Genetic analysis with RNA sequencing can increase diagnostic yield, the study shows

Reviewed by Emily Henderson, B.Sc.October 28, 2020

In the world of rare genetic diseases, exome and genome sequencing are two powerful tools used to make a diagnosis. A recent addition to the toolkit, RNA sequencing, has been shown to help researchers narrow down the candidate disease variants first identified on exome and genome sequencing.

A new study from Baylor College of Medicine finds that initiating genetic analysis with RNA sequencing can further increase diagnostic yield. The results are published in Journal of Clinical Investigation.

Baylor has been a leader in developing clinical applications of exome and genome sequencing, a technique that is now used in clinics around the world. Researchers from the National Institutes of Health (NIH) Undiagnosed Diseases Network (UDN) have successfully used exome and genome sequencing to increase the diagnostic rate of rare genetic diseases to about 35%.

“It’s impressive because these cases have already had such extensive work,” said Dr. Brendan Lee, corresponding author of the study and professor and president of molecular and human genetics at Baylor. “The 35% diagnostic rate is great, but unfortunately it means there is still 65% that goes undiagnosed.”

Exome and genome sequencing has limitations. Over the years, scientists have identified approximately 4,000 disease-causing genes and 7,000 distinct associated clinical diseases, but relatively little is known about the approximately 16,000 other genes in the genome. Furthermore, only about 1 or 2% of the genome is coding, which means it is translated into RNA and proteins. Researchers are limited in their ability to interpret genetic changes in non-coding regions of the genome.

When a patient’s exome and genome are sequenced, we interpret the results and create a list of gene mutations that could cause disease. Often, we can’t assign a definitive effect to many DNA mutations because there isn’t enough information. “

Brendan Lee, study author and corresponding professor, Robert and Janice McNair, chairs of molecular and human genetics, Baylor College of Medicine

To aid in the interpretation of exome and genome sequencing, UDN has increasingly turned to RNA sequencing. While exome and genome sequencing identifies genetic changes in DNA, RNA sequencing can reveal the effects of those changes, for example if a gene has a lower expression than expected. RNA sequencing can also tell us about the effects of non-coding changes, something that is very important during the transition from exome to genome sequencing.

Trying a new approach

RNA sequencing has been used as a secondary tool to help prioritize disease gene candidates identified with exome and genome sequencing, and has been shown to increase diagnostic yield to varying degrees.

Baylor’s team wanted to try a different approach with UDN cases. Using a new pipeline developed with collaborators in Germany, they started with RNA sequencing to first identify unique differences in gene expression and splicing. The researchers could then trace the problem back to a corresponding genetic modification in the exome and genome sequencing data.

“This strategy really changes the way we normally approach a case, looking at the end result in RNA and working backwards to find the cause in the exome or genome. It allows biology to tell us where to look to make a diagnosis,” he said. said Dr. David Murdock, lead author of the study and assistant professor of molecular and human genetics at Baylor.

“We found that this first RNA sequencing approach was extremely powerful,” Lee said. “He was able to point very quickly to the gene we should be looking at. Plus, he did so in cases where we wouldn’t be able to identify the disease candidate gene using only exome and genome sequencing. If we had used it. the old way and generated a list of priority candidates, these gene mutations wouldn’t even be on the priority list. “

Greater diagnostic yield

The team found that exome and genome sequencing sometimes lacked small deletions in the genes. However, the RNA sequencing data showed that these deletions could greatly affect gene expression. RNA sequencing also detected changes in expression and splicing caused by variants in non-coding regions that would not have been tagged in normal exome and genome sequencing.

“We see a lot of changes in the non-coding region and there’s no way of knowing if they’re important,” Lee said. “But the RNA sequencing will show an 80% decrease in expression relative to that gene, and then we can assign causality to that non-coding variant.”

The Baylor study found that starting with RNA sequencing could increase the diagnostic yield by 17% compared to the traditional exome and genome sequencing approach, bringing the overall diagnosis rate to about 50%. As part of the study, the researchers analyzed both skin cells and blood cells and found that skin cells were more informative in diagnosis due to their homogeneous nature and better gene expression.

“I see RNA sequencing with this approach as eventually becoming standard practice, especially as we move more from exome to genome sequencing. It allows us to diagnose so many more patients and gives families the answer they were looking for.” Murdock said.

“A diagnosis is not black and white. It involves varying amounts of certainty,” Lee said. “The availability of this tool will change the level of certainty, improving diagnostic yield and increasing confidence in that diagnosis.”