Tumors are typically sequenced to depths of 75-100× (exome) or 30-50× (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ~312×) whole genome sequencing (WGS) and exome capture (up to ~433×) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ~200,000 putative SNVs by sequencing them to depths of ~1,000×. Additional targeted sequencing provided over 10,000× coverage and ddPCR assays provided up to ~250,000× sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP accession id phs000159).
Malachi Griffith, Ph.D., Obi Griffith, Ph.D., Chris Miller, Ph.D., Zachary Skidmore, Avinash Ramu, Jason Walker, Ha Dang, Ph.D., Lee Trani, David Larson, Ph.D., Ryan Demeter, Michael Wendl, Ph.D., Joshua McMichael, Rachel Austin, Amy Ly, Shashikant Kulkarni, Matthew Cordes, Catrina Fronick, Robert Fulton, Christopher Maher, Ph.D., Li Ding, Ph.D., Timothy Ley, M.D.