Project description:Grapevine red blotch is a recently identified viral disease that was first recognized in the Napa Valley of California. Infected plants showed foliar symptoms similar to leafroll, another grapevine viral disease, on vines testing negative for known grapevine leafroll-associated virus. Later, the Grapevine red blotch virus (GRBV) was independently discovered in the US states of California and New York and was demonstrated to be the causal agent of red blotch disease. Due to its wide occurrence in the US, vector transmission and impacts on grape industry, this virus has the potential to cause serious economic losses. Despite numerous attempts, it was not possible to isolate or visualize viral particles from GRBV infected plants. Consequently, this has hampered the development of a serological assay that would facilitate GRBV detection in grapevine. We therefore decided to explore mass spectrometry approaches in order to quantify GRBV in infected plants and to identify potential biomarkers for viral infection. We present for the first time the physical detection on the protein level of the two GRBV genes V1 (coat protein) and V2 in grapevine tissue lysates. The GRBV coat protein load in leaf petioles was determined to be in the range of 100 to 900 million copies per milligram wet weight by using three heavy isotope labeled reference peptides as internal standards. The V1 copy number per unit wet tissue weight in leaves appeared to be about six times lower, and about 200-times lower in terms of protein concentration in the extractable protein mass than in petioles. We found a consistent upregulation of several enzymes involved in flavonoid biosynthesis in leaf and petiole extracts of GRBV-infected plants by label-free shotgun proteomics, indicating the activation of a defense mechanism against GRBV, a plant response already described for grapevine leafroll associated virus infection on the transcriptome level. Last but not least, we identified some other microorganisms belonging to the grapevine leaf microbiota, two bacterial species (Novosphingobium sp. Rr 2-17 and Methylobacterium) and one virus, Grapevine rupestris stem pitting associated virus.
Project description:Grapevine red blotch is a recently identified viral disease that was first recognized in the Napa Valley of California. Infected plants showed foliar symptoms similar to leafroll, another grapevine viral disease, on vines testing negative for known grapevine leafroll-associated virus. Later, the Grapevine red blotch virus (GRBV) was independently discovered in the US states of California and New York and was demonstrated to be the causal agent of red blotch disease. Due to its wide occurrence in the US, vector transmission and impacts on grape industry, this virus has the potential to cause serious economic losses. Despite numerous attempts, it was not possible to isolate or visualize viral particles from GRBV infected plants. Consequently, this has hampered the development of a serological assay that would facilitate GRBV detection in grapevine. We therefore decided to explore mass spectrometry approaches in order to quantify GRBV in infected plants and to identify potential biomarkers for viral infection. We present for the first time the physical detection on the protein level of the two GRBV genes V1 (coat protein) and V2 in grapevine tissue lysates. The GRBV coat protein load in leaf petioles was determined to be in the range of 100 to 900 million copies per milligram wet weight by using three heavy isotope labeled reference peptides as internal standards. The V1 copy number per unit wet tissue weight in leaves appeared to be about six times lower, and about 200-times lower in terms of protein concentration in the extractable protein mass than in petioles. We found a consistent upregulation of several enzymes involved in flavonoid biosynthesis in leaf and petiole extracts of GRBV-infected plants by label-free shotgun proteomics, indicating the activation of a defense mechanism against GRBV, a plant response already described for grapevine leafroll associated virus infection on the transcriptome level. Last but not least, we identified some other microorganisms belonging to the grapevine leaf microbiota, two bacterial species (Novosphingobium sp. Rr 2-17 and Methylobacterium) and one virus, Grapevine rupestris stem pitting associated virus.
Project description:Expression profiling of 7,530 Heterodera glycines probesets present on the Affymetrix Soybean Genome Array GeneChip throughout the life cycle of the nematode (egg, infective J2, parasitic J2, J3, J4, adult female).
Project description:Purpose: Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae) and soybean cyst nematode, Heterodera glycines Ichinohe, (SCN) are the two most economically important pests of soybean, Glycine max (L.) Merr., in the Midwest. Although the soybean aphid is an aboveground pest and SCN is a belowground pest there is evidence that concomitant infestations result in improved SCN reproduction. This study is aimed to characterize the three-way interactions among soybean, soybean aphid and SCN using demographic and genetic datasets. Results: More than 1.1 billion reads (61.4 GB) of transcriptomic data were yielded from 47 samples derived from the experiment using whole roots of G. max. The phred quality scores per base for all the samples were higher than 30. The GC content ranged from 43 to 45% and followed the normal distribution. After trimming, more than 99% of the reads were retained as the clean and good quality reads. Upon mapping these reads, we obtained high mapping rate ranging from 73.8% to 94.3%. Among the mapped reads, 67.1% to 87.6% reads were uniquely mapped. Conclusions: The comprehensive understanding of these transcriptome data would help in understanding the molecular interactions among soybean, A. glycines, and H. glycines. The use of multifaceted bioinformatics approaches could facilitate finding candidate genes and their function that might play a crucial role in various pathways for host resistance against both soybean aphids and SCN. For differential gene expression analysis, EdgeR, limma, and DEseq2 could be used. Apart from standalone tools like iDEP, Galaxy (https://usegalaxy.org), CyVerse (http://www.cyverse.org), and MeV (http://mev.tm4.org) could also be used for both analysis and visualization of RNA- seq data.
Project description:Gene expression profiles in the bacterial pustule-resistant soybean cultivars To investigate the differential action between resistance and susceptible cultivars, we examined genome wide expression levels at five time points after X. axonopodis pv. Glycines (Xag) inoculation using microarray.