High-resolution mapping and analysis of copy number variations in the human genome: A data resource for clinical and research applications

  1. Tamim H. Shaikh,1,
  2. Xiaowu Gai,
  3. Juan C Perin,
  4. Joseph T Glessner,
  5. Hongbo Xie,
  6. Kevin Murphy,
  7. Ryan O'Hara,
  8. Tracy Casalunovo,
  9. Laura K Conlin,
  10. Monica D'arcy,
  11. Edward C Franckelton,
  12. Elizabeth A Geiger,
  13. Chad Haldeman-Englert,
  14. Marcin Imielinski,
  15. Cecelia E Kim,
  16. Livija Medne,
  17. Kiran Annaiah,
  18. Jonathan Bradfield,
  19. Elvira Dabaghyan,
  20. Andrew Eckert,
  21. Chioma C Onyiah,
  22. Svetlana Ostapenko,
  23. F. George Otieno,
  24. Erin Santa,
  25. Julie L Shaner,
  26. Robert Skraban,
  27. Ryan M Smith,
  28. Josephine Elia,
  29. Elizabeth Goldmuntz,
  30. Nancy B Spinner,
  31. Elaine H Zackai,
  32. Rosetta M Chiavacci,
  33. Robert Grundmeier,
  34. Eric F Rappaport,
  35. Struan F.A. Grant,
  36. Peter S White and
  37. Hakon Hakonarson
  1. The Children's Hospital of Philadelphia
  1. 1 E-mail: tshaikh{at}mail.med.upenn.edu

Abstract

We present a database of copy number variations (CNVs) detected in 2,026 disease-free individuals, using high-density, SNP-based oligonucleotide microarrays. This large cohort, comprised mainly of Caucasians (65.2%) and African-Americans (34.2%), was analyzed for CNVs in a single study using a uniform array platform and computational process. We have catalogued and characterized 54,462 individual CNVs, 77.8% of which were identified in multiple unrelated individuals. These non-unique CNVs mapped to 3,272 distinct regions of genomic variation spanning 5.9% of the genome; 51.5% of these were previously unreported, and >85% are rare. Our annotation and analysis confirmed and extended previously reported correlations between CNVs and several genomic features such as repetitive DNA elements, segmental duplications and genes. We demonstrate the utility of this data set in distinguishing CNVs with pathologic significance from normal variants. Together, this analysis and annotation provides a useful resource to assist with the assessment of CNVs in the contexts of human variation, disease susceptibility, and clinical molecular diagnostics.

Footnotes

    • Received December 1, 2008.
    • Accepted June 17, 2009.
ACCEPTED MANUSCRIPT

This Article

  1. Published in Advance July 10, 2009, doi: 10.1101/gr.083501.108 Genome Res. gr.083501.108 Copyright © 2009, Cold Spring Harbor Laboratory Press

Article Category

Share

Preprint Server



Current Issue

  1. February 2026, 36 (2)
  1. Current Issue
  1. Alert me to new issues of Genome Research