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Review
. 2007 Jan 26;315(5811):476-80.
doi: 10.1126/science.1127573.

Recombination and the nature of bacterial speciation

Affiliations
Review

Recombination and the nature of bacterial speciation

Christophe Fraser et al. Science. .

Abstract

Genetic surveys reveal the diversity of bacteria and lead to the questioning of species concepts used to categorize bacteria. One difficulty in defining bacterial species arises from the high rates of recombination that results in the transfer of DNA between relatively distantly related bacteria. Barriers to this process, which could be used to define species naturally, are not apparent. Here, we review conceptual models of bacterial speciation and describe our computer simulations of speciation. Our findings suggest that the rate of recombination and its relation to genetic divergence have a strong influence on outcomes. We propose that a distinction be made between clonal divergence and sexual speciation. Hence, to make sense of bacterial diversity, we need data not only from genetic surveys but also from experimental determination of selection pressures and recombination rates and from theoretical models.

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Figures

Figure 1
Figure 1
A, Recombination rate for a range of related donors, as a function of the proportion of sequence which is different (sequence divergence), for a variety of bacterial recipients: ●, Bacillus subtilis, □, Bacillus mojavensis, ◆, Streptococcus pneumoniae and Δ, Escherichia coli. The best fit log-linear curve is shown, with intercept 0.8% and slope 19.8. Data are from (12-14). Slopes for individual named species range from 17.9 for S. pneumoniae to 25.7 for E. coli. B, genome of S. pneumoniae (from (35)) and location of the MLST genes. C, schematic representation of the simulated genomes, in a stochastic neutral model: MLST genes are highlighted.
Figure 2
Figure 2
Simulated genetic structure of a clonal population (A-C) and sexual population (D-F). All populations are evolving under neutral drift and are homogeneously mixing. Genetic maps (A,D,G), which are determined by principal co-ordinate analysis (36), represent the genetic distances between 1,000 randomly chosen isolates from the simulated population after 106 generations have elapsed. Co-ordinates are expressed in units of sequence divergence. An alternative way to represent clustering is the distribution of sequence divergence between pairs of isolates in the population (B, E, H). The thin lines show the distance between five random strains and all the other strains in the sample, while the thick red line shows the distribution of all the pairwise distances (thick red line). Where there is little clustering (E), all pairwise distances are similar and the distribution has a single peak, while where there is strong clustering (B, H), the distribution has multiple peaks corresponding to pairwise comparisons within and between clusters. (C, F, I) show this distribution of pairwise comparisons evolving over 106 generations. To normalise the distribution, pairs of isolates are compared for the number of alleles that are different, between 0 and 70, rather than for the proportion of base pairs, as in (B, E, H). The height of the distribution is represented by color shade, ranging from black (0.0) to red (>0.1), so that peaks in the (B, E, H) correspond to red shaded areas in (C, F, I). C and I show clusters moving apart, visible as red peaks moving up through time. When clusters split, a new peak appears at the bottom, while extinctions are apparent from peaks disappearing. F shows instead more stable population structure with a stable diffuse cluster being maintained throughout the simulation. Parameter values for θ and ρ, the population mutation and recombination rates, are θ=2, ρ=0.01 (A-C), ρ=20*10-18x, where x is the sequence divergence (D-F). We also explored under which conditions clustering could occur in the presence of high recombination rates (G-I). Clusters with high within cluster recombination can be generated, mimicking spontaneous speciation (G-I), but require that recombination rate declines as a function of sequence divergence at a very rapid rate uncharacteristic of most bacteria studied to date, such that ρ=20*10-300x.
Figure 3
Figure 3
Genetic maps of a population temporarily divided by a strong barrier. With parameters as in Fig 2 for the sexual population, a split is introduced after 300,000 generations (A). After 300,000 generations apart, the populations have drifted and are clearly distinct (B). At this point the populations are re-united; after 10,000 generations, little distinction remains (C), and after a further 10,000 generations no remnants of the separation are evident (D).
Figure 4
Figure 4
Genetic map of the Streptococcus genus, based on concatenated sequences of MLST genes (excluding ddl). Samples from four named species are highlighted as: red, S. pneumoniae, yellow, S. pseudopneumoniae, purple, S. mitis and brown, S. oralis. The three light blue dots represent strains for which the named species status could not be assessed.

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