Dataset Information

Draft Genome Sequences of Seven Strains of Dickeya dadantii, a Quick Decline-Causing Pathogen in Fruit Trees, Isolated in Japan.

ABSTRACT: The plant-pathogenic bacterium Dickeya dadantii causes quick decline in fruit trees (e.g., apple, Japanese pear, and peach). In this study, we report on the draft genome sequences of seven strains of D. dadantii that were isolated from fruit trees with typical quick decline symptoms in Japan.

SUBMITTER: Fujikawa T

PROVIDER: S-EPMC7348025 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Draft Genome Sequences of Seven Strains of Dickeya dadantii, a Quick Decline-Causing Pathogen in Fruit Trees, Isolated in Japan.

Fujikawa Takashi T Hatomi Hiroe H Ota Nobuyoshi N

Microbiology resource announcements 20200709 28

The plant-pathogenic bacterium <i>Dickeya dadantii</i> causes quick decline in fruit trees (e.g., apple, Japanese pear, and peach). In this study, we report on the draft genome sequences of seven strains of <i>D. dadantii</i> that were isolated from fruit trees with typical quick decline symptoms in Japan. ...[more]

PMID: 32646907

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Project description:Dickeya dadantii is a phytopathogenic bacterium that causes soft rot in a wide range of plant hosts worldwide and a model organism for studying virulence gene regulation. The present study provides a comprehensive and annotated transcriptomic map of D. dadantii obtained by a computational method combining five independent transcriptomic data sets: (i) paired-end RNA sequencing (RNA-seq) data for a precise reconstruction of the RNA landscape; (ii) DNA microarray data providing transcriptional responses to a broad variety of environmental conditions; (iii) long-read Nanopore native RNA-seq data for isoform-level transcriptome validation and determination of transcription termination sites; (iv) differential RNA sequencing (dRNA-seq) data for the precise mapping of transcription start sites; (v) in planta DNA microarray data for a comparison of gene expression profiles between in vitro experiments and the early stages of plant infection. Our results show that transcription units sometimes coincide with predicted operons but are generally longer, most of them comprising internal promoters and terminators that generate alternative transcripts of variable gene composition. We characterize the occurrence of transcriptional read-through at terminators, which might play a basal regulation role and explain the extent of transcription beyond the scale of operons. We finally highlight the presence of noncontiguous operons and excludons in the D. dadantii genome, novel genomic arrangements that might contribute to the basal coordination of transcription. The highlighted transcriptional organization may allow D. dadantii to finely adjust its gene expression program for a rapid adaptation to fast-changing environments. IMPORTANCE This is the first transcriptomic map of a Dickeya species. It may therefore significantly contribute to further progress in the field of phytopathogenicity. It is also one of the first reported applications of long-read Nanopore native RNA-seq in prokaryotes. Our findings yield insights into basal rules of coordination of transcription that might be valid for other bacteria and may raise interest in the field of microbiology in general. In particular, we demonstrate that gene expression is coordinated at the scale of transcription units rather than operons, which are larger functional genomic units capable of generating transcripts with variable gene composition for a fine-tuning of gene expression in response to environmental changes. In line with recent studies, our findings indicate that the canonical operon model is insufficient to explain the complexity of bacterial transcriptomes.

Dataset Information

Draft Genome Sequences of Seven Strains of Dickeya dadantii, a Quick Decline-Causing Pathogen in Fruit Trees, Isolated in Japan.

Publications

Draft Genome Sequences of Seven Strains of Dickeya dadantii, a Quick Decline-Causing Pathogen in Fruit Trees, Isolated in Japan.

Similar Datasets

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