The biology of Cixius wagneri, the planthopper vector of ‘Candidatus Phlomobacter fragariae’ in strawberry production tunnels and its consequence for the epidemiology of strawberry marginal chlorosis

Abstract«Candidatus Phlomobacter fragariae» is the prevalent agent of strawberry marginal chlorosis (SMC) and is transmitted by the planthopper Cixius wagneri. Because the insect vector biology was unknown, a field experiment was set up to determine if it was able to reproduce on strawberry plants, to determine the number of insect generations per year and the ability of nymphs to transmit SMC. During spring 2004, 80 C. wagneri adults were delivered into 4 small insectproof tunnels containing 30 healthy plants. Fifteen percent of the delivered insect population were carrying the pathogen. In October 2004, only 3 young L1 instar nymphs were found in the first tunnel, demonstrating there were no new insect generations during the summer. In April 2005, 330 C. wagneri of early L1 to late L5 nymph instars were collected at the roots of the plants,clearly indicating that a single insect generation had overwintered as larvae andemerged at the following spring. All instars were shown to carry ‘Ca. P. fragariae’ (70 to 75 % of the larvae) and were able to transmit SMC as assessed by transmission assays. An insecticide treatment was applied in March 2005 in a third tunnel and a fourth tunnel was kept as a control. More than 120 C. wagneri adults were collected in the control tunnel 4 in June 2005 confirming that an insect generation arose in the tunnel, whereas no insects could be found in the treated tunnel 3. All plants were kept for two years, surveyed for symptom expression and tested for ‘Ca. P. fragariae’ infection by 16S-PCR. Results indicated a reduced mortality and SMC incidence in tunnel 3, and a higher mortality and SMC incidence in tunnel 2 than in tunnel 1, attesting that C. wagneri larvae had spread SMC and that an early insecticide treatment could control the disease.Keywords: Phloem-restricted bacteria, planthopper, insect vector, Fragaria x ananass

Triplex real-time PCR assay for sensitive and simultaneous detection of grapevine phytoplasmas of the 16SrV and 16SrXII-A groups with an endogenous analytical control

Flavescence dorée (FD) and Bois noir (BN) are the two main yellows of grapevine in Europe and are caused by phytoplasmas of the 16SrV and 16SrXII-A groups respectively. A new triplex real-time PCR assay was developed in order to detect simultaneously the FD and BN phytoplasmas as well as grapevine chloroplastic DNA with TaqMan minor groove binder probes. Each set of designed primers and probes specifically detected the map gene of the FD and BN phytoplasmas, respectively and did not detect phytoplasmas from other phylogenetic groups. PCR efficiencies varied from 90 to 110 %. The PCR assay showed good intra-test and inter-test reproducibility. Triplex real-time PCR was compared to the conventional biplex nested-PCR method. The sensitivity of the real-time PCR, tested on several infected periwinkle and grapevine samples, was up to 5 and 100 times higher for the BN-P and the FD-P targets, respectively. Out of 109 grapevine samples analysed 10, which were negative with the nested PCR, turned to be FD-P positive with the real-time PCR. A decision scheme was set up according to the Ct values of the FD-P, BN-P and grapevine targets in order to assess the routine detection results

PCR/RFLP-based method for molecular characterization of ‘Candidatus Phytoplasma prunorum’ strains using the aceF gene.

New molecular typing tools for phytoplasmas belonging to the 16SrX phytoplasma group have recently been developed based on the non-ribosomal genes aceF, pnp, imp, and SecY. In the present work we chose to perform a PCR-RFLP method based on the aceF gene. This genetic marker had previously shown high variability among strains of the 16SrX group, moreover, it had allowed for the differentiation of French hypovirulent ‘Candidatus Phytoplasma prunorum’ strains from virulent ones.Most of the stone fruit samples were collected in north-east Italy, although a few samples from Bosnia and Herzegovina, and Turkey were also included in the work to explore variability. French hypovirulent and virulent strains, one Azerbaijan strain and ‘Ca. P. prunorum’ strains maintained in periwinkles were used as reference strains. Some of the Italian samples were not collected in the field and they became infected by Cacopsylla pruni under controlled conditions.Sequencing of the aceF gene was performed on some of the samples tested and based on the alignment, a few restriction enzymes were selected for ‘Ca. P. prunorum’ strain differentiation. Nested PCR was performed using previously developed primers on all samples and RFLP analyses were carried out with BpiI, HaeIII and Tsp509I enzymes. BpiI and HaeIII enzymes generated two different profiles, one profile was undigested and the second one constituted by two different fragments. The Tsp509I enzyme enabled three different pattern types to be distinguished. Combining the results obtained with the three restriction enzymes, it was possible to distinguish between the ‘Ca. P. prunorum’ strains investigated in this study: 6 different RFLP subgroups AceF-A, -B, -C, -D, -E and –F. We confirmed that strains belonging to 4 subgroups, AceF-A, -B, -C and -E were present in north-east Italy, where a large number of the samples were processed. The strains of AceF-A and -E subgroups were the predominant ones (21.6% and 17.0%, respectively) and mixed infections of AceF-A+E subgroups (17.0%), and AceF-B+E (14.8%) subgroups were quite common. Keywords: phytoplasma, European stone fruit yellows, molecular differentiation, sequencin

When a Palearctic bacterium meets a Nearctic insect vector: Genetic and ecological insights into the emergence of the grapevine Flavescence dorée epidemics in Europe

Flavescence dorée (FD) is a European quarantine grapevine disease transmitted by the Deltocephalinae leafhopper Scaphoideus titanus. Whereas this vector had been introduced from North America, the possible European origin of FD phytoplasma needed to be challenged and correlated with ecological and genetic drivers of FD emergence. For that purpose, a survey of genetic diversity of these phytoplasmas in grapevines, S. titanus, black alders, alder leafhoppers and clematis were conducted in five European countries. Out of 132 map genotypes, only 11 were associated to FD outbreaks, three were detected in clematis, whereas 127 were detected in alder trees, alder leafhoppers or in grapevines out of FD outbreaks. Most of the alder trees were found infected, including 8% with FD genotypes M6, M38 and M50, also present in alders neighboring FD-free vineyards and vineyard-free areas. The Macropsinae Oncopsis alni could transmit genotypes unable to achieve transmission by S. titanus, while the Deltocephalinae Allygus spp. and Orientus ishidae transmitted M38 and M50 that proved to be compatible with S. titanus. Variability of vmpA and vmpB adhesin-like genes clearly discriminated 3 genetic clusters. Cluster Vmp-I grouped genotypes only transmitted by O. alni, while clusters Vmp-II and -III grouped genotypes transmitted by Deltocephalinae leafhoppers. Interestingly, adhesin repeated domains evolved independently in cluster Vmp-I, whereas in clusters Vmp-II and-III showed recent duplications. Latex beads coated with various ratio of VmpA of clusters II and I, showed that cluster II VmpA promoted enhanced adhesion to the Deltocephalinae Euscelidius variegatus epithelial cells and were better retained in both E. variegatus and S. titanus midguts. Our data demonstrate that most FD phytoplasmas are endemic to European alders. Their emergence as grapevine epidemic pathogens appeared restricted to some genetic variants pre-existing in alders, whose compatibility to S. titanus correlates with different vmp gene sequences and VmpA binding properties

A General Definition and Nomenclature for Alternative Splicing Events

Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is one of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenon contributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora of different transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify the different types of reflected splicing variation. In this work, we present a general definition of the AS event along with a notation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assigns a specific “AS code” to every possible pattern of splicing variation. On the basis of this definition and the corresponding codes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of AS events in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversity across genes, chromosomes, and species. Our analysis reveals that a substantial part—in human more than a quarter—of the observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate and to compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that proportions of AS events change substantially depending on the annotation protocol, species-specific attributes, and coding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conduct specific studies investigating the occurrence, impact, and regulation of AS

Automating Genomic Data Mining via a Sequence-based Matrix Format and Associative Rule Set

There is an enormous amount of information encoded in each genome – enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands

Using ESTs to improve the accuracy of de novo gene prediction

BACKGROUND: ESTs are a tremendous resource for determining the exon-intron structures of genes, but even extensive EST sequencing tends to leave many exons and genes untouched. Gene prediction systems based exclusively on EST alignments miss these exons and genes, leading to poor sensitivity. De novo gene prediction systems, which ignore ESTs in favor of genomic sequence, can predict such "untouched" exons, but they are less accurate when predicting exons to which ESTs align. TWINSCAN is the most accurate de novo gene finder available for nematodes and N-SCAN is the most accurate for mammals, as measured by exact CDS gene prediction and exact exon prediction. RESULTS: TWINSCAN_EST is a new system that successfully combines EST alignments with TWINSCAN. On the whole C. elegans genome TWINSCAN_EST shows 14% improvement in sensitivity and 13% in specificity in predicting exact gene structures compared to TWINSCAN without EST alignments. Not only are the structures revealed by EST alignments predicted correctly, but these also constrain the predictions without alignments, improving their accuracy. For the human genome, we used the same approach with N-SCAN, creating N-SCAN_EST. On the whole genome, N-SCAN_EST produced a 6% improvement in sensitivity and 1% in specificity of exact gene structure predictions compared to N-SCAN. CONCLUSION: TWINSCAN_EST and N-SCAN_EST are more accurate than TWINSCAN and N-SCAN, while retaining their ability to discover novel genes to which no ESTs align. Thus, we recommend using the EST versions of these programs to annotate any genome for which EST information is available. TWINSCAN_EST and N-SCAN_EST are part of the TWINSCAN open source software package