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

Area of Science:

• Genomics
• Bioinformatics
• Medical Genetics

Background:

• Accurate detection of rare functional DNA variants is crucial for medical resequencing.
• Minimizing false positive base-calls reduces unnecessary costs associated with sequence verification.

Purpose of the Study:

• To develop and validate a novel statistical method, Sequence Robust Multi-Array Analysis (SRMA), for enhanced rare variant detection.
• To improve the accuracy and reduce the cost of identifying genetic variations in medical applications.

Main Methods:

• SRMA employs single and multi-array analysis, incorporating technical variables and accounting for low- and high-frequency genomic variations.
• Base-call confidence is ranked using two quality measures.
• The method was compared against Sanger capillary sequencing.

Main Results:

• SRMA achieved a 2% false discovery rate (1.2 × 10⁻⁵ false positive rate, 5% false negative rate), comparable to second-generation sequencing technologies.
• Analysis of 39 nuclear candidate genes in mitochondrial DNA maintenance disorders confirmed known POLG mutations and identified novel variants in TOP1MT, MUTYH, and APEX2.
• Rare heterozygous variants in functionally interacting genes were observed in some patients, suggesting potential synergistic genetic effects.

Conclusions:

• SRMA is an effective method for accurate rare variant detection in medical resequencing.
• The findings highlight potential novel genetic contributors to disorders of mitochondrial DNA maintenance.
• Synergistic genetic effects may play a role in clinically similar genetic disorders.