BMC Medical Genomics (Mar 2011)

Comparison of genome-wide array genomic hybridization platforms for the detection of copy number variants in idiopathic mental retardation

  • Marra Marco,
  • Lemyre Emmanuelle,
  • Langlois Sylvie,
  • Lam Wan L,
  • Eydoux Patrice,
  • Delaney Allen,
  • Coe Bradley P,
  • Chénier Sébastien,
  • Chan Susanna,
  • Chai David,
  • Montpetit Alexandre,
  • Tucker Tracy,
  • Qian Hong,
  • Rouleau Guy A,
  • Vincent David,
  • Michaud Jacques L,
  • Friedman Jan M

DOI
https://doi.org/10.1186/1755-8794-4-25
Journal volume & issue
Vol. 4, no. 1
p. 25

Abstract

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Abstract Background Clinical laboratories are adopting array genomic hybridization as a standard clinical test. A number of whole genome array genomic hybridization platforms are available, but little is known about their comparative performance in a clinical context. Methods We studied 30 children with idiopathic MR and both unaffected parents of each child using Affymetrix 500 K GeneChip SNP arrays, Agilent Human Genome 244 K oligonucleotide arrays and NimbleGen 385 K Whole-Genome oligonucleotide arrays. We also determined whether CNVs called on these platforms were detected by Illumina Hap550 beadchips or SMRT 32 K BAC whole genome tiling arrays and tested 15 of the 30 trios on Affymetrix 6.0 SNP arrays. Results The Affymetrix 500 K, Agilent and NimbleGen platforms identified 3061 autosomal and 117 X chromosomal CNVs in the 30 trios. 147 of these CNVs appeared to be de novo, but only 34 (22%) were found on more than one platform. Performing genotype-phenotype correlations, we identified 7 most likely pathogenic and 2 possibly pathogenic CNVs for MR. All 9 of these putatively pathogenic CNVs were detected by the Affymetrix 500 K, Agilent, NimbleGen and the Illumina arrays, and 5 were found by the SMRT BAC array. Both putatively pathogenic CNVs identified in the 15 trios tested with the Affymetrix 6.0 were identified by this platform. Conclusions Our findings demonstrate that different results are obtained with different platforms and illustrate the trade-off that exists between sensitivity and specificity. The large number of apparently false positive CNV calls on each of the platforms supports the need for validating clinically important findings with a different technology.