Regulation of gene activity during the cell cycle is fundamental to bacterial replication but is challenging to study in unperturbed, asynchronous bacterial populations. Using single cell RNA-sequencing of heterogeneousStaphylococcus aureuspopulations, we uncovered a global gene expression pattern dominated by chromosomal position. We show that this pattern results from the effect of DNA replication on gene expression, and inEscherichia coli, changes under different growth rates and modes of replication. By constructing a quantitative model in each species that links replication to cell cycle gene expression, we identified divergent genes that may be instead subject to distinct regulation, and applied this cell cycle framework to characterize heterogeneity in responses to antibiotic stress. Our approach reveals a highly dynamic cell cycle transcriptional landscape and may be broadly applicable across species.

Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome1. These modes interact with a changing cellular environment to yield highly dynamic expression patterns2. In bacteria, the relationship between a gene’s regulatory architecture and its expression is well understood for individual model gene circuits3,4. However, a broader perspective of these dynamics at the genome-scale is lacking, in part because bacterial transcriptomics have hitherto captured only a static snapshot of expression averaged across millions of cells5. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on each gene’s transcriptional response to its own replication, which we term the Transcription-Replication Interaction Profile (TRIP). We found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal a gene’s local regulatory context. While the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, including altered timing or amplitude of expression, and this is shaped by factors such as intra-operon position, repression state, or presence on mobile genetic elements. Our transcriptome analysis also simultaneously captures global properties, such as the rates of replication and transcription, as well as the nestedness of replication patterns. This work challenges previous notions of the drivers of expression heterogeneity within a population of cells, and unearths a previously unseen world of gene transcription dynamics.