Digitalni repozitorij raziskovalnih organizacij Slovenije

Iskanje po repozitoriju
A+ | A- | Pomoč | SLO | ENG

Iskalni niz: išči po
išči po
išči po
išči po

Možnosti:
  Ponastavi


Iskalni niz: "avtor" (Neil Boonham) .

1 - 2 / 2
Na začetekNa prejšnjo stran1Na naslednjo stranNa konec
1.
Looking beyond virus detection in RNA sequencing data : lessons learned from a community-based effort to detect cellular plant pathogens and pests
Annelies Haegeman, Yoika Foucart, Kris De Jonghe, Thomas Goedefroit, Maher Al Rwahnih, Neil Boonham, Thierry Candresse, Yahya Gaafar, Oscar Hurtado-Gonzales, Zala Kogej Zwitter, Denis Kutnjak, Janja Lamovšek, Irena Mavrič Pleško, 2023, izvirni znanstveni članek

Povzetek: High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.
Ključne besede: plant viruses, plant virus detection, plant virology, high-throughput sequencing, RNA sequencing, plant tissues, plant pathogen, diagnostics, high-throughput sequencing, metagenomics, metatranscriptomics
Objavljeno v DiRROS: 12.07.2024; Ogledov: 3; Prenosov: 2
.pdf Celotno besedilo (1,70 MB)

2.
Highly specific qPCR and amplicon sequencing method for detection of quarantine citrus pathogen Phyllosticta citricarpaapplicable for air samples
Janja Zajc, Zala Kogej Zwitter, Sara Fišer, Cene Gostinčar, Antonio Vicent, Anaïs Galvañ Domenech, Luca Riccioni, Neil Boonham, Maja Ravnikar, Polona Kogovšek, 2023, izvirni znanstveni članek

Povzetek: The fungus Phyllosticta citricarpa is a quarantine pathogen in the EU and is of high economic importance in many parts of the world where favourable climate conditions drive the development of citrus black spot (CBS) disease. Disease symptoms include necrotic lesions on leaves and fruits. Low disease pressure can reduce crop market-ability, while higher disease pressure can cause premature fruit drop, significantly increasing crop losses. The wind-dispersed spores of P. citricarpa are especially prob-lematic for rapid pathogen dispersal, but also provide an opportunity for early detec-tion of the disease spreading into a new area. In this study we have developed and validated a quantitative PCR (qPCR) assay based on the TEF1-α sequence. Specificity testing demonstrated that it is currently the only qPCR assay that does not cross- react with closely related Phyllosticta species. The assay is sensitive and can detect a single copy of the TEF1 gene in a reaction, it is highly repeatable and reproducible and can be used for testing of the sticky tapes from spore traps as well as citrus fruit sam-ples. High-throughput sequencing (HTS) of the DNA barcodes ITS1 and TEF1 was also explored for the detection and discrimination of P. citricarpa. The limit of detection of the HTS was 1000 spores on a daily spore trap tape. This study makes an important improvement to the diagnostics of the CBS and the methods developed can also be applied to improve the surveillance and early detection of the pathogen when linked to spore samplers in the field.
Ključne besede: detection, fungal spore sampling, internal transcribed region (ITS), translation elongation factor 1-α (TEF1)
Objavljeno v DiRROS: 12.07.2024; Ogledov: 11; Prenosov: 4
.pdf Celotno besedilo (1,49 MB)
Gradivo ima več datotek! Več...

Iskanje izvedeno v 0.06 sek.
Na vrh