Abstract
BackgroundIntrachromosomal segmental duplications provide the substrate for non-allelic homologous recombination, facilitating extensive copy number variation in the human genome. Many multi-copy gene families are embedded within genomic regions with high levels of sequence identity (>95%) and therefore pose considerable analytical challenges. In some cases, the complexity involved in analyzing such regions is largely underestimated. Rapid, cost effective analysis of multi-copy gene regions have typically implemented quantitative approaches, however quantitative data are not an absolute means of certainty. Therefore any technique prone to degrees of measurement error can produce ambiguous results that may lead to spurious associations with complex disease.ResultsIn this study we have focused on testing the accuracy and reproducibility of quantitative analysis techniques. With reference to the C-C Chemokine Ligand-3-like-1 (CCL3L1) gene, we performed analysis using real-time Quantitative PCR (QPCR), Multiplex Ligation-dependent Probe Amplification (MLPA) and Paralogue Ratio Test (PRT). After controlling for potential outside variables on assay performance, including DNA concentration, quality, preparation and storage conditions, we find that real-time QPCR produces data that does not cluster tightly around copy number integer values, with variation substantially greater than that of the MLPA or PRT systems. We find that the method of rounding real-time QPCR measurements can potentially lead to mis-scoring of copy number genotypes and suggest caution should be exercised in interpreting QPCR data.ConclusionsWe conclude that real-time QPCR is inherently prone to measurement error, even under conditions that would seem favorable for association studies. Our results indicate that potential variability in the physicochemical properties of the DNA samples cannot solely explain the poor performance exhibited by the real-time QPCR systems. We recommend that more robust approaches such as PRT or MLPA should be used to genotype multi-allelic copy number variation in disease association studies and suggest several approaches which can be implemented to ensure the quality of the copy number typing using quantitative methods.
Highlights
Intrachromosomal segmental duplications provide the substrate for non-allelic homologous recombination, facilitating extensive copy number variation in the human genome
In this study we aim to demonstrate some simple approaches for assessing the quality of genotyping data when using methods such as real-time Quantitative Polymerase Chain Reaction (PCR) (QPCR), Paralogue Ratio Test (PRT) and Multiplex Ligation-dependent Probe Amplification (MLPA) for the analysis of multi-allelic copy number
As the real-time QPCR assay targets exon 3 and the PRT assay targets exon 1, we could compare both techniques to the two individual probe results generated by the MLPA assay
Summary
Intrachromosomal segmental duplications provide the substrate for non-allelic homologous recombination, facilitating extensive copy number variation in the human genome. The quantitative methods commonly used to genotype multi-allelic copy number polymorphisms (CNPs) are not absolute, accuracy and reproducibly are required to generate robust disease associations [2]. A challenging aspect of multi-allelic copy number analysis is that the relative difference between copy number classes becomes smaller and more difficult to discriminate as copy number increases [4]. Despite this challenge, CNP analysis should produce data that clusters tightly around integer values [5], unless there is evidence for tissue mosaicism in which different cell types contain different copy numbers [6]. Similar data can be produced when measurements of non-mosaic tissues are imprecise and unable to discriminate CNVs with a high level of accuracy, potentially leading to erroneous conclusions
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