Insight gained into the effect that synonymous mutation have on protein development

A team of experts have uncovered a unique way of verifying a gene’s level of expression. This novel methodology is believed to aid in differentiating between the effective and ineffective genes. This research was conducted by the biologists from the University of Pennsylvania.

These biologists have evaluated the process of how the level of proteins may be controlled by the mute mutations that take place within the protein-coding region. Such mutations may not have the ability to influence the amino-acid sequence of the protein; however they may have an effect on the total number of generated proteins.

The underlying methodology of this process was unveiled by these biologists. They have stated that the silent or synonymous mutations have an effect on the folding on the mRNA, which would in turn influence the level of proteins. Other than this, these biologists were also said to have discovered a set of mutations which didn’t seem to have an effect on the level of the proteins, but they decelerated the bacterial growth.

Joshua B. Plotkin, the Martin Meyerson Assistant Professor, Department of Biology, School of Arts and Sciences, University of Pennsylvania, says that, “At first we were stumped. How were the silent mutations influencing protein levels? Eventually, we looked at mRNA structure and discovered that this was the underlying mechanism.”

The function of synonymous mutations was earlier supposedly believed to be evolutionarily neutral, however these findings have suggested otherwise. The observed results could even be of great help in bettering the design of therapeutic genes.

It was mentioned that the genome of a human body consists of more than 20,000 genes, which have the ability to encode the proteins that are present in the body. The investigators have stated that certain proteins are required in large amounts, whereas for others only a little amount is required. The main criterion of these biologists was to determine the process of how does the cell “know” how much of each protein to produce. This criterion was better understood by engineering a synthetic library of 154 genes.

Their findings have been published in the Science journal.