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MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases
Increasing numbers of diseases are associated with mitochondrial dysfunction. This is unsurprising given mitochondria have major roles in bioenergy generation, signalling, detoxification, apoptosis and biosynthesis. However, fundamental questions of mitochondrial biology remain, including: which nuc...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323904/ https://www.ncbi.nlm.nih.gov/pubmed/30398659 http://dx.doi.org/10.1093/nar/gky1072 |
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author | Smith, Anthony C Robinson, Alan J |
author_facet | Smith, Anthony C Robinson, Alan J |
author_sort | Smith, Anthony C |
collection | PubMed |
description | Increasing numbers of diseases are associated with mitochondrial dysfunction. This is unsurprising given mitochondria have major roles in bioenergy generation, signalling, detoxification, apoptosis and biosynthesis. However, fundamental questions of mitochondrial biology remain, including: which nuclear genes encode mitochondrial proteins; how their expression varies with tissue; and which are associated with disease. But experiments to catalogue the mitochondrial proteome are incomplete and sometimes contradictory. This arises because the mitochondrial proteome has tissue- and stage-specific variability, plus differences among experimental techniques and localization evidence types used. This leads to limitations in each technique’s coverage and inevitably conflicting results. To support identification of mitochondrial proteins, we developed MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk/), a database combining evidence of mitochondrial localization with information from public resources. Here we report upgrades to MitoMiner, including its re-engineering to be gene-centric to enable easier sharing of evidence among orthologues and support next generation sequencing, plus new data sources, including expression in different tissues, information on phenotypes and diseases of genetic mutations and a new mitochondrial proteome catalogue. MitoMiner is a powerful platform to investigate mitochondrial localization by providing a unique combination of experimental sub-cellular localization datasets, tissue expression, predictions of mitochondrial targeting sequences, gene annotation and links to phenotype and disease. |
format | Online Article Text |
id | pubmed-6323904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63239042019-01-10 MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases Smith, Anthony C Robinson, Alan J Nucleic Acids Res Database Issue Increasing numbers of diseases are associated with mitochondrial dysfunction. This is unsurprising given mitochondria have major roles in bioenergy generation, signalling, detoxification, apoptosis and biosynthesis. However, fundamental questions of mitochondrial biology remain, including: which nuclear genes encode mitochondrial proteins; how their expression varies with tissue; and which are associated with disease. But experiments to catalogue the mitochondrial proteome are incomplete and sometimes contradictory. This arises because the mitochondrial proteome has tissue- and stage-specific variability, plus differences among experimental techniques and localization evidence types used. This leads to limitations in each technique’s coverage and inevitably conflicting results. To support identification of mitochondrial proteins, we developed MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk/), a database combining evidence of mitochondrial localization with information from public resources. Here we report upgrades to MitoMiner, including its re-engineering to be gene-centric to enable easier sharing of evidence among orthologues and support next generation sequencing, plus new data sources, including expression in different tissues, information on phenotypes and diseases of genetic mutations and a new mitochondrial proteome catalogue. MitoMiner is a powerful platform to investigate mitochondrial localization by providing a unique combination of experimental sub-cellular localization datasets, tissue expression, predictions of mitochondrial targeting sequences, gene annotation and links to phenotype and disease. Oxford University Press 2019-01-08 2018-11-06 /pmc/articles/PMC6323904/ /pubmed/30398659 http://dx.doi.org/10.1093/nar/gky1072 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Smith, Anthony C Robinson, Alan J MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
title | MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
title_full | MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
title_fullStr | MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
title_full_unstemmed | MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
title_short | MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
title_sort | mitominer v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323904/ https://www.ncbi.nlm.nih.gov/pubmed/30398659 http://dx.doi.org/10.1093/nar/gky1072 |
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