On the importance of skewed offspring distributions and background selection in viral population genetics

Viruses are excellent biological models for understanding how populations evolve because they have characteristics (like high mutation rates and large population sizes) that make it easier to observe evolution in real-time. However, as argued in a new review paper in the journal Heredity, the unusual biology of viruses means that some common, simplifying assumptions of population genetics are not met by viral populations.

In particular, viruses tend to have highly skewed offspring distributions, with some virions producing either many more or many fewer offspring than assumed, and viral populations often experience drastic changes in size (i.e. bottlenecks) as a result of transmission or infection. These features of virus biology mean that the Kingman coalescent and Wright-Fisher model (part a in the Figure below) that are traditionally used in population genetics can lead to an erroneous inference of how the virus populations are evolving. The authors argue that the multiple merger coalescent class of models (part b of the Figure) can account for these limitations of traditional models by allowing more than two lineages to coalesce at a time.

New computational approaches, such as the use of multiple merger coalescent models or forward simulations, will elucidate how the unusual biology of viruses influences their genomic diversity and evolution.

multiple_merger_coalescent

Figure: Each row of dots shows the alleles in a single generation, with the lines connecting dots showing reproduction events. For each type of coalescent (a and b), the left panel shows the evolutionary process of the whole population, whereas the right panel shows a possible sampling and its genealogy. Unlike the Kingman coalescent (a), the multiple merger coalescent (b) allows parents to give rise to more than two offspring in the next generation. (Figure taken from figure 1 of the paper.)

–This summary was written by Telmo Cunha & Hermina Ghenu

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