Dataset Information

In Silico identification and annotation of non-coding RNAs by RNA-seq and De Novo assembly of the transcriptome of Tomato Fruits.

ABSTRACT: The complexity of the tomato (Solanum lycopersicum) transcriptome has not yet been fully elucidated. To gain insights into the diversity and features of coding and non-coding RNA molecules of tomato fruits, we generated strand-specific libraries from berries of two tomato cultivars grown in two open-field conditions with different soil type. Following high-throughput Illumina RNA-sequencing (RNA-seq), more than 90% of the reads (over one billion, derived from twelve dataset) were aligned to the tomato reference genome. We report a comprehensive analysis of the transcriptome, improved with 39,095 transcripts, which reveals previously unannotated novel transcripts, natural antisense transcripts, long non-coding RNAs and alternative splicing variants. In addition, we investigated the sequence variants between the cultivars under investigation to highlight their genetic difference. Our strand-specific analysis allowed us to expand the current tomato transcriptome annotation and it is the first to reveal the complexity of the poly-adenylated RNA world in tomato. Moreover, our work demonstrates the usefulness of strand specific RNA-seq approach for the transcriptome-based genome annotation and provides a resource valuable for further functional studies.

SUBMITTER: Scarano D

PROVIDER: S-EPMC5302821 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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In Silico identification and annotation of non-coding RNAs by RNA-seq and De Novo assembly of the transcriptome of Tomato Fruits.

Scarano Daria D Rao Rosa R Corrado Giandomenico G

PloS one 20170210 2

The complexity of the tomato (Solanum lycopersicum) transcriptome has not yet been fully elucidated. To gain insights into the diversity and features of coding and non-coding RNA molecules of tomato fruits, we generated strand-specific libraries from berries of two tomato cultivars grown in two open-field conditions with different soil type. Following high-throughput Illumina RNA-sequencing (RNA-seq), more than 90% of the reads (over one billion, derived from twelve dataset) were aligned to the ...[more]

PMID: 28187155

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Project description:BackgroundMassive forest decline has been observed almost everywhere as a result of negative anthropogenic and climatic effects, which can interact with pests, fungi and other phytopathogens and aggravate their effects. Climatic changes can weaken trees and make fungi, such as Armillaria more destructive. Armillaria borealis (Marxm. & Korhonen) is a fungus from the Physalacriaceae family (Basidiomycota) widely distributed in Eurasia, including Siberia and the Far East. Species from this genus cause the root white rot disease that weakens and often kills woody plants. However, little is known about ecological behavior and genetics of A. borealis. According to field research data, A. borealis is less pathogenic than A. ostoyae, and its aggressive behavior is quite rare. Mainly A. borealis behaves as a secondary pathogen killing trees already weakened by other factors. However, changing environment might cause unpredictable effects in fungus behavior.ResultsThe de novo genome assembly and annotation were performed for the A. borealis species for the first time and presented in this study. The A. borealis genome assembly contained ~ 68 Mbp and was comparable with ~ 60 and ~ 79.5 Mbp for the A. ostoyae and A. mellea genomes, respectively. The N50 for contigs equaled 50,544 bp. Functional annotation analysis revealed 21,969 protein coding genes and provided data for further comparative analysis. Repetitive sequences were also identified. The main focus for further study and comparative analysis will be on the enzymes and regulatory factors associated with pathogenicity.ConclusionsPathogenic fungi such as Armillaria are currently one of the main problems in forest conservation. A comprehensive study of these species and their pathogenicity is of great importance and needs good genomic resources. The assembled genome of A. borealis presented in this study is of sufficiently good quality for further detailed comparative study on the composition of enzymes in other Armillaria species. There is also a fundamental problem with the identification and classification of species of the Armillaria genus, where the study of repetitive sequences in the genomes of basidiomycetes and their comparative analysis will help us identify more accurately taxonomy of these species and reveal their evolutionary relationships.

Dataset Information

In Silico identification and annotation of non-coding RNAs by RNA-seq and De Novo assembly of the transcriptome of Tomato Fruits.

Publications

In Silico identification and annotation of non-coding RNAs by RNA-seq and De Novo assembly of the transcriptome of Tomato Fruits.

Similar Datasets

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