Interview: Maize genome complexity traversed with Oxford Nanopore Technology


Frontline Genomics Webinar

Date: Thursday 8th November

Time: 10am PST/1pm EST/6pm GMT

Speaker: Todd P. Michael, PhD, Professor and Director of Informatics, JCVI

Todd Michael is Professor and Director of Informatics at the J. Craig Venter Institute (JCVI) in San Diego, and is currently directing the JCVI Sequencing Core. His research interests are wide ranging but focus on how sequencing technology and informatics can be utilised to understand how information is stored in genomes. In this interview he describes his current research interests, how he became interested in genomics and the impact long-read sequencing is having on his research.

Professor Michael is presenting a webinar on ‘Maize genome complexity traversed with Oxford Nanopore technology’ with Frontline Genomics on Thursday 8th November 10am PST/6pm GMT.

What are you current research interests?

My overall interest is sequencing genomes to understand genome architecture and how that shapes an organism’s response to its environment. This means that my group spans kingdoms and not only looks at the genome but also the epigenome. For instance, we are interested in how memories are formed in mammals and we have been perusing the hypothesis that at some level memories are stored in the epigenome. Most recently my group has been interested in sequencing plants and macroalgae to identify important biochemical pathways.

What first ignited your interest in genomics?

During the 1980’s and before ‘genomics’, I did a project in seventh grade where I collected leaves and then wrote something about the tree they came from. Before that point, I thought all trees were the same. However, they were not the same and in fact, the trees were all different sizes and shapes and their leaves had all these amazing patterns. I figured there must be a code that controlled how they were all different and from that point I knew I wanted to figure that out.

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

Many genomes were not accessible before long-reads. For instance, in plants repeat structures are on average 10-20 kb, and in many cases much larger, so the ultra-long reads of Oxford Nanopore have been making it possible to resolve some previously difficult to intractable plant genomes. Now the throughput of the PromethION coupled to ultra-long reads is a game changer in terms of sequencing populations of complex genomes or really large (> 3 Gb) genomes.

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

While the sequencing technology has completely changed genomics over the past 15 years, one of the major challenges has always been identifying the best germplasm to sequence and isolating high amounts of high quality, high molecular weight DNA. My group has spent a lot of time developing a panel of methods to address new organisms. This requires an intimate knowledge of your species and patience, because the only way to make a high-quality genome or genomes is to start with the best DNA.

What is your advice for someone getting started?

Learn some bioinformatics and if you are motivated, learn some scripting/coding. In addition, before starting any project, even a genome sequencing project, make sure you have a question or hypothesis that drives the approach that you will take to sequence your genome or genomes.

What’s next for your research?

We have spent a lot of time resequencing genomes using short-read technology and mapping it back to a reference genome. This has been a very successful approach and we have learned a great deal. However, it is becoming increasingly clear that complete de novo genomes reveal new levels of variation that we would like to probe. My group is now spending time developing tools to do “pan genomics” based on whole de novo assembled genomes. Specifically, we would like to see the private variation across human genomes that become apparent when you sequence them de novo using long-read technologies.