University Of Rochester Breaks Gene Code; 17 Inefficient Codons Discovered


University of Rochester breaks the genetic code to explain why some genes are not translated into proteins. Researchers led by Beth Grayhack, Ph.D of the Center of RNA Biology  discovered 17 pairs of codons that are inefficiently working within the genetic code. Grayhack said that switching orders of the codons may lead to different meaning and functions, but of same principle behind.

The genetic code transmits directions to every protein. It consists of 64 triplets of nucleotide sequences and each of the triplets makes a codon. The identity of proteins from genetic codes has been known for over 50 years and this genetic code affects the function of proteins in ways that scientists cannot comprehend.

For scientists to figure out how genes can affect the progress of diseases, they need to understand how to read the codes, as well as how changes in the codes have consequential effects towards genes, BBC reported.

In genetic code study, the research team focused on crucial analysis of a specific region in a single yeast gene to identify specific combinations of codons that contribute to the reduction of gene expression, the University official website reported.

Grayhack and Christina Brule, a graduate student in Grayhack Lab, teamed up with Stan Fields, Ph.D. of the University of Washington, as well as Caitlin Gamble, a co-author in Seattle.  The team successfully identified 17 codon pairs that work together to hinder gene expression and slow the ribosome.

Grayhack said that their findings can be to roadways. She said that good codons, which can effectively make proteins are the superhighways for translating genes. Currently, single codons are being clustered into suboptimal category similar to a dirt road. The suboptimal category seen in the group's recent data is analogous to adding a pointed curve in the dirt road.

The gene code discovery opens doors for how the codon pairs work and contribute to the ineffective protein translation.  It was the National Science Foundation and National Institutes of Health that funded these research.

© 2024 University Herald, All rights reserved. Do not reproduce without permission.
Join the Discussion
Real Time Analytics