Origins and functional impact of copy number variation in the human genome

Abstract

Structural variations of DNA greater than 1 kilobase in size account for most bases that vary among human genomes, but are still relatively under-ascertained. Here we use tiling oligonucleotide microarrays, comprising 42 million probes, to generate a comprehensive map of 11,700 copy number variations (CNVs) greater than 443 base pairs, of which most (8,599) have been validated independently. For 4,978 of these CNVs, we generated reference genotypes from 450 individuals of European, African or East Asian ancestry. The predominant mutational mechanisms differ among CNV size classes. Retrotransposition has duplicated and inserted some coding and non-coding DNA segments randomly around the genome. Furthermore, by correlation with known trait-associated single nucleotide polymorphisms (SNPs), we identified 30 loci with CNVs that are candidates for influencing disease susceptibility. Despite this, having assessed the completeness of our map and the patterns of linkage disequilibrium between CNVs and SNPs, we conclude that, for complex traits, the heritability void left by genome-wide association studies will not be accounted for by common CNVs.

Translating Lung Function Genome-Wide Association Study (GWAS) Findings

“…In addition to SNPs potentially contributing to human lung function and COPD susceptibility, copy number variation (duplication or deletion of regions of DNA, CNVs) is also an important area of study, with 4% of the genome harbouring copy number variants (Conrad et al, 2010). For example, previous reports have identified the Beta Defensins to have 2-10 copies in the UK population (Fode et al, 2011;Hardwick et al, 2011).…”

The pursuit of genome-wide association studies: where are we now?

“…160 In fact, a recent study also confirmed that most of the common CNVs are well tagged by SNPs, suggesting that the existing GWAS have indirectly interrogated the association of common CNVs with complex diseases relatively well. 161 Nevertheless, as the non-SNP variants that have been discovered so far are only a fraction of the total number, there are still many uncertainties remaining about the LD. Therefore, when a more complete map or catalog of non-SNP variants is available in the future, more studies will be needed to further interrogate the LD relationship between them and SNPs.…”

“…[162][163][164][165][166] In addition, one study has shown the correlations of about 30 SNPs (that found to be associated with various traits by GWAS) with CNVs at r 2 40.5, this provides preliminary evidence of the associations and possible roles of CNVs in human complex traits. 161 The amount of evidence is expected to increase in the near future, when we have a better understanding of the characteristics of non-SNP variants and a more comprehensive map of them constructed upon the completion of the 1000 Genomes Project, and when more efficient and accurate methods are available to detect the non-SNP variants for disease-association studies. It is crucial to remember that the current GWAS using the commercial genotyping arrays cover only a portion of the total genetic variants, thus a substantial false-negative rate or a significant portion of missing heritability could be attributed to incomplete interrogation of all the genetic variants for disease association.…”

A commentary on Implication of gene copy number variation in health and diseases

“…5 In contrast, some recent GWAS of common CNVs reported rather pessimistic results in common diseases as follows. 6,7 Common CNV-based GWAS in 16 000 cases of eight common diseases-bipolar disorder, breast cancer, coronary artery disease, Crohn's disease, hypertension, rheumatoid arthritis, type-1 diabetes and type-2 diabetes-and 3000 controls revealed that common CNVs were unlikely to contribute to the genetic basis of these diseases. 7 In addition, another study based on the assessment of the patterns of linkage disequilibrium between CNVs and SNPs suggested that for complex traits the heritability void left by GWAS could not be compensated by common CNVs.…”

“…7 In addition, another study based on the assessment of the patterns of linkage disequilibrium between CNVs and SNPs suggested that for complex traits the heritability void left by GWAS could not be compensated by common CNVs. 6 As both authors concluded, other platforms or resources of genetic variants could elucidate more disease susceptibilities. Maps of precise nucleotide CNVs and rare CNVs, as well as rare SNPs would be important resources for association studies of human diseases.…”