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Chapter 10 : Multilocus Models of Bacterial Population Genetics
Authors:
William P. Hanage1,
Christophe Fraser2,
Thomas R. Connor3,
Brian G. Spratt4
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Affiliations:
1: Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Hospital, London, United Kingdom;
2: Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Hospital, London, United Kingdom;
3: Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Hospital, London, United Kingdom;
4: Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Hospital, London, United Kingdom
Content Type: Monograph
Publication Year:
2008
Category: Fungi and Fungal Pathogenesis; Bacterial Pathogenesis
Book DOI:
10.1128/9781555815639
Chapter DOI:
10.1128/9781555815639.ch10
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Abstract:
In the multilocus Fisher-Wright model allele frequencies and the combinations of alleles (STs) fluctuate solely through genetic drift. Using multiple loci prevents recombination from obscuring the relationships between strains, because a change at one locus will not alter the information about relationships between strains present at the others. Computer simulation of bacterial populations is complementary to an analytic approach. Furthermore, simulation of the evolution of bacterial populations provides an alternative means of testing hypotheses: the effects of various evolutionary scenarios may be explored by introducing them into a simulation based on the neutral model. An example of this type of approach is discussed in this chapter, where the conditions under which an evolving bacterial population splits into separate clusters, mimicking speciation, are explored. In sum, while coalescent analyses may be the most appropriate for individual loci, and certainly have a much wider body of theoretical work to draw on than the methods discussed in the chapter, the authors are excited by the potential of methods such as multilocus sequence typing (MLST) that consider the genetics of populations of strains rather than of individual loci, to demonstrate forces other than neutrality influencing the structure of populations. The chapter also talks about the modeling of alleles and their association using recently developed techniques designed to simulate and analyze data sets obtained from MLST studies.
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
Figures
Multilocus Models of Bacterial Population Genetics
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Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10fig01
Figure 1.
The simple model of diversification assumed by eBURST. (a) At the earliest time point, a strain or clone (ST1) begins to increase in frequency in the population, either through selection or drift. Different lineages are shown, but we focus for the purposes of illustration solely on the lineage starting with ST1. The size of the circle is proportional to the number of isolates with that genotype. Eventually, ST1 generates a single locus variant (SLV), by mutation or recombination, shown as ST2. Over time, as ST1 becomes increasingly common, a cloud of such SLVs surround it, and some of these may go on to produce their own SLVs (as ST2 has in the last panel). Such groups of related strains are termed clonal complexes. (b) Shows an eBURST diagram constructed from allelic profiles in the S. pneumoniae database. The clonal complex shown is predicted to have descended from ST81, a major internationally distributed antibiotic-resistant clone. SLV labels have been removed for purposes of clarity.
10.1128/9781555815639/f0095-01_thmb.gif
10.1128/9781555815639/f0095-01.gif
Figure 1.
The simple model of diversification assumed by eBURST. (a) At the earliest time point, a strain or clone (ST1) begins to increase in frequency in the population, either through selection or drift. Different lineages are shown, but we focus for the purposes of illustration solely on the lineage starting with ST1. The size of the circle is proportional to the number of isolates with that genotype. Eventually, ST1 generates a single locus variant (SLV), by mutation or recombination, shown as ST2. Over time, as ST1 becomes increasingly common, a cloud of such SLVs surround it, and some of these may go on to produce their own SLVs (as ST2 has in the last panel). Such groups of related strains are termed clonal complexes. (b) Shows an eBURST diagram constructed from allelic profiles in the S. pneumoniae database. The clonal complex shown is predicted to have descended from ST81, a major internationally distributed antibiotic-resistant clone. SLV labels have been removed for purposes of clarity.
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10eq01
Untitled
10.1128/9781555815639/e0096-01_thmb.gif
10.1128/9781555815639/e0096-01.gif
Untitled
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10eq02
Untitled
10.1128/9781555815639/e0096-02_thmb.gif
10.1128/9781555815639/e0096-02.gif
Untitled
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10eq03
Untitled
10.1128/9781555815639/e0096-03_thmb.gif
10.1128/9781555815639/e0096-03.gif
Untitled
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10fig02
Figure 2.
Schematic illustration of an infinite-alleles Fisher-Wright model for seven loci as used in the text. Three consecutive time steps are shown. Mutation events always produce a new allele. Contrastingly, recombination events shuffle alleles among the population and may result in no change at the locus if the donor and recipient alleles are identical. t + n shows the population once run to equilibrium. For simplicity, only a population of N = 5 is shown.
10.1128/9781555815639/f0097-01_thmb.gif
10.1128/9781555815639/f0097-01.gif
Figure 2.
Schematic illustration of an infinite-alleles Fisher-Wright model for seven loci as used in the text. Three consecutive time steps are shown. Mutation events always produce a new allele. Contrastingly, recombination events shuffle alleles among the population and may result in no change at the locus if the donor and recipient alleles are identical. t + n shows the population once run to equilibrium. For simplicity, only a population of N = 5 is shown.
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10fig03
Figure 3.
Allelic mismatch distributions for simulated population. (a) A near clonal population (low rate of recombination) and (b) A population with high rates of recombination.
10.1128/9781555815639/f0097-02_thmb.gif
10.1128/9781555815639/f0097-02.gif
Figure 3.
Allelic mismatch distributions for simulated population. (a) A near clonal population (low rate of recombination) and (b) A population with high rates of recombination.
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
/content/10.1128/9781555815639.ch10.ch10fig04
Figure 4.
Populations of bacteria simulated using HRST. (a) In the absence of recombination (strict clonality), the initially uniform population splits into distinct clusters. (b) With a high recombination rate ρ/θ = 10, the population forms subclusters, but these are invariably drawn back into the main population because of the cohesive force of recombination. In this example recombination between all strains occurs at the same rate. The allelic distance (over 140 loci) is reduced to two dimensions using multidimensional scaling implemented in R. The relatedness of strains (points) is shown by their distance apart in the diagram.
10.1128/9781555815639/f0100-01_thmb.gif
10.1128/9781555815639/f0100-01.gif
Figure 4.
Populations of bacteria simulated using HRST. (a) In the absence of recombination (strict clonality), the initially uniform population splits into distinct clusters. (b) With a high recombination rate ρ/θ = 10, the population forms subclusters, but these are invariably drawn back into the main population because of the cohesive force of recombination. In this example recombination between all strains occurs at the same rate. The allelic distance (over 140 loci) is reduced to two dimensions using multidimensional scaling implemented in R. The relatedness of strains (points) is shown by their distance apart in the diagram.
Citation:
Hanage W, Fraser C, Connor T, Spratt B.
2008.
Multilocus Models of Bacterial Population Genetics,
p 93-104.
In
Baquero F, Nombela C, Cassell G, Gutiérrez-Fuentes J (ed),
Evolutionary Biology of Bacterial and Fungal Pathogens.
ASM Press, Washington, DC.
doi: 10.1128/9781555815639.ch10
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