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1
Zhou, Jian-Min, and Wei Wang. "Single-cell multi-omics tell the secrets of plant immunity." Molecular Cell 85, no. 5 (2025): 862–64. https://doi.org/10.1016/j.molcel.2025.02.008.
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Dikobe, Tshegofatso, Kedibone Masenya, and Madira C. Manganyi. "Molecular technologies ending with ‘omics’: The driving force toward sustainable plant production and protection." F1000Research 12 (May 10, 2023): 480. http://dx.doi.org/10.12688/f1000research.131413.1.
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As the global population is surging, the agricultural industry is required to meet the food demand while simultaneously providing eco-friendly sustainable crops that can withstand numerous abiotic and biotic stresses. The current era requires high-throughput biotechnology approaches to alleviate the current plant production and protection crisis. Omics approaches are regarded as a collection of high throughput technologies ending with “omics” such as genomics, proteomics, transcriptomics, metabolomics, phenomics and epigenomics. Furthermore, omics provide the best tactic to increase high quality crop production yield. A body of evidence has shown that microbial diversity, abundance, composition, functional gene patterns, and metabolic pathways at the genome level could also assist in understanding the contributions of the microbial community towards plant growth and protection. In addition, the link between plant genomes and phenotypes under physiological and environmental settings is highlighted by the integration of functional genomics with other omics. However, application of single omics technologies results in one disciplinary solution while raising multiple questions without answers. To address these challenges, we need to find new age solutions. For instance, omics technologies focusing on plant production and protection. Multi-layered information gathered from systems biology provides a comprehensive understanding of molecular regulator networks for improving plant growth and protection, which is supported by large-scale omics datasets. The conclusion drawn from the in-depth information is the holistic integration of multi-disciplinary omics approaches to pave the way towards eco-friendly, sustainable, agricultural productivity.
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Brophy, Jennifer A. N. "Toward synthetic plant development." Plant Physiology 188, no. 2 (2021): 738–48. http://dx.doi.org/10.1093/plphys/kiab568.
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Abstract The ability to engineer plant form will enable the production of novel agricultural products designed to tolerate extreme stresses, boost yield, reduce waste, and improve manufacturing practices. While historically, plants were altered through breeding to change their size or shape, advances in our understanding of plant development and our ability to genetically engineer complex eukaryotes are leading to the direct engineering of plant structure. In this review, I highlight the central role of auxin in plant development and the synthetic biology approaches that could be used to turn auxin-response regulators into powerful tools for modifying plant form. I hypothesize that recoded, gain-of-function auxin response proteins combined with synthetic regulation could be used to override endogenous auxin signaling and control plant structure. I also argue that auxin-response regulators are key to engineering development in nonmodel plants and that single-cell -omics techniques will be essential for characterizing and modifying auxin response in these plants. Collectively, advances in synthetic biology, single-cell -omics, and our understanding of the molecular mechanisms underpinning development have set the stage for a new era in the engineering of plant structure.
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de Souza, Leonardo Perez, Monica Borghi, and Alisdair Fernie. "Plant Single-Cell Metabolomics—Challenges and Perspectives." International Journal of Molecular Sciences 21, no. 23 (2020): 8987. http://dx.doi.org/10.3390/ijms21238987.
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Omics approaches for investigating biological systems were introduced in the mid-1990s and quickly consolidated to become a fundamental pillar of modern biology. The idea of measuring the whole complement of genes, transcripts, proteins, and metabolites has since become widespread and routinely adopted in the pursuit of an infinity of scientific questions. Incremental improvements over technical aspects such as sampling, sensitivity, cost, and throughput pushed even further the boundaries of what these techniques can achieve. In this context, single-cell genomics and transcriptomics quickly became a well-established tool to answer fundamental questions challenging to assess at a whole tissue level. Following a similar trend as the original development of these techniques, proteomics alternatives for single-cell exploration have become more accessible and reliable, whilst metabolomics lag behind the rest. This review summarizes state-of-the-art technologies for spatially resolved metabolomics analysis, as well as the challenges hindering the achievement of sensu stricto metabolome coverage at the single-cell level. Furthermore, we discuss several essential contributions to understanding plant single-cell metabolism, finishing with our opinion on near-future developments and relevant scientific questions that will hopefully be tackled by incorporating these new exciting technologies.
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Katam, Ramesh, Chuwei Lin, Kirstie Grant, Chaquayla S. Katam, and Sixue Chen. "Advances in Plant Metabolomics and Its Applications in Stress and Single-Cell Biology." International Journal of Molecular Sciences 23, no. 13 (2022): 6985. http://dx.doi.org/10.3390/ijms23136985.
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In the past two decades, the post-genomic era envisaged high-throughput technologies, resulting in more species with available genome sequences. In-depth multi-omics approaches have evolved to integrate cellular processes at various levels into a systems biology knowledge base. Metabolomics plays a crucial role in molecular networking to bridge the gaps between genotypes and phenotypes. However, the greater complexity of metabolites with diverse chemical and physical properties has limited the advances in plant metabolomics. For several years, applications of liquid/gas chromatography (LC/GC)-mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been constantly developed. Recently, ion mobility spectrometry (IMS)-MS has shown utility in resolving isomeric and isobaric metabolites. Both MS and NMR combined metabolomics significantly increased the identification and quantification of metabolites in an untargeted and targeted manner. Thus, hyphenated metabolomics tools will narrow the gap between the number of metabolite features and the identified metabolites. Metabolites change in response to environmental conditions, including biotic and abiotic stress factors. The spatial distribution of metabolites across different organs, tissues, cells and cellular compartments is a trending research area in metabolomics. Herein, we review recent technological advancements in metabolomics and their applications in understanding plant stress biology and different levels of spatial organization. In addition, we discuss the opportunities and challenges in multiple stress interactions, multi-omics, and single-cell metabolomics.
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Chele, Kekeletso H., Lizelle A. Piater, Justin J. J. van der van der Hooft, and Fidele Tugizimana. "Bridging Ethnobotanical Knowledge and Multi-Omics Approaches for Plant-Derived Natural Product Discovery." Metabolites 15, no. 6 (2025): 362. https://doi.org/10.3390/metabo15060362.
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For centuries, plant-derived natural products (NPs) have been fundamental to traditional medicine, providing essential therapeutic compounds. Ethnobotanical knowledge has historically guided NP discovery, leading to the identification of key pharmaceuticals such as aspirin, morphine, and artemisinin. However, conventional bioactivity-guided fractionation methods for NP isolation are labour-intensive and can result in the loss of bioactive properties due to the focus on a single compound. Advances in omics sciences—genomics, transcriptomics, proteomics, metabolomics, and phenomics—coupled with computational tools have altogether revolutionised NP research by enabling high-throughput screening and more precise compound identification. This review explores how integrating traditional medicinal knowledge with multi-omics strategies enhances NP discovery. We highlight emerging bioinformatics tools, mass spectrometry techniques, and metabologenomics approaches that accelerate the identification, annotation, and functional characterisation of plant-derived metabolites. Additionally, we discuss challenges in omics data integration and propose strategies to harness ethnobotanical knowledge for targeted NP discovery and drug development. By combining traditional wisdom with modern scientific advancements, this integrated approach paves the way for novel therapeutic discoveries and the sustainable utilisation of medicinal plants.
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Martínez-Esteso, María José, Jaime Morante-Carriel, Antonio Samper-Herrero, et al. "Proteomics: An Essential Tool to Study Plant-Specialized Metabolism." Biomolecules 14, no. 12 (2024): 1539. https://doi.org/10.3390/biom14121539.
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Plants are a valuable source of specialized metabolites that provide a plethora of therapeutic applications. They are natural defenses that plants use to adapt and respond to their changing environment. Decoding their biosynthetic pathways and understanding how specialized plant metabolites (SPMs) respond to biotic or abiotic stress will provide vital knowledge for plant biology research and its application for the future sustainable production of many SPMs of interest. Here, we focus on the proteomic approaches and strategies that help with the study of plant-specialized metabolism, including the: (i) discovery of key enzymes and the clarification of their biosynthetic pathways; (ii) study of the interconnection of both primary (providers of carbon and energy for SPM production) and specialized (secondary) metabolism; (iii) study of plant responses to biotic and abiotic stress; (iv) study of the regulatory mechanisms that direct their biosynthetic pathways. Proteomics, as exemplified in this review by the many studies performed to date, is a powerful tool that forms part of omics-driven research. The proteomes analysis provides an additional unique level of information, which is absent from any other omics studies. Thus, an integrative analysis, considered versus a single omics analysis, moves us more closely toward a closer interpretation of real cellular processes. Finally, this work highlights advanced proteomic technologies with immediate applications in the field.
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Bian, Jianwen, Zelong Zhuang, Xiangzhuo Ji, et al. "Research Progress of Single-Cell Transcriptome Sequencing Technology in Plants." Agronomy 14, no. 11 (2024): 2530. http://dx.doi.org/10.3390/agronomy14112530.
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Multicellular organisms exhibit inherent cellular heterogeneity that cannot be captured by traditional high-throughput sequencing techniques, resulting in the unique cellular characteristics of individual cells being neglected. Single-cell transcriptome sequencing (scRNA-seq) technology can be used to determine the gene expression levels of each individual cell, facilitating the study of intercellular expression heterogeneity. This review provides a comprehensive overview of the development and applications of scRNA-seq technology in plant research. We highlight the significance of integrating single-cell multi-omics approaches to achieve a holistic understanding of plant systems. Additionally, we discuss the current challenges and future research directions for scRNA-seq technology in plant studies, aiming to offer valuable insights for its application across various plant species.
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Yang, Ming-Chao, Zi-Chen Wu, Liang-Liang Huang, Farhat Abbas, and Hui-Cong Wang. "Systematic Methods for Isolating High Purity Nuclei from Ten Important Plants for Omics Interrogation." Cells 11, no. 23 (2022): 3919. http://dx.doi.org/10.3390/cells11233919.
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Recent advances in developmental biology have been made possible by using multi-omic studies at single cell resolution. However, progress in plants has been slowed, owing to the tremendous difficulty in protoplast isolation from most plant tissues and/or oversize protoplasts during flow cytometry purification. Surprisingly, rapid innovations in nucleus research have shed light on plant studies in single cell resolution, which necessitates high quality and efficient nucleus isolation. Herein, we present efficient nuclei isolation protocols from the leaves of ten important plants including Arabidopsis, rice, maize, tomato, soybean, banana, grape, citrus, apple, and litchi. We provide a detailed procedure for nucleus isolation, flow cytometry purification, and absolute nucleus number quantification. The nucleus isolation buffer formula of the ten plants tested was optimized, and the results indicated a high nuclei yield. Microscope observations revealed high purity after flow cytometry sorting, and the DNA and RNA quality extract from isolated nuclei were monitored by using the nuclei in cell division cycle and single nucleus RNA sequencing (snRNA-seq) studies, with detailed procedures provided. The findings indicated that nucleus yield and quality meet the requirements of snRNA-seq, cell division cycle, and likely other omic studies. The protocol outlined here makes it feasible to perform plant omic studies at single cell resolution.
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Gomes de Oliveira Dal’Molin, Cristiana, and Lars Keld Nielsen. "Plant genome-scale reconstruction: from single cell to multi-tissue modelling and omics analyses." Current Opinion in Biotechnology 49 (February 2018): 42–48. http://dx.doi.org/10.1016/j.copbio.2017.07.009.
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Berger, Margot M. J., Vincent Lailheugue, Gergana Zhelyazova, et al. "One prep to catch them all: “2 in 1”, an efficient method for the simultaneous extraction of DNA and RNA from Grapevine tissues." OENO One 56, no. 2 (2022): 1–13. http://dx.doi.org/10.20870/oeno-one.2022.56.2.5000.
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Recent advances in our understanding of plant physiology and adaptation to the environment are tightly related to the development of ‘omics’ technologies such as metabolomics, transcriptomics, genomics and epigenomics that allow a more comprehensive view of the plant functioning. In this context, the ability to extract DNA and RNA from small amounts of plant material can be a limiting factor, worse in the case of non-model plants for which efficient nucleic extraction procedures are lacking. In the case of grapevine, extraction of high-quality DNA is typically limited by the high polyphenolic and polysaccharide contents of the different tissues. Here, we propose an adaptation of the method of Reid et al. (2006) that allows the simultaneous and efficient extraction of DNA and RNA from grapevine vegetative and berry tissues from in vitro grown grapevine plants and cells and from other plants. The protocol allows the extraction of high-quality RNA and DNA for standard molecular biology methods as well as for Next Generation Sequencing (NGS). It also works with a limited amount of plant material, such as young developing buds, and provides the means to analyse “omics” data from a single plant sample.
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Watanabe, Mutsumi, and Rainer Hoefgen. "Sulphur systems biology—making sense of omics data." Journal of Experimental Botany 70, no. 16 (2019): 4155–70. http://dx.doi.org/10.1093/jxb/erz260.
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Abstract Systems biology approaches have been applied over the last two decades to study plant sulphur metabolism. These ‘sulphur-omics’ approaches have been developed in parallel with the advancing field of systems biology, which is characterized by permanent improvements of high-throughput methods to obtain system-wide data. The aim is to obtain a holistic view of sulphur metabolism and to generate models that allow predictions of metabolic and physiological responses. Besides known sulphur-responsive genes derived from previous studies, numerous genes have been identified in transcriptomics studies. This has not only increased our knowledge of sulphur metabolism but has also revealed links between metabolic processes, thus indicating a previously unexpected complex interconnectivity. The identification of response and control networks has been supported through metabolomics and proteomics studies. Due to the complex interlacing nature of biological processes, experimental validation using targeted or systems approaches is ongoing. There is still room for improvement in integrating the findings from studies of metabolomes, proteomes, and metabolic fluxes into a single unifying concept and to generate consistent models. We therefore suggest a joint effort of the sulphur research community to standardize data acquisition. Furthermore, focusing on a few different model plant systems would help overcome the problem of fragmented data, and would allow us to provide a standard data set against which future experiments can be designed and compared.
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Vidal, Catalina, Felipe González, Christian Santander, et al. "Management of Rhizosphere Microbiota and Plant Production under Drought Stress: A Comprehensive Review." Plants 11, no. 18 (2022): 2437. http://dx.doi.org/10.3390/plants11182437.
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Drought generates a complex scenario worldwide in which agriculture should urgently be reframed from an integrative point of view. It includes the search for new water resources and the use of tolerant crops and genotypes, improved irrigation systems, and other less explored alternatives that are very important, such as biotechnological tools that may increase the water use efficiency. Currently, a large body of evidence highlights the role of specific strains in the main microbial rhizosphere groups (arbuscular mycorrhizal fungi, yeasts, and bacteria) on increasing the drought tolerance of their host plants through diverse plant growth-promoting (PGP) characteristics. With this background, it is possible to suggest that the joint use of distinct PGP microbes could produce positive interactions or additive beneficial effects on their host plants if their co-inoculation does not generate antagonistic responses. To date, such effects have only been partially analyzed by using single omics tools, such as genomics, metabolomics, or proteomics. However, there is a gap of information in the use of multi-omics approaches to detect interactions between PGP and host plants. This approach must be the next scale-jump in the study of the interaction of soil–plant–microorganism. In this review, we analyzed the constraints posed by drought in the framework of an increasing global demand for plant production, integrating the important role played by the rhizosphere biota as a PGP agent. Using multi-omics approaches to understand in depth the processes that occur in plants in the presence of microorganisms can allow us to modulate their combined use and drive it to increase crop yields, improving production processes to attend the growing global demand for food.
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O’Banion, Bridget S., Lindsey O’Neal, Gladys Alexandre, and Sarah L. Lebeis. "Bridging the Gap Between Single-Strain and Community-Level Plant-Microbe Chemical Interactions." Molecular Plant-Microbe Interactions® 33, no. 2 (2020): 124–34. http://dx.doi.org/10.1094/mpmi-04-19-0115-cr.
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Although the influence of microbiomes on the health of plant hosts is evident, specific mechanisms shaping the structure and dynamics of microbial communities in the phyllosphere and rhizosphere are only beginning to become clear. Traditionally, plant–microbe interactions have been studied using cultured microbial isolates and plant hosts but the rising use of ‘omics tools provides novel snapshots of the total complex community in situ. Here, we discuss the recent advances in tools and techniques used to monitor plant–microbe interactions and the chemical signals that influence these relationships in above- and belowground tissues. Particularly, we highlight advances in integrated microscopy that allow observation of the chemical exchange between individual plant and microbial cells, as well as high-throughput, culture-independent approaches to investigate the total genetic and metabolic contribution of the community. The chemicals discussed have been identified as relevant signals across experimental spectrums. However, mechanistic insight into the specific interactions mediated by many of these chemicals requires further testing. Experimental designs that attempt to bridge the gap in biotic complexity between single strains and whole communities will advance our understanding of the chemical signals governing plant–microbe associations in the rhizosphere and phyllosphere.
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Ye, Chonghang, Kai Li, Weicheng Sun, et al. "Biological Prior Knowledge-Embedded Deep Neural Network for Plant Genomic Prediction." Genes 16, no. 4 (2025): 411. https://doi.org/10.3390/genes16040411.
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Background/Objectives: Genomic prediction is a powerful approach that predicts phenotypic traits from genotypic information, enabling the acceleration of trait improvement in plant breeding. Traditional genomic prediction methods have primarily relied on linear mixed models, such as Genomic Best Linear Unbiased Prediction (GBLUP), and conventional machine learning methods like Support Vector Regression (SVR). Traditional methods are limited in handling high-dimensional data and nonlinear relationships. Thus, deep learning methods have also been applied to genomic prediction in recent years. Methods: We proposed iADEP, Integrated Additive, Dominant, and Epistatic Prediction model based on deep learning. Specifically, single nucleotide polymorphism (SNP) data integrating latent genetic interactions and genome-wide association study results as biological prior knowledge are fused to an SNP embedding block, which is then input to a local encoder. The local encoder is fused with an omic-data-incorporated global decoder through a multi-head attention mechanism, followed by multilayer perceptrons. Results: Firstly, we demonstrated through experiments on four datasets that iADEP outperforms existing methods in genotype-to-phenotype prediction. Secondly, we validated the effectiveness of SNP embedding through ablation experiments. Third, we provided an available module for combining other omics data in iADEP and propose a novel method for fusing them. Fourthly, we explored the impact of feature selection on iADEP performance and conclude that utilizing the full set of SNPs generally provides optimal results. Finally, by altering the partition of training and testing sets, we investigated the differences between transductive learning and inductive learning. Conclusions: iADEP provides a new approach for AI breeding, a promising method that integrates biological prior knowledge and enables combination with other omics data.
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Coulibaly, Issa, and Grier P. Page. "Bioinformatic Tools for Inferring Functional Information from Plant Microarray Data II: Analysis Beyond Single Gene." International Journal of Plant Genomics 2008 (July 3, 2008): 1–13. http://dx.doi.org/10.1155/2008/893941.
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While it is possible to interpret microarray experiments a single gene at a time, most studies generate long lists of differentially expressed genes whose interpretation requires the integration of prior biological knowledge. This prior knowledge is stored in various public and private databases and covers several aspects of gene function and biological information. In this review, we will describe the tools and places where to find prior accurate biological information and how to process and incorporate them to interpret microarray data analyses. Here, we highlight selected tools and resources for gene class level ontology analysis (Section 2), gene coexpression analysis (Section 3), gene network analysis (Section 4), biological pathway analysis (Section 5), analysis of transcriptional regulation (Section 6), and omics data integration (Section 7). The overall goal of this review is to provide researchers with tools and information to facilitate the interpretation of microarray data.
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Murai, Toshiyuki, and Satoru Matsuda. "Integrated Multimodal Omics and Dietary Approaches for the Management of Neurodegeneration." Epigenomes 7, no. 3 (2023): 20. http://dx.doi.org/10.3390/epigenomes7030020.
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Neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease, are caused by a combination of multiple events that damage neuronal function. A well-characterized biomarker of neurodegeneration is the accumulation of proteinaceous aggregates in the brain. However, the gradually worsening symptoms of neurodegenerative diseases are unlikely to be solely due to the result of a mutation in a single gene, but rather a multi-step process involving epigenetic changes. Recently, it has been suggested that a fraction of epigenetic alternations may be correlated to neurodegeneration in the brain. Unlike DNA mutations, epigenetic alterations are reversible, and therefore raise the possibilities for therapeutic intervention, including dietary modifications. Additionally, reactive oxygen species may contribute to the pathogenesis of Alzheimer’s disease and Parkinson’s disease through epigenetic alternation. Given that the antioxidant properties of plant-derived phytochemicals are likely to exhibit pleiotropic effects against ROS-mediated epigenetic alternation, dietary intervention may be promising for the management of neurodegeneration in these diseases. In this review, the state-of-the-art applications using single-cell multimodal omics approaches, including epigenetics, and dietary approaches for the identification of novel biomarkers and therapeutic approaches for the treatment of neurodegenerative diseases are discussed.
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Li, Haozhen, Kangkang Song, Xiaohua Zhang, et al. "Application of Multi-Perspectives in Tea Breeding and the Main Directions." International Journal of Molecular Sciences 24, no. 16 (2023): 12643. http://dx.doi.org/10.3390/ijms241612643.
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Tea plants are an economically important crop and conducting research on tea breeding contributes to enhancing the yield and quality of tea leaves as well as breeding traits that satisfy the requirements of the public. This study reviews the current status of tea plants germplasm resources and their utilization, which has provided genetic material for the application of multi-omics, including genomics and transcriptomics in breeding. Various molecular markers for breeding were designed based on multi-omics, and available approaches in the direction of high yield, quality and resistance in tea plants breeding are proposed. Additionally, future breeding of tea plants based on single-cellomics, pangenomics, plant–microbe interactions and epigenetics are proposed and provided as references. This study aims to provide inspiration and guidance for advancing the development of genetic breeding in tea plants, as well as providing implications for breeding research in other crops.
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Knoch, Dominic, Christian R. Werner, Rhonda C. Meyer, et al. "Multi-omics-based prediction of hybrid performance in canola." Theoretical and Applied Genetics 134, no. 4 (2021): 1147–65. http://dx.doi.org/10.1007/s00122-020-03759-x.
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Abstract Key message Complementing or replacing genetic markers with transcriptomic data and use of reproducing kernel Hilbert space regression based on Gaussian kernels increases hybrid prediction accuracies for complex agronomic traits in canola. In plant breeding, hybrids gained particular importance due to heterosis, the superior performance of offspring compared to their inbred parents. Since the development of new top performing hybrids requires labour-intensive and costly breeding programmes, including testing of large numbers of experimental hybrids, the prediction of hybrid performance is of utmost interest to plant breeders. In this study, we tested the effectiveness of hybrid prediction models in spring-type oilseed rape (Brassica napus L./canola) employing different omics profiles, individually and in combination. To this end, a population of 950 F1 hybrids was evaluated for seed yield and six other agronomically relevant traits in commercial field trials at several locations throughout Europe. A subset of these hybrids was also evaluated in a climatized glasshouse regarding early biomass production. For each of the 477 parental rapeseed lines, 13,201 single nucleotide polymorphisms (SNPs), 154 primary metabolites, and 19,479 transcripts were determined and used as predictive variables. Both, SNP markers and transcripts, effectively predict hybrid performance using (genomic) best linear unbiased prediction models (gBLUP). Compared to models using pure genetic markers, models incorporating transcriptome data resulted in significantly higher prediction accuracies for five out of seven agronomic traits, indicating that transcripts carry important information beyond genomic data. Notably, reproducing kernel Hilbert space regression based on Gaussian kernels significantly exceeded the predictive abilities of gBLUP models for six of the seven agronomic traits, demonstrating its potential for implementation in future canola breeding programmes.
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Ali, Ahmad, Mehran Khan, Rahat Sharif, Muhammad Mujtaba, and San-Ji Gao. "Sugarcane Omics: An Update on the Current Status of Research and Crop Improvement." Plants 8, no. 9 (2019): 344. http://dx.doi.org/10.3390/plants8090344.
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Sugarcane is an important crop from Poaceae family, contributing about 80% of the total world’s sucrose with an annual value of around US$150 billion. In addition, sugarcane is utilized as a raw material for the production of bioethanol, which is an alternate source of renewable energy. Moving towards sugarcane omics, a remarkable success has been achieved in gene transfer from a wide variety of plant and non-plant sources to sugarcane, with the accessibility of efficient transformation systems, selectable marker genes, and genetic engineering gears. Genetic engineering techniques make possible to clone and characterize useful genes and also to improve commercially important traits in elite sugarcane clones that subsequently lead to the development of an ideal cultivar. Sugarcane is a complex polyploidy crop, and hence no single technique has been found to be the best for the confirmation of polygenic and phenotypic characteristics. To better understand the application of basic omics in sugarcane regarding agronomic characters and industrial quality traits as well as responses to diverse biotic and abiotic stresses, it is important to explore the physiology, genome structure, functional integrity, and collinearity of sugarcane with other more or less similar crops/plants. Genetic improvements in this crop are hampered by its complex genome, low fertility ratio, longer production cycle, and susceptibility to several biotic and abiotic stresses. Biotechnology interventions are expected to pave the way for addressing these obstacles and improving sugarcane crop. Thus, this review article highlights up to date information with respect to how advanced data of omics (genomics, transcriptomic, proteomics and metabolomics) can be employed to improve sugarcane crops.
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Leão, André Pereira, Cleiton Barroso Bittencourt, Thalliton Luiz Carvalho da Silva, et al. "Insights from a Multi-Omics Integration (MOI) Study in Oil Palm (Elaeis guineensis Jacq.) Response to Abiotic Stresses: Part Two—Drought." Plants 11, no. 20 (2022): 2786. http://dx.doi.org/10.3390/plants11202786.
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Drought and salinity are two of the most severe abiotic stresses affecting agriculture worldwide and bear some similarities regarding the responses of plants to them. The first is also known as osmotic stress and shows similarities mainly with the osmotic effect, the first phase of salinity stress. Multi-Omics Integration (MOI) offers a new opportunity for the non-trivial challenge of unraveling the mechanisms behind multigenic traits, such as drought and salinity resistance. The current study carried out a comprehensive, large-scale, single-omics analysis (SOA) and MOI studies on the leaves of young oil palm plants submitted to water deprivation. After performing SOA, 1955 DE enzymes from transcriptomics analysis, 131 DE enzymes from proteomics analysis, and 269 DE metabolites underwent MOI analysis, revealing several pathways affected by this stress, with at least one DE molecule in all three omics platforms used. Moreover, the similarities and dissimilarities in the molecular response of those plants to those two abiotic stresses underwent mapping. Cysteine and methionine metabolism (map00270) was the most affected pathway in all scenarios evaluated. The correlation analysis revealed that 91.55% of those enzymes expressed under both stresses had similar qualitative profiles, corroborating the already known fact that plant responses to drought and salinity show several similarities. At last, the results shed light on some candidate genes for engineering crop species resilient to both abiotic stresses.
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Wang, Xinfeng, Yaxuan Wang, Houhong Yang, et al. "Integrative Omics Strategies for Understanding and Combating Brown Planthopper Virulence in Rice Production: A Review." International Journal of Molecular Sciences 25, no. 20 (2024): 10981. http://dx.doi.org/10.3390/ijms252010981.
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The brown planthopper (Nilaparvata lugens, BPH) is a serious insect pest responsible for causing immense economic losses to rice growers around the globe. The development of high-throughput sequencing technologies has significantly improved the research on this pest, and its genome structure, gene expression profiles, and host–plant interactions are being unveiled. The integration of genomic sequencing, transcriptomics, proteomics, and metabolomics has greatly increased our understanding of the biological characteristics of planthoppers, which will benefit the identification of resistant rice varieties and strategies for their control. Strategies like more optimal genome assembly and single-cell RNA-seq help to update our knowledge of gene control structure and cell type-specific usage, shedding light on how planthoppers adjust as well. However, to date, a comprehensive genome-wide investigation of the genetic interactions and population dynamics of BPHs has yet to be exhaustively performed using these next-generation omics technologies. This review summarizes the recent advances and new perspectives regarding the use of omics data for the BPH, with specific emphasis on the integration of both fields to help develop more sustainable pest management strategies. These findings, in combination with those of post-transcriptional and translational modifications involving non-coding RNAs as well as epigenetic variations, further detail intricate host–brown planthopper interaction dynamics, especially regarding resistant rice varieties. Finally, the symbiogenesis of the symbiotic microbial community in a planthopper can be characterized through metagenomic approaches, and its importance in enhancing virulence traits would offer novel opportunities for plant protection by manipulating host–microbe interactions. The concerted diverse omics approaches collectively identified the holistic and complex mechanisms of virulence variation in BPHs, which enables efficient deployment into rice resistance breeding as well as sustainable pest management.
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Lv, Zhuo, Shuaijun Jiang, Shuxin Kong, et al. "Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants." Plants 13, no. 12 (2024): 1679. http://dx.doi.org/10.3390/plants13121679.
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“Omics” typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell’s metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.
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Xu, Xiaocai, Cezary Smaczniak, Jose M. Muino, and Kerstin Kaufmann. "Cell identity specification in plants: lessons from flower development." Journal of Experimental Botany 72, no. 12 (2021): 4202–17. http://dx.doi.org/10.1093/jxb/erab110.
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Abstract Multicellular organisms display a fascinating complexity of cellular identities and patterns of diversification. The concept of ‘cell type’ aims to describe and categorize this complexity. In this review, we discuss the traditional concept of cell types and highlight the impact of single-cell technologies and spatial omics on the understanding of cellular differentiation in plants. We summarize and compare position-based and lineage-based mechanisms of cell identity specification using flower development as a model system. More than understanding ontogenetic origins of differentiated cells, an important question in plant science is to understand their position- and developmental stage-specific heterogeneity. Combinatorial action and crosstalk of external and internal signals is the key to cellular heterogeneity, often converging on transcription factors that orchestrate gene expression programs.
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Santos-Silva, Carlos André dos, José Ribamar Costa Ferreira-Neto, Vinícius Costa Amador, et al. "From Gene to Transcript and Peptide: A Deep Overview on Non-Specific Lipid Transfer Proteins (nsLTPs)." Antibiotics 12, no. 5 (2023): 939. http://dx.doi.org/10.3390/antibiotics12050939.
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Non-specific lipid transfer proteins (nsLTPs) stand out among plant-specific peptide superfamilies due to their multifaceted roles in plant molecular physiology and development, including their protective functions against pathogens. These antimicrobial agents have demonstrated remarkable efficacy against bacterial and fungal pathogens. The discovery of plant-originated, cysteine-rich antimicrobial peptides such as nsLTPs has paved the way for exploring the mentioned organisms as potential biofactories for synthesizing antimicrobial compounds. Recently, nsLTPs have been the focus of a plethora of research and reviews, providing a functional overview of their potential activity. The present work compiles relevant information on nsLTP omics and evolution, and it adds meta-analysis of nsLTPs, including: (1) genome-wide mining in 12 plant genomes not studied before; (2) latest common ancestor analysis (LCA) and expansion mechanisms; (3) structural proteomics, scrutinizing nsLTPs’ three-dimensional structure/physicochemical characteristics in the context of nsLTP classification; and (4) broad nsLTP spatiotemporal transcriptional analysis using soybean as a study case. Combining a critical review with original results, we aim to integrate high-quality information in a single source to clarify unexplored aspects of this important gene/peptide family.
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Joshi, Shubham, Viswanathan Chinnusamy, and Rohit Joshi. "Root System Architecture and Omics Approaches for Belowground Abiotic Stress Tolerance in Plants." Agriculture 12, no. 10 (2022): 1677. http://dx.doi.org/10.3390/agriculture12101677.
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Plant growth and productivity is negatively affected by several abiotic stresses. To overcome the antagonistic effect of a changing environment, plants have evolved several modifications at the physiological as well as molecular levels. Besides being a vital organ for a plant’s nutrient uptake, roots also plays a significant role in abiotic stress regulation. This review provides insight into changing Root System Architecture (RSA) under varying environmental stimuli using high-throughput omics technologies. Several next-generation and high-throughput omics technologies, such as phenomics, genomics, transcriptomics, proteomics, and metabolomics, will help in the analysis of the response of root architectural traits under climatic vagaries and their impact on crop yield. Various phenotypic technologies have been implied for the identification of diverse root traits in the field as well as laboratory conditions, such as root-box pinboards, rhizotrons, shovelomics, ground-penetrating radar, etc. These phenotypic analyses also help in identifying the genetic regulation of root-related traits in different crops. High-throughput genomic as well as transcriptome analysis has led researchers to unravel the role of the root system in response to these environmental cues, even at the single-cell level. Detailed analysis at the protein and metabolite levels can provide a better understanding of the response of roots under different abiotic stresses. These technologies will help in the improvement of crop productivity and development of resistant varieties.
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Liu, Haipei, Amanda J. Able, and Jason A. Able. "Integrated Analysis of Small RNA, Transcriptome, and Degradome Sequencing Reveals the Water-Deficit and Heat Stress Response Network in Durum Wheat." International Journal of Molecular Sciences 21, no. 17 (2020): 6017. http://dx.doi.org/10.3390/ijms21176017.
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Water-deficit and heat stress negatively impact crop production. Mechanisms underlying the response of durum wheat to such stresses are not well understood. With the new durum wheat genome assembly, we conducted the first multi-omics analysis with next-generation sequencing, providing a comprehensive description of the durum wheat small RNAome (sRNAome), mRNA transcriptome, and degradome. Single and combined water-deficit and heat stress were applied to stress-tolerant and -sensitive Australian genotypes to study their response at multiple time-points during reproduction. Analysis of 120 sRNA libraries identified 523 microRNAs (miRNAs), of which 55 were novel. Differentially expressed miRNAs (DEMs) were identified that had significantly altered expression subject to stress type, genotype, and time-point. Transcriptome sequencing identified 49,436 genes, with differentially expressed genes (DEGs) linked to processes associated with hormone homeostasis, photosynthesis, and signaling. With the first durum wheat degradome report, over 100,000 transcript target sites were characterized, and new miRNA-mRNA regulatory pairs were discovered. Integrated omics analysis identified key miRNA-mRNA modules (particularly, novel pairs of miRNAs and transcription factors) with antagonistic regulatory patterns subject to different stresses. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis revealed significant roles in plant growth and stress adaptation. Our research provides novel and fundamental knowledge, at the whole-genome level, for transcriptional and post-transcriptional stress regulation in durum wheat.
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Britz, Margaret L., and Arnold L. Demain. "Industrial revolution with microorganisms." Microbiology Australia 33, no. 3 (2012): 91. http://dx.doi.org/10.1071/ma12091.
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Mankind has used microbes from the dawn of history to perform services and produce useful chemicals and bioactives. Mixed complex communities, which are resilient over time, preserved food, made alcoholic beverages and treated wastes, all in the absence of an understanding of the underlying biological processes. Moving to single microbial transformation systems led to high-level production of primary (amino acids, nucleotides, vitamins ? used as flavour-enhancing agents, nutritional supplements and pharmaceuticals ? solvents and organic acids, including biofuels) and secondary (pharmaceuticals, enzyme inhibitors, bio-herbicides and pesticides, plant growth regulators) metabolites and bioactives (including bacteriocins and enzymes). Several hallmark discoveries in microbiology and other sciences over the last 60 years transformed our ability to discover, manipulate, enhance and derive commercial benefit from industrial applications of microorganisms. This article attempts to capture some of the key discoveries that revolutionised industrial microbiology and speculates about where the ?omics? revolution will take us next.
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Li, Zhenkai, Xin Luo, Yanli Yao, et al. "Integrated Analysis of Metabolomics, Flavoromics, and Transcriptomics for Evaluating New Varieties of Amomum villosum Lour." Plants 13, no. 17 (2024): 2382. http://dx.doi.org/10.3390/plants13172382.
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Amomum villosum Lour. (A. villosum) is the original plant of the medicinal and culinary spice Amomi Fructus (Sharen) and is an important economic crop in the Lingnan region of China. During the cultivation and production of A. villosum, prolonged reliance on single asexual reproduction has exacerbated the degradation of its varieties, leading to inconsistent yields and quality. Building upon earlier cultivar selection efforts, this study provides a comprehensive evaluation of two newly bred A. villosum varieties (A11 and A12) from perspectives including plant traits, product characteristics, active ingredients, and multi-omics analysis. It was found that A12 plants display enhanced robustness, more aromatic fruits, higher yields, and elevated levels of bornyl acetate, A11 shows the advantage of a high camphor content, and the different metabolites and differentially expressed genes of the two varieties were significantly enriched in multiple metabolic pathways. Additionally, A12 contained more terpenoids and substances with aromatic odors such as sweet, fruity, floral, and green. Furthermore, a key gene (Wv_032842) regulating the acetylation of bornyl was discovered, and its significantly higher expression, in A12. In conclusion, this study has a guiding significance for the evaluation of germplasm resources and the breeding of excellent varieties of A. villosum.
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Fraser, Paul D., Asaph Aharoni, Robert D. Hall, et al. "Metabolomics should be deployed in the identification and characterization of gene‐edited crops." Plant Journal 102 (January 10, 2020): 897–902. https://doi.org/10.1111/tpj.14679.
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Gene‐editing techniques are currently revolutionizing biology, allowing far greater precision than previous mutagenic and transgenic approaches. They are becoming applicable to a wide range of plant species and biological processes. Gene editing can rapidly improve a range of crop traits, including disease resistance, abiotic stress tolerance, yield, nutritional quality and additional consumer traits. Unlike transgenic approaches, however, it is not facile to forensically detect gene‐editing events at the molecular level, as no foreign DNA exists in the elite line. These limitations in molecular detection approaches are likely to focus more attention on the products generated from the technology than on the process in itself. Rapid advances in sequencing and genome assembly increasingly facilitate genome sequencing as a means of characterizing new varieties generated by gene‐editing techniques. Nevertheless, subtle edits such as single base changes or small deletions may be difficult to distinguish from normal variation within a genotype. Given these emerging scenarios, downstream ‘omics’ technologies reflective of edited affects, such as metabolomics, need to be used in a more prominent manner to fully assess compositional changes in novel foodstuffs. To achieve this goal, metabolomics or ‘non‐targeted metabolite analysis’ needs to make significant advances to deliver greater representation across the metabolome. With the emergence of new edited crop varieties, we advocate: (i) concerted efforts in the advancement of ‘omics’ technologies, such as metabolomics, and (ii) an effort to redress the use of the technology in the regulatory assessment for metabolically engineered biotech crops.
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Devi, B. Rama, Jayshree Kamble, Maddali Anusha, et al. "Unravelling Updates in Deciphering Plant Defence Mechanisms with Insights from Functional Genomics and Proteomics." Journal of Advances in Biology & Biotechnology 28, no. 3 (2025): 357–70. https://doi.org/10.9734/jabb/2025/v28i32096.
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Functional genomics and proteomics have revolutionized plant defence studies by providing insights into the molecular mechanisms underlying immunity against pathogens. Functional genomics approaches, including genome-wide association studies (GWAS), RNA sequencing (RNA-Seq), and CRISPR/Cas9 genome editing, have identified key resistance (R) genes, susceptibility (S) genes, and transcriptional networks regulating plant defence responses. Proteomics complements genomics by revealing protein-protein interactions, post-translational modifications, and dynamic changes in protein abundance during pathogen attacks. The integration of these approaches has facilitated the development of disease-resistant crop varieties through marker-assisted selection (MAS), transgenic technologies, and biotechnology-based interventions. Despite significant advancements, challenges persist in data integration, the complexity of plant genomes, and the dynamic nature of proteomic responses. Computational tools, artificial intelligence, and systems biology approaches are being employed to address these limitations, enabling precise gene function annotation and predictive modelling of plant immune responses. Additionally, advances in mass spectrometry-based proteomics, single-cell transcriptomics, and data-independent acquisition (DIA) techniques are enhancing our ability to capture molecular changes associated with plant-pathogen interactions. These technological advancements are crucial for improving crop resilience against biotic stressors, contributing to global food security. The future of functional genomics and proteomics in plant defence lies in multi-omics integration, precision agriculture, and gene editing technologies that enable the development of climate-resilient, high-yielding crops with durable resistance. Collaboration among researchers, breeders, and computational biologists will be essential to translate these findings into practical agricultural applications. As we move towards a more data-driven and system-level understanding of plant immunity, functional genomics and proteomics will continue to be indispensable tools in sustainable agriculture, helping to mitigate the impacts of emerging pathogens and environmental stressors on global crop production.
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Razzaq, Ali, Fozia Saleem, Mehak Kanwal, et al. "Modern Trends in Plant Genome Editing: An Inclusive Review of the CRISPR/Cas9 Toolbox." International Journal of Molecular Sciences 20, no. 16 (2019): 4045. http://dx.doi.org/10.3390/ijms20164045.
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Increasing agricultural productivity via modern breeding strategies is of prime interest to attain global food security. An array of biotic and abiotic stressors affect productivity as well as the quality of crop plants, and it is a primary need to develop crops with improved adaptability, high productivity, and resilience against these biotic/abiotic stressors. Conventional approaches to genetic engineering involve tedious procedures. State-of-the-art OMICS approaches reinforced with next-generation sequencing and the latest developments in genome editing tools have paved the way for targeted mutagenesis, opening new horizons for precise genome engineering. Various genome editing tools such as transcription activator-like effector nucleases (TALENs), zinc-finger nucleases (ZFNs), and meganucleases (MNs) have enabled plant scientists to manipulate desired genes in crop plants. However, these approaches are expensive and laborious involving complex procedures for successful editing. Conversely, CRISPR/Cas9 is an entrancing, easy-to-design, cost-effective, and versatile tool for precise and efficient plant genome editing. In recent years, the CRISPR/Cas9 system has emerged as a powerful tool for targeted mutagenesis, including single base substitution, multiplex gene editing, gene knockouts, and regulation of gene transcription in plants. Thus, CRISPR/Cas9-based genome editing has demonstrated great potential for crop improvement but regulation of genome-edited crops is still in its infancy. Here, we extensively reviewed the availability of CRISPR/Cas9 genome editing tools for plant biotechnologists to target desired genes and its vast applications in crop breeding research.
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Pardo-Hernández, Miriam, Pascual García-Pérez, Luigi Lucini, and Rosa M. Rivero. "Multi-Omics Exploration of ABA Involvement in Identifying Unique Molecular Markers for Single and Combined Stresses in tomato plants." Journal of Experimental Botany, September 12, 2024. http://dx.doi.org/10.1093/jxb/erae372.
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Abstract Over the past decade, our research group has found that plant responses to combined abiotic stresses are unique and cannot be inferred from studying plants exposed to individual stresses. Understanding how adaptative plant mechanisms integrate from stress perception to biochemical and physiological adjustments is a major challenge in abiotic stress signaling studies. Considering abscisic acid (ABA) as a key regulator in plant abiotic stress responses, in our study, ABA-deficient plants (flc) exposed to single or combined salinity and heat stresses were evaluated and different -omics analyses were conducted. Significant changes in biomass, photosynthesis, ions, transcripts, and metabolites occurred in mutant plants under single or combined stresses. Exogenous ABA application in flc mutants did not fully recover plant phenotypes or metabolic levels but induced cellular reprogramming with changes in specific markers. Multi-omics analysis aimed to identify ABA-dependent, ABA-independent, or stress-dependent markers in plant responses to single or combined stresses. We demonstrated that studying different -omics as a whole led to the identification of specific markers for each stress condition that were not detectable when each -omic was studied individually. This resource article provides an important and novel reference for scientists working in the field of plant abiotic stress. Future exploration of the transcriptomic, ionomic and metabolomic data presented in this study could lead to the identification of new pathways and genes associated with ABA signaling processes. These findings may be utilized to enhance crop resilience to heat waves, salinity, and their combination, contributing to addressing food security challenges in a climate change scenario.
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Chen, Ce, Yining Ge, and Lingli Lu. "Opportunities and challenges in the application of single-cell and spatial transcriptomics in plants." Frontiers in Plant Science 14 (August 11, 2023). http://dx.doi.org/10.3389/fpls.2023.1185377.
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Single-cell and spatial transcriptomics have diverted researchers’ attention from the multicellular level to the single-cell level and spatial information. Single-cell transcriptomes provide insights into the transcriptome at the single-cell level, whereas spatial transcriptomes help preserve spatial information. Although these two omics technologies are helpful and mature, further research is needed to ensure their widespread applicability in plant studies. Reviewing recent research on plant single-cell or spatial transcriptomics, we compared the different experimental methods used in various plants. The limitations and challenges are clear for both single-cell and spatial transcriptomic analyses, such as the lack of applicability, spatial information, or high resolution. Subsequently, we put forth further applications, such as cross-species analysis of roots at the single-cell level and the idea that single-cell transcriptome analysis needs to be combined with other omics analyses to achieve superiority over individual omics analyses. Overall, the results of this review suggest that combining single-cell transcriptomics, spatial transcriptomics, and spatial element distribution can provide a promising research direction, particularly for plant research.
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Wang, Mingcheng, Shuqiao Zhang, Rui Li, and Qi Zhao. "Unraveling the specialized metabolic pathways in medicinal plant genomes: a review." Frontiers in Plant Science 15 (December 24, 2024). https://doi.org/10.3389/fpls.2024.1459533.
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Medicinal plants are important sources of bioactive specialized metabolites with significant therapeutic potential. Advances in multi-omics have accelerated the understanding of specialized metabolite biosynthesis and regulation. Genomics, transcriptomics, proteomics, and metabolomics have each contributed new insights into biosynthetic gene clusters (BGCs), metabolic pathways, and stress responses. However, single-omics approaches often fail to fully address these complex processes. Integrated multi-omics provides a holistic perspective on key regulatory networks. High-throughput sequencing and emerging technologies like single-cell and spatial omics have deepened our understanding of cell-specific and spatially resolved biosynthetic dynamics. Despite these advancements, challenges remain in managing large datasets, standardizing protocols, accounting for the dynamic nature of specialized metabolism, and effectively applying synthetic biology for sustainable specialized metabolite production. This review highlights recent progress in omics-based research on medicinal plants, discusses available bioinformatics tools, and explores future research trends aimed at leveraging integrated multi-omics to improve the medicinal quality and sustainable utilization of plant resources.
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Nobori, Tatsuya. "Exploring the untapped potential of single‐cell and spatial omics in plant biology." New Phytologist, May 21, 2025. https://doi.org/10.1111/nph.70220.
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SummaryAdvances in single‐cell and spatial omics technologies have revolutionised biology by revealing the diverse molecular states of individual cells and their spatial organization within tissues. The field of plant biology has widely adopted single‐cell transcriptome and chromatin accessibility profiling and spatial transcriptomics, which extend traditional cell biology and genomics analyses and provide unique opportunities to reveal molecular and cellular dynamics of tissues. Using these technologies, comprehensive cell atlases have been generated in several model plant species, providing valuable platforms for discovery and tool development. Other emerging technologies related to single‐cell and spatial omics, such as multiomics, lineage tracing, molecular recording, and high‐content genetic and chemical perturbation phenotyping, offer immense potential for deepening our understanding of plant biology yet remain underutilised due to unique technical challenges and resource availability. Overcoming plant‐specific barriers, such as cell wall complexity and limited antibody resources, alongside community‐driven efforts in developing more complete reference atlases and computational tools, will accelerate progress. The synergy between technological innovation and targeted biological questions is poised to drive significant discoveries, advancing plant science. This review highlights the current applications of single‐cell and spatial omics technologies in plant research and introduces emerging approaches with the potential to transform the field.
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Sarfraz, Zareen, Yusra Zarlashat, Alia Ambreen, et al. "Plant Biochemistry in the Era of Omics: Integrated Omics Approaches to Unravel the Genetic Basis of Plant Stress Tolerance." Plant Breeding, March 19, 2025. https://doi.org/10.1111/pbr.13277.
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ABSTRACTThe challenge of feeding the world's growing population is impaired by declining arable land, water quality and erratic weather patterns due to climate change. Abiotic stresses such as drought, heat, salinity and cold disrupt plant growth, reducing crop yields and quality. Modern biotechnological tools including high‐throughput sequencing and bioinformatics have enabled the characterization of plant stress responses through advanced “omics” technologies. Genomics, transcriptomics, proteomics, metabolomics and epigenomics describe molecular mechanisms underlying plant stress tolerance. Integrating multi‐omics approaches provides a deeper understanding of these mechanisms, addressing the limitations of single‐omics studies. The combination of multi‐omics data (genomics, transcriptomics, proteomics and metabolomics) identifies important biomarkers, regulatory networks and genetic targets that enhance plant stress resilience. This multi‐omics information regarding plants is crucial for genome‐assisted breeding (GAB) to improve crop traits and the development of climate‐resilient crops to withstand environmental challenges. Therefore, researchers use multi‐omics pipelines to enhance productive crops, quality and stress tolerance, solving global food security challenges caused by climate change and environmental stressors. This review discusses the role of omics technologies in describing the genetic mechanisms of plant stress responses and explores how this information is applied to enhance crop resilience and productivity, which leads to improved crops. The application of combining omics approaches to develop next‐generation crops that are capable of thriving under adverse environmental conditions, ensuring reliable and safe food supply for the future under stress conditions.
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Li, Chenxin, Joshua C. Wood, Anh Hai Vu, et al. "Single-cell multi-omics in the medicinal plant Catharanthus roseus." Nature Chemical Biology, May 15, 2023. http://dx.doi.org/10.1038/s41589-023-01327-0.
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AbstractAdvances in omics technologies now permit the generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells and high-resolution determination of gene regulatory features. Here, using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anticancer drugs. We identified clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes and extensive gene duplication of MIA pathway genes. Clustering was not limited to the linear genome, and through chromatin interaction data, MIA pathway genes were present within the same topologically associated domain, permitting the identification of a secologanin transporter. Single-cell RNA-sequencing revealed sequential cell-type-specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a single-cell metabolomics approach, permitted the identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. We also revealed cell-type-specific expression in the root MIA pathway.
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Jin, Jingjing, Shizhou Yu, Peng Lu, and Peijian Cao. "Deciphering plant cell–cell communications using single-cell omics data." Computational and Structural Biotechnology Journal, June 2023. http://dx.doi.org/10.1016/j.csbj.2023.06.016.
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Redmond, Ethan J., James Ronald, Seth J. Davis, and Daphne Ezer. "Single-plant-omics reveals the cascade of transcriptional changes during the vegetative-to-reproductive transition." Plant Cell, August 9, 2024. http://dx.doi.org/10.1093/plcell/koae226.
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Abstract Plants undergo rapid developmental transitions, which occur contemporaneously with gradual changes in physiology. Moreover, individual plants within a population undergo developmental transitions asynchronously. Single-plant-omics has the potential to distinguish between transcriptional events that are associated with these binary and continuous processes. Furthermore, we can use single-plant-omics to order individual plants by their intrinsic biological age, providing a high-resolution transcriptional time series. We performed RNA-seq on leaves from a large population of wild-type Arabidopsis (Arabidopsis thaliana) during the vegetative-to-reproductive transition. Though most transcripts were differentially expressed between bolted and unbolted plants, some regulators were more closely associated with leaf size and biomass. Using a pseudotime inference algorithm, we determined that some senescence-associated processes, such as the reduction in ribosome biogenesis, were evident in the transcriptome before a bolt was visible. Even in this near-isogenic population, some variants are associated with developmental traits. These results support the use of single-plant-omics to uncover rapid transcriptional dynamics by exploiting developmental asynchrony.
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Thibivilliers, Sandra, and Marc Libault. "Enhancing Our Understanding of Plant Cell-to-Cell Interactions Using Single-Cell Omics." Frontiers in Plant Science 12 (August 5, 2021). http://dx.doi.org/10.3389/fpls.2021.696811.
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Plants are composed of cells that physically interact and constantly adapt to their environment. To reveal the contribution of each plant cells to the biology of the entire organism, their molecular, morphological, and physiological attributes must be quantified and analyzed in the context of the morphology of the plant organs. The emergence of single-cell/nucleus omics technologies now allows plant biologists to access different modalities of individual cells including their epigenome and transcriptome to reveal the unique molecular properties of each cell composing the plant and their dynamic regulation during cell differentiation and in response to their environment. In this manuscript, we provide a perspective regarding the challenges and strategies to collect plant single-cell biological datasets and their analysis in the context of cellular interactions. As an example, we provide an analysis of the transcriptional regulation of the Arabidopsis genes controlling the differentiation of the root hair cells at the single-cell level. We also discuss the perspective of the use of spatial profiling to complement existing plant single-cell omics.
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Zhang, Jun, Mayra Ahmad, and Hongbo Gao. "Application of single-cell multi-omics approaches in horticulture research." Molecular Horticulture 3, no. 1 (2023). http://dx.doi.org/10.1186/s43897-023-00067-y.
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AbstractCell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research. Graphical Abstract
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Yang, Lifang, Ye Yang, Luqi Huang, Xiuming Cui, and Yuan Liu. "From single- to multi-omics: future research trends in medicinal plants." Briefings in Bioinformatics, November 22, 2022. http://dx.doi.org/10.1093/bib/bbac485.
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Abstract Medicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomics, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.
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Mo, Yajin, and Yuling Jiao. "Advances and Applications of Single‐cell Omics Technologies in Plant Research." Plant Journal, April 15, 2022. http://dx.doi.org/10.1111/tpj.15772.
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Zhou, Rong, Fangling Jiang, Lifei Niu, et al. "Increase Crop Resilience to Heat Stress Using Omic Strategies." Frontiers in Plant Science 13 (May 17, 2022). http://dx.doi.org/10.3389/fpls.2022.891861.
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Varieties of various crops with high resilience are urgently needed to feed the increased population in climate change conditions. Human activities and climate change have led to frequent and strong weather fluctuation, which cause various abiotic stresses to crops. The understanding of crops’ responses to abiotic stresses in different aspects including genes, RNAs, proteins, metabolites, and phenotypes can facilitate crop breeding. Using multi-omics methods, mainly genomics, transcriptomics, proteomics, metabolomics, and phenomics, to study crops’ responses to abiotic stresses will generate a better, deeper, and more comprehensive understanding. More importantly, multi-omics can provide multiple layers of information on biological data to understand plant biology, which will open windows for new opportunities to improve crop resilience and tolerance. However, the opportunities and challenges coexist. Interpretation of the multidimensional data from multi-omics and translation of the data into biological meaningful context remained a challenge. More reasonable experimental designs starting from sowing seed, cultivating the plant, and collecting and extracting samples were necessary for a multi-omics study as the first step. The normalization, transformation, and scaling of single-omics data should consider the integration of multi-omics. This review reports the current study of crops at abiotic stresses in particular heat stress using omics, which will help to accelerate crop improvement to better tolerate and adapt to climate change.
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Huo, Qiang, Rentao Song, and Zeyang Ma. "Recent advances in exploring transcriptional regulatory landscape of crops." Frontiers in Plant Science 15 (June 5, 2024). http://dx.doi.org/10.3389/fpls.2024.1421503.
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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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Depuydt, Thomas, Bert De Rybel, and Klaas Vandepoele. "Charting plant gene functions in the multi-omics and single-cell era." Trends in Plant Science, October 2022. http://dx.doi.org/10.1016/j.tplants.2022.09.008.
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Gupta, Parul, Justin Elser, Elizabeth Hooks, Peter D’Eustachio, Pankaj Jaiswal, and Sushma Naithani. "Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis." Nucleic Acids Research, November 20, 2023. http://dx.doi.org/10.1093/nar/gkad1052.
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Abstract Plant Reactome (https://plantreactome.gramene.org) is a freely accessible, comprehensive plant pathway knowledgebase. It provides curated reference pathways from rice (Oryza sativa) and gene-orthology-based pathway projections to 129 additional species, spanning single-cell photoautotrophs, non-vascular plants, and higher plants, thus encompassing a wide-ranging taxonomic diversity. Currently, Plant Reactome houses a collection of 339 reference pathways, covering metabolic and transport pathways, hormone signaling, genetic regulations of developmental processes, and intricate transcriptional networks that orchestrate a plant's response to abiotic and biotic stimuli. Beyond being a mere repository, Plant Reactome serves as a dynamic data discovery platform. Users can analyze and visualize omics data, such as gene expression, gene-gene interaction, proteome, and metabolome data, all within the rich context of plant pathways. Plant Reactome is dedicated to fostering data interoperability, upholding global data standards, and embracing the tenets of the Findable, Accessible, Interoperable and Re-usable (FAIR) data policy.
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ENEA, Casaccia Research Centre. "Plant Sample Collection and Shipment for Multi‐omic Analyses and Phytosanitary Evaluation." December 28, 2023. https://doi.org/10.1002/cpz1.952.
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Plant sample preparation for analyses is a fundamental step in high-throughput omics strategies. Especially for plant metabolomics, quenching of hydrolytic enzymes able to affect metabolite concentrations is crucial for the accuracy of results. Given that DNA is usually less labile than metabolites, most sampling and shipment procedures able to preserve the metabolome are also suitable for preventing the degradation of plant DNA or of DNA of pathogens in the plant tissue. In this article, we describe all the steps of sample collection, shipment (including the phytosanitary issues of moving plant samples), and processing for combined genomics and metabolomics from a single sample, as well as the protocols used in our laboratories for downstream approaches for crop plants, allowing collection of multi-omic datasets in large experimental setups. The protocols have been adjusted to apply to both freeze-dried and fresh-frozen material to allow the processing of crop plant samples that will require longdistance transport.
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Kwon, Ji-Su, Jayabalan Shilpha, Junesung Lee, and Seon-In Yeom. "Beyond NGS data sharing for plant ecological resilience and improvement of agronomic traits." Scientific Data 11, no. 1 (2024). http://dx.doi.org/10.1038/s41597-024-03305-0.
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AbstractDecoding complex plant omics is essential for advancing our understanding of plant biology, evolution, and breeding as well as for practical applications in agriculture, conservation, and biotechnology. The advent of Next-Generation Sequencing (NGS) has revolutionized global plant genomic research, offering high-throughput, cost-effective, and accurate methods for generating genomic data. However, challenges still exist that suggest an entirely unresolved genome characterized by high heterozygosity, extensive repetitive sequences, and complex ploidy features. In addition, individual investigation of genomic information from various genetic resources is essential for omics research, as there are differences in traits within a single breed beyond a species due to the uniqueness of sequence variation. This article provides high-quality genomic and transcriptomic insights targeted at the agronomical background.