Evolution May Yield Most Abundant Traits, Not Best

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Main Category: Genetics
Also Included In: Biology / Biochemistry
Article Date: 18 Jul 2008 - 0:00 PDT

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Evolution may provide us with the most abundant phenotypes (observable genetic characteristics) rather than the fittest, according to a new theory published on July 18 in the open-access journal PLoS Computational Biology. That is, natural selection may be optimal for choosing the most fit organism of the moment, but evolutionary biologists question if the process leads to the optimal organisms in the long run. Researchers from The University of Texas at Austin, led by Drs. Matthew Cowperthwaite and Lauren Ancel Meyers, propose a new theory: life may not always be optimal.

Natural selection is driven by genetic mutations, and we usually can predict and understand the short-term fate of a mutation. If a mutation makes the organism more fit, it tends to last through the years; if the mutation is harmful, it usually dies off with its host organism. Evolutionary biologists, however, do not have such a complete understanding of the long-term consequences of mutations. Is it possible that what is good now may be not-so-good later?

To study this question, researchers modeled RNA molecules that evolved by mutation and natural selection. RNA is similar to DNA and is necessary in life processes. Additionally, RNA functions as genetic material for viruses such as HIV and influenza.

The computer analysis revealed that long sequences of interacting mutations are often required for evolution to create the optimal organism. Each mutation in the sequence, however, must arise by chance and survive natural selection in the short run. Cowperthwaite explains that, "Some traits are easy to evolve - formed by many different combinations of mutations. Others are hard to evolve - made from an unlikely genetic recipe. Evolution gives us the easy ones, even when they are not the best."

The analysis leads the group to conclude that it may be the easy traits - the abundant ones - that dominate life rather than the best ones.

The Ascent of the Abundant: How Mutational Networks Constrain Evolution
Cowperthwaite MC, Economo EP, Harcombe WR, Miller EL, Ancel Meyers L
PLoS Computational Biology (2008). 4(7):e1000110.
doi:10.1371/journal.pcbi.1000110
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Written by: Peter M Crosta
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