In short
- A species' pangenome is the full set of genes found across its strains: a core genome shared by all, plus accessory genes found in some strains and unique genes found in one.
- In the study that introduced the concept, the core genome made up about 80% of any single Streptococcus agalactiae genome, and new genes kept appearing with each strain sequenced.
- Tools such as Roary and Panaroo cluster genes across hundreds or thousands of genomes. Panaroo corrects many errors caused by annotation and fragmented assemblies.
- Pangenome results are only as good as the annotations that go into them, so every genome should be annotated the same way.
From one genome to many
A single genome describes one strain, not a species. When Tettelin and colleagues compared six genomes of Streptococcus agalactiae, they found a core genome shared by all isolates that made up about 80% of any single genome. The rest was a "dispensable" genome of partially shared and strain-specific genes. Extrapolating from the data suggested that the species' gene pool is vast, and that new genes would keep appearing even after hundreds of genomes had been sequenced [1]. They called the whole set the pan-genome.
A pangenome like this, which keeps growing as strains are added, is called open. Species with a closed pangenome add few new genes after a handful of genomes. Whether a pangenome is open or closed says a lot about how a species lives and how much it exchanges genes with other bacteria.
How genes are categorised
| Category | Found in | What it usually contains |
|---|---|---|
| Core | 99–100% of strains | Essential functions: replication, transcription, translation, central metabolism |
| Soft core | 95–99% of strains | Near-universal genes, sometimes missing because of assembly gaps |
| Shell | 15–95% of strains | Traits shared by groups of strains, such as specific metabolic pathways |
| Cloud | Fewer than 15% of strains | Strain-specific genes, often on plasmids, prophages and other mobile elements |
These are the default categories reported by Roary [2]. Other tools use similar cut-offs, so always state the thresholds you used.
Tools for building a pangenome
Roary made large pangenomes practical. On a single processor it can build the pangenome of 1,000 isolates in about 4.5 hours using 13 GB of memory [2]. Panaroo builds a graph of genes and their neighbours, which lets it correct errors that build up across many genomes. These include genes split by fragmented assemblies, contamination, divergent gene families and misassemblies [3]. Without such corrections, annotation errors inflate the accessory genome and make strains look more different than they are.
This is why consistent annotation matters. Genomes downloaded from public databases were annotated with many different pipelines. Re-annotating every genome in the comparison with the same tool, such as Prokka [4], removes an important source of artificial differences.
What a pangenome can tell you
- Which genes make your strain different from others in its species, such as carbohydrate utilisation genes in a probiotic or a biosynthetic cluster in a producer strain.
- How strains are related, using a phylogeny built from the core genome.
- Which accessory genes travel together on mobile elements, which links to plasmid and mobile element analysis.
- Whether a trait is shared by a whole clade or unique to one isolate, which helps you choose strains for further study.
Pitfalls to avoid
- Mixing annotation tools between genomes, which inflates the accessory genome.
- Including low-quality or contaminated assemblies. Check them first, as explained in assembly quality metrics.
- Including genomes with the wrong species name. Confirm identity with ANI before building the pangenome.
- Uneven sampling, where many near-identical outbreak isolates can make the core genome look larger than it is for the species as a whole.
Comparative genomics with BacSeq Analytics
The Standard and Premium packages include comparative genomics: pangenome, core-genome and phylogenomic comparison of your strains with each other and with relevant public genomes. The report describes the core and accessory genome, highlights genes unique to your strains, and explains what they mean for your research question.
References
- Tettelin H, Masignani V, Cieslewicz MJ, et al. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome". Proc Natl Acad Sci USA. 2005;102:13950–13955. doi:10.1073/pnas.0506758102
- Page AJ, Cummins CA, Hunt M, et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics. 2015;31:3691–3693. doi:10.1093/bioinformatics/btv421
- Tonkin-Hill G, MacAlasdair N, Ruis C, et al. Producing polished prokaryotic pangenomes with the Panaroo pipeline. Genome Biol. 2020;21:180. doi:10.1186/s13059-020-02090-4
- Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–2069. doi:10.1093/bioinformatics/btu153