Frequency-dependent selection in vaccine-associated pneumococcal population dynamics

Corander, Jukka; Fraser, Christophe; Gutmann, Michael U.; Arnold, Brian J.; Hanage, William P.; Bentley, Stephen D.; Lipsitch, Marc; Croucher, Nicholas J.

doi:10.1038/s41559-017-0337-x

Cited by 132 publications

(202 citation statements)

References 82 publications

(118 reference statements)

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“…We used a previously generated core genome alignment from 616 S. pneumoniae samples isolated from the nasopharynx of asymptomatically carrying children in Massachusetts 37– 40 . We ran IQ-TREE on the whole alignment using a GTR model (-m GTR).…”

Section: Methodsmentioning

confidence: 99%

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Lees¹,

Kendall²,

Parkhill³

et al. 2018

Wellcome Open Res

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Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined “true tree” using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.

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Section: Methodsmentioning

confidence: 99%

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Lees¹,

Kendall²,

Parkhill³

et al. 2018

Wellcome Open Res

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“…This can have profound implications for the resulting estimates of the pangenome whereby a higher number genomes leads to a higher number of errors (16,17). Such errors can cause difficulties in any downstream mod-D R A F T eling of the pangenome, such as the modeling of negative frequency-dependent selection (NFDS) acting through the loci in the accessory genome (18,19). Errors can be introduced into pangenome analyses by fragmented assemblies, mis-annotation, contamination and mis-assembly.…”

Section: Introductionmentioning

confidence: 99%

Producing Polished Prokaryotic Pangenomes with the Panaroo Pipeline

Tonkin‐Hill

MacAlasdair

Ruis

et al. 2020

Preprint

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110

137

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Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content, resulting from frequent horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here we introduce Panaroo, a graph based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. We verified our approach through extensive simulations of de novo assemblies using the infinitely many genes model and by analysing a number of publicly available large bacterial genome datasets. Using a highly clonal Mycobacterium tuberculosis dataset as a negative control case, we show that failing to account for annotation errors can lead to pangenome estimates that are dominated by error. We additionally demonstrate the utility of the improved graphical output provided by Panaroo by performing a pan-genome wide association study in Neisseria gonorrhoeae and by analysing gene gain and loss rates across 51 of the major global pneumococcal sequence clusters. Panaroo is freely available under an open source MIT licence at https://github.com/gtonkinhill/panaroo.

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“…Bacterial populations vary greatly in their sequence content, and mapping short variation within their core genes (coding sequences shared by all members of the population) is generally insufficient to capture all of the variation within the samples. In particular, accessory gene content has been shown to both vary independently of core variation (32) , associated with clinically relevant phenotypes (12,33) , and be useful for predicting the evolution of the population (34,35) .…”

Section: Efficiently Modelling the Entire Pan-genomementioning

confidence: 99%

Improved inference and prediction of bacterial genotype-phenotype associations using pangenome-spanning regressions

Lees

Mai

Wheeler

et al. 2019

Preprint

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Discovery of influential genetic variants and prediction of phenotypes such as antibiotic resistance are becoming routine tasks in bacterial genomics. Genome-wide association study (GWAS) methods can be applied to study bacterial populations, with a particular emphasis on alignment-free approaches, which are necessitated by the more plastic nature of bacterial genomes. Here we advance bacterial GWAS by introducing a computationally scalable joint modeling framework, where genetic variants covering the entire pangenome are compactly represented by unitigs, and the model fitting is achieved using elastic net penalization. In contrast to current leading GWAS approaches, which test each genotype-phenotype association separately for each variant, our joint modelling approach is shown to lead to increased statistical power while maintaining control of the false positive rate. Our inference procedure also delivers an estimate of the narrow-sense heritability, which is gaining considerable interest in studies of bacteria. Using an extensive set of state-of-the-art bacterial population genomic datasets we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. We expect that these advances will pave the way for the next generation of high-powered association and prediction studies for an increasing number of bacterial species.

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Frequency-dependent selection in vaccine-associated pneumococcal population dynamics

Cited by 132 publications

References 82 publications

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Producing Polished Prokaryotic Pangenomes with the Panaroo Pipeline

Improved inference and prediction of bacterial genotype-phenotype associations using pangenome-spanning regressions

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