Ruler Arrays Reveal Haploid Genomic Structural Variation

• Main Authors: Gifford, David K. (Contributor), Rolfe, Philip Alexander (Contributor), Fink, Gerald R. (Contributor), Bernstein, Douglas A. (Author), Grisafi, Paula (Author)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
• Format: Article
• Language: English
• Published: Public Library of Science, 2012-11-09T19:19:12Z.
• Subjects: Article
• Online Access: Get fulltext

Despite the known relevance of genomic structural variants to pathogen behavior, cancer, development, and evolution, certain repeat based structural variants may evade detection by existing high-throughput techniques. Here, we present ruler arrays, a technique to detect genomic structural variants including insertions and deletions (indels), duplications, and translocations. A ruler array exploits DNA polymerase's processivity to detect physical distances between defined genomic sequences regardless of the intervening sequence. The method combines a sample preparation protocol, tiling genomic microarrays, and a new computational analysis. The analysis of ruler array data from two genomic samples enables the identification of structural variation between the samples. In an empirical test between two closely related haploid strains of yeast ruler arrays detected 78% of the structural variants larger than 100 bp.
United States. National Institutes of Health (Grant R01GM069676)