Data and code for “Resolving the paradox in <i>Streptomyces</i>: eco-evolutionary dynamics sustain a potent yet rare antibiotic gene cluster” item

<p dir="ltr">This dataset comprises the raw and processed data supporting the research article “Resolving the paradox in <i>Streptomyces</i>: eco-evolutionary dynamics sustain a potent yet rare antibiotic gene cluster”. The data are organized into the following components:</p><p dir="ltr">1. Antagonism Assay Data: Raw image files from pairwise competition assays.</p><p dir="ltr">2. Microcosm Experiment Data: Amplicon sequencing data and raw cell counts for the producer, resistant, and sensitive strains across different environmental conditions.</p><p dir="ltr">3. Chemical Characterization Data: High-Resolution Electrospray Ionization Mass Spectrometry (HR-ESI-MS) files confirming the identity and production of kosinostatin.</p><p dir="ltr">4. Genomic and Bioinformatic Resources: Publicly available <i>Actinomycetota </i>genome accession numbers analyzed in this study, along with custom Python scripts for data analysis and the raw data from codon adaptation index (CAI) calculations.</p><p dir="ltr">Collectively, these data provide the empirical foundation for the study's conclusions on context-dependent selection, fitness trade-offs, and the role of horizontal gene transfer in shaping antibiotic BGC distribution. They are essential for reproducing the findings and will facilitate future comparative studies and meta-analyses on the evolution of microbial secondary metabolism.</p>