Methods and strategies for analyzing copy number variation using DNA microarrays

Abstract

The association of DNA copy-number variation (CNV) with specific gene function and human disease has been long known, but the wide scope and prevalence of this form of variation has only recently been fully appreciated. The latest studies using microarray technology have demonstrated that as much as 12% of the human genome and thousands of genes are variable in copy number, and this diversity is likely to be responsible for a significant proportion of normal phenotypic variation. Current challenges involve developing methods not only for detecting and cataloging CNVs in human populations at increasingly higher resolution but also for determining the association of CNVs with biological function, recent human evolution, and common and complex human disease.

High-resolution SNP arrays in mental retardation diagnostics: how much do we gain?

“…2,[4][5][6][7][8] In the past few years, DNA microarrays have increased capabilities for the detection of both pathological and neutral polymorphic variations by analyzing the entire genome with a resolution depending on the number, length and type of probes. 1,[9][10][11][12][13][14] Genome tiling microarrays are now available, allowing DNA analysis at an intermediary resolution between cytogenetic techniques (Z5 Mb) and conventional DNA sequence analysis (1-800 bp). 9 Mental retardation (MR) is a relatively frequent disorder affecting about 3% of the general population.…”

“…1,[9][10][11][12][13][14] Genome tiling microarrays are now available, allowing DNA analysis at an intermediary resolution between cytogenetic techniques (Z5 Mb) and conventional DNA sequence analysis (1-800 bp). 9 Mental retardation (MR) is a relatively frequent disorder affecting about 3% of the general population. MR etiological diagnoses are made usually in fewer than half of the affected individuals.…”

“…One limitation of these arrays is that probe selection is not homogeneous, as it reflects the distribution of SNPs in the genome, and SNPs are very sparse in genomic segments containing low-copy repeats and segmental duplications. 9 SNP arrays frequently offer a better detection of CNVs in gene-poor regions. 20 To overcome this restriction, the latest generation high-resolution SNP array platforms were generated by adding nonpolymorphic sequences to cover the SNP-poor region (Illumina, San Diego, CA, USA and Affymetrix, Santa Clara, CA, USA).…”

“…21 The theoretical resolution of a microarray depends on the length, number and genomic density of probes; however, many other parameters can determine the practical resolution, including the level of experiment noise and the sensitivity of copy number measurements. 9,22,23 Thus, in oligonucleotide arrays as in SNP arrays, the reduced length of probes tends to generate a lower signal-to-noise ratio of hybridization, and analyses need to average data from several consecutive spotted sequences, thus diminishing the overall resolution. 9 In this study, we analyzed 70 karyotyped patients affected by MR/ MCA, who were previously analyzed with an oligonucleotide array with an average spacing of 32 kb.…”

Genetic Susceptibility to Rhodococcus equi

“…The SNP arrays also are not well suited for identifying CNVs in structurally complex regions (eg, gene families, segmentally duplicated regions). Probe design often is difficult in these regions, thus they are excluded from the array 67, 68, 69…”