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Povzetek: Understanding the molecular mechanisms behind plant response to stress can enhancebreeding strategies and help us design crop varieties with improved stress tolerance,yield, and quality. To investigate resource redistribution from growth- to defense-relatedprocesses in an essential tuber crop, potato, here we generate a large-scale compartmen-talized genome-scale metabolic model (GEM), potato-GEM. Apart from a large-scalereconstruction of primary metabolism, the model includes the full known potato sec-ondary metabolism, spanning over 566 reactions that facilitate the biosynthesis of 182distinct potato secondary metabolites. Constraint-based modeling identifies that theactivation of the largest amount of secondary (defense) pathways occurs at a decreaseof the relative growth rate of potato leaf, due to the costs incurred by defense. We thenobtain transcriptomics data from experiments exposing potato leaves to two bioticstress scenarios, a herbivore and a viral pathogen, and apply them as constraints toproduce condition-specific models. We show that these models recapitulate experimen-tally observed decreases in relative growth rates under treatment as well as changes inmetabolite levels between treatments, enabling us to pinpoint the metabolic rewiringunderlying growth–defense trade-offs. Potato- GEM thus presents a useful resource tostudy and broaden our understanding of potato and general plant defense responsesunder stress conditions.
Ključne besede: systems biology, constraint-based metabolic modeling, growth-defence trade-offs, secondary metabolism
Objavljeno v DiRROS: 24.09.2025; Ogledov: 360; Prenosov: 144
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Povzetek: Understanding the molecular mechanisms of potato development and responses to environmental stressors is of utmost importance for achieving stable crop yields. RNA sequencing (RNA-Seq) provides an insight into responses of all of the organism genes to the environmental and developmental cues and thus provides insights into underlying modes of action. In this chapter, we guide a researcher through some of the most important steps in the analysis of transcriptomics data. The initial topic of experimental design is followed by a more wet-lab-oriented section on RNA-Seq sample preparation. Next, we present intermediate steps of data retrieval, quality control, mapping, and differential expression of the dataset and a section on how to expose your data to the public (i.e., public repositories) and make it findable, accessible, interoperable, and reusable (FAIR). In the last four sections, we describe specific tools or Web applications, which ease the exploration of generated results in the context of their gene function and network-based visualizations, specifically GoMapMan, GSEA, DiNAR, and Biomine Explorer. All sections are accompanied by potato dataset examples and include general hints and tricks, as well as potato specificities that one should be aware of.
Objavljeno v DiRROS: 06.08.2025; Ogledov: 397; Prenosov: 199
Celotno besedilo (3,14 MB)
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Ključne besede: podatki, ravnanje s podatki, ravnanje z raziskovalnimi podatki, raziskovalni podatki, odprta znanost
Objavljeno v DiRROS: 26.05.2025; Ogledov: 791; Prenosov: 473
Celotno besedilo (2,76 MB)

Povzetek: The discovery of genes that code for a specific enzymatic activity is important in various fields of life science and provides valuable biotechnological tools. Many genes that contribute to the production of secondary metabolites and specialized metabolic pathways are still not identified. Due to the great diversity of metabolic functions found in nature and their rapid evolutionary adaptation, we need precise but high-throughput approaches for a targeted search based on minimal prior knowledge. In this chapter, we describe a transcriptomics pipeline that was used to search for candidate genes coding for a specific enzymatic activity in a nonmodel species. We generated and combined short- and long-read transcriptomic data to obtain reliable full-length transcript sequences along with information on allelic variation, isoform expression, and condition-specific expression. Based on protein domain annotations of coding sequences and transcriptomic data, we selected candidate genes for activity assays. We provide detailed instructions for analysis and quality control steps in our pipeline that can be applied to other biological questions.
Ključne besede: genes, enzymatic activity, transcriptomics, metabolic pathways, allelic variation, isoform expression, biotechnological tools
Objavljeno v DiRROS: 14.04.2025; Ogledov: 671; Prenosov: 321
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Ključne besede: odprti podatki, odprta znanost, delo z delotoki, projekt Spoznaj, okolje Galaxy, raziskovalni podatki, uporabljanje podatkov
Objavljeno v DiRROS: 12.03.2025; Ogledov: 791; Prenosov: 355
Celotno besedilo (13,57 MB)
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