UNDER CONSTRUCTION!
Welcome to the rpoC Database!
The current version of the database (v 2.0) contains 65,156 unique, high-quality rpoC full-length gene sequences, spanning both bacterial and archaeal lineages. This resource supports microbiome and prokaryotic phylogenetic research by enabling precise taxonomic profiling and robust phylogenetic analysis.
Why rpoC?
The rpoC gene encodes the β’ subunit of the DNA-directed RNA polymerase complex – an essential enzyme for all cellular life. As a single-copy, protein-coding marker gene, rpoC offers distinct advantages for microbial community analysis:
🔍 High Phylogenetic Resolution - Discriminates taxa at the species and strain level, surpassing limiations of ribosomal RNA genes
🌍 Universal Applicability - Features a conserved domain (RNA_pol_N terminal region) for reliable primer design across diverse prokaryotes
🧬 Single Copy Locus - Unlike multi-copy markers (e.g., 16S rRNA), rpoC avoids biases in abundance estimates.
💲 Cost Effective - Uses standard PCR/sequencing protocols and is cheaper than whole-genome sequencing
While 16S rRNA sequencing remains a gold standard for microbial surveys, rpoC complements and expands the toolkit for researchers seeking finer taxonomic granularity and functional insights into microbial ecology.
Publications using (or about) rpoC as a marker gene!
- Hassler HB et al. 2022. Phylogenies of the 16S rRNA gene and its hypervariable regions lack concordance with core genome phylogenies. Microbiome 10 (104).
- Mann AE et al. 2023. Impact of HIV on the oral microbiome of children living in Sub-Saharan Africa, determined by using an rpoC gene fragment metataxonomic approach. Microbiology Spectrum 11 (4)
- Mann AE et al. 2024. Heterogeneous lineage-specific arginine deiminase expression within dental microbiome species. Microbiology Spectrum 12 (4)
- Mann AE et al. 2025. HIV infection and exposure increases cariogenic taxa, reduces taxonomic turnover, and homogenizes spatial differentiation for the supragingival microbiome. Microbiome (In Press)
Ready to explore?
This database provides curated reference sequences pre-formatted in commonly used microbiome data analysis packages, user-friendly analysis pipelines, and optimzed wet-lab protocols. Dive in using the menu links to learn more!
Cite this database: [DOI LINK]