The performance of MALBAC and MDA methods in the identification of concurrent mutations and aneuploidy screening to diagnose beta-thalassaemia disorders at the single- and multiple-cell levels.

Abstract

To select an optimal whole-genome amplification (WGA) method to improve the efficiency of the preimplantation genetic diagnosis and screening (PGD/PGS) of beta-thalassaemia disorders. Fifty-seven fibroblast samples with defined beta-thalassaemia variations and forty-eight single-blastomere samples were amplified from single-, two-, and five-cell samples by multiple annealing and looping-based amplification cycles (MALBAC) and the multiple displacement amplification (MDA) method. Low-depth, high-throughput sequencing was performed to evaluate and compare the coefficiencies of the chromosomal copy number variation (CNV) detection rate and the allele dropout (ADO) rate between these two methods. At the single-cell level, the success rates of the CNV detection in the fibroblast samples were 100% in the MALBAC group and 91.67% in the MDA group; the coefficient of variation in the CNV detection in the MALBAC group was significantly superior to that in the MDA group (0.15 vs 0.37). The total ADO rate in the HBB allele detection was 4.55% in the MALBAC group, which was significantly lower than the 22.5% rate observed in the MDA group. However, when five or more cells were used as the starting template, the ADO rate significantly decreased, and these two methods did not differ significantly. For the genetic diagnosis of HBB gene variation at the single-cell level, MALBAC is a more suitable method due to its higher level of uniformity and specificity. When five or more cells are used as the starting template, both methods exhibit similar efficiency, increased accuracy, and a similar success rate in PGD/PGS.