Abstract: Long read, single molecule sequencing from Pacific Biosciences (PacBio) and Oxford Nanopore are revolutionizing genomics with increased power to resolve and study genomes. Most notably, these technologies have recently enabled the sequencing of the first completely gap-free human genome and have enabled the discovery of tens of thousands of structural variants that were previously invisible to short read sequencing, including within clinically relevant genes. While these technologies were previously too slow, costly, and erroneous for widespread use, their recent improvements have made them competitive or superior to short read sequencing in nearly all ways. This is opening up new avenues for widespread applications for population and clinical studies, including of cancer. In this presentation, I’ll discuss how we are using these technologies for human genomics, with a focus on studying genomic and epigenomic instability in cancer.
Brief Bio: Michael Schatz is the Bloomberg Distinguished Associate Professor of Computer Science and Biology at Johns Hopkins University. His research is at the intersection of computer science, biology, and biotechnology, and focuses on development of novel algorithms and systems for comparative genomics, human genetics, and personalized medicine. In 2015, Schatz received the Alfred P. Sloan Foundation Fellowship to develop computational methods to probe the genetic components of autism and cancer, and in 2014 Schatz received the NSF CAREER award to develop computational methods to study plant and animal genomes using new long-read single molecule DNA sequencing technologies. Schatz joined JHU in 2016, after spending 6 years at Cold Spring Harbor Laboratory where he remains an Adjunct Associate Professor of Quantitative Biology. Schatz received his Ph.D. and M.S. in Computer Science from the University of Maryland in 2010 and 2008, his B.S. in Computer Science from Carnegie Mellon University in 2000, and spent 5 years at the Institute for Genomic Research (TIGR) in between. More information is available on his lab website: http://schatz-lab.org