From case studies to community knowledge base: MSeqDR provides a platform for the curation and genomic analysis of mitochondrial diseases

Mitochondrial disease is now recognized to represent a highly heterogeneous group of genetic disorders that impair energy metabolism and can potentially involve every organ system, with more than 250 causative genes already confirmed across both the nuclear and mitochondrial genomes (Koopman et al. 2012). Novel variants in a recently recognized nuclear disease gene are reported in this issue to cause an autosomal-recessive multisystemic mitochondrial disease affecting two cousins from a Lebanese family (Joshi et al. 2016). As has now essentially become commonplace in the highly heterogeneous classes of neurologic and mitochondrial diseases, massively parallel genomic sequencing in a single family with a complex phenotype proved to be an effective means to identify potentially pathogenic novel mutations in a nuclear gene encoding a mitochondrial protein that was recently linked to cerebellar ataxia (Choquet et al. 2015; Jobling et al. 2015). Protein modeling, functional analyses in patient fibroblasts, and wild-type cDNA rescue were then used to conclusively demonstrate the causality of the novel PMPCA mutations in their patients’ more expansive phenotype that extended beyond isolated cerebellar atrophy to also include multisystemic mitochondrial disease. In this iterative fashion that directly relies on continual publication of case reports and data sharing within community resources, community knowledge steadily grows of new gene disorders, newmutations within known genes, and their expanded phenotypes, further improving community recognition of the functional significance of the up to 1500 proteins that localize within mitochondria (Calvo et al. 2016). However, given the large number of mitochondrial disease genes having low prevalence, their wide spectrum of clinical presentations, and often overlapping clinical phenotypes (Koopman et al. 2012), it is increasingly challenging for any one clinician or researcher to recognize or stay current on all potential gene causes for a patient’s disease presentation. Large public databases such as ClinVar serve as centralized warehouses for annotation assertions on potential gene causes for diverse disease presentations but remain dependent on user contributions (Landrum et al. 2016). To aid the community of mitochondrial disease researchers in curating and accessing the rapidly expanding knowledge base of mitochondrial disease genetics, a Web-based resource has been built, the Mitochondrial Disease Sequence Data Resource (MSeqDR; https://mseqdr.org). This multidimensional data resource aims to support both clinicians and researchers in the mitochondrial disease community as conceived and built by the MSeqDR Consortium (Falk et al. 2015), a grass-roots effort begun in 2012 by mitochondrial disease researchers, clinicians, and bioinformaticians with the support of the United Corresponding author: falkm@ email.chop.edu