Long-term evolution of Streptococcus mitis and Streptococcus pneumoniae leads to higher genetic diversity within rather than between human populations.

Evaluation of the apportionment of genetic diversity of human bacterial commensals within and between human populations is an important step in the characterization of their evolutionary potential. Recent studies showed a correlation between the genomic diversity of human commensal strains and that of their host, but the strength of this correlation and of the geographic structure among human populations is a matter of debate. Here, we studied the genomic diversity and evolution of the phylogenetically related oro-nasopharyngeal healthy-carriage Streptococcus mitis and Streptococcus pneumoniae, whose lifestyles range from stricter commensalism to high pathogenic potential. A total of 119 S. mitis genomes showed higher within- and among-host variation than 810 S. pneumoniae genomes in European, East Asian and African populations. Summary statistics of the site-frequency spectrum for synonymous and non-synonymous variation and ABC modelling showed this difference to be due to higher ancestral bacterial population effective size (Ne) in S. mitis, whose genomic variation has been maintained close to mutation-drift equilibrium across (at least many) generations, whereas S. pneumoniae has been expanding from a smaller ancestral bacterial population. Strikingly, both species show limited differentiation among human populations. As genetic differentiation is inversely proportional to the product of effective population size and migration rate (Nem), we argue that large Ne have led to similar differentiation patterns, even if m is very low for S. mitis. We conclude that more diversity within than among human populations and limited population differentiation must be common features of the human microbiome due to large Ne.

Interpreting the pervasive observation of U-shaped Site Frequency Spectra.

The standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis.

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders). Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.

Cannings models, population size changes and multiple-merger coalescents.

Multiple-merger coalescents, e.g. [Formula: see text]-n-coalescents, have been proposed as models of the genealogy of n sampled individuals for a range of populations whose genealogical structures are not captured well by Kingman's n-coalescent. [Formula: see text]-n-coalescents can be seen as the limit process of the discrete genealogies of Cannings models with fixed population size, when time is rescaled and population size [Formula: see text]. As established for Kingman's n-coalescent, moderate population size fluctuations in the discrete population model should be reflected by a time-change of the limit coalescent. For [Formula: see text]-n-coalescents, this has been explicitly shown for only a limited subclass of [Formula: see text]-n-coalescents and exponentially growing populations. This article gives a more general construction of time-changed [Formula: see text]-n-coalescents as limits of specific Cannings models with rather arbitrary time changes.

Population Genomic Evidence for a Repeated Introduction and Rapid Expansion of the Fungal Maize Pathogen Setosphaeria turcica in Europe.

Modern agricultural practices, climate change, and globalization foster the rapid spread of plant pathogens, such as the maize fungal pathogen Setosphaeria turcica, which causes Northern corn leaf blight and expanded into Central Europe during the twentieth century. To investigate the rapid expansion of S. turcica, we sequenced 121 isolates from Europe and Kenya. Population genomic inference revealed a single genetically diverse cluster in Kenya and three clonal lineages with low diversity, as well as one cluster of multiple clonal sublineages in Europe. Phylogenetic dating suggests that all European lineages originated through sexual reproduction outside Europe and were subsequently introgressed multiple times. Unlike isolates from Kenya, European isolates did not show sexual recombination, despite the presence of both MAT1-1 and MAT1-2 mating types. For the clonal lineages, coalescent model selection supported a selectively neutral model with strong exponential population growth, rather than models with pervasive positive selection caused by host defense resistance or environmental adaptation. Within clonal lineages, phenotypic variation in virulence to different monogenic resistances, which defines the pathogen races, suggests that these races may originate from repeated mutations in virulence genes. Association testing based on k-mers did not identify genomic regions linked to pathogen races, but it did uncover strongly differentiated genomic regions between clonal lineages, which harbor genes with putative roles in pathogenicity. In conclusion, the expansion and population growth of S. turcica in Europe are mainly driven by an expansion of the maize cultivation area and not by rapid adaptation.

Exome sequencing of geographically diverse barley landraces and wild relatives gives insights into environmental adaptation.

After domestication, during a process of widespread range extension, barley adapted to a broad spectrum of agricultural environments. To explore how the barley genome responded to the environmental challenges it encountered, we sequenced the exomes of a collection of 267 georeferenced landraces and wild accessions. A combination of genome-wide analyses showed that patterns of variation have been strongly shaped by geography and that variant-by-environment associations for individual genes are prominent in our data set. We observed significant correlations of days to heading (flowering) and height with seasonal temperature and dryness variables in common garden experiments, suggesting that these traits were major drivers of environmental adaptation in the sampled germplasm. A detailed analysis of known flowering-associated genes showed that many contain extensive sequence variation and that patterns of single- and multiple-gene haplotypes exhibit strong geographical structuring. This variation appears to have substantially contributed to range-wide ecogeographical adaptation, but many factors key to regional success remain unidentified.

Can the site-frequency spectrum distinguish exponential population growth from multiple-merger coalescents?

The ability of the site-frequency spectrum (SFS) to reflect the particularities of gene genealogies exhibiting multiple mergers of ancestral lines as opposed to those obtained in the presence of population growth is our focus. An excess of singletons is a well-known characteristic of both population growth and multiple mergers. Other aspects of the SFS, in particular, the weight of the right tail, are, however, affected in specific ways by the two model classes. Using an approximate likelihood method and minimum-distance statistics, our estimates of statistical power indicate that exponential and algebraic growth can indeed be distinguished from multiple-merger coalescents, even for moderate sample sizes, if the number of segregating sites is high enough. A normalized version of the SFS (nSFS) is also used as a summary statistic in an approximate Bayesian computation (ABC) approach. The results give further positive evidence as to the general eligibility of the SFS to distinguish between the different histories.