A list of some of the papers directly from our group, with some short explanations.
Accurate and fast graph-based pangenome annotation and clustering with ggCaller
Samuel T. Horsfield, Nicholas J. Croucher and John A. Lees (2023). Accurate and fast graph-based pangenome annotation and clustering with ggCaller bioRxiv
Annotation of bacterial pangenomes is typically done one at a time. Each input assembly is annotated by calling and scoring open-reading frames (ORFs), and aligning all of these against databases to annotate function by homology. However, this is highly redundant. Many of these sequences will be shared and therefore the same computational operations used repeatedly. Furthermore, if genomes were annotated together population information could be used to guide this process, with higher quality sequences guiding annotation in lower quality samples, and overall more consistent gene calls.
ggCaller (graph-gene-caller) is a new approach which annotates ORFs within a population de Bruijn graph. Building on key tools bifrost and panaroo, ggCaller combines the steps of annotation and pangenome clustering, going from a set of input assemblies to annotated GFFs and a pangenome matrix. We show this saves time (up to 50x faster), and can give more accurate gene and cluster of orthologous genes (COG) calls, particularly in ‘difficult’ regions. We also show that this is a nice addition to the application and interpretation of bacterial GWAS. Good results can be obtained for whole genomes, but also smaller complex regions such as the capsule operon.
ggCaller packages a lot of the steps for analysis of bacterial genomes into one place:
- Annotation of fasta files to GFFs.
- Pangenome clustering and correction, typical plots (rarefaction, SFS).
- Core and accessory genome alignment.
- SNP calling in core and accessory genes.
- Structural variant calling.
- Sequence search.
- Basic phylogenetics and visualisation.
See the code on the software page.
Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation
John A Lees, Gerry Tonkin-Hill, Zhirong Yang and Jukka Corander (2022). Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation. Philosophical Transactions of the Royal Society B 377:20210237
Dimension reduction methods are a popular way to work with large amounts of genetic data: PCA, t-SNE and UMAP have all been used to analyse and visualise lots of samples in two-dimensions. These techniques are often used to cluster data, but have not been explicitly designed to do so. Some of these methods also stuggle to work with the millions of genomes now available.
Here we re-implement and extend the stochastic cluster embedding (SCE) method to work with genetic data, which is optimised to find visually identifiable clusters. Stochastic gradient descent is used to optimise, which we port to GPUs, and can run through datasets with millions of samples in a couple of hours.
We show good clustering of all bacterial data in the ENA as of 2018 (661k samples) and SARS-CoV-2 as of Nov 2021 (about 1M samples). We also make some fun videos and audio of the optimisation process.
See the code on the software page too.
Pneumococcal genetic variability in age-dependent bacterial carriage
Philip HC Kremer, Bart Ferwerda, Hester J Bootsma, Nienke Y Rots, Alienke J Wijmenga-Monsuur, Elisabeth AM Sanders, Krzysztof Trzciński, Anne L Wyllie, Paul Turner, Arie van der Ende, Matthijs C Brouwer, Stephen D Bentley, Diederik van de Beek, John A Lees (2022). Pneumococcal genetic variability in age-dependent bacterial carriage. eLife 11:e69244
Previous studies have suggested that piliated S. pneumoniae strains are more commonly carried by infants, and there is a lot of evidence showing that infant immune response is different from adult immune response to carriage. Vaccine modelling studies have also suggested that to more effectively immunise against pneumococcal disease, the presently circulating population and distribution in adults and children should be accounted for.
We use genome-wide association studies (GWAS) to search for genetic factors associated with S. pneumoniae carriage in infants versus adults, in a meta-analysis over two populations. Overall we find wide between-cohort differences in strain composition, and between ages, but no clear independent genetic signals associated with infants or adults. This supports proposals future vaccination strategies which are primarily targeted at dominant circulating serotypes in specific pathogen populations.
Here’s our tree and metadata (view on microreact.org):