MitoLSDB: A Comprehensive Resource to Study Genotype to Phenotype Correlations in Human Mitochondrial DNA Variations

Abstract

Human mitochondrial DNA (mtDNA) encodes a set of 37 genes which are essential structural and functional components of the electron transport chain. Variations in these genes have been implicated in a broad spectrum of diseases and are extensively reported in literature and various databases. In this study, we describe MitoLSDB, an integrated platform to catalogue disease association studies on mtDNA (http://mitolsdb.igib.res.in). The main goal of MitoLSDB is to provide a central platform for direct submissions of novel variants that can be curated by the Mitochondrial Research Community. MitoLSDB provides access to standardized and annotated data from literature and databases encompassing information from 5231 individuals, 675 populations and 27 phenotypes. This platform is developed using the Leiden Open (source) Variation Database (LOVD) software. MitoLSDB houses information on all 37 genes in each population amounting to 132397 variants, 5147 unique variants. For each variant its genomic location as per the Revised Cambridge Reference Sequence, codon and amino acid change for variations in protein-coding regions, frequency, disease/phenotype, population, reference and remarks are also listed. MitoLSDB curators have also reported errors documented in literature which includes 94 phantom mutations, 10 NUMTs, six documentation errors and one artefactual recombination. MitoLSDB is the largest repository of mtDNA variants systematically standardized and presented using the LOVD platform. We believe that this is a good starting resource to curate mtDNA variants and will facilitate direct submissions enhancing data coverage, annotation in context of pathogenesis and quality control by ensuring non-redundancy in reporting novel disease associated variants.

FROG - Fingerprinting Genomic Variation Ontology

“…The rapidly increasing amount of genomic variations data poses a challenge for storage and searching complex queries efficiently. An example dataset of 29,241 RNA and 1,13,255 protein variants from MitoLSDB [ 18 ] have been used as a test case to generate binary fingerprints using FROG. These fingerprints are stored in a database wrapped by Galaxy framework [ 19 ].…”

“…To showcase the application of FROG fingerprints, data comprising of nearly 1,42,500 variations from 37 mitochondrial genes is used [ 18 ]. Next, FROG fingerprints of DNA, protein and variation levels were generated for all these genomic variations using in-house PERL script.…”

mit-o-matic: A Comprehensive Computational Pipeline for Clinical Evaluation of Mitochondrial Variations from Next-Generation Sequencing Datasets

“…Mitochondrial variants and annotations were primarily derived from MITOMAP [Kogelnik et al., ], mtDB [Ingman and Gyllensten, ], and MitoLSDB [K et al., ]. The variant data were compiled into compatible data files and uploaded into MySQL.…”

“…The small genome size and availability of tools including tiling microarrays and sequencing has enabled us to understand the diversity of mitochondrial variations [Maitra et al., ]. This has been complemented by a number of informatics resources such as MITOMAP [Kogelnik et al., ] and MitoLSDB [K et al., ], which have systematically curated information from various resources on mitochondrial variations.…”

Resources, challenges and way forward in rare mitochondrial diseases research

“…Over the years, a large number of web-based resources have been developed on various aspects of mitochondrial diseases, most of them focusing on the data from mtDNA. Some of these include, MitoMap, a database on human mitochondrial variation 6 , MitoLSDB, the largest curated data on mtDNA variation with phenotype using LOVD 16 , MitoCarta, a resource on mitochondrial proteins based on localization 17 , MitoMiner, a mitochondrial protein identification system based on multiple evidences 18 , 19 , MitoBreak, a curated dataset on mtDNA rearrangements 20 , HmtDB, an online resource for data on mitochondrial genome sequences annotated with population and variation data 21 , Mitochondrial Database (mitoDB), the mitochondrial database on clinical features seen in mitochondrial diseases 22 , to name a few. Analysis pipelines and platforms have also been developed, including the MtSNPscore which assesses the role of variation in context of disease association using a combined evidence approach 23 , Mit-o-matic, an analysis pipeline for clinical evaluation of mitochondrial variations from the NGS datasets 24 .…”