Clinical Bioinformatics in Precise Diagnosis of Mitochondrial Disease

Clin Lab Med. 2020 Jun;40(2):149-161. doi: 10.1016/j.cll.2020.02.002.

Abstract

Clinical bioinformatics system is well-established for diagnosing genetic disease based on next-generation sequencing, but requires special considerations when being adapted for the next-generation sequencing-based genetic diagnosis of mitochondrial diseases. Challenges are caused by the involvement of mitochondrial DNA genome in disease etiology. Heteroplasmy and haplogroup are key factors in interpreting mitochondrial DNA variant effects. Data resources and tools for analyzing variant and sequencing data are available at MSeqDR, MitoMap, and HmtDB. Revised specifications of the American College of Medical Genetics/Association of Molecular Pathology standards and guidelines for mitochondrial DNA variant interpretation are proposed by the MSeqDr Consortium and community experts.

Keywords: Bioinformatics; Clinical sequencing; Mitochondrial disease; Pathogenicity; Phenotype; Variant annotation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Computational Biology*
  • Genome, Mitochondrial / genetics
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Mitochondrial Diseases* / diagnosis
  • Mitochondrial Diseases* / genetics
  • Molecular Diagnostic Techniques*
  • Pathology, Molecular
  • Sequence Analysis, DNA*