Bioinformatics Tools for NGS-Based Identification of Single Nucleotide Variants and Large-Scale Rearrangements in...

Area of Science:

• Genetics and Genomics
• Bioinformatics
• Molecular Biology

Background:

• Mitochondrial DNA (mtDNA) diseases are challenging to diagnose due to mtDNA's unique genetic features like heteroplasmy and NUMTs.
• Next-generation sequencing (NGS) has improved mtDNA disease diagnosis, but interpreting the complex data requires specialized bioinformatics tools.
• Existing NGS analysis pipelines for mtDNA are not always optimized for the mitochondrial genome's specific characteristics.

Purpose of the Study:

• To present and evaluate novel bioinformatics approaches for enhanced accuracy in diagnostic mtDNA analysis.
• To assess the utility of two free bioinformatics tools, Mitopore and MitoSAlt, for analyzing short- and long-read sequencing data.
• To improve the interpretation of genetic variants in mitochondrial DNA for clinical diagnostics.

Main Methods:

• Evaluation of Mitopore and MitoSAlt bioinformatics tools on patient samples with previously diagnosed mtDNA variants (single nucleotide variants, large-scale deletions).
• Analyses were conducted using Linux-based environments and web servers.
• The tools were implemented in programming languages including Python, Perl, Java, and R.

Main Results:

• Both Mitopore and MitoSAlt demonstrated high sensitivity and specific accuracy in identifying and quantifying various pathogenic mtDNA variants.
• The tools effectively analyzed both short- and long-read sequencing data.
• Each tool proved adept at handling the complexities of mitochondrial genome analysis.

Conclusions:

• The integrated and parallel use of Mitopore and MitoSAlt offers a significant advantage over traditional methods for interpreting mtDNA genetic variants.
• These bioinformatics tools reduce computational demands, providing an accurate and efficient diagnostic solution for mtDNA-related diseases.
• The study highlights the potential of these advanced bioinformatics approaches to improve clinical diagnostics for mitochondrial disorders.