Priority Research Perspective:
Tumor diversity and evolution revealed through RADseq
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Elizabeth B. Perry1,2, Alvin Makohon-Moore3, Caihong Zheng4, Charles K. Kaufman5, Jun Cai4, Christine A. Iacobuzio-Donahue3 and Richard M. White1
1 Cancer Biology & Genetics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
2 Biostatistics, Yale University, New Haven, Connecticut, USA
3 The David M. Rubenstein Center for Pancreatic Cancer Research, Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA
4 Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
5 Washington University School of Medicine, St. Louis, Missouri, USA
Elizabeth B. Perry, email:
Richard M. White, email:
Keywords: restriction-site associated DNA sequencing, RADseq, cancer, next-generation sequencing, tumor evolution
Received: April 09, 2017 Accepted: May 12, 2017 Published: June 03, 2017
Summary: Cancer is an evolutionary disease, and there is increasing interest in applying tools from evolutionary biology to understand cancer progression. Restriction-site associated DNA sequencing (RADseq) was developed for the field of evolutionary genetics to study adaptation and identify evolutionary relationships among populations. Here we apply RADseq to study tumor evolution, which allows for unbiased sampling of any desired frequency of the genome, overcoming the selection bias and cost limitations inherent to exome or whole-genome sequencing. We apply RADseq to both human pancreatic cancer and zebrafish melanoma samples. Using either a low-frequency (SbfI, 0.4% of the genome) or high-frequency (NsiI, 6-9% of the genome) cutter, we successfully identify single nucleotide substitutions and copy number alterations in tumors, which can be augmented by performing RADseq on sublineages within the tumor. We are able to infer phylogenetic relationships between primary tumors and metastases. These same methods can be used to identify somatic mosaicism in seemingly normal, non-cancerous tissues. Evolutionary studies of cancer that focus on rates of tumor evolution and evolutionary relationships among tumor lineages will benefit from the flexibility and efficiency of restriction-site associated DNA sequencing.
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