RNA Sequencing Analyses for Deciphering Potato Molecular Responses.

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.

Cultivar-specific transcriptome and pan-transcriptome reconstruction of tetraploid potato.

Although the reference genome of Solanum tuberosum Group Phureja double-monoploid (DM) clone is available, knowledge on the genetic diversity of the highly heterozygous tetraploid Group Tuberosum, representing most cultivated varieties, remains largely unexplored. This lack of knowledge hinders further progress in potato research. In conducted investigation, we first merged and manually curated the two existing partially-overlapping DM genome-based gene models, creating a union of genes in Phureja scaffold. Next, we compiled available and newly generated RNA-Seq datasets (cca. 1.5 billion reads) for three tetraploid potato genotypes (cultivar Désirée, cultivar Rywal, and breeding clone PW363) with diverse breeding pedigrees. Short-read transcriptomes were assembled using several de novo assemblers under different settings to test for optimal outcome. For cultivar Rywal, PacBio Iso-Seq full-length transcriptome sequencing was also performed. EvidentialGene redundancy-reducing pipeline complemented with in-house developed scripts was employed to produce accurate and complete cultivar-specific transcriptomes, as well as to attain the pan-transcriptome. The generated transcriptomes and pan-transcriptome represent a valuable resource for potato gene variability exploration, high-throughput omics analyses, and breeding programmes.

Multiomics analysis of tolerant interaction of potato with potato virus Y.

Potato virus Y (PVY) is the most economically important viral pathogen of potato worldwide. Different potato cultivars react to the pathogen differently, resulting in resistant, tolerant or disease outcome of the interaction. Here we focus on tolerant interaction between potato cv. Désirée and PVYNTN. To capture the response in its full complexity, we analyzed the dynamic changes on multiple molecular levels, including transcriptomics, sRNAomics, degradomics, proteomics and hormonomics. The analysis was complemented by the measurements of viral accumulation, photosynthetic activity and phenotypisation of the symptoms. Besides cv. Désirée we also studied its transgenic counterpart depleted for the accumulation of salicylic acid (NahG-Désirée). This multiomics analysis provides better insights into the mechanisms leading to tolerant response of potato to viral infection and can be used as a base in further studies of plant immunity regulation.

Network Modeling Unravels Mechanisms of Crosstalk between Ethylene and Salicylate Signaling in Potato.

To develop novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modeling represents a powerful tool that can unravel properties of complex biological systems. In this study, we aimed to use network modeling to better understand immune signaling in potato (Solanum tuberosum). For this, we first built on a reliable Arabidopsis (Arabidopsis thaliana) immune signaling model, extending it with the information from diverse publicly available resources. Next, we translated the resulting prior knowledge network (20,012 nodes and 70,091 connections) to potato and superimposed it with an ensemble network inferred from time-resolved transcriptomics data for potato. We used different network modeling approaches to generate specific hypotheses of potato immune signaling mechanisms. An interesting finding was the identification of a string of molecular events illuminating the ethylene pathway modulation of the salicylic acid pathway through Nonexpressor of PR Genes1 gene expression. Functional validations confirmed this modulation, thus supporting the potential of our integrative network modeling approach for unraveling molecular mechanisms in complex systems. In addition, this approach can ultimately result in improved breeding strategies for potato and other sensitive crops.

Bimodal dynamics of primary metabolism-related responses in tolerant potato-Potato virus Y interaction.

BACKGROUND: Potato virus Y (PVY) is a major pathogen that causes substantial economic losses in worldwide potato production. Different potato cultivars differ in resistance to PVY, from severe susceptibility, through tolerance, to complete resistance. The aim of this study was to better define the mechanisms underlying tolerant responses of potato to infection by the particularly aggressive PVY(NTN) strain. We focused on the dynamics of the primary metabolism-related processes during PVY(NTN) infection. RESULTS: A comprehensive analysis of the dynamic changes in primary metabolism was performed, which included whole transcriptome analysis, nontargeted proteomics, and photosynthetic activity measurements in potato cv. Désirée and its transgenic counterpart depleted for accumulation of salicylic acid (NahG-Désirée). Faster multiplication of virus occurred in the NahG-Désirée, with these plants developing strong disease symptoms. We show that while the dynamics of responses at the transcriptional level are extensive and bimodal, this is only partially translated to the protein level, and to the final functional outcome. Photosynthesis-related genes are transiently induced before viral multiplication is detected and it is down-regulated later on. This is reflected as a deficiency of the photosynthetic apparatus at the onset of viral multiplication only. Interestingly, specific and constant up-regulation of some RuBisCO transcripts was detected in Désirée plants, which might be important, as these proteins have been shown to interact with viral proteins. In SA-deficient and more sensitive NahG-Désirée plants, consistent down-regulation of photosynthesis-related genes was detected. A constant reduction in the photochemical efficiency from the onset of viral multiplication was identified; in nontransgenic plants this decrease was only transient. The transient reduction in net photosynthetic rate occurred in both genotypes with the same timing, and coincided with changes in stomatal conductivity. CONCLUSIONS: Down-regulation of photosynthesis-related gene expression and decreased photosynthetic activity is in line with other studies that have reported the effects of biotic stress on photosynthesis. Here, we additionally detected induction of light-reaction components in the early stages of PVY(NTN) infection of tolerant interaction. As some of these components have already been shown to interact with viral proteins, their overproduction might contribute to the absence of symptoms in cv. Désirée.

Optimising droplet digital PCR analysis approaches for detection and quantification of bacteria: a case study of fire blight and potato brown rot.

Here we report on the first assessment of droplet digital PCR (ddPCR) for detection and absolute quantification of two quarantine plant pathogenic bacteria that infect many species of the Rosaceae and Solanaceae families: Erwinia amylovora and Ralstonia solanacearum. An open-source R script was written for the ddPCR data analysis. Analysis of a set of samples with known health status aided the assessment and selection of different threshold settings (QuantaSoft analysis, definetherain pipeline and manual threshold), which led to optimal diagnostic specificity. The interpretation of the E. amylovora ddPCR was straightforward, and the analysis approach had little influence on the final results and the concentrations determined. The sensitivity and linear range were similar to those for real-time PCR (qPCR), for the analysis of both bacterial suspensions and plant material, making ddPCR a viable choice when both detection and quantification are desired. With the R. solanacearum ddPCR, the use of a high global threshold was necessary to exclude false-positive reactions that are sometimes observed in healthy plant material. ddPCR significantly improved the analytical sensitivity over that of qPCR, and improved the detection of low concentrations of R. solanacearum in potato tuber samples. Accurate and rapid absolute quantification of both of these bacteria in pure culture was achieved by direct ddPCR. Our data confirm the suitability of these ddPCR assays for routine detection and quantification of plant pathogens and for preparation of defined in-house reference materials with known target concentrations.