4.5 Article

Genome-wide SNP assay reveals structural genomic variation, extended homozygosity and cell-line induced alterations in normal individuals

Journal

HUMAN MOLECULAR GENETICS
Volume 16, Issue 1, Pages 1-14

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/hmg/ddl436

Keywords

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Funding

  1. Intramural NIH HHS Funding Source: Medline
  2. Medical Research Council [G0701075] Funding Source: Medline
  3. Parkinson&apos
  4. s UK [G-0907] Funding Source: Medline
  5. MRC [G0701075] Funding Source: UKRI

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The recent hapmap effort has placed focus on the application of genome- wide SNP analysis to assess the contribution of genetic variability, particularly SNPs, to traits such as disease. Here, we describe the utility of genome-wide SNP analysis in the direct detection of extended homozygosity and structural genomic variation. We use this approach to assess the frequency of genomic alterations resulting from the lymphoblast immortalization and culture processes commonly used in cell repositories. We have assayed 408 804 SNPs in 276 DNA samples extracted from Epstein-Barr virus immortalized cell lines, which were derived from lymphocytes of elderly neurologically normal subjects. These data reveal extended homozygosity (contiguous tracts > 5 Mb) in 9.5% (26/272) and 340 structural genomic alterations in 182 (66.9%) DNA samples assessed, 66% of which did not overlap with previously described structural variations. Examination of DNA extracted directly from the blood of 30 of these subjects confirmed all examined instances of extended homozygosity (6/6), 75% of structural genomic alteration < 5 Mb in size (12/16) and 13% (1/8) of structural genomic alteration > 5 Mb in size. These data suggest that structural genomic variation is a common phenomenon in the general population. While a proportion of this variability may be caused or its relative abundance altered by the immortalization and clonal process this will have only a minor effect on genotype and allele frequencies in a large cohort. It is likely that this powerful methodology will augment existing techniques in the identification of chromosomal abnormalities.

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