Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis

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Skwark , M J , Croucher , N J , Puranen , S , Chewapreecha , C , Pesonen , M , Xu , Y Y , Turner , P , Harris , S R , Beres , S B , Musser , J M , Parkhill , J , Bentley , S D , Aurell , E & Corander , J 2017 , ' Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis ' , PLoS Genetics , vol. 13 , no. 2 , 1006508 . https://doi.org/10.1371/journal.pgen.1006508

Title: Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
Author: Skwark, Marcin J.; Croucher, Nicholas J.; Puranen, Santeri; Chewapreecha, Claire; Pesonen, Maiju; Xu, Ying Ying; Turner, Paul; Harris, Simon R.; Beres, Stephen B.; Musser, James M.; Parkhill, Julian; Bentley, Stephen D.; Aurell, Erik; Corander, Jukka
Contributor: University of Helsinki, Department of Mathematics and Statistics
Date: 2017-02
Language: eng
Number of pages: 24
Belongs to series: PLoS Genetics
ISSN: 1553-7404
URI: http://hdl.handle.net/10138/178231
Abstract: Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein- protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.
Subject: DIRECT-COUPLING ANALYSIS
STREPTOCOCCUS-PNEUMONIAE
PENICILLIN RESISTANCE
STATISTICAL-METHODS
CONTACT PREDICTION
RESIDUE CONTACTS
EVOLUTION
PROTEINS
ASSOCIATION
COEVOLUTION
1183 Plant biology, microbiology, virology
1184 Genetics, developmental biology, physiology
112 Statistics and probability
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