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Correlating Multiallelic Copy Number Polymorphisms with Disease Susceptibility

Authors

  • Stuart Cantsilieris,

    1. Centre for Reproduction and Development, Monash Institute of Medical Research, Monash University, Melbourne, Victoria, Australia
    2. Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
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  • Stefan J. White

    Corresponding author
    • Centre for Reproduction and Development, Monash Institute of Medical Research, Monash University, Melbourne, Victoria, Australia
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  • Communicated by Arupa Ganguly

  • Contract grant sponsors: Monash University, Melbourne; National Health and Medical Research Council of Australia.

Correspondence to: Stefan J. White, Centre for Reproduction and Development, Monash Institute of Medical Research, 27-31 Wright Street, Clayton, 3168, Victoria, Australia. E-mail: stefan.white@monash.edu

Abstract

The human genome contains a significant amount of sequence variation, from single nucleotide polymorphisms to large stretches of DNA that may be present in a range of different copies between individuals. Several such regions are variable in >1% of the population (referred to as copy number polymorphisms or CNPs), and many studies have looked for associations between the copy number of genes within multiallelic CNPs and disease susceptibility. Associations have indeed been described for several genes, including the β-defensins (DEFB4, DEFB103, DEFB104), chemokine ligand 3 like 1 (CCL3L1), Fc gamma receptor 3B (FCGR3B), and complement component C4 (C4). However, follow-up replication in independent cohorts has failed to reproduce a number of these associations. It is clear that replicated associations such as those between C4 and systemic lupus erythematosus, and β-defensin and psoriasis, have used robust genotyping methodologies. Technical issues associated with genotyping sequences of high identity may therefore account for failure to replicate other associations. Here, we compare and contrast the most popular approaches that have been used to genotype CNPs, describe how they have been applied in different situations, and discuss potential reasons for the difficulty in reproducibly linking multiallelic CNPs to complex diseases.

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