Noncoding Structural Variants Highlighted in Integrated Cancer Genome Analysis

NEW YORK (GenomeWeb) – An international team led by investigators at the Salk Institute for Biological Studies, Pennsylvania State University, and elsewhere has developed an integrative strategy for systematically profiling structural variants (SVs) in cancer genomes — an approach that pointed to non-coding SVs as potentially “underappreciated mutational drivers” in cancer.

The researchers took a crack at several methods for profiling SVs — including high-throughput chromosome conformation capture (Hi-C) in combination with a new Hi-C-base algorithm, whole-genome sequencing, and Bionano Genomics’ Irys next-generation optical mapping — in a broad set of cancer and normal samples and cell lines. They noted that each method made it possible to pick up SVs at different scales and resolutions in a preliminary analysis on new and published data for dozens of cancer cell lines.

“Each method by itself can only review a portion of the structural variations, but when you integrate the results of the three different methods, you can get the most comprehensive view of the cancer genome,” co-corresponding author Feng Yue, a biochemistry and molecular biology researcher at Penn State, said in a statement. 

By bringing the Hi-C, sequencing, and optical mapping data together with a new computational pipeline, the team identified

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