Comparative analyses of selection operating on non-translated intergenic regions of diverse bacterial species

Harry A. Thorpe, Sion C. Bayliss, Laurence D. Hurst, Edward J. Feil

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41 Citations (SciVal)


Non-translated intergenic regions (IGRs) comprise 10-15% of bacterial genomes, and containmany regulatory elements with key functions. Despite this, there are few systematic studies on thestrength and direction of selection operating on IGRs in bacteria using whole genome sequencedatasets. Here we exploit representative whole genome datasets from six diverse bacterialspecies;​ Staphylococcus aureus, ​ Streptococcus pneumoniae , ​ Mycobacteriumtuberculosis,Salmonellaenterica, ​ Klebsiella pneumoniae and ​ Escherichia coli . We comparepatterns of selection operating on IGRs using two independent methods; the proportion ofsingleton mutations, and the dI/dS ratio; where dI is the number of intergenic SNPs per intergenicsite. We find that the strength of purifying selection operating over all intergenic sites is consistentlyintermediate between that operating on synonymous and non-synonymous sites. Ribosomebinding sites and non-coding RNAs tend to be under stronger selective constraint than promotersand rho-independent terminators. Strikingly, a clear signal of purifying selection remains evenwhen all these major categories of regulatory elements are excluded, and this constraint is highestimmediately upstream of genes. Whilst a paucity of variation means that the data for ​ M.tuberculosis are more equivocal than for the other species, we find strong evidence for positiveselection within​ promoters of​ this species. This points to a key adaptive role for regulatory changesin this important pathogen. Our study underlines the feasibility and utility of gauging the selectiveforces operating on bacterial IGRs from whole genome sequence data, and suggests that ourcurrent understanding of the functionality of these sequences is far from complete.
Original languageEnglish
Article number195784
Pages (from-to)363-376
Issue number1
Early online date9 Mar 2017
Publication statusPublished - 5 May 2017


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