Epigenome Characterization of Human Genomes using the PacBio Platform Jonas Korlach1, Yuta Suzuki2, Marie Classon3, Vasantharajan Janakiraman3, Eric W. Stawiski3, Matthew Boitano1, Jason Chin1, Khai Luong1, Stephen W. Turner1, Steffen Durinck3, Somasekar Seshagiri3 and Shinichi Morishita2 1Pacific Biosciences Inc., Menlo Park, CA 94025, 2University of Tokyo, Tokyo, Japan, and 3Molecular Biology, Bioinformatics, and Department of Oncology, Genentech Inc., South San Francisco, CA 94080
Abstract Cancer Epigenome Resolving Repetitive Regions1
In addition to the genome and transcriptome, Differential methylation status of CpG Example of hypomethylated repeat epigenetic information is essential to understand islands inferred genome-wide from PacBio occurrences (chr. 6): biological processes and their regulation, and their misregulation underlying disease. Traditionally, Sequencing data, algorithm at epigenetic DNA modifications are detected using https://github.com/hacone/AgIn upfront sample preparation steps such as bisulfite conversion, followed by sequencing. Bisulfite 85 sequencing has provided a wealth of knowledge about Drug-sensitive human epigenetics, however it does not access the Drug-resistant entire genome due to limitations in read length and GC- 80 bias of the sequencing technologies used. PCA analysis for 4 selected classes of In contrast, Single Molecule, Real-Time (SMRT) DNA 75 Sequencing is unique in that it can detect DNA base repetitive elements: modifications as part of the sequencing process. It can thereby leverage the long read lengths and lack of GC 70 bias for more comprehensive views of the human epigenome. I will highlight several examples of this 65 capability towards the generation of new biological % Hypermethylated CpG Islands CpG Hypermethylated % insights, including the resolution of methylation states 60 in repetitive and GC-rich regions of the genome, and 12345678910111213141516171819202122 large-scale changes in the methylation status across a Chromosome cancer genome as a function of drug sensitivity. More hypermethylated CpG islands in drug-resistant sample Background
Examples: Chr. 4: ANKRD17 (already implicated in breast cancer)
Genome-wide distribution of hypomethylated repetitive elements:
Cancer Epigenome Study Design Chr. 4: WHSC1 (already implicated in myelomas) Summary of methylation status on • PC-9 lung cancer Drug- repetitive elements: cell line, studying sensitive
drug susceptibility Sustained treatment with • Methyltransferase erlotinib
(MT) inhibitor Drug- reverts cells to resistant drug-sensitive MT inhibitor Mutations
Stably Drug- drug- sensitive resistant Chr. 4: FGFR3 (fibroblast growth factor 3)
• Utilized PacBio Sequencing for: References
• Generate de novo cancer genome 1Suzuki et al. (2015) Landscape of CpG methylation of assembly individual repetitive elements. • Characterize cancer genome http://biorxiv.org/content/early/2015/04/24/018531 structural variation Chr. 4: RASSF6 (tumor suppressor gene) • Detect gene fusions Acknowledgements • Characterize genome-wide The authors would like to thank everyone methylome who helped generate data for the poster.
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