Near-optimal Genetic Code Model Created By Researchers
August 29, 2013

Model Of ‘Near Optimal’ Genetic Code Created By NYU Researchers

redOrbit Staff & Wire Reports - Your Universe Online

By creating a model of genetic code evolution, researchers have discovered new information about how RNA signaling could have developed into the “near-optimal” modern genetic code.

Lead author Justin Jee, a doctoral student at NYU School of Medicine, and colleagues set out to account for the composition of the genetic code, which makes it possible for proteins to be constructed from amino acids with high specificity based on information stored in a RNA or DNA genome.

“Our model shows that today's genetic code probably resulted from a combination of selective forces and random chance,” Jee said. His team’s research, which they say could help explain the complexities of the origins of life, appears in the latest edition of the Journal of the Royal Society Interface.

The translation process between nucleic acids and amino acids is largely universal – a phenomenon the researchers refer to as mysterious and remarkable. The same code is shared in all types of organisms, ranging from bacteria to humans, and at the same time it is nearly perfect in terms of how well it is able to select the correct type of amino acids for specific particular nucleic acid sequences.

Ever since the code was first discovered some five decades ago, experts have wondered how a near-optimal code also became so universal in nature. In order to try and discover the answer, Jee and his associates crafted a model of genetic code evolution in which multiple "translating" RNAs and "genomic" RNAs competed for survival. The translating RNAs were able to link amino acids together using data stored in the genomic RNA, they explained.

“In running computer simulations of RNA interactions, they could see two phenomena. First, it was necessary for the translating and genomic RNAs to organize into cells, which aided the coordination of a code between the translating and genomic RNAs. Second, selective forces led a single set of translating RNAs to dominate the population,” the university said. “In other words, the emergence of a single, universal, near-optimal code was a natural outcome of the model. Even more remarkably, the results occurred under realistic conditions – specifically, they held under parameters such as protein lengths and rates of mutation that likely existed in a natural RNA world.”

“The most elegant ideas in this paper are rather obvious consequences of a well-studied model based on sender-receiver games,” added senior author Bud Mishra of the NYU School of Medicine’s Sackler Institute of Graduate Biomedical Sciences. “Yet the results are still very surprising because they suggest, for example, that proteins, the most prized molecules of biology, might have had their origin as undesirable toxic trash. Other studies based on phylogenomic analysis seem to be coming to similar conclusions independently.”

In addition to Jee and Mishra, study co-authors included Andrew Sundstrom of the Courant Institute and Steven Massey of the University of Puerto Rico's Department of Biology. The research was funded by grants from the National Science Foundation (NSF) and a National Defense Science and Engineering Graduate Fellowship from the US Department of Defense.