We have recently identified an ethylene response factor, StPti5, as a susceptibility factor that negatively regulates immune responses to diverse pathogens. Here, we investigated the role of StPti5 in the processes involved in the colonization of potato with beneficial organisms. RNA-seq showed that at the time of Bacillus subtilis biofilm establishment, immune responses in interacting roots were attenuated, and a complex transcriptional network was triggered, with ethylene signaling being a central module and StPti5 strongly induced. Interestingly, the response is intensified if plants are inoculated by two antagonistic B. subtilis strains. While StPti5 is not involved in the establishment of biofilm on roots, we show that bacterial abundance increases in shoots of StPti5-silenced plants. Remarkably, root colonization by the arbuscular mycorrhizal fungus Rhizophagus irregularis was also higher in the StPti5-silenced plants. To decipher the mechanistic basis of StPti5 function, we performed a DAP-seq experiment and showed that StRIN13, a regulator of plant immune signaling, is a direct target of StPti5. StPti5 is involved both in suppressing defense against harmful and limiting colonization by beneficial microbes. Such a mechanistic understanding of plant-microbe interaction paves the way for sustainable crop management.

Abstract Accurate pre-harvest prediction of crop yield informs variety selection, optimizes management, and accelerates breeding. As potato is the world’s leading non-grain staple, here we evaluate a diverse panel of varieties in a three-year field trial across five European locations. Canopy development and environmental parameters are monitored throughout the growing season using drone-based imaging, in-field sensors and gene expression measurements, while tuber yield and quality traits are quantified at harvest. We show that these data enable the identification of climate-resilient, high-yielding genotypes and support the development of machine learning models that explain over 80% of yield variation in independent test sets. Strikingly, measurements collected within the first two months after planting achieve predictive performance comparable to models trained on full-season data. Model interrogation further shows that over 70% of yield variation can already be predicted based on a simple five-parameter linear equation. Our framework thus demonstrates the potential of integrative field phenotyping and data-driven modeling to improve variety selection across heterogeneous environments.

Genetically encoded biosensors are one of the essential tools in biological research. They enable visualization of molecules of interest from the subcellular level to entire organism level in vivo and can be used to monitor the presence of small molecules, gene expression, protein activity, and protein degradation. However, multiplexing fluorescent biosensors in plants is notoriously difficult due to signal bleed-through and strong autofluorescence from chlorophyll. In this study, we investigated the potential of multiplexing biosensors based on the selection of reporter fluorescent proteins. We characterized the emission spectra, fluorescence lifetimes, and relative brightness of diverse fluorescent proteins in plant leaves. We show that selected proteins exhibit comparable brightness, supporting their use in co-expression experiments and reliable quantification of individual signals. To separate three overlapping signals, we applied two different linear unmixing approaches and compared them to results obtained without unmixing. We identified the channel separation unmixing approach as the most suitable for biosensors. Additionally, we show how unmixing with the selected approach can be applied to separate autofluorescence and five fluorescent proteins. We further validated this approach in virus-infected cells by following organelle dynamics in vivo. Finally, we demonstrate the feasibility of high-throughput segmentation and quantification with a custom MATLAB workflow for nuclei, chloroplasts, and cytoplasm signal analysis. Overall, our work demonstrates that biosensors can be multiplexed, even when their emission spectra overlap.

Climate change is intensifying drought stress in viticultural regions, threatening grapevine productivity and quality. New genotypes previously bred for disease resistance are an untested resource regarding their water deficit tolerance. Field experiments were conducted over two seasons, applying well-watered and water-stress treatments in two disease-resistant varieties, Fleurtai and Cabernet Volos. Physiological measurements, RNA sequencing, and GC-MS-based metabolite profiling of leaves were integrated, correlating gene expression and metabolite accumulation with stem water potential (ΨS) using a factorial analyses design by FaDSeqSes script. We identified three categories of response: (1) genes and metabolites similarly regulated by water deficit in both genotypes, belonging to several different pathways (such as carbohydrate metabolism, amino acid metabolism, secondary metabolism, and hormone metabolism), among which sugar metabolism was one of the most striking ones, including changes in accumulation of raffinose and galactinol, and induction of genes coding for their synthesis; (2) responses specific to Cabernet Volos, characterized by downregulation of kinase and receptor genes likely to be involved in shutting down biotic defense response; and (3) responses specific to Fleurtai, including accumulation of caffeoylquinate and upregulation of genes involved terpene synthesis and in ABA regulation. We found that each genotype has an individual way to combat water deficits; Cabernet Volos accumulates more osmoprotectant compounds at a constant and higher level, while Fleurtai synthesizes these compounds as needed when stress occurs. This study underscores overall grapevine responses to water deficits, as well as the contribution of the genotype.

Plant pan-genomes, which aggregate genomic sequences and annotations from multiple individuals of a species, have emerged as transformative tools for understanding genetic diversity, adaptation, and evolutionary dynamics. However, the absence of standardized practices for data generation, analysis, and sharing hinders reproducibility and interoperability. This white paper presents a harmonized framework developed by the ELIXIR E-PAN consortium, addressing nomenclature, quality control (QC), data formats, visualization, and community practices. By adopting these guidelines, researchers can enhance FAIR (Findable, Accessible, Interoperable, Reusable) compliance, foster collaboration, and accelerate translational applications in crop improvement and evolutionary biology.

Plant pan-genomes, which aggregate genomic sequences and annotations from multiple individuals of a species, have emerged as transformative tools for understanding genetic diversity, adaptation, and evolutionary dynamics. Super-pan-genomes, extending across species boundaries, further enable comparative analyses of clades or genera, bridging breeding applications with evolutionary insights (Shang et al., 2022; Li et al., 2023a). However, the absence of standardized practices for data generation, analysis, and sharing hinders reproducibility and interoperability. This white paper presents a harmonized framework developed by the ELIXIR E-PAN consortium, addressing nomenclature, quality control (QC), data formats, visualization, and community practices. By adopting these guidelines, researchers can enhance FAIR (Findable, Accessible, Interoperable, Reusable) compliance, foster collaboration, and accelerate translational applications in crop improvement and evolutionary biology.

Allele-specific expression analysis can reveal cis-regulatory differences (e.g., promoter variants, epigenetic changes) that cause imbalanced gene expression between haplotypes. Haplotype-resolved reference genomes and long-read RNA sequencing enable allele-specific expression analysis at gene and isoform-levels. However, existing tools are largely restricted to short-read RNA sequencing data and diploid organisms. We developed LongPolyASE, an end-to-end computational framework for allele-specific gene and isoform expression analysis in diploid and polyploid organisms using long-read RNA sequencing, consisting of three components: Syntelogfinder, for identifying syntenic gene relationships and annotation inconsistencies; longrnaseq, for novel isoform discovery and haplotype-level quantification; and PolyASE, for statistical testing and visualization of allelic imbalance and isoform usage. We applied LongPolyASE to diploid rice, autotetraploid potato, allotetraploid rapeseed, and allooctoploid strawberry using Oxford Nanopore and PacBio long-read RNA-seq. The framework enabled identification of cis-regulatory variation, tissue-specific trans-regulatory effects, differential isoform usage, and haplotype-specific splicing differences. In addition, it facilitated the discovery of novel transcripts and genes with potential functional relevance in plant development. LongPolyASE addresses a key methodological gap by enabling allele-specific expression analysis in polyploid organisms using long-read RNA sequencing. By combining haplotype-aware quantification with isoform-level resolution in a reproducible workflow, the framework provides a practical tool for plant researchers working with complex genomes. Its application to crop species highlights its potential to support the identification of regulatory variation and candidate targets for plant breeding.

Motivation: Long-read RNA-seq and phased reference genomes enable haplotype-resolved gene and isoform expression analysis. While methods and tools exist for diploid organisms, analysis tools for polyploids are lacking. Results: We developed an end-to-end framework for allele-specific gene and isoform analysis in polyploids with three components: Syntelogfinder dentifies syntenic genes in phased assemblies; longrnaseq quantifies transcripts, discovers novel isoforms, and performs quality control of long-read RNA-seq; and PolyASE analyzes differential allelic expression, differential isoform usage between conditions, and structural differences in major isoforms between haplotypes. We demonstrate the use of the framework on diploid rice and autotetraploid potato. Availability and Implementation: Syntelogfinder and longrnaseq are implemented in Nextflow and available on GitHub. PolyASE is a Python package available on PyPI. The framework is fully documented and tutorials are provided. Contact: Nadja.nolte.franziska{at}nib.si Supplementary information: Supplementary data are available online and at Zenodo. ### Competing Interest Statement The authors have declared no competing interest. European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions Doctoral Network “LongTREC” Slovenian Research and Innovation Agency grant agreements, P4-0463, P4–0431

Plant pan-genomes, which aggregate genomic sequences and annotations from multiple individuals of a species, have emerged as transformative tools for understanding genetic diversity, adaptation, and evolutionary dynamics. Super-pan-genomes, extending across species boundaries, further enable comparative analyses of clades or genera, bridging breeding applications with evolutionary insights (Shang et al., 2022; Li et al., 2023a). However, the absence of standardized practices for data generation, analysis, and sharing hinders reproducibility and interoperability. This white paper presents a harmonized framework developed by the ELIXIR E-PAN consortium, addressing nomenclature, quality control (QC), data formats, visualization, and community practices. By adopting these guidelines, researchers can enhance FAIR (Findable, Accessible, Interoperable, Reusable) compliance, foster collaboration, and accelerate translational applications in crop improvement and evolutionary biology.

Understanding the molecular mechanisms behind plant response to stress can enhance breeding strategies and help us design crop varieties with improved stress tolerance, yield, and quality. To investigate resource redistribution from growth- to defense-related processes in an essential tuber crop, potato, here we generate a large-scale compartmentalized genome-scale metabolic model (GEM), potato-GEM. Apart from a large-scale reconstruction of primary metabolism, the model includes the full known potato secondary metabolism, spanning over 566 reactions that facilitate the biosynthesis of 182 distinct potato secondary metabolites. Constraint-based modeling identifies that the activation of the largest amount of secondary (defense) pathways occurs at a decrease of the relative growth rate of potato leaf, due to the costs incurred by defense. We then obtain transcriptomics data from experiments exposing potato leaves to two biotic stress scenarios, a herbivore and a viral pathogen, and apply them as constraints to produce condition-specific models. We show that these models recapitulate experimentally observed decreases in relative growth rates under treatment as well as changes in metabolite levels between treatments, enabling us to pinpoint the metabolic rewiring underlying growth-defense trade-offs. Potato-GEM thus presents a useful resource to study and broaden our understanding of potato and general plant defense responses under stress conditions.

The rapid evolution of bioinformatics and data-driven life sciences necessitates widespread, effective training solutions capable of transcending geographical and institutional boundaries. ELIXIR, as a pan-European bioinformatics research infrastructure, has strategically embraced e-learning methodologies to meet this challenge. This white paper systematically reviews the current landscape of e-learning initiatives across various ELIXIR Nodes and Communities, detailing both historical developments and contemporary practices. It identifies core attributes and desirable features of effective e-learning, presenting an analysis of diverse educational platforms and the deployment of Learning Management Systems (LMS) within ELIXIR’s framework. Emphasis is placed on the interactive, open-access, and sustainable nature of these resources, exemplified by platforms such as the Training e-Support System (TeSS) and the ELIXIR-SI eLearning Platform (EeLP). The paper highlights critical advancements toward standardization and interoperability through initiatives such as the adoption of SCORM protocols, facilitating resource reuse across Nodes. Additionally, the integration of e-learning into broader educational strategies—such as hybrid learning environments and structured learning paths—is examined. Finally, future directions are discussed, including strategies for integrating e-learning with traditional training methods, enhancing trainer expertise, and further expanding the availability and FAIRification of bioinformatics training resources.

Potato virus Y (PVY) is one of the top ten economically most important plant viruses and responsible for major yield losses. We previously suggested the involvement of the N terminal region of potato virus Y coat protein (CP) in PVY spread. By constructing different PVY N terminal deletion mutants, we here show that deletions of 40 or more amino acid residues from the N terminal region of the CP resulted in the PVY multiplication limited to primary infected cells. Deletion of 26 residues profoundly impaired PVY cell-to-cell movement and prevented systemic PVY spread, while deletions of 19-23 residues allowed delayed systemic PVY spread. Introduced point mutations in the identified region hinder the filaments formation (S21G) and prevent (S21G) or delay (G20P) PVY movement. In addition, the mutants with deletion of more than 23 residues were not able to form full length viral particles in bombarded leaves, which confirms the overall significance of this region also in capsid assembly. Author summary Potato virus Y is one of the most economically important plant viruses worldwide, since it causes major yield losses in Solanaceae , especially in potato, where it is the causal agent of potato tuber necrosis ringspot disease, negatively impacting tubers quality and significantly reduces potato yield. By constructing different PVY N terminal deletion mutants, we identified the regions of the coat protein that are important for efficient PVY cell-to-cell movement and putative mechanisms supporting it. Furthermore, our findings indicate that potato virus Y N terminal region plays an important role in efficiency of assembly into full length viral particles. Understanding these regions, responsible for cell-to-cell as well as long distance movement, is crucial for economically important plant viruses such as PVY, since dissolving such complex processes will enhance our understanding of the PVY infective cycle and contribute to the development of effective tackling strategies against PVY infections in potato and prevent yield losses. ### Competing Interest Statement The authors have declared no competing interest. Slovenian Research AgencySlovenian Research Agency, , P4-0165, P4-0407, J1-2467

Cultivar Désirée is an important model for potato functional genomics studies to assist breeding strategies. Here, we present a haplotype-resolved genome assembly of Désirée, achieved by assembling PacBio HiFi reads and Hi-C scaffolding, resulting in a high-contiguity chromosome-level assembly. We implemented a comprehensive annotation pipeline incorporating gene models and functional annotations from the Solanum tuberosum Phureja DM reference genome alongside RNA-seq reads to provide high-quality gene and transcript annotations. Additionally, we provide a genome-wide DNA methylation profile using Oxford Nanopore reads, enabling insights into potato epigenetics. The assembled genome, annotations, methylation and expression data are visualised in a publicly accessible genome browser, providing a valuable resource for the potato research community.

We investigated the spatial dynamics of potato (Solanum tuberosum) responses to herbivory and mechanical wounding. We first followed the spatiotemporal response of jasmonic acid (JA) signaling, known to be involved in the response. We generated two potato sensor lines: a JAZ degradation sensor and a downstream multicystatin (MC) transcriptional reporter. Both sensors revealed concentric, locally restricted responses on wounded leaves. Notably, JA-dependent gene expression was absent in cells immediately adjacent to the wound, whereas JAZ degradation spread continuously outward from the wound site. This pattern occurred after both herbivore attack and mechanical injury by the needle. To probe the mechanism, a salicylic acid (SA) reporter showed SA accumulation near the wound. Introducing the MC reporter into SA-depleted NahG plants produced a uniform spread of MC expression, confirming that SA attenuates the JA response in proximal cells. Together, these results show that a locally distinct, spatiotemporal SA-JA crosstalk shapes wound responses in potato, extending principles known from pathogen-plant interactions to herbivory and mechanical damage.

The rapid evolution of bioinformatics and data-driven life sciences necessitates widespread, effective training solutions capable of transcending geographical and institutional boundaries. ELIXIR, as a pan-European bioinformatics research infrastructure, has strategically embraced e-learning methodologies to meet this challenge. This white paper systematically reviews the current landscape of e-learning initiatives across various ELIXIR Nodes and Communities, detailing both historical developments and contemporary practices. It identifies core attributes and desirable features of effective e-learning, presenting an analysis of diverse educational platforms and the deployment of Learning Management Systems (LMS) within ELIXIR's framework. Emphasis is placed on the interactive, open-access, and sustainable nature of these resources, exemplified by platforms such as the Training e-Support System (TeSS) and the ELIXIR-SI eLearning Platform (EeLP). The paper highlights critical advancements toward standardization and interoperability through initiatives such as the adoption of SCORM protocols, facilitating resource reuse across Nodes. Additionally, the integration of e-learning into broader educational strategies-such as hybrid learning environments and structured learning paths-is examined. Finally, future directions are discussed, including strategies for integrating e-learning with traditional training methods, enhancing trainer expertise, and further expanding the availability and FAIRification of bioinformatics training resources.

Potato virus Y (PVY) is one of the top 10 economically most important plant viruses and responsible for major yield losses. We previously suggested the involvement of the N-terminal region of PVY coat protein (CP) in PVY spread. By constructing different N-terminal deletion mutants of the PVY N605 strain, we here show that deletions of 40 or more amino acid residues from the N-terminal region of the CP resulted in the PVY multiplication limited to primary infected cells in Nicotiana clevelandii plants. Deletion of 26 residues profoundly impaired PVY cell-to-cell movement and prevented systemic PVY spread, while deletions of 19-23 residues allowed delayed systemic PVY spread. Introduced point mutations in the identified region prevent (S21G) or delay (G20P) PVY movement. In summary, this work shows the significance of the CP N-terminus for movement of the PVY. IMPORTANCE:Potato virus Y (PVY) is one of the most economically important plant viruses worldwide, since it causes major yield losses in Solanaceae, especially in potato, where it is the causal agent of potato tuber necrosis ringspot disease, negatively impacting tuber quality and significantly reducing potato yield. By constructing different PVY N-terminal deletion mutants, we identified the regions of the coat protein that are important for efficient PVY cell-to-cell movement. Understanding these regions, responsible for cell-to-cell as well as long-distance movement, is crucial for economically important plant viruses such as PVY, since dissolving such complex processes will enhance our understanding of the PVY infective cycle and contribute to the development of effective tackling strategies against PVY infections in potato and prevent yield losses.

Potato (Solanum tuberosum) is highly water and space efficient but susceptible to abiotic stresses such as heat, drought, and flooding, which are severely exacerbated by climate change. Our understanding of crop acclimation to abiotic stress, however, remains limited. Here, we present a comprehensive molecular and physiological high-throughput profiling of potato (Solanum tuberosum, cv. Désirée) under heat, drought, and waterlogging applied as single stresses or in combinations designed to mimic realistic future scenarios. Stress responses were monitored via daily phenotyping and multi-omics analyses of leaf samples comprising proteomics, targeted transcriptomics, metabolomics, and hormonomics at several timepoints during and after stress treatments. Additionally, critical metabolites of tuber samples were analyzed at the end of the stress period. We performed integrative multi-omics data analysis using a bioinformatic pipeline that we established based on machine learning and knowledge networks. Waterlogging produced the most immediate and dramatic effects on potato plants, interestingly activating ABA responses similar to drought stress. In addition, we observed distinct stress signatures at multiple molecular levels in response to heat or drought and to a combination of both. In response to all treatments, we found a downregulation of photosynthesis at different molecular levels, an accumulation of minor amino acids, and diverse stress-induced hormones. Our integrative multi-omics analysis provides global insights into plant stress responses, facilitating improved breeding strategies toward climate-adapted potato varieties.

The ELIXIR Plant Sciences Community is an interdisciplinary group of researchers with diverse backgrounds from computer science to different fields of plant biology. We answer the needs of both bioinformaticians and plant biologists. The Community objective is to develop services supporting the integration and linking of phenotypic, genotypic, omics (e.g. expression, metabolomics, etc.), environmental, and bibliographic data. The underlying scientific use cases encompass fundamental and applied plant sciences, including genetics, system biology and omics approaches, within the broader context of climate change, agroecology, food security, and sustainable agriculture. To meet the current challenges in agriculture, the ELIXIR Community promotes tools, databases, standards, and best practices for plant research while developing joint initiatives such as international projects and events in collaboration with European infrastructures (EMPHASIS, AnaEE-ERIC, Euro-Bioimaging, METROFOOD-RI). The ELIXIR Community also supports the establishment of links to structuring national projects and initiatives such as NFDI in Germany, or the french Agroecology and ICT program. Despite ongoing efforts, challenges remain, such as the continued scattering of plant molecular and cellular data, which hampers efficient data integration and reuse. Additionally, progressing toward a comprehensive agriculture data space is essential to address the interdisciplinary challenges that modern agriculture faces. Strengthening engagement with related research communities, such as those working on plant pathogens, is also a priority to ensure a holistic approach to plant science and agricultural research. Finally the Plant Sciences Community links with other ELIXIR Communities and Focus Groups, in particular to contribute to the objectives and priority of the Biodiversity, Food Security and Pathogens and of the Cellular and Molecular Research scientific priority areas.

We have recently identified ERF transcription factor PTI5 as a susceptibility factor, negatively regulating immune response to diverse pathogens. Here we investigated the processes involved in colonisation of potato with beneficial organisms. RNAseq showed that at the time of Bacillus subtilis biofilm establishment, immune responses in interacting roots were attenuated, and complex transcriptional network was triggered, with ethylene signalling being a central module and PTI5 strongly induced. Interestingly, the response is intensified if plants are inoculated by two antagonistic B. subtilis strains. While PTI5 is not involved in the establishment of biofilm on roots, we show that bacterial abundance increases in PTI5-silenced plants. Remarkably, root colonization by the arbuscular mycorrhizal fungus Rhizophagus irregularis was also higher in the PTI5-silenced plants. PTI5 is thus involved both in blocking defence against harmful and blocking colonisation with beneficial microbes. Such mechanistic understanding of plant–microbe interaction paves the way for sustainable crop management. ### Competing Interest Statement The authors have declared no competing interest. Slovenian Research Agency, https://ror.org/059bp8k51, P4-0165, P4-0116, J4-9302, J4-4550, J4-3089 European Union, https://ror.org/019w4f821, MCIN/AEI/ PID2021-124813OBC31

Arbuscular mycorrhizal (AM) symbiosis can prime plant defenses, leading to mycorrhiza-induced resistance (MIR) against different attackers, including insect herbivores. Still, our knowledge of the complex molecular regulation leading to MIR is very limited. Here, we showed that the AM fungus Funneliformis mosseae protects tomato plants against two different chewing herbivores, Spodoptera exigua and Manduca sexta. We explored the underlying molecular mechanism through genome-wide transcriptional profiling, bioinformatics network analyses, and functional bioassays. Herbivore-triggered jasmonate (JA)-regulated defenses were primed in leaves of mycorrhizal plants. Likewise, ethylene (ET) biosynthesis and signaling were also higher in leaves of mycorrhizal plants both before and after herbivory. We hypothesized that fine-tuned ET signaling is required for the primed defense response leading to MIR. ET is a complex regulator of plant responses to stress and is generally considered a negative regulator of plant defenses against herbivory. However, ET-deficient or insensitive lines did not show AM-primed JA biosynthesis or defense response, and were unable to develop MIR against any of the herbivores. Thus, we demonstrate that hormone crosstalk is central to the priming of plant immunity by beneficial microbes, with ET fine-tuning being essential for the primed JA biosynthesis and boosted defenses leading to MIR in tomato.