An MLPA-based approach for high-resolution genotyping of disease-related multi-allelic CNVs

Abstract

Copy number variation has recently been recognized as an important type of genetic variation that modifies human phenotypes. Copy number variants (CNVs) are being increasingly associated with various human phenotypes and diseases. However, the lack of an appropriate method that allows fast, inexpensive and, most importantly, accurate CNVs genotyping significantly hampers CNV analysis. This limitation especially affects the analysis of multi-allelic CNVs that frequently modify various phenotypes. Recently, we developed a multiplex ligation-dependent probe amplification (MLPA)-based strategy for multiplex copy number genotyping and the validation of candidate CNV-miRNAs. Here we present the adaptation and optimization of this recently developed method for high-resolution genotyping of individual disease-related multi-allelic CNVs. We developed appropriate assays for three well-known and extensively studied CNVs: CNV-CCL3L1, CNV-DEFB, and CNV-UGT2B17, which have been associated with various human phenotypes including inflammation-related and infectious diseases. With the use of these assays we identified several general factors that allow to increase the resolution of the copy number genotyping. Performed experiments confirmed the high reproducibility and accuracy of the obtained genotyping results. The reliability of the results and relatively low per-genotype cost makes this strategy an attractive method for large-scale experiments such as genotype-phenotype association studies.

Keywords: CCL3L1; DEFB; MLPA; Multi-allelic CNV; UGT2B17.