Dataset Information

High-throughput sequence analysis of small RNAs in grapevine (Vitis vinifera L.) affected by grapevine leafroll disease.

ABSTRACT: Grapevine leafroll disease (GLRD) is one of the most economically important virus diseases of grapevine (Vitis spp.) worldwide. In this study, we used high-throughput sequencing of cDNA libraries made from small RNAs (sRNAs) to compare profiles of sRNA populations recovered from own-rooted Merlot grapevines with and without GLRD symptoms. The data revealed the presence of sRNAs specific to Grapevine leafroll-associated virus 3, Hop stunt viroid (HpSVd), Grapevine yellow speckle viroid 1 (GYSVd-1) and Grapevine yellow speckle viroid 2 (GYSVd-2) in symptomatic grapevines and sRNAs specific only to HpSVd, GYSVd-1 and GYSVd-2 in nonsymptomatic grapevines. In addition to 135 previously identified conserved microRNAs in grapevine (Vvi-miRs), we identified 10 novel and several candidate Vvi-miRs in both symptomatic and nonsymptomatic grapevine leaves based on the cloning of miRNA star sequences. Quantitative real-time reverse transcriptase-polymerase chain reaction (RT-PCR) of selected conserved Vvi-miRs indicated that individual members of an miRNA family are differentially expressed in symptomatic and nonsymptomatic leaves. The high-resolution mapping of sRNAs specific to an ampelovirus and three viroids in mixed infections, the identification of novel Vvi-miRs and the modulation of certain conserved Vvi-miRs offers resources for the further elucidation of compatible host-pathogen interactions and for the provision of ecologically relevant information to better understand host-pathogen-environment interactions in a perennial fruit crop.

SUBMITTER: Alabi OJ

PROVIDER: S-EPMC6638782 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High-throughput sequence analysis of small RNAs in grapevine (Vitis vinifera L.) affected by grapevine leafroll disease.

Alabi Olufemi J OJ Zheng Yun Y Jagadeeswaran Guru G Sunkar Ramanjulu R Naidu Rayapati A RA

Molecular plant pathology 20120724 9

Grapevine leafroll disease (GLRD) is one of the most economically important virus diseases of grapevine (Vitis spp.) worldwide. In this study, we used high-throughput sequencing of cDNA libraries made from small RNAs (sRNAs) to compare profiles of sRNA populations recovered from own-rooted Merlot grapevines with and without GLRD symptoms. The data revealed the presence of sRNAs specific to Grapevine leafroll-associated virus 3, Hop stunt viroid (HpSVd), Grapevine yellow speckle viroid 1 (GYSVd-1 ...[more]

PMID: 22827483

Similar Datasets

Project description:UnlabelledCrown gall disease of grapevine is caused by virulent Agrobacterium strains and establishes a suitable habitat for agrobacteria and, potentially, other bacteria. The microbial community associated with grapevine plants has not been investigated with respect to this disease, which frequently results in monetary losses. This study compares the endophytic microbiota of organs from grapevine plants with or without crown gall disease and the surrounding vineyard soil over the growing seasons of 1 year. Amplicon-based community profiling revealed that the dominating factor causing differences between the grapevine microbiota is the sample site, not the crown gall disease. The soil showed the highest microbial diversity, which decreased with the distance from the soil over the root and the graft union of the trunk to the cane. Only the graft union microbiota was significantly affected by crown gall disease. The bacterial community of graft unions without a crown gall hosted transient microbiota, with the three most abundant bacterial species changing from season to season. In contrast, graft unions with a crown gall had a higher species richness, which in every season was dominated by the same three bacteria (Pseudomonas sp., Enterobacteriaceae sp., and Agrobacterium vitis). For in vitro-cultivated grapevine plantlets, A. vitis infection alone was sufficient to cause crown gall disease. Our data show that microbiota in crown galls is more stable over time than microbiota in healthy graft unions and that the microbial community is not essential for crown gall disease outbreak.ImportanceThe characterization of bacterial populations in animal and human diseases using high-throughput deep-sequencing technologies, such as 16S amplicon sequencing, will ideally result in the identification of disease-specific microbiota. We analyzed the microbiota of the crown gall disease of grapevine, which is caused by infection with the bacterial pathogen Agrobacterium vitis. All other Agrobacterium species were found to be avirulent, even though they lived together with A. vitis in the same crown gall tumor. As has been reported for human cancer, the crown gall tumor also hosted opportunistic bacteria that are adapted to the tumor microenvironment. Characterization of the microbiota in various diseases using amplicon sequencing may help in early diagnosis, to serve as a preventative measure of disease in the future.

Project description:BackgroundSingle-nucleotide polymorphisms (SNPs) are the most abundant type of DNA sequence polymorphisms. Their higher availability and stability when compared to simple sequence repeats (SSRs) provide enhanced possibilities for genetic and breeding applications such as cultivar identification, construction of genetic maps, the assessment of genetic diversity, the detection of genotype/phenotype associations, or marker-assisted breeding. In addition, the efficiency of these activities can be improved thanks to the ease with which SNP genotyping can be automated. Expressed sequence tags (EST) sequencing projects in grapevine are allowing for the in silico detection of multiple putative sequence polymorphisms within and among a reduced number of cultivars. In parallel, the sequence of the grapevine cultivar Pinot Noir is also providing thousands of polymorphisms present in this highly heterozygous genome. Still the general application of those SNPs requires further validation since their use could be restricted to those specific genotypes.ResultsIn order to develop a large SNP set of wide application in grapevine we followed a systematic re-sequencing approach in a group of 11 grape genotypes corresponding to ancient unrelated cultivars as well as wild plants. Using this approach, we have sequenced 230 gene fragments, what represents the analysis of over 1 Mb of grape DNA sequence. This analysis has allowed the discovery of 1573 SNPs with an average of one SNP every 64 bp (one SNP every 47 bp in non-coding regions and every 69 bp in coding regions). Nucleotide diversity in grape (pi = 0.0051) was found to be similar to values observed in highly polymorphic plant species such as maize. The average number of haplotypes per gene sequence was estimated as six, with three haplotypes representing over 83% of the analyzed sequences. Short-range linkage disequilibrium (LD) studies within the analyzed sequences indicate the existence of a rapid decay of LD within the selected grapevine genotypes. To validate the use of the detected polymorphisms in genetic mapping, cultivar identification and genetic diversity studies we have used the SNPlextrade mark genotyping technology in a sample of grapevine genotypes and segregating progenies.ConclusionThese results provide accurate values for nucleotide diversity in coding sequences and a first estimate of short-range LD in grapevine. Using SNPlextrade mark genotyping we have shown the application of a set of discovered SNPs as molecular markers for cultivar identification, linkage mapping and genetic diversity studies. Thus, the combination a highly efficient re-sequencing approach and the SNPlextrade mark high throughput genotyping technology provide a powerful tool for grapevine genetic analysis.

Dataset Information

High-throughput sequence analysis of small RNAs in grapevine (Vitis vinifera L.) affected by grapevine leafroll disease.

Publications

High-throughput sequence analysis of small RNAs in grapevine (Vitis vinifera L.) affected by grapevine leafroll disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets