Identification of rare DNA variants in mitochondrial disorders with improved array-based sequencing

Abstract

A common goal in the discovery of rare functional DNA variants via medical resequencing is to incur a relatively lower proportion of false positive base-calls. We developed a novel statistical method for resequencing arrays (SRMA, sequence robust multi-array analysis) to increase the accuracy of detecting rare variants and reduce the costs in subsequent sequence verifications required in medical applications. SRMA includes single and multi-array analysis and accounts for technical variables as well as the possibility of both low- and high-frequency genomic variation. The confidence of each base-call was ranked using two quality measures. In comparison to Sanger capillary sequencing, we achieved a false discovery rate of 2% (false positive rate 1.2 × 10−5, false negative rate 5%), which is similar to automated second-generation sequencing technologies. Applied to the analysis of 39 nuclear candidate genes in disorders of mitochondrial DNA (mtDNA) maintenance, we confirmed mutations in the DNA polymerase gamma POLG in positive control cases, and identified novel rare variants in previously undiagnosed cases in the mitochondrial topoisomerase TOP1MT, the mismatch repair enzyme MUTYH, and the apurinic-apyrimidinic endonuclease APEX2. Some patients carried rare heterozygous variants in several functionally interacting genes, which could indicate synergistic genetic effects in these clinically similar disorders.

High-quality DNA sequence capture of 524 disease candidate genes

“…On the basis of five HapMap samples (Table 1), we estimated a false negative rate (FNR) of 2.9% and a false discovery rate (FDR) of 1.3%. A slightly lower performance was found in the analysis of variant positions in 38 patient samples that we had verified previously using Sanger capillary sequencing (16). Manual inspection revealed that most discordant base calls were related to limitations in the microarray analysis, which could be improved as more samples are studied (Fig.…”

“…The array hybridization data were also used to assess the success of the LPP-based technology to capture the targeted exons in each sample. The capture pools were directly hybridized to this microarray (1 array per sample) and we performed data analysis with a statistical software developed for resequencing arrays (16). First, to identify rare instances of hybridization failure, we verified the overall signal quality on each array by measuring the average differences in signal intensities across all reference match (RM) and alternative match (AM) probes.…”

“…For positions in amplicons with R ≥ 0.9, we performed an automated clustering analysis of the 63 sample arrays and assigned a position-specific quality score to measure the confidence of each base call (16). Similar to Bainbridge et al (11), the variants discovered were compared with known HapMap SNPs and to dbSNP.…”

“…These two DNA sequence capture technologies are complementary (one method cannot fully measure what the other measures and they support each other) and applied together allow to maximize sequence coverage and to control the false discovery rate for rare (minor allele frequency, MAF < 1%) variants. Similarly, because of different biases and error rates of the current sequencing technology (11,16,24,25), high-quality variant discovery in medical samples may be best performed through a combination of technologies. A comparison of different sequencing technologies (e.g., array based vs. sequencing by synthesis) is our next goal to identify the cause of sequencing errors inherent to each method and to improve the protocols for targeted medical resequencing.…”

“…A subset of amplicons in each sample was inspected by 1.2% aga- We used multiarray clustering for base calling of each position with the R package mclust (26) and ranked the confidence of each base call using a position-specific quality score (cutoff 0.67) (16). This analysis focused on verified DNA variants with a minor allele frequency larger than 0.05 in five HapMap individuals (columns 2-5) and in a pool of 38 medical cases (column 6) that we confirmed through Sanger sequencing (16). The variant calls from this study (ii) were compared with all previously reported sample variants in each sample (i) to estimate this method's performance.…”