This repository contains code and data for generating and analyzing the E. coli non-coding alleleome and associated figures. This alleleome contains 1,169 reference non-coding regions from strain K-12 MG1655 that are well-annotated with non-coding functional sites such as transcription factor binding sites, core promoters, and transcriptional attenuators from RegulonDB. These regions are mapped across 2,350 E. coli strains downloaded from BV-BRC (formerly known as PATRIC).
Microbial genome sequences are rapidly accumulating, enabling large-scale studies of sequence variation. Existing studies primarily focus on coding regions to study patterns of amino acid substitutions in proteins. However, non-coding regulatory regions also play a distinct role in determining physiologic responses. To investigate intergenic sequence variation on a large-scale, we identified non-coding regulatory region alleles across 2,350 fully-sequenced Escherichia coli strains. This “alleleome” consists of 117,781 unique alleles for 1,169 reference regulatory regions (transcribing 1,975 genes) at single base-pair resolution. We find a high degree of conservation in non-coding sequences; overall 64% of nucleotide positions are invariant, and variant positions vary in a median of just 0.6% of strains. Additionally, non-coding alleles are sufficient to recover E. coli phylogroups. We find that core promoter elements and transcription factor binding sites are conserved, especially those located upstream of essential or highly-expressed genes. However, variability in conservation of transcription factor binding sites is significant both within and across regulons. Finally, we contrast mutations acquired during adaptive laboratory evolution with wild-type variation, finding that the former preferentially alter positions that the latter conserves. Overall, this analysis elucidates the wealth of information found in E. coli non-coding sequence variation and expands pangenomic studies to non-coding regions at single-nucleotide resolution.
The following software are required to successfully run this workflow and analysis:
- Python 3.10+
- Python packages (can be installed with
pip <package name>):- biopython
- logomaker
- matplotlib
- numpy
- pandas
- pymodulon
- scipy
- sklearn
- statsmodels
- seaborn
- Command line programs
The processing and analysis workflow are organized into 2 Jupyter notebooks: 0__build_alleleome and 1__analyze_alleleome. Only the latter need be run to analyze the pre-processed and analyzed alleleome reported in this publication. Otherwise, the former notebook may be used to re-generate an alleleome with more genomes/reference regions, or for a different organism. See these notebooks for detailed instructions on execution and analysis.