New view of evolving genes, proteins to aid bioinformatics

Rockville, MD -- Today's evolutionary theory is not enough to tell us how even simple mutation biases may skew the evolutionary process, according to a report by scientists from the University of Maryland Biotechnology Institute (UMBI).

In the March edition of the journal Evolution and Development, research associate Lev Yampolsky and research biologist Arlin Stoltzfus of UMBI's Center for Advanced Research in Biotechnology (CARB) make a case that simple biases in mutation will change the evolutionary process. They use mathematics and computer simulations to explore the role of mutation biases using the classic "Bateson-Dobzhansky-Muller" model.

"Recognizing this kind of bias as an evolutionary cause will increase our ability to explain and predict evolution, and will aid researchers as they seek to understand such things as the amino acid composition of proteins, the appearance of new strains of viruses strains, and the distribution of introns in genes, all of which exhibit components of change that suggest a role of biases in the process of mutation," explains Stoltzfus. (Introns are DNA sequences in genes that don't encode proteins, thus having no defined purpose.)

The CARB study also helps to make more sense of the results of the rapidly growing science of bioinformatics, the data analysis of genomes and proteins. Since the 1970's when the technique of gene sequencing was developed, evidence has been accumulating that mutation biases strongly influence the evolution of genes and proteins, say the authors. The influence has been interpreted as a sign of "neutral evolution", a kind of random noise in the evolutionary process.

But now Yampolsky and Stoltzfus argue that in a more general theory, mutation-biased evolution does not have to be neutral.

In historic perspective, the new paper shows that it is still possible to stake out a new position on an old issue in evolutionary theory. Charles Darwin and other 19th century scientists realiz

Contact: Steve Berberich
University of Maryland Biotechnology Institute

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