159 research outputs found

    Correlation Network Analysis reveals a sequential reorganization of metabolic and transcriptional states during germination and gene-metabolite relationships in developing seedlings of Arabidopsis

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    <p>Abstract</p> <p>Background</p> <p>Holistic profiling and systems biology studies of nutrient availability are providing more and more insight into the mechanisms by which gene expression responds to diverse nutrients and metabolites. Less is known about the mechanisms by which gene expression is affected by endogenous metabolites, which can change dramatically during development. Multivariate statistics and correlation network analysis approaches were applied to non-targeted profiling data to investigate transcriptional and metabolic states and to identify metabolites potentially influencing gene expression during the heterotrophic to autotrophic transition of seedling establishment.</p> <p>Results</p> <p>Microarray-based transcript profiles were obtained from extracts of Arabidopsis seeds or seedlings harvested from imbibition to eight days-old. <sup>1</sup>H-NMR metabolite profiles were obtained for corresponding samples. Analysis of transcript data revealed high differential gene expression through seedling emergence followed by a period of less change. Differential gene expression increased gradually to day 8, and showed two days, 5 and 7, with a very high proportion of up-regulated genes, including transcription factor/signaling genes. Network cartography using spring embedding revealed two primary clusters of highly correlated metabolites, which appear to reflect temporally distinct metabolic states. Principle Component Analyses of both sets of profiling data produced a chronological spread of time points, which would be expected of a developmental series. The network cartography of the transcript data produced two distinct clusters comprising days 0 to 2 and days 3 to 8, whereas the corresponding analysis of metabolite data revealed a shift of day 2 into the day 3 to 8 group. A metabolite and transcript pair-wise correlation analysis encompassing all time points gave a set of 237 highly significant correlations. Of 129 genes correlated to sucrose, 44 of them were known to be sucrose responsive including a number of transcription factors.</p> <p>Conclusions</p> <p>Microarray analysis during germination and establishment revealed major transitions in transcriptional activity at time points potentially associated with developmental transitions. Network cartography using spring-embedding indicate that a shift in the state of nutritionally important metabolites precedes a major shift in the transcriptional state going from germination to seedling emergence. Pair-wise linear correlations of transcript and metabolite levels identified many genes known to be influenced by metabolites, and provided other targets to investigate metabolite regulation of gene expression during seedling establishment.</p

    *omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants

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    Background: Modern biology uses experimental systems that involve the exploration of phenotypic variation as a result of the recombination of several genomes. Such systems are useful to investigate the functional evolution of metabolic networks. One such approach is the analysis of transcript and metabolite profiles. These kinds of studies generate a large amount of data, which require dedicated computational tools for their analysis.Results: This paper presents a novel software named *omeSOM (transcript/metabol-ome Self Organizing Map) that implements a neural model for biological data clustering and visualization. It allows the discovery of relationships between changes in transcripts and metabolites of crop plants harboring introgressed exotic alleles and furthermore, its use can be extended to other type of omics data. The software is focused on the easy identification of groups including different molecular entities, independently of the number of clusters formed. The *omeSOM software provides easy-to-visualize interfaces for the identification of coordinated variations in the co-expressed genes and co-accumulated metabolites. Additionally, this information is linked to the most widely used gene annotation and metabolic pathway databases.Conclusions: *omeSOM is a software designed to give support to the data mining task of metabolic and transcriptional datasets derived from different databases. It provides a user-friendly interface and offers several visualization features, easy to understand by non-expert users. Therefore, *omeSOM provides support for data mining tasks and it is applicable to basic research as well as applied breeding programs. The software and a sample dataset are available free of charge at http://sourcesinc.sourceforge.net/omesom/.Fil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; ArgentinaFil: Kamenetzky, Laura. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: López, Mariana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Lee, Je M.. Cornell University; Estados UnidosFil: Giovannoni, James J.. Cornell University; Estados UnidosFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentin

    Seed Priming: An Interlinking Technology between Seeds, Seed Germination and Seedling Establishment

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    Biologically seed is a small embryonic plant along with either endosperm or cotyledons, enclosed with in an outer protecting covering called seed coat. During the time of seed development large metabolic conversions take place, including proper partitioning of photo-assimilates and the formation of complex polymeric forms of carbohydrate, protein and fats for storing as seed reserves. In developing phase of seeds, every detail information stored in the embryonic plant are genetically and sometimes epigenetically also predetermined and influenced by various environmental/external factors already faced by the mother plant. In the growth cycle of plants, seed germination and seedling establishment are the two critical phases where survivability of the seedlings in natural habitats is a matter of question until the onset of photosynthesis by the established seedling. The various sequence of complex processes known to occur in both the phases i.e., an array of metabolic activities are initiating which eventually leads to the renewal of embryo growth of the dormant seeds and ultimately seedlings are established. Efficient seed germination is an important factor for agricultural sciences and successful establishment of germinated seedling requires a rapid and uniform emergence and root growth. With these aspects of seed physiology kept in mind the present chapter will be designed in such a way where, a gap filling, inter linking, eco- and farmers\u27 friendly technology i.e., ‘seed priming’ (a pre-sowing partial hydration of seeds) will be considered to improve the rate and uniformity of germination and seedling establishment. Under optimal and adverse environmental conditions, the primed seeds of diversified species lead to an enhanced germination performance with increased vigor index has been reported by various scientists which indicates a good establishment of seedlings in the field and thereafter enhance the performance of crops as a whole

    Improving clustering with metabolic pathway data

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    Background: It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. Results: A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Conclusions: Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.Fil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Lopez, Mariana Gabriela. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kamenetzky, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentin

    A root phloem pole cell atlas reveals common transcriptional states in protophloem-adjacent cells

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    The phloem pole atlas has over 10,000 cells, with an unprecedented resolution of the transcriptional dynamics in phloem development. Despite distinct mature transcriptional states, co-expression networks show common states in protophloem-adjacent cells. Single-cell sequencing has recently allowed the generation of exhaustive root cell atlases. However, some cell types are elusive and remain underrepresented. Here we use a second-generation single-cell approach, where we zoom in on the root transcriptome sorting with specific markers to profile the phloem poles at an unprecedented resolution. Our data highlight the similarities among the developmental trajectories and gene regulatory networks common to protophloem sieve element (PSE)-adjacent lineages in relation to PSE enucleation, a key event in phloem biology. As a signature for early PSE-adjacent lineages, we have identified a set of DNA-binding with one finger (DOF) transcription factors, the PINEAPPLEs (PAPL), that act downstream of PHLOEM EARLY DOF (PEAR) genes and are important to guarantee a proper root nutrition in the transition to autotrophy. Our data provide a holistic view of the phloem poles that act as a functional unit in root development.Peer reviewe

    Understanding the mechanism(s) of hydro-priming to improve seed vigour and seedling establishment of Solanum lycopersicum

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    Seeds are very complex and diverse plant organs. Seed germination is the most sensitive stage of plant life and is influenced by various environmental signals including phytohormones, salt, light, temperature and water potential. Seeds have an innate mechanism called dormancy that blocks germination, and plants have developed several dormancy-inducing strategies to optimise the timing of germination. Seed germination vigour is an important factor in crop yield. Seedling vigour is defined as the sum of the seed properties which determine the level of activity and performance during germination and seedling emergence. A poor seed lot can be improved by post-harvest treatment such as hydro-priming as it is used in the seed industry, but the biological mechanism is unknown. The aim of this study is to understand the mechanism(s) of hydro-priming in order to improve seed vigour and seed germination. I set seeds at different temperatures to produce variation in seed vigour and it showed that germination of seeds with low vigour can be improved by hydro-priming. Using LC-IT-ToF/MS I characterised compounds that leach from seeds during hydro-priming, and showed that some of these are putative germination inhibitors. Adding these compounds to the water during hydro-priming showed that the inhibitory effect of these compounds is not the main mechanism that regulates germination. Also, transcriptomic analysis showed that genes involved in OPDA pathway are expressed during hydro-priming as well as during endosperm weakening cap associated genes. I concluded that hydro-priming improves the speed of germination of low temperature set and its efficiency is dependent of activation of metabolic activity.Enza Zaden BBSRC University of Exete

    Plant Proteomic Research 4.0

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    As an important tool of systems biology, proteomics has enabled a deep understanding of different plant processes and functions. Complemented with genomic data, computational tools, and improved sample preparation strategies, proteomics has an unprecedented opportunity to characterize plant proteoforms in high spatial and temporal resolution. This special issue of Plant Proteomic Research 4.0 captures the recent advancements in proteomics and addresses the current challenges of plant stress response and resilience in the ever-changing climate. It contains 12 articles, including three reviews and nine original research articles. The three reviews deal with pollen phosphoproteomics, starch biosynthesis-related proteins and posttranslational modifications (PTMs) in rice developing seeds, and PTMs of waxy proteins in rice grain. The nine research articles include three related to temperature, two on water stress, two on salt stress, one on fungal pathogen, and the last one on field-grown potato apoplast proteome. The articles reflect the current frontiers of plant proteomics, focusing on themes of environmental stresses, proteoforms/PTMs, crop species, and new development in data-independent acquisition mass spectrometry. They provide readers insights into current technologies, their utility in understanding plant growth and resilience, as well as directions of proteomics in the frontiers of systems biology and synthetic biology

    UVR8 mediated spatial differences as a prerequisite for UV-B induced inflorescence phototropism

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    In Arabidopsis hypocotyls, phototropins are the dominant photoreceptors for the positive phototropism response towards unilateral ultraviolet-B (UV-B) radiation. We report a stark contrast of response mechanism with inflorescence stems with a central role for UV RESISTANCE LOCUS 8 (UVR8). The perception of UV-B occurs mainly in the epidermis and cortex with a lesser contribution of the endodermis. Unilateral UV-B exposure does not lead to a spatial difference in UVR8 protein levels but does cause differential UVR8 signal throughout the stem with at the irradiated side 1) increase of the transcription factor ELONGATED HYPOCOTYL 5 (HY5), 2) an associated strong activation of flavonoid biosynthesis genes and flavonoid accumulation, 3) increased GA2oxidase expression, diminished gibberellin1 levels and accumulation of DELLA protein REPRESSOR OF GA1 (RGA) and, 4) increased expression of the auxin transport regulator, PINOID, contributing to local diminished auxin signalling. Our molecular findings are in support of the Blaauw theory (1919), suggesting that differential growth occurs trough unilateral photomorphogenic growth inhibition. Together the data indicate phototropin independent inflorescence phototropism through multiple locally UVR8-regulated hormone pathways

    Perspectives on Systematic Analyses of Gene Function in Arabidopsis thaliana: New Tools, Topics and Trends

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    Since the sequencing of the nuclear genome of Arabidopsis thaliana ten years ago, various large-scale analyses of gene function have been performed in this model species. In particular, the availability of collections of lines harbouring random T-DNA or transposon insertions, which include mutants for almost all of the ~27,000 A. thaliana genes, has been crucial for the success of forward and reverse genetic approaches. In the foreseeable future, genome-wide phenotypic data from mutant analyses will become available for Arabidopsis, and will stimulate a flood of novel in-depth gene-function analyses. In this review, we consider the present status of resources and concepts for systematic studies of gene function in A. thaliana. Current perspectives on the utility of loss-of-function and gain-of-function mutants will be discussed in light of the genetic and functional redundancy of many A. thaliana genes
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