Dataset Information

Annotation of gene sequence and protein structure of brinjal EDS1.

ABSTRACT: Enhanced Disease Susceptibility1 (EDS1) is a nucleo-cytoplasmic protein, known to be a key regulator of plant basal defense and effector-triggered immunity. Sequence of a single copy brinjal EDS1 gene (SmEDS1) was mined from draft brinjal genome assembly. The extracted sequence was found to be incomplete and polished with the help of transcriptome sequence data. Full-length SmEDS1 gene is 4.5kb long having three exons that coded for 1.8kb mRNA. SmEDS1 protein is a 602 amino acid long protein consisting of Lipase3 and EP domain regions. Predicted tertiary structure of SmEDS1 using homology modelling had a mass of 68.8kD and was made of 10 strands, 26 alpha helices, five 310 helices and 43 beta turns. Phylogenetic analysis based on protein sequence grouped the species in clades defined by botanical family suggesting that EDS1 protein has evolved through the speciation process. Phylogenetic tree based on EDS1 structures grouped Solanum species of American origin (tomato, wild tomato and potato) together but brinjal EDS1 (Asiatic origin) occupied a unique position. In silico information generated in this study is expected to be the first step toward cloning and expression analysis of SmEDS1 gene.

SUBMITTER: Sharma S

PROVIDER: S-EPMC5451380 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Annotation of gene sequence and protein structure of brinjal EDS1.

Sharma Soumya S Jaiswal Sarika S Archak Sunil S

Bioinformation 20170302 3

Enhanced Disease Susceptibility1 (EDS1) is a nucleo-cytoplasmic protein, known to be a key regulator of plant basal defense and effector-triggered immunity. Sequence of a single copy brinjal EDS1 gene (SmEDS1) was mined from draft brinjal genome assembly. The extracted sequence was found to be incomplete and polished with the help of transcriptome sequence data. Full-length SmEDS1 gene is 4.5kb long having three exons that coded for 1.8kb mRNA. SmEDS1 protein is a 602 amino acid long protein con ...[more]

PMID: 28584443

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Project description:BackgroundMicrobiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis.ResultsHerein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample.ConclusionsOverall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples. Video Abstract.

Dataset Information

Annotation of gene sequence and protein structure of brinjal EDS1.

Publications

Annotation of gene sequence and protein structure of brinjal EDS1.

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