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The Mediator complex is a multisubunit transcription coregulator that transfers regulatory signals from different transcription factors to RNA polymerase II (Pol II) to control Pol II-dependent transcription in eukaryotes. Studies on Arabidopsis Mediator subunits have revealed their unique or overlapping functions in various aspects of plant growth, stress adaptation and metabolite homeostasis. Therefore, the utilization of the plant Mediator complex for crop improvement has been of great interest. Advances in genome editing and sequencing techniques have expedited the characterization of Mediator subunits in economically important crops such as tomato, rice, wheat, soybean, sugarcane, pea, chickpea, rapeseed and hop. In this review, we summarize recent progress in understanding the molecular mechanisms of how the Mediator complex regulates crop growth, development and adaptation to environmental stress. We also discuss the conserved and diverse functions of the Mediator complex in different plant species. In addition, we propose several future research directions to deepen our understanding of the important roles of Mediator subunits and their interacting proteins, which would provide promising targets for genetic modification to develop new cultivars with desirable agronomic traits.

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Crop improvement and production domains encounter large amounts of expanding data with multi-layer complexity that forces researchers to use machine-learning approaches to establish predictive and informative models to understand the sophisticated mechanisms underlying these processes. All machine-learning approaches aim to fit models to target data; nevertheless, it should be noted that a wide range of specialized methods might initially appear confusing. The principal objective of this study is to offer researchers an explicit introduction to some of the essential machine-learning approaches and their applications, comprising the most modern and utilized methods that have gained widespread adoption in crop improvement or similar domains. This article explicitly explains how different machine-learning methods could be applied for given agricultural data, highlights newly emerging techniques for machine-learning users, and lays out technical strategies for agri/crop research practitioners and researchers.

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MAIN CONCLUSION: This review discusses the Finger millet's rich nutritional profile, bioactive potential, and industrial applications, combined with its climate resilience, which make it a promising crop for enhancing food security and promoting sustainable agriculture. This review also highlights its significant potential to address malnutrition and mitigate climate change impacts. The emergence of Finger millet from "poor man's staple food" to "a nutrient rich cereal" has encouraged the need to explore this crop at a wider scale. It is a highly significant crop due to its rich nutritional and bioactive profile, diverse biological activities, and promising industrial applications, along with the high climate resilience. This comprehensive review evaluates its nutritional composition by comparing favorably with other cereals and millets and emphasizing its potential to address malnutrition and enhance food security. Furthermore, it explores the phytochemical/bioactive potential and strategies to enhance their bioavailability followed biological activities of Finger millet by highlighting its various health-promoting properties. The review also discusses industrial potential of finger millet including its role in nutraceutical and functional food production, as well as bioenergy generation. In addition, role of Finger millet as a climate-resilient crop; specifically, the available genetic resources and identification of genes and quantitative trait loci (QTLs) associated with major stress tolerance traits have also been discussed. By providing a comprehensive synthesis of existing knowledge, this study offers valuable insights for researchers, policymakers, and stakeholders engaged in efforts to promote sustainable agriculture, enhance food and nutrition security, and mitigate the impacts of climate change.

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Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technologies have revolutionized genome editing, significantly advancing the improvement of cultivated crop species. This review provides an overview of genome-edited crops that have either reached the market or received the necessary approvals but are not yet available to consumers. We analyze various genome-editing studies to understand the distribution of different genome-editing systems, the types of site-directed nucleases employed, and the geographical spread of these studies, with a specific focus on global and European contexts. Additionally, we examine the target crops involved. The review also outlines the multiple steps required for the legal acceptance of genome-edited crops within European jurisdictions. We conclude with suggestions for the future prospects of genome-editing research in Europe, aiming to streamline the approval process and enhance the development and adoption of genome-edited crops.

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Mutagenic effectiveness and efficiency are the most important factors determining the success of mutation breeding, a coherent tool for quickly enhancing diversity in crops. This study was carried out at Lovely Professional University's agricultural research farm in Punjab, India, during the year 2023. The experimental design followed a randomized complete block design (RCBD) with three replications. The experiment aimed to assess the effect of three chemical mutagens, sodium azide (SA), ethyl methyl sulphonates (EMSs), and methyl methane sulfonate (MMS), at three different concentrations (0.2%, 0.4%, and 0.6%), in SL958 and SL744 soybean varieties to select the mutant exhibiting the highest yield. The data were collected and analysed using a two-way ANOVA test through SPSS software (version 22), and the means were separated using Duncan's multiple range test (DMRT) at the 5% level of significance. Between the two varieties, the highest seed germination percentage (76.0% seedlings/plot) was recorded in SL958 (0.4% SA), while the lowest (30.33% seedlings/plot) was observed in 0.6% MMS as compared to the control (53% and 76% in SL744 and SL958 at 10 days after sowing, respectively). Several weeks after sowing, the average plant height was observed to be higher (37.84 ± 1.32 cm) in SL958 (0.4% SA) and lower (20.58 ± 0.30 cm) in SL744 (0.6% SA), as compared to the controls (SL958: 26.09 ± 0.62 cm and SL744: 27.48 ± 0.74 cm). The average leaf count was the highest (234.33 ± 3.09 tetrafoliate leaves/plant) in SL958 (0.4% SA) while it was the lowest (87 leaves/plant) in 0.6% MMS as compared to the control (SL744 180.00 ± 1.63 and SL958 160.73 ± 1.05). The highest total leaf areas recorded in the SL958 and SL744 M1plants were 3625.8 ± 1.43 cm2 and 2311.03 ± 3.65 cm2, respectively. Seeds of the SL958 variety treated with 0.4% SA resulted in the development of tetrafoliate leaves with a broad leaf base and the maximum yield (277.55 ± 1.37 pods/plant) compared to the narrow pentafoliate leaves obtained through the treatment with EMS. Meanwhile, in the SL744 variety, the same treatment led to tetrafoliate leaves with a comparatively lower yield of 206.54 ± 23.47 pods/plant as compared to the control (SL744 164.33 ± 8.58 and SL958 229.86 ± 0.96). The highest protein content (47.04 ± 0.87% TSP) was recorded in the SL958 (0.4% SA) M2 seeds followed by a content of 46.14 ± 0.64% TSP in the SL744 (0.4% SA) M2 seeds, whereas the lowest content (38.13 ± 0.81% TSP) was found in SL958 (0.6% MMS). Similar observations were recorded for the lipid and fibre content. The 0.4% SA treatment in SL958 proved to be efficient in generating the highest leaf area (tetrafoliate leaves) and a reasonable yield of M1 (the first generation after mutation) plants.

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Genetic engineering has become an essential element in developing climate-resilient crops and environmentally sustainable solutions to respond to the increasing need for global food security. Genome editing using CRISPR/Cas [Clustered regulatory interspaced short palindromic repeat (CRISPR)-associated protein (Cas)] technology is being applied to a variety of organisms, including plants. This technique has become popular because of its high specificity, effectiveness, and low production cost. Therefore, this technology has the potential to revolutionize agriculture and contribute to global food security. Over the past few years, increasing efforts have been seen in its application in developing higher-yielding, nutrition-rich, disease-resistant, and stress-tolerant "crops", fruits, and vegetables. Cas proteins such as Cas9, Cas12, Cas13, and Cas14, among others, have distinct architectures and have been used to create new genetic tools that improve features that are important for agriculture. The versatility of Cas has accelerated genomic analysis and facilitated the use of CRISPR/Cas to manipulate and alter nucleic acid sequences in cells of different organisms. This review provides the evolution of CRISPR technology exploring its mechanisms and contrasting it with traditional breeding and transgenic approaches to improve different aspects of stress tolerance. We have also discussed the CRISPR/Cas system and explored three Cas proteins that are currently known to exist: Cas12, Cas13, and Cas14 and their potential to generate foreign-DNA-free or non-transgenic crops that could be easily regulated for commercialization in most countries.

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Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements. Simultaneously, the exponential growth of computational power and big data now promote the application of machine learning for biological research. In this regard, machine learning shows great potential in the refinement of genome editing systems and crop improvement. Here, we review the advances of machine learning to genome editing optimization, with emphasis placed on editing efficiency and specificity enhancement. Additionally, we demonstrate how machine learning bridges genome editing and crop breeding, by accurate key site detection and guide RNA design. Finally, we discuss the current challenges and prospects of these two techniques in crop improvement. By integrating advanced genome editing techniques with machine learning, progress in crop breeding will be further accelerated in the future.

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Plants are exposed to a myriad of stresses, stemming from abiotic and biotic sources, significantly threatening agricultural productivity. The low crop yield, coupled with the global burden of population has resulted in the scarcity of quality food, exacerbating socio-economic issues like poverty, hunger, and malnutrition. Conventional breeding methods for the generation of stress-tolerant plants are time-consuming, limit genetic diversity, and are not sustainable for the consistent production of high-yielding crops. In recent years, the use of high-throughput, genome editing (GE) technique has revolutionized the crop-improvement paradigm, ushering greater prospects for agricultural progress. Among these tools, the Clustered regularly interspaced short palindromic repeat (CRISPR), and its associated nuclease protein Cas9, have appeared as a ground-breaking technology, allowing precise knockout (KO), upregulation, and downregulation of target gene expression. Apart from its high efficacy and speed, this programmable nuclease offers exceptional specificity with minimal off-target effects. Here in, we aim to review the latest findings on the application of the CRISPR/Cas9 genome editing tool for generating resilience in plants against environmental stresses.

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Many African countries are unable to meet the food demands of their growing population and the situation is worsened by climate change and disease outbreaks. This issue of food insecurity may lead to a crisis of epic proportion if effective measures are not in place to make more food available. Thus, deploying biotechnology towards the improvement of existing crop varieties for tolerance or resistance to both biotic and abiotic stresses is crucial to increasing crop production. In order to optimize crop production, several African countries have implemented strategies to make the most of this innovative technology. For example, Nigerian government has implemented the National Biotechnology Policy to facilitate capacity building, research, bioresource development and commercialization of biotechnology products for over two decades. Several government ministries, research centers, universities, and agencies have worked together to implement the policy, resulting in the release of some genetically modified crops to farmers for cultivation and Commercialization, which is a significant accomplishment. However, the transgenic crops were only brought to Nigeria for confined field trials; the manufacturing of the transgenic crops took place outside the country. This may have contributed to the suspicion of pressure groups and embolden proponents of biotechnology as an alien technology. Likewise, this may also be the underlying issue preventing the adoption of biotechnology products in other African countries. It is therefore necessary that African universities develop capacity in various aspects of biotechnology, to continuously train indigenous scientists who can generate innovative ideas tailored towards solving problems that are peculiar to respective country. Therefore, this study intends to establish the role of genetic engineering and genome editing towards the achievement of food security in Africa while using Nigeria as a case study. In our opinion, biotechnology approaches will not only complement conventional breeding methods in the pursuit of crop improvements, but it remains a viable and sustainable means of tackling specific issues hindering optimal crop production. Furthermore, we suggest that financial institutions should offer low-interest loans to new businesses. In order to promote the growth of biotechnology products, especially through the creation of jobs and revenues through molecular farming.

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This study provides sequence datasets of endophytic and rhizobacteria of jute using 16S rRNA gene sequencing. The plant samples were first surface sterilized and DNA of the bacteria from soil and jute roots and stem was extracted using Quick-DNA™ Fungal/Bacterial Miniprep Kit. The purified DNA was amplified and subjected to polymerase chain reaction using forward and reverse primers. The PCR products were sequenced on Applied Biosystems ABI 3500XL Genetic Analyser (Applied Biosystems, ThermoFisher Scientific). The sequences were analyzed using BioEdit version 7.2.5 and then BLAST on NCBI. The identifiable bacteria include the rhizobacteria, Citrobacter fruendii RZS23 (accession number: CP024673.1), endophytic bacteria, Bacillus cereus EDR23 (accession number: LN890242.1), and Morganella morganii EDS23 (accession number: KR094121.1). The plant growth-promoting traits exhibited by these bacteria suggest their future exploration as bioinoculants.

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14-3-3 proteins, ubiquitously present in eukaryotic cells, are regulatory proteins involved in a plethora of cellular processes. In plants, they have been studied in the context of metabolism, development, and stress responses. Recent studies have highlighted the pivotal role of 14-3-3 proteins in regulating plant immunity. The ability of 14-3-3 proteins to modulate immune responses is primarily attributed to their function as interaction hubs, mediating protein-protein interactions and thereby regulating the activity and overall function of their binding partners. Here, we shed light on how 14-3-3 proteins contribute to plant defense mechanisms, the implications of their interactions with components of plant immunity cascades, and the potential for leveraging this knowledge for crop improvement strategies.

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KEY MESSAGE: This comprehensive review underscores the application of genome editing in plant reproductive biology, including recent advances and challenges associated with it. Genome editing (GE) is a powerful technology that has the potential to accelerate crop improvement by enabling efficient, precise, and rapid engineering of plant genomes. Over the last decade, this technology has rapidly evolved from the use of meganucleases (homing endonucleases), zinc-finger nucleases, transcription activator-like effector nucleases to the use of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (CRISPR/Cas), which has emerged as a popular GE tool in recent times and has been extensively used in several organisms, including plants. GE has been successfully employed in several crops to improve plant reproductive traits. Improving crop reproductive traits is essential for crop yields and securing the world's food supplies. In this review, we discuss the application of GE in various aspects of plant reproductive biology, including its potential application in haploid induction, apomixis, parthenocarpy, development of male sterile lines, and the regulation of self-incompatibility. We also discuss current challenges and future prospects of this technology for crop improvement, focusing on plant reproduction.

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Finlay-Wilkinson regression is a popular method for modeling genotype-environment interaction in plant breeding and crop variety testing. When environment is a random factor, this model may be cast as a factor-analytic variance-covariance structure, implying a regression on random latent environmental variables. This paper reviews such models with a focus on their use in the analysis of multi-environment trials for the purpose of making predictions in a target population of environments. We investigate the implication of random versus fixed effects assumptions, starting from basic analysis-of-variance models, then moving on to factor-analytic models and considering the transition to models involving observable environmental covariates, which promise to provide more accurate and targeted predictions than models with latent environmental variables.

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Plants evolved, over millions of years, complex defense systems against pathogens. Once infected, the interaction between pathogen effector molecules and host receptors triggers plant immune responses, which include apoptosis, systemic immune response, among others. An important protein family responsible for pathogen effector recognition is the nucleotide binding site-leucine repeat rich (NBS-LRR) proteins. The NBS-LRR gene family is the largest disease resistance gene class in plants. These proteins are widely distributed in vascular plants and have a complex multigenic cluster distribution in plant genomes. To counteract the genetic load of such a large gene family on fitness cost, plants evolved a mechanism using post transcriptional gene silencing induced by small RNAs, particularly microRNAs. For the NBS-LRR gene family, the small RNAs involved in this silencing mechanism are mainly the microRNA482/2118 superfamily. This suppression mechanism is relieved upon pathogen infection, thus allowing increased NBS-LRR expression and triggering plant immunity. In this review, we will discuss the biogenesis of microRNAs and secondary RNAs involved in this silencing mechanism, biochemical and structural features of NBS-LRR proteins in response to pathogen effectors and the evolution of microRNA-based silencing mechanism with a focus on the miR482/2118 family. Furthermore, the biotechnological manipulation of microRNA expression, using both transgenic or genome editing approaches to improve cultivated plants will be discussed, with a focus on the miR482/2118 family in soybean.

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The rhizosphere contains both essential nutrients and potentially harmful substances for plant growth. Plants, as sessile organisms, must efficiently absorb the necessary nutrients while actively avoiding the uptake of toxic compounds. Metalloids, which are elements that exhibit properties of both metals and nonmetals, can have different effects on plant growth, ranging from being essential and beneficial to being toxic. The toxicity of metalloids in plants arises due to either the dosage of exposure or the specific elemental type. To utilize or detoxify these elements, plants have developed various transporters that regulate their uptake and distribution in plants. Arguably, genomic sequence analysis suggests the presence of such transporter families throughout the plant kingdom, from chlorophytes to higher plants. These transporters form defined families with related transport preferences. The isoforms within these families have evolved with specialized functions regulated by defined selectivity. Hence, understanding transporters' chemistry to atomic detail is important to achieve desired genetic modifications for crop improvement. Here, we outline various adaptations in plant transport systems to deal with metalloids, including their uptake, distribution, detoxification, and homeostasis in plant tissues. Structural parallels are drawn to other nutrient transporter systems to support emerging themes of functional diversity of active sites of transporters, elucidating adaptations of plants to utilize and extrude metalloid concentrations. Considering the observed physiological importance of metalloids, this review intends to highlight the shared and disparate features in metalloid transport systems and their corresponding nutrient transporters.

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As climate changes and a growing global population continue to escalate the need for greater production capabilities of food crops, technological advances in agricultural and crop research will remain a necessity. While great advances in crop improvement over the past century have contributed to massive increases in yield, classic breeding schemes lack the rate of genetic gain needed to meet future demands. In the past decade, new breeding techniques and tools have been developed to aid in crop improvement. One such advancement is the use of speed breeding. Speed breeding is known as the application of methods that significantly reduce the time between crop generations, thereby streamlining breeding and research efforts. These rapid-generation advancement tactics help to accelerate the pace of crop improvement efforts to sustain food security and meet the food, feed, and fiber demands of the world's growing population. Speed breeding may be achieved through a variety of techniques, including environmental optimization, genomic selection, CRISPR-Cas9 technology, and epigenomic tools. This review aims to discuss these prominent advances in crop breeding technologies and techniques that have the potential to greatly improve plant breeders' ability to rapidly produce vital cultivars.

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Cell-penetrating peptides (CPPs) are short (typically 5-30 amino acids), cationic, amphipathic, or hydrophobic peptides that facilitate the cellular uptake of diverse cargo molecules by eukaryotic cells via direct translocation or endocytosis across the plasma membrane. CPPs can deliver a variety of bioactive cargos, including proteins, peptides, nucleic acids, and small molecules into the cell. Once inside, the delivered cargo may function in the cytosol, nucleus, or other subcellular compartments. Numerous CPPs have been used for studies and drug delivery in mammalian systems. Although CPPs have many potential uses in plant research and agriculture, the application of CPPs in plants remains limited. Here we review the structures and mechanisms of CPPs and highlight their potential applications for sustainable agriculture.

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Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

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Polyamines are involved in several plant physiological processes. In Arabidopsis thaliana, five FAD-dependent polyamine oxidases (AtPAO1 to AtPAO5) contribute to polyamine homeostasis. AtPAO5 catalyzes the back-conversion of thermospermine (T-Spm) to spermidine and plays a role in plant development, xylem differentiation, and abiotic stress tolerance. In the present study, to verify whether T-Spm metabolism can be exploited as a new route to improve stress tolerance in crops and to investigate the underlying mechanisms, tomato (Solanum lycopersicum) AtPAO5 homologs were identified (SlPAO2, SlPAO3, and SlPAO4) and CRISPR/Cas9-mediated loss-of-function slpao3 mutants were obtained. Morphological, molecular, and physiological analyses showed that slpao3 mutants display increased T-Spm levels and exhibit changes in growth parameters, number and size of xylem elements, and expression levels of auxin- and gibberellin-related genes compared to wild-type plants. The slpao3 mutants are also characterized by improved tolerance to drought stress, which can be attributed to a diminished xylem hydraulic conductivity that limits water loss, as well as to a reduced vulnerability to embolism. Altogether, this study evidences conservation, though with some significant variations, of the T-Spm-mediated regulatory mechanisms controlling plant growth and differentiation across different plant species and highlights the T-Spm role in improving stress tolerance while not constraining growth.

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The growing demand for global food production is likely to be a defining issue facing humanity over the next 50 years. To tackle this challenge, there is a desire to bioengineer crops with higher photosynthetic efficiencies, to increase yields. Recently, there has been a growing interest in engineering leaves with higher mesophyll conductance (gm), which would allow CO2 to move more efficiently from the substomatal cavities to the chloroplast stroma. However, if crop yield gains are to be realised through this approach, it is essential that the methodological limitations associated with estimating gm are fully appreciated. In this review, we summarise these limitations, and outline the uncertainties and assumptions that can affect the final estimation of gm. Furthermore, we critically assess the predicted quantitative effect that elevating gm will have on assimilation rates in crop species. We highlight the need for more theoretical modelling to determine whether altering gm is truly a viable route to improve crop performance. Finally, we offer suggestions to guide future research on gm, which will help mitigate the uncertainty inherently associated with estimating this parameter.

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