Genetic Sequencing Gets Boost From A New Proofreading Enzyme

Error prone 3-billion-year-old process fixed

HIV virus

The human immunodeficiency virus (HIV)

HIV virusCDC

When a virus invades a cell, it uses that cell's machinery to replicate itself by throwing the typical process for replicating genetic material into reverse. This strategy is called reverse transcription, and it's messy, leading to numerous errors in the copied sequences. According to experts, this sloppiness might be a fluke, but it has likely turned into an evolutionary strategy to promote viral diversity and mutation, helping viruses stay ahead of the human immune response.

Since the reverse transcription process was discovered in the 70s, it has been a boon for molecular biology, allowing scientists to clone, sequence, and gain a deeper understanding of RNA. But the inherent glitchiness of the process has remained problematic.

Now a team of researchers from the University of Texas at Austin has taken the unreliability out of reverse transcription. They started with reverse transcriptase (RT), the enzyme that drives the process, and targeted a 3 billion-year-old genetic error that inhibited them from "proofreading" their gene-copying work. The new enzyme they created, called RTX, can correct its mistakes, creating far more accurate genomic sequences than ever before.

According to their paper, published in Science, RTX can produce transcriptions that are three to 10 times more accurate than what was possible before.

From the press release:

“As we move towards an age of personalized medicine where everyone’s transcripts will be read out almost as easily as taking a pulse, the accuracy of the sequence information will become increasingly important,” says Andy Ellington, a professor of molecular biosciences. “The significance of this is that we can now also copy large amounts of RNA information found in modern genomes, in the form of the RNA transcripts that encode almost every aspect of our physiology. This means that diagnoses made based on genomic information are far more likely to be accurate.”