Project description:As virus diseases cannot be controlled by traditional plant protection methods the risk of their spread have to be minimized on vegetatively propagated plants, such as grapevine. Metagenomics approaches used for virus diagnostics, offer a unique opportunity to reveal the presence of all viral pathogens in the investigated plant, why their usage can reduce the risk of using infected material for a new plantation. Here we used a special field, deep sequencing of virus derived small RNAs, of this high throughput method for virus diagnostics and determined viromes of vineyards in Hungary. With NGS of virus derived small RNAs we could detect not only the viruses tested routinely, but also new ones, which have never been described in Hungary before. Virus presence didn’t correlated with the age of the plantation, moreover phylogenetic analysis of the identified virus isolates suggests that infections mostly caused by the usage of infected propagating material. Our results, validated by other molecular methods, highlighted further questions to be answered before these method can be introduced as a routine, reliable test for grapevine virus diagnostics.
2018-04-05 | GSE106240 | GEO
Project description:Plant metagenomics tomato virus for NDR
Project description:This series includes a 32-array training dataset used to evaluate E-Predict normalization and similarity metric parameters as well as 13 microarrays used as examples in (Urisman, et. al 2005). Training data set includes 15 independent HeLa RNAhybridizations (microarrays 1-15), 10 independent nasal lavage samples positive for Respiratory Syncytial virus (microarrays 16-25), and 7 independent nasal lavage samples positive for Influenza A virus (microarrays 26-32). Examples iclude a serum sample positive for Hepatitis B virus (microarray 33), a nasal lavage sample positive for both Influenza A virus and Respiratory Syncytial virus (microarray 34), and culture samples of 11 distinct Human Rhinovirus serotypes (microarrays 35-45). Keywords = virus detection, E-Predict, species identification, metagenomics
Project description:This series includes a 32-array training dataset used to evaluate E-Predict normalization and similarity metric parameters as well as 13 microarrays used as examples in (Urisman, et. al 2005). Training data set includes 15 independent HeLa RNAhybridizations (microarrays 1-15), 10 independent nasal lavage samples positive for Respiratory Syncytial virus (microarrays 16-25), and 7 independent nasal lavage samples positive for Influenza A virus (microarrays 26-32). Examples iclude a serum sample positive for Hepatitis B virus (microarray 33), a nasal lavage sample positive for both Influenza A virus and Respiratory Syncytial virus (microarray 34), and culture samples of 11 distinct Human Rhinovirus serotypes (microarrays 35-45). Keywords = virus detection, E-Predict, species identification, metagenomics Keywords: other
Project description:We have performed RNA sequencing on kidneys from inclusion body nephropathy-affected mice and compared the data to healthy, uninfected controls. Using a metagenomics approach, we report the identification of the disease causing agent as an atypical virus, mouse kidney parvovirus (MKPV), belonging to a divergent genus of the Parvoviridae. The RNA sequencing also enabled us to assess the host response to MKPV-infection.
2018-07-27 | GSE117710 | GEO
Project description:Plant virus metagenomic data 2022
| PRJNA808246 | ENA
Project description:Plant virus metagenomic data 2021