Dickeya dadantii is a phytopathogenic bacterium that causes soft rot in a wide range of plant hosts worldwide and a model organism for studying gene regulation during the pathogenic process. The present study provides a comprehensive and annotated transcriptomic map of D. dadantii obtained by a computational method combining three independent transcriptomic datasets covering a wide range of conditions which closely reproduce the variations of transcription occurring in the course of plant infection: (1) paired-end RNA-seq data for a precise reconstruction of the RNA landscape, (2) DNA microarray data reflecting gene response to sudden environmental shocks mimicking conditions encountered by bacteria in the plant, (3) dRNA-seq data for a specific high-resolution mapping of transcription start sites. We define transcription units throughout the genome, and map the associated transcription start and termination sites with a quantitative magnitude analysis. Our results show that transcription units sometimes coincide with predicted operons but are generally longer, most of them exhibiting 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 D. dadantii genome, novel genomic arrangements that might contribute to the basal coordination of transcription. The highlighted transcriptional organization may allow D. dadantii finely adjusting its gene expression program for a rapid adaptation to fast changing environment relevant to plant infection. Importance: this is the first transcriptomic map of a phytopathogen, characterized under physiological conditions encountered by the bacteria during the infection process. It might therefore significantly contribute to further progress in the field of phytopathogenicity. Our findings also provide 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.