Abstract
Interest in human mitochondrial genetic data is constantly increasing among both clinicians and researchers, due to the involvement of mitochondrial DNA (mtDNA) in a number of physiological and pathological processes. Thanks to new sequencing technologies and modern databases, the large amount of information on mtDNA variability may be exploited to gain insights into the relationship between mtDNA variants, phenotypes and diseases. To facilitate this process, we have developed the HmtVar resource, a variant-focused database that allows the exploration of a dataset of over 40 000 human mitochondrial variants. Mitochondrial variation data, initially gathered from the HmtDB platform, are integrated with in-house pathogenicity assessments based on various evaluation criteria and with a set of additional annotations from third-party resources. The result is a comprehensive collection of information of crucial importance for human mitochondrial variation studies and investigation of common and rare diseases in which the mitochondrion may be involved. HmtVar is accessible at https://www.hmtvar.uniba.it and data may be retrieved using either a web interface through the Query page or a state-of-the-art API for programmatic access.
Highlights
The mitochondrion, traditionally defined as the powerhouse of the eukaryotic cell, plays a role in a number of biological processes, and shows extensive variation in proteomic composition and function, differentiated in tissues and cell types
HmtVar offers a wide range of information regarding human mitochondrial genome variants, representing one of the most comprehensive resources for mitochondrial genomic variation studies
The broad set of mitochondrial DNA (mtDNA) data hosted on several different online sources was exploited to build a unique aggregated database to fulfill the clinician’s needs when looking for pathogenicity information on mitochondrial variants
Summary
The mitochondrion, traditionally defined as the powerhouse of the eukaryotic cell, plays a role in a number of biological processes, and shows extensive variation in proteomic composition and function, differentiated in tissues and cell types. By virtue of such pivotal involvement, its dysfunction causes or contributes to human pathologies, such as neurodegenerative diseases, diabetes, cancer and metabolic syndromes. Recent advances in high-throughput sequencing techniques have provided an unprecedented amount of genetic data capable of offering invaluable insights into different life science questions This becomes even more significant in the light of the high number of sequences and related metadata available in public databases. Most of these data regard genomic variability, which can be exploited to achieve a better understanding of the correlations between DNA variants, phenotypes and diseases
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