The recent Xylella fastidiosa subsp. pauca (Xfp) outbreak in olive (Olea europaea) groves in southern Italy is causing a destructive disease denoted Olive Quick Decline Syndrome (OQDS). Field observations disclosed that Xfp-infected plants of cv. Leccino show much milder symptoms, than the more widely grown and highly susceptible cv. Ogliarola salentina. To determine whether these field observations underlie a tolerant condition of cv. Leccino, which could be exploited for lessening the economic impact of the disease on the local olive industry, transcriptional changes occurring in plants of the two cultivars affected by Xfp were investigated. A global quantitative transcriptome profiling comparing susceptible (Ogliarola salentina) and tolerant (Leccino) olive cultivars, infected or not by Xfp, was done on messenger RNA (mRNAs) extracted from xylem tissues. The study revealed that 659 and 447 genes were differentially regulated in cvs Leccino and Ogliarola upon Xfp infection, respectively, whereas 512 genes were altered when the transcriptome of both infected cultivars was compared. Analysis of these differentially expressed genes (DEGs) shows that the presence of Xfp is perceived by the plants of both cultivars, in which it triggers a differential response strongly involving the cell wall. Up-regulation of genes encoding receptor-like kinases (RLK) and receptor-like proteins (RLP) is the predominant response of cv. Leccino, which is missing in cv. Ogliarola salentina. Moreover, both cultivars react with a strong re-modelling of cell wall proteins. These data suggest that Xfp elicits a different transcriptome response in the two cultivars, which determines a lower pathogen concentration in cv. Leccino and indicates that this cultivar may harbor genetic constituents and/or regulatory elements which counteract Xfp infection. Collectively these findings suggest that cv. Leccino is endowed with an intrinsic tolerance to Xfp, which makes it eligible for further studies aiming at investigating molecular basis and pathways modulating its different defense response.

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects.

We determined the draft genome sequence of the Xylella fastidiosa CoDiRO strain, which has been isolated from olive plants in southern Italy (Apulia). It is associated with olive quick decline syndrome (OQDS) and characterized by extensive scorching and desiccation of leaves and twigs.