EMBARGO: February 19th, 2015, 11am Pacific/2pm Eastern/7pm UK
The Geometry of a Population Affects the Speed of Genetic Change
New research shows that the way a population is arranged can alter the rate of genetic change.
Investigators at Emmanuel College in Boston and at Harvard University used mathematical
modeling to challenge conventional wisdom about how our genomes change over time.
The findings, publishing this week in PLOS Computational Biology, concern neutral or “silent”
mutations—random genetic changes that do not affect the organism but can be passed on to
offspring. Previous research suggested that these changes accrue at a predictable rate over
time, forming a kind of “molecular clock”. This study shows that the spatial layout of a
population’s habitat can change the rate at which this clock ticks.
Imagine, for example, a population of birds spread over a cluster of islands. If one island is
particularly fruitful—rapidly producing new offspring that spread to other islands—new
mutations will accumulate more rapidly than if all birds were together on one island. As the
birds evolve over time, this habitat structure could leave a signature in their genome.
In addition to biological evolution, the researchers also looked at whether the shape of social
networks could affect the success of new ideas. “We have this idea that our networked world
makes ideas spread faster and faster,” said Dr. Benjamin Allen, who led the research. “But
when we looked at real-world Twitter networks, we found that most of them actually suppress
the chances of an average idea to gain a foothold. This happens because, with so much
information flying around, ordinary ideas become lost in the shuffle, and only the most viral
content survives.”
Image Caption: A real-world Twitter network among 80 users. This network, like the vast
majority of those studied, hinders the chances of ordinary (non-viral) ideas to become
established.
Image Credit: Benjamin Allen, based on data from the Stanford Large Network Dataset
Collection
Image Link: http://www.plos.org/wp-content/uploads/2015/02/19-Feb-Allen.png
Press Release
PLOS Computational Biology 2015
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Press Release
PLOS Computational Biology 2015