Evolution of diversity surprisingly predictable

Similar—or even identical—mutations can occur during diversification in completely separate populations of E. coli evolving over more than 1,000 generations, according to researchers at the University of British Columbia and the University of Montana.

The findings by UBC zoologist and mathematician Michael Doebeli and Matthew Herron, a postdoctoral researcher at the University of Montana, were published today in the open access journal PLOS Biology.

The researchers allowed three populations of E. coli, each consisting of generalist bacteria competing for two food sources (glucose and acetate), to evolve independently. After 1,200 generations all three populations had evolved into two coexisting types, each with a specialized physiology adapted to one of the foods.

Herron and Doebeli sequenced the genomes of populations of bacteria frozen at 16 different points during their evolution, and discovered a surprising amount of similarity between independently evolving populations.

"Understanding the intricacies of diversification is important for understanding why there are so many species on Earth," says Doebeli.

"Not only did similar genetic changes occur, but the temporal sequence in which the changes occur over evolutionary time was also similar between the different evolving populations. This 'parallelism' implies that diversification is a deterministic process driven by natural selection."

Herron and Doebeli argue that a particular form of selection—negative frequency dependence—plays an important role in driving diversification. When bacteria are either glucose specialists or acetate specialists, a higher density of one type will mean fewer resources for that type, so bacteria specializing on the alternative resource will be at an advantage.

Recent advances in sequencing technology allowed Doebeli and Herron to sequence large numbers of whole bacterial genomes. As technology advances, they believe similar experiments in larger organisms will be possible.


For more information, contact…

Chris Balma

balma@science.ubc.ca
  • Biodiversity
  • Math + Data Science
  • Mathematics
  • Zoology

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