.

Thermal study of single phase nanofluid model using radiative γAl2O3 nanomaterial under Hall current and momentum slip phenomena

The applications of nanofluids frequently occur in thermal insulation, cooling of electronic instruments, chemical engineering and to control the heat transfer during many experimental setups, interaction of nanoparticles with water for plants growth, crop improvement, crop protection, plant biology and biological sciences. Therefore, this research emphasis on the performance of radiated γAl2O3/H2O by adding the influential physical constraints (momentum slip and Hall current). The governing model for the flow through a disk with slippery surface is transformed into the final version via necessary mathematical operations and analyzed the problem numerically. Further, the thermal conductivity is computed using Effective Prandtl Number Model (EPNM) by taking nanoparticles amount up to 0.06%. After careful analysis of the problem, it is examined that when Al2O3 nanoparticles amount added in the range of 0.01%-0.06% then EPN increased from 100.398% to 102.636%, density from 100.298% to 101.786% and dynamic viscosity from 100.742% to 104.823%, respectively. Moreover, the electrical and thermal conductivities varied from 100.3% to 101.811% to 101.65%. The moving dynamics of Al2O3/water can be increased or controlled for [Formula: see text] and [Formula: see text], respectively. The Hall index n from 1.0, 3.0, 5.0, 7.0 strongly opposed the velocity and unsteadiness number slightly favor it. Further, the heat transport rate of Al2O3/water improved from 1.05371 to 1.41891 and the shear drag enhanced absolutely from [Formula: see text] to [Formula: see text] against the high nanoparticles amount.

Insights into ACO genes across Rosaceae: evolution, expression, and regulatory networks in fruit development.

ACO (1-aminocyclopropane-1-carboxylic acid) serves as a pivotal enzyme within the plant ethylene synthesis pathway, exerting influence over critical facets of plant biology such as flowering, fruit ripening, and seed development. This study aims to identify ACO genes from representative Rosaceae genomes, reconstruct their phylogenetic relationships by integrating synteny information, and investigate their expression patterns and networks during fruit development. we utilize a specialized Hidden Markov Model (HMM), crafted on the sequence attributes of ACO gene-encoded proteins, to systematically identify and analyze ACO gene family members across 12 representative species within the Rosaceae botanical family. Through transcriptome analysis, we delineate the expression patterns of ACO genes in six distinct Rosaceae fruits. Our investigation reveals the presence of 62 ACO genes distributed among the surveyed Rosaceae species, characterized by hydrophilic proteins predominantly expressed within the cytoplasm. Phylogenetic analysis categorizes these ACO genes into three discernible classes, namely Class I, Class II, and Class III. Further scrutiny via collinearity assessment indicates a lack of collinearity relationships among these classes, highlighting variations in conserved motifs and promoter types within each class. Transcriptome analysis unveils significant disparities in both expression levels and trends of ACO genes in fruits exhibiting respiratory bursts compared to those that do not. Employing Weighted Gene Co-Expression Network Analysis (WGCNA), we discern that the co-expression correlation of ACO genes within loquat fruit notably differs from that observed in apples. Our findings, derived from Gene Ontology (GO) enrichment results, signify the involvement of ACO genes and their co-expressed counterparts in biological processes linked to terpenoid metabolism and carbohydrate synthesis in loquat. Moreover, our exploration of gene regulatory networks (GRN) highlights the potential pivotal role of the GNAT transcription factor (Ejapchr1G00010380) in governing the overexpression of the ACO gene (Ejapchr10G00001110) within loquat fruits. The constructed HMM of ACO proteins offers a precise and systematic method for identifying plant ACO proteins, facilitating phylogenetic reconstruction. ACO genes from representative Rosaceae fruits exhibit diverse expression and regulative patterns, warranting further function characterizations.

Comparative transcriptomics of Venus flytrap (Dionaea muscipula) across stages of prey capture and digestion.

The Venus flytrap, Dionaea muscipula, is perhaps the world's best-known botanical carnivore. The act of prey capture and digestion along with its rapidly closing, charismatic traps make this species a compelling model for studying the evolution and fundamental biology of carnivorous plants. There is a growing body of research on the genome, transcriptome, and digestome of Dionaea muscipula, but surprisingly limited information on changes in trap transcript abundance over time since feeding. Here we present the results of a comparative transcriptomics project exploring the transcriptomic changes across seven timepoints in a 72-hour time series of prey digestion and three timepoints directly comparing triggered traps with and without prey items. We document a dynamic response to prey capture including changes in abundance of transcripts with Gene Ontology (GO) annotations related to digestion and nutrient uptake. Comparisons of traps with and without prey documented 174 significantly differentially expressed genes at 1 hour after triggering and 151 genes with significantly different abundances at 24 hours. Approximately 50% of annotated protein-coding genes in Venus flytrap genome exhibit change (10041 of 21135) in transcript abundance following prey capture. Whereas peak abundance for most of these genes was observed within 3 hours, an expression cluster of 3009 genes exhibited continuously increasing abundance over the 72-hour sampling period, and transcript for these genes with GO annotation terms including both catabolism and nutrient transport may continue to accumulate beyond 72 hours.