Interview: Long-read sequencing technologies reveal mutations lurking in the “camouflaged” genome

Date: Tuesday 8th October

Time: 4pm BST/11am EDT

Speaker: Mark Ebbert, Mayo Clinic

Dr. Mark T.W. Ebbert is Assistant Professor of Neuroscience at the Mayo Clinic, USA with a background in computational biology, bioinformatics and genomic studies. His research focuses on characterising the structural mutations associated with Alzheimer’s disease, amyotrophic lateral sclerosis (ALS), and frontotemporal dementia. In this interview he describes why he became interested in genomics, and the impact long-read sequencing is having on the study of uncharacterised genomic regions.

Mark will be presenting a webinar: ‘Long-read sequencing technologies reveal mutations lurking in the “camouflaged” genome’ with Technology Networks on Tuesday 8th October 4pm BST/11am EDT.

What are your current research interests?

I am fascinated by the human genome as a ‘blueprint’ for life as it contains instructions for development, growth, and life-long function—from the cellular level to large organs and how they function together. Unfortunately, ‘errors’, or DNA mutations, in an individual’s genome can either increase the individual’s risk for disease or will directly cause a disease. Most research over the past decade has focused on small mutations, but many diseases are affected by large structural DNA mutations (≥50 contiguous nucleotides) that standard short-read sequencing technologies are not well suited to identify. I want to help identify functional mutations that drive diseases, such as Alzheimer’s, and am particularly focused on identifying structural mutations using long-read sequencing technologies.

Similarly, most RNA sequencing studies treat all RNA isoforms for a given gene as one, which is an oversimplification of the underlying biology. For example, the top genes involved in Alzheimer’s disease average approximately 10 unique RNA isoforms. A next major milestone in understanding human health and disease will be to understand the purpose for individual isoforms and their role in health and disease — this is now possible with long-read sequencing technologies that are capable of traversing an entire RNA transcript rather than attempting to assemble isoforms from short-read data.

What first ignited your interest in genomics?

I love learning about how life works and what causes disease. I have always wanted to help alleviate pain and challenges that arise from disease, and genomics is foundational to accomplishing that goal.

Can you tell us more about how long-read sequencing is changing your field? How has it benefited your work?

It is difficult to estimate how much high-throughput short-read sequencing has benefited disease research, but we have reached the natural limitations of that technology. We are just beginning to understand how important genome structure is — particularly the importance of genome structure differences across populations and down to the individual, but short-read sequencing cannot resolve an individual’s genome structure.

What impact could a deeper understanding of understudied genomic regions have?

Our research highlighted over 6000 gene bodies that remain at least partially ‘dark’ or ‘camouflaged’ using standard short-read sequencing approaches, where approximately 4000 of those are protein-coding genes. Many of these genes are already known to be involved in human diseases, and most researchers are not aware that mutations are being overlooked. Examples include SMN1 and SMN2, which are over 90% camouflaged, and CR1—a top Alzheimer’s disease gene—is 26% camouflaged. Using long-read sequencing, it is possible to resolve both large and small mutations in these regions that will be otherwise overlooked.

What have been the main challenges in your work, and how have you approached them?

Unfortunately, resources are finite, and sequencing can be expensive. But prices continue to drop rapidly, making it possible to do large-scale genomics studies in disease cohorts. This is an exciting time to be involved in genomics research.

What’s next for your research?

Ultimately, I want to help develop pre-symptomatic disease diagnostics and meaningful therapeutics for neurodegenerative diseases like Alzheimer’s disease and amyotrophic lateral sclerosis (ALS). Long-read sequencing technologies will be critical in this effort.