High-throughput DNA methylation profiling using universal bead arrays

  1. Marina Bibikova1,
  2. Zhenwu Lin2,
  3. Lixin Zhou1,
  4. Eugene Chudin1,
  5. Eliza Wickham Garcia1,
  6. Bonnie Wu1,
  7. Dennis Doucet1,
  8. Neal J. Thomas3,
  9. Yunhua Wang2,
  10. Ekkehard Vollmer5,
  11. Torsten Goldmann5,
  12. Carola Seifart6,
  13. Wei Jiang7,
  14. David L. Barker1,
  15. Mark S. Chee1,
  16. Joanna Floros2,3,4, and
  17. Jian-Bing Fan1,8
  1. 1 Illumina, Inc., San Diego, California 92121, USA, Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA
  2. 2 Department of Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA
  3. 3 Department of Pediatrics and Health Evaluation Sciences, Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA
  4. 4 Department of Obstetrics and Gynecology, Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA
  5. 5 Clinical and Experimental Pathology, Research Center Borstel, Parkallee, 23845 Borstel, Germany
  6. 6 Department of Internal Medicine, Division of Respiratory Medicine, Philipps-University of Marburg, Baldingerstasse, 35043 Marburg, Germany
  7. 7 The Burnham Institute, La Jolla, California 92037, USA

Abstract

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

Footnotes

  • [Supplemental material is available online at www.genome.org.]

  • Article published online ahead of print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.4410706.

  • Freely available online through the Genome Research Open Access option.

  • 8 Corresponding author. E-mail jfan@{at}illumina.com; fax (858) 202-4680.

    • Accepted November 1, 2005.
    • Received July 10, 2005.
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