
MitoAge: a database for comparative analysis of mitochondrial DNA, with a special focus on animal longevity
2016

Dmitri Toren 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

Thomer Barzilay 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

Robi Tacutu 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

Gilad Lehmann 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

The Rappaport Faculty of Medicine and Research Institute
Tumor and Vascular Biology Research Center
Technion -Israel Institute of Technology
HaifaIsrael

Khachik K Muradian 
Institute of Gerontology
Life Span Prolongation Group
KievUkraine

Vadim E Fraifeld 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

MitoAge: a database for comparative analysis of mitochondrial DNA, with a special focus on animal longevity

Nucleic Acids Research
44201610.1093/nar/gkv1187Received August 20, 2015; Revised October 21, 2015; Accepted October 23, 2015
Mitochondria are the only organelles in the animal cells that have their own genome. Due to a key role in energy production, generation of damaging factors (ROS, heat), and apoptosis, mitochondria and mtDNA in particular have long been considered one of the major players in the mechanisms of aging, longevity and age-related diseases. The rapidly increasing number of species with fully sequenced mtDNA, together with accumulated data on longevity records, provides a new fascinating basis for comparative analysis of the links between mtDNA features and animal longevity. To facilitate such analyses and to support the scientific community in carrying these out, we developed the MitoAge database containing calculated mtDNA compositional features of the entire mitochondrial genome, mtDNA coding (tRNA, rRNA, protein-coding genes) and non-coding (D-loop) regions, and codon usage/amino acids frequency for each protein-coding gene. MitoAge includes 922 species with fully sequenced mtDNA and maximum lifespan records. The database is available through the MitoAge website (www.mitoage.org or www.mitoage.info), which provides the necessary tools for searching, browsing, comparing and downloading the data sets of interest for selected taxonomic groups across the Kingdom Animalia. The Mi-toAge website assists in statistical analysis of different features of the mtDNA and their correlative links to longevity.

INTRODUCTION

Mitochondria are the only organelles in the animal cells that have their own genome. The stability of the mitochondrial DNA (mtDNA) is vital for mitochondrial proper functioning; therefore, changes in mtDNA may have far-reaching consequences for the cell fate and, ultimately, for the whole organism. Not surprisingly, due to a key role in energy production, generation of damaging factors (ROS, heat), and regulation of apoptosis, mitochondria and mtDNA in particular have long been considered one of the major players in the mechanisms of aging, longevity and age-related diseases (1)(2)(3)(4)(5)(6).

Mitochondrial DNA exists in multiple copies and typically contains genes encoding for 13 key subunits of the respiratory chain enzymes, a set of 22 tRNA genes, and 2 genes for the large (16S) and small (12S) rRNA subunits. In contrast to the nuclear DNA, mtDNA is a circular, intronless, extremely compact molecule, with asymmetric distribution of nucleotides between the heavy (G-rich) and light (C-rich) strands (7,8). With very few exceptions, such structure of mtDNA is typical for the vast majority of animal species. Longevity (generally estimated by maximum lifespan, MLS) varies greatly among animal species (9) (genomics.senescence.info/species). Species also differ in their mtDNA compositional features (10), which to a great extent may determine the mtDNA stability and mutability. A few lines of evidence point towards a putative significance of mtDNA in aging and longevity. Firstly, mtDNA mutations accumulate with advanced age (5,11,12). Secondly, strong correlative links between mammalian MLS and mtDNA compositional features have been found (4,6,(13)(14)(15)(16)(17)(18).

The rapidly increasing number of species with fully sequenced mtDNA genomes, together with accumulated data on longevity records, provide now a strong basis for * To whom correspondence should be addressed. Tel: +972 8 6477292; Fax: +972 8 6477626; Email: vadim.fraifeld@gmail.com † These authors contributed equally to the paper as first authors. comprehensive comparative analysis of the links between mtDNA features and animal longevity. Yet, efficient processing of such amount of data is computationally demanding. In turn, this generates a need for appropriate databases and bioinformatics tools. With the creation of MitoAge, we aim to encourage the modeling of mtDNA-longevity relationships, providing the scientific community with one single place to access, compare and analyze the data, based on most updated resources. MitoAge (www.mitoage.org, www.mitoage.info) is a curated, publicly available database, which contains an extensive repository of mtDNA data integrated with longevity records and the results of the statistical and correlative analysis of the links between them.


DATABASE CONTENT AND INTERFACE

To date, 5337 entries with complete mitochondrial genomes and 4237 entries with longevity records are available at NCBI RefSeq database and the AnAge database, respectively (see the Data Sources section). The overlap of these two data sets after curation, encompassing 922 animal species covering 304 families, 106 orders and 13 classes from the Kingdom Animalia, was included in MitoAge, Build 1.0. As seen in Table 1, the vast majority of species are vertebrates, with only few representatives of invertebrates.

MitoAge contains compositional features (base content, GC%, AT%, sequence length) of the entire mitochondrial genome, mtDNA coding (tRNA, rRNA, protein-coding genes) and non-coding (D-loop) regions for each species and taxonomic group. For protein-coding genes of a given species, codon usage with distribution of codons by base position (e.g. codons with first base G, C, A or T) and amino acids frequencies are included. Along with mtDNA data, longevity records (MLS) are presented.

Additionally, the MitoAge database tools provide the user with a number of options for (i) computation of basic statistics (range, median, mean ± standard deviation, coefficient of variation, Pearson's coefficient of correlation with log-transformed MLS); (ii) comparison of stats between selected taxonomic groups (two or more); (iii) data export for a data set of interest (in a CSV format), without downloading the entire database. If a user needs a more complex analysis, the website allows downloading the entire database, which can be done from the Download page in versioned releases (numbered database builds).

MitoAge has a user-friendly website interface with simple and intuitive navigation tools (Figures 1 and 2). Searching can be done either by species common or scientific name, or by taxonomy groups (i.e. by classes, orders or families). Alternatively, the data can be reached by Browsing in three different ways: (i) Browsing Taxonomy (classes, orders, families or species); (ii) Browsing Stats, which calculates on-thefly statistical information for the total mtDNA or specific genes/regions for the selected taxonomic group; (iii) Brows-  ing Genes, an option similar to that of browsing stats, but providing data restricted to a gene of interest.


DATA SOURCES AND DATA CURATION

The MitoAge database was constructed using publicly available data, is being constantly updated through automatic tools and is manually curated for problematic issues. Complete mtDNA sequences were taken from NCBI RefSeq database (www.ncbi.nlm.nih.gov/refseq) (19); longevity records were retrieved from the HAGR: Human Ageing Genomic Resources--AnAge database (genomics.senescence.info/species) (9), and full taxonomy data were retrieved from the Integrated Taxonomic Information System (ITIS) on-line database [31-Jul-2015 Build] (www.itis.gov).

Most of the data included in the MitoAge database were computed offline, using a series of automated scripts and programs developed in our lab, with a number of parameters computed on-the-fly through the website. Together with a series of administration tools, this ensures frequent updates of the database.

Data were computed and analyzed as follows: (i) base composition and size were generated for total mtDNA and its specific regions/genes (D-loop, protein-coding genes, rRNA-coding genes and tRNA-coding genes); (ii) for each protein-coding gene and for the total protein-coding sequence, both base composition and codon usage/amino acids frequency were computed.

All data available at MitoAge have undergone a threestep validation: (i) the collected raw data from NCBI Ref-Seq was processed through our software and log files were generated; (ii) reports of errors and inconsistencies from log files were then manually curated; and finally (iii) additional tests for database consistency (e.g. duplicates, faulty values, etc.) were performed by the administrative tools in the MitoAge website. The list of errors and inconsistencies found in the mtDNA sequence annotations were reported to the NCBI admin and subsequently corrected by the NCBI team. Upon successful validation, the corrected data were uploaded into the MitoAge database and various statistical metrics were computed.


DATA CALCULATION

The compositional features of the mtDNA heavy strand (H-strand) were mostly considered (unless indicated otherwise), since the H-strand represents a primary target for the directional mutation pressure (20). For computing codon usage, data were taken from the complement of the coding strand and Thymine (T) was replaced with Uracil (U) (i.e. transforming it into the mRNA sequence). When combining multiple genes (e.g. when computing the total proteincoding genes), we append one gene to another and use the entire sequence for the analysis. In case of overlap between genes, we count the overlapping sequences only once for the computation of base composition, and we count them twice for the computation of codon usage and amino acids frequencies for each gene. Sequences are always analyzed from 5 to 3 (both for DNA and RNA).


AVAILABILITY

The MitoAge database is available at www.mitoage.org and www.mitoage.info, with the data made available under the permissive Creative Commons license, allowing data to be used in other analyses. There are options to either download the entire database or its parts, or to export specific results of the website. Feedback via email is welcome.


CONCLUSION

The MitoAge database is an integrated web resource for comparative analysis of mtDNA, with a special focus on animal longevity. Thus, it fills the gap in one of the 'hot spots' at the crossroad of aging research, evolutionary and mitochondrial biology. MitoAge novelties, together with a userfriendly interface, provide unique capabilities for in-depth investigation of: (i) the abundance of mtDNA bases and its variability across animal taxa with different MLS; (ii) the links between longevity and the mtDNA compositional features (total, region or gene-specific), including codon usage and amino acids frequency. Using the MitoAge database, we revealed more than 3780 statistically significant correlations between mtDNA features and animal longevity in different taxonomic groups. MitoAge could be also a useful supporting tool for building predictive models of animal longevity, involving mtDNA features. 

CFigure 1 .
1The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Nucleic Acids Research, 2016, Vol. 44, Database issue D1263 A labeled diagram of the MitoAge interface.

Figure 2 .
2Example: viewing data for Arctica islandica.

FUNDING
Fund in Memory of Dr Amir Abramovich. Funding for open access charge: Ben-Gurion University of the Negev [to V.E.F.]. Conflict of interest statement. None declared.

Table 1 .
1Number of species per taxon in MitoAgeTaxa (scientific name) 


A mitochondrial paradigm of metabolic and degenerative diseases, aging, and cancer: a dawn for evolutionary medicine. D C Wallace, Annu. Rev. Genet. 39Wallace,D.C. (2005) A mitochondrial paradigm of metabolic and degenerative diseases, aging, and cancer: a dawn for evolutionary medicine. Annu. Rev. Genet., 39, 359-407.

The hallmarks of aging. C Lopez-Otin, M A Blasco, L Partridge, M Serrano, G Kroemer, Cell. 153Lopez-Otin,C., Blasco,M.A., Partridge,L., Serrano,M. and Kroemer,G. (2013) The hallmarks of aging. Cell, 153, 1194-1217.

Mitochondria sentencing about cellular life and death: a matter of oxidative stress. N Apostolova, A Blas-Garcia, J V Esplugues, Curr. Pharm. Des. 17Apostolova,N., Blas-Garcia,A. and Esplugues,J.V. (2011) Mitochondria sentencing about cellular life and death: a matter of oxidative stress. Curr. Pharm. Des., 17, 4047-4060.

Do mitochondrial DNA and metabolic rate complement each other in determination of the mammalian maximum longevity?. G Lehmann, E Segal, K K Muradian, V E Fraifeld, Rejuvenation Res. 11Lehmann,G., Segal,E., Muradian,K.K. and Fraifeld,V.E. (2008) Do mitochondrial DNA and metabolic rate complement each other in determination of the mammalian maximum longevity? Rejuvenation Res., 11, 409-417.

) mtDNA mutations in human aging and longevity: controversies and new perspectives opened by high-throughput technologies. F Sevini, C Giuliani, D Vianello, E Giampieri, A Santoro, F Biondi, P Garagnani, G Passarino, D Luiselli, M Capri, Exp. Gerontol. 56Sevini,F., Giuliani,C., Vianello,D., Giampieri,E., Santoro,A., Biondi,F., Garagnani,P., Passarino,G., Luiselli,D., Capri,M. et al. (2014) mtDNA mutations in human aging and longevity: controversies and new perspectives opened by high-throughput technologies. Exp. Gerontol., 56, 234-244.

Mitochondrial DNA mutations in aging. K Khrapko, D Turnbull, Prog. Mol. Biol. Transl. Sci. 127Khrapko,K. and Turnbull,D. (2014) Mitochondrial DNA mutations in aging. Prog. Mol. Biol. Transl. Sci., 127, 29-62.

Transcription and replication of mitochondrial DNA. D A Clayton, Hum. Reprod. 15Suppl. 2Clayton,D.A. (2000) Transcription and replication of mitochondrial DNA. Hum. Reprod., 15(Suppl. 2), 11-17.

Replication and transcription of mammalian mitochondrial DNA. P Fernandez-Silva, J A Enriquez, J Montoya, Exp. Physiol. 88Fernandez-Silva,P., Enriquez,J.A. and Montoya,J. (2003) Replication and transcription of mammalian mitochondrial DNA. Exp. Physiol., 88, 41-56.

Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing. R Tacutu, T Craig, A Budovsky, D Wuttke, G Lehmann, D Taranukha, J Costa, V E Fraifeld, De Magalhaes, Nucleic Acids Res. 41J.P.Tacutu,R., Craig,T., Budovsky,A., Wuttke,D., Lehmann,G., Taranukha,D., Costa,J., Fraifeld,V.E. and de Magalhaes,J.P. (2013) Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing. Nucleic Acids Res., 41, D1027-D1033.

Mitochondrial DNA in metazoa: degree of freedom in a frozen event. C Saccone, C Gissi, A Reyes, A Larizza, E Sbisa, G Pesole, Gene. 286Saccone,C., Gissi,C., Reyes,A., Larizza,A., Sbisa,E. and Pesole,G. (2002) Mitochondrial DNA in metazoa: degree of freedom in a frozen event. Gene, 286, 3-12.

Reconsidering the Role of Mitochondria in Aging. M Gonzalez-Freire, R De Cabo, M Bernier, S J Sollott, E Fabbri, P Navas, L Ferrucci, J. Gerontol. A Biol. Sci. Med. Sci. 70Gonzalez-Freire,M., de Cabo,R., Bernier,M., Sollott,S.J., Fabbri,E., Navas,P. and Ferrucci,L. (2015) Reconsidering the Role of Mitochondria in Aging. J. Gerontol. A Biol. Sci. Med. Sci., 70, 1334-1342.

Do mtDNA deletions drive premature aging in mtDNA mutator mice?. Y Kraytsberg, D K Simon, D M Turnbull, K Khrapko, Aging Cell. 8Kraytsberg,Y., Simon,D.K., Turnbull,D.M. and Khrapko,K. (2009) Do mtDNA deletions drive premature aging in mtDNA mutator mice? Aging Cell, 8, 502-506.

Telomere length and body temperature-independent determinants of mammalian longevity?. G Lehmann, K K Muradian, V E Fraifeld, Front. Genet. 4111Lehmann,G., Muradian,K.K. and Fraifeld,V.E. (2013) Telomere length and body temperature-independent determinants of mammalian longevity? Front. Genet., 4, 111.

Life span is related to the free energy of mitochondrial DNA. D C Samuels, Mech. Ageing Dev. 126Samuels,D.C. (2005) Life span is related to the free energy of mitochondrial DNA. Mech. Ageing Dev., 126, 1123-1129.

Mitochondrial DNA repeats constrain the life span of mammals. D C Samuels, Trends Genet. 20Samuels,D.C. (2004) Mitochondrial DNA repeats constrain the life span of mammals. Trends Genet., 20, 226-229.

Inverse relationship between longevity and evolutionary rate of mitochondrial proteins in mammals and birds. N Galtier, P U Blier, B Nabholz, Mitochondrion. 9Galtier,N., Blier,P.U. and Nabholz,B. (2009) Inverse relationship between longevity and evolutionary rate of mitochondrial proteins in mammals and birds. Mitochondrion, 9, 51-57.

Mitochondrial genome anatomy and species-specific lifespan. G Lehmann, A Budovsky, K K Muradian, V E Fraifeld, Rejuvenation Res. 9Lehmann,G., Budovsky,A., Muradian,K.K. and Fraifeld,V.E. (2006) Mitochondrial genome anatomy and species-specific lifespan. Rejuvenation Res., 9, 223-226.

Mitochondrial inverted repeats strongly correlate with lifespan: mtDNA inversions and aging. J N Yang, A Seluanov, V Gorbunova, PLoS One. 873318Yang,J.N., Seluanov,A. and Gorbunova,V. (2013) Mitochondrial inverted repeats strongly correlate with lifespan: mtDNA inversions and aging. PLoS One, 8, e73318.

Update on RefSeq microbial genomes resources. T Tatusova, S Ciufo, S Federhen, B Fedorov, R Mcveigh, K O&apos;neill, I Tolstoy, L Zaslavsky, Nucleic Acids Res. 43Tatusova,T., Ciufo,S., Federhen,S., Fedorov,B., McVeigh,R., O'Neill,K., Tolstoy,I. and Zaslavsky,L. (2015) Update on RefSeq microbial genomes resources. Nucleic Acids Res., 43, D599-D605.

Asymmetrical directional mutation pressure in the mitochondrial genome of mammals. A Reyes, C Gissi, G Pesole, C Saccone, Mol. Biol. Evol. 15Reyes,A., Gissi,C., Pesole,G. and Saccone,C. (1998) Asymmetrical directional mutation pressure in the mitochondrial genome of mammals. Mol. Biol. Evol., 15, 957-966.

Mitochondria are the only organelles in the animal cells that have their own genome. Due to a key role in energy production, generation of damaging factors (ROS, heat), and apoptosis, mitochondria and mtDNA in particular have long been considered one of the major players in the mechanisms of aging, longevity and age-related diseases. The rapidly increasing number of species with fully sequenced mtDNA, together with accumulated data on longevity records, provides a new fascinating basis for comparative analysis of the links between mtDNA features and animal longevity. To facilitate such analyses and to support the scientific community in carrying these out, we developed the MitoAge database containing calculated mtDNA compositional features of the entire mitochondrial genome, mtDNA coding (tRNA, rRNA, protein-coding genes) and non-coding (D-loop) regions, and codon usage/amino acids frequency for each protein-coding gene. MitoAge includes 922 species with fully sequenced mtDNA and maximum lifespan records. The database is available through the MitoAge website (www.mitoage.org or www.mitoage.info), which provides the necessary tools for searching, browsing, comparing and downloading the data sets of interest for selected taxonomic groups across the Kingdom Animalia. The Mi-toAge website assists in statistical analysis of different features of the mtDNA and their correlative links to longevity.
Dmitri Toren 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael
 Thomer Barzilay 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael
 Robi Tacutu 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael
 Gilad Lehmann 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

The Rappaport Faculty of Medicine and Research Institute
Tumor and Vascular Biology Research Center
Technion -Israel Institute of Technology
HaifaIsrael
 Khachik K Muradian 
Institute of Gerontology
Life Span Prolongation Group
KievUkraine
 Vadim E Fraifeld 
The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael

The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael The Rappaport Faculty of Medicine and Research Institute
Tumor and Vascular Biology Research Center
Technion -Israel Institute of Technology
HaifaIsrael Institute of Gerontology
Life Span Prolongation Group
KievUkraine The Shraga Segal Department of Microbiology, Immunology and Genetics
Center for Multidisciplinary Research on Aging
Ben-Gurion University of the Negev
Beer-ShevaIsrael
D C Wallace,  C Lopez-Otin,  M A Blasco,  L Partridge,  M Serrano,  G Kroemer,  N Apostolova,  A Blas-Garcia,  J V Esplugues,  G Lehmann,  E Segal,  K K Muradian,  V E Fraifeld,  F Sevini,  C Giuliani,  D Vianello,  E Giampieri,  A Santoro,  F Biondi,  P Garagnani,  G Passarino,  D Luiselli,  M Capri,  K Khrapko,  D Turnbull,  D A Clayton,  P Fernandez-Silva,  J A Enriquez,  J Montoya,  R Tacutu,  T Craig,  A Budovsky,  D Wuttke,  G Lehmann,  D Taranukha,  J Costa,  V E Fraifeld,  De Magalhaes,  C Saccone,  C Gissi,  A Reyes,  A Larizza,  E Sbisa,  G Pesole,  M Gonzalez-Freire,  R De Cabo,  M Bernier,  S J Sollott,  E Fabbri,  P Navas,  L Ferrucci,  Y Kraytsberg,  D K Simon,  D M Turnbull,  K Khrapko,  G Lehmann,  K K Muradian,  V E Fraifeld,  D C Samuels,  D C Samuels,  N Galtier,  P U Blier,  B Nabholz,  G Lehmann,  A Budovsky,  K K Muradian,  V E Fraifeld,  J N Yang,  A Seluanov,  V Gorbunova,  T Tatusova,  S Ciufo,  S Federhen,  B Fedorov,  R Mcveigh,  K O&apos;neill,  I Tolstoy,  L Zaslavsky,  A Reyes,  C Gissi,  G Pesole,  C Saccone, 
D C C M A L M G N A J V G E K K V E F C D E A F P G D M K D D A P J A J R T A D G D J V E C C A A E G M R M S J E P L Y D K D M K G K K V E D C D C N P U B G A K K V E J N A V T S S B R K I L A C G C
Wallace Lopez-Otin Blasco Partridge Serrano Kroemer Apostolova Blas-Garcia Esplugues Lehmann Segal Muradian Fraifeld Sevini Giuliani Vianello Giampieri Santoro Biondi Garagnani Passarino Luiselli Capri Khrapko Turnbull Clayton Fernandez-Silva Enriquez Montoya Tacutu Craig Budovsky Wuttke Lehmann Taranukha Costa Fraifeld De Magalhaes Saccone Gissi Reyes Larizza Sbisa Pesole Gonzalez-Freire De Cabo Bernier Sollott Fabbri Navas Ferrucci Kraytsberg Simon Turnbull Khrapko Lehmann Muradian Fraifeld Samuels Samuels Galtier Blier Nabholz Lehmann Budovsky Muradian Fraifeld Yang Seluanov Gorbunova Tatusova Ciufo Federhen Fedorov Mcveigh O&apos;neill Tolstoy Zaslavsky Reyes Gissi Pesole Saccone
A mitochondrial paradigm of metabolic and degenerative diseases, aging, and cancer: a dawn for evolutionary medicine. D C Wallace, Annu. Rev. Genet. 39Wallace,D.C. (2005) A mitochondrial paradigm of metabolic and degenerative diseases, aging, and cancer: a dawn for evolutionary medicine. Annu. Rev. Genet., 39, 359-407. The hallmarks of aging. C Lopez-Otin, M A Blasco, L Partridge, M Serrano, G Kroemer, Cell. 153Lopez-Otin,C., Blasco,M.A., Partridge,L., Serrano,M. and Kroemer,G. (2013) The hallmarks of aging. Cell, 153, 1194-1217. Mitochondria sentencing about cellular life and death: a matter of oxidative stress. N Apostolova, A Blas-Garcia, J V Esplugues, Curr. Pharm. Des. 17Apostolova,N., Blas-Garcia,A. and Esplugues,J.V. (2011) Mitochondria sentencing about cellular life and death: a matter of oxidative stress. Curr. Pharm. Des., 17, 4047-4060. Do mitochondrial DNA and metabolic rate complement each other in determination of the mammalian maximum longevity?. G Lehmann, E Segal, K K Muradian, V E Fraifeld, Rejuvenation Res. 11Lehmann,G., Segal,E., Muradian,K.K. and Fraifeld,V.E. (2008) Do mitochondrial DNA and metabolic rate complement each other in determination of the mammalian maximum longevity? Rejuvenation Res., 11, 409-417. ) mtDNA mutations in human aging and longevity: controversies and new perspectives opened by high-throughput technologies. F Sevini, C Giuliani, D Vianello, E Giampieri, A Santoro, F Biondi, P Garagnani, G Passarino, D Luiselli, M Capri, Exp. Gerontol. 56Sevini,F., Giuliani,C., Vianello,D., Giampieri,E., Santoro,A., Biondi,F., Garagnani,P., Passarino,G., Luiselli,D., Capri,M. et al. (2014) mtDNA mutations in human aging and longevity: controversies and new perspectives opened by high-throughput technologies. Exp. Gerontol., 56, 234-244. Mitochondrial DNA mutations in aging. K Khrapko, D Turnbull, Prog. Mol. Biol. Transl. Sci. 127Khrapko,K. and Turnbull,D. (2014) Mitochondrial DNA mutations in aging. Prog. Mol. Biol. Transl. Sci., 127, 29-62. Transcription and replication of mitochondrial DNA. D A Clayton, Hum. Reprod. 15Suppl. 2Clayton,D.A. (2000) Transcription and replication of mitochondrial DNA. Hum. Reprod., 15(Suppl. 2), 11-17. Replication and transcription of mammalian mitochondrial DNA. P Fernandez-Silva, J A Enriquez, J Montoya, Exp. Physiol. 88Fernandez-Silva,P., Enriquez,J.A. and Montoya,J. (2003) Replication and transcription of mammalian mitochondrial DNA. Exp. Physiol., 88, 41-56. Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing. R Tacutu, T Craig, A Budovsky, D Wuttke, G Lehmann, D Taranukha, J Costa, V E Fraifeld, De Magalhaes, Nucleic Acids Res. 41J.P.Tacutu,R., Craig,T., Budovsky,A., Wuttke,D., Lehmann,G., Taranukha,D., Costa,J., Fraifeld,V.E. and de Magalhaes,J.P. (2013) Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing. Nucleic Acids Res., 41, D1027-D1033. Mitochondrial DNA in metazoa: degree of freedom in a frozen event. C Saccone, C Gissi, A Reyes, A Larizza, E Sbisa, G Pesole, Gene. 286Saccone,C., Gissi,C., Reyes,A., Larizza,A., Sbisa,E. and Pesole,G. (2002) Mitochondrial DNA in metazoa: degree of freedom in a frozen event. Gene, 286, 3-12. Reconsidering the Role of Mitochondria in Aging. M Gonzalez-Freire, R De Cabo, M Bernier, S J Sollott, E Fabbri, P Navas, L Ferrucci, J. Gerontol. A Biol. Sci. Med. Sci. 70Gonzalez-Freire,M., de Cabo,R., Bernier,M., Sollott,S.J., Fabbri,E., Navas,P. and Ferrucci,L. (2015) Reconsidering the Role of Mitochondria in Aging. J. Gerontol. A Biol. Sci. Med. Sci., 70, 1334-1342. Do mtDNA deletions drive premature aging in mtDNA mutator mice?. Y Kraytsberg, D K Simon, D M Turnbull, K Khrapko, Aging Cell. 8Kraytsberg,Y., Simon,D.K., Turnbull,D.M. and Khrapko,K. (2009) Do mtDNA deletions drive premature aging in mtDNA mutator mice? Aging Cell, 8, 502-506. Telomere length and body temperature-independent determinants of mammalian longevity?. G Lehmann, K K Muradian, V E Fraifeld, Front. Genet. 4111Lehmann,G., Muradian,K.K. and Fraifeld,V.E. (2013) Telomere length and body temperature-independent determinants of mammalian longevity? Front. Genet., 4, 111. Life span is related to the free energy of mitochondrial DNA. D C Samuels, Mech. Ageing Dev. 126Samuels,D.C. (2005) Life span is related to the free energy of mitochondrial DNA. Mech. Ageing Dev., 126, 1123-1129. Mitochondrial DNA repeats constrain the life span of mammals. D C Samuels, Trends Genet. 20Samuels,D.C. (2004) Mitochondrial DNA repeats constrain the life span of mammals. Trends Genet., 20, 226-229. Inverse relationship between longevity and evolutionary rate of mitochondrial proteins in mammals and birds. N Galtier, P U Blier, B Nabholz, Mitochondrion. 9Galtier,N., Blier,P.U. and Nabholz,B. 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CFigure 1 .
1The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Nucleic Acids Research, 2016, Vol. 44, Database issue D1263 A labeled diagram of the MitoAge interface. 
Figure 2 .
2Example: viewing data for Arctica islandica. 
FUNDING
Fund in Memory of Dr Amir Abramovich. Funding for open access charge: Ben-Gurion University of the Negev [to V.E.F.]. Conflict of interest statement. None declared. 
Table 1 .
1Number of species per taxon in MitoAgeTaxa (scientific name) 

The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Nucleic Acids Research, 2016, Vol. 44, Database issue D1263 A labeled diagram of the MitoAge interface. Example: viewing data for Arctica islandica. Fund in Memory of Dr Amir Abramovich. Funding for open access charge: Ben-Gurion University of the Negev [to V.E.F.]. Conflict of interest statement. None declared. Number of species per taxon in MitoAge
Mitochondria are the only organelles in the animal cells that have their own genome. The stability of the mitochondrial DNA (mtDNA) is vital for mitochondrial proper functioning; therefore, changes in mtDNA may have far-reaching consequences for the cell fate and, ultimately, for the whole organism. Not surprisingly, due to a key role in energy production, generation of damaging factors (ROS, heat), and regulation of apoptosis, mitochondria and mtDNA in particular have long been considered one of the major players in the mechanisms of aging, longevity and age-related diseases (1)(2)(3)(4)(5)(6). Mitochondrial DNA exists in multiple copies and typically contains genes encoding for 13 key subunits of the respiratory chain enzymes, a set of 22 tRNA genes, and 2 genes for the large (16S) and small (12S) rRNA subunits. In contrast to the nuclear DNA, mtDNA is a circular, intronless, extremely compact molecule, with asymmetric distribution of nucleotides between the heavy (G-rich) and light (C-rich) strands (7,8). With very few exceptions, such structure of mtDNA is typical for the vast majority of animal species. Longevity (generally estimated by maximum lifespan, MLS) varies greatly among animal species (9) (genomics.senescence.info/species). Species also differ in their mtDNA compositional features (10), which to a great extent may determine the mtDNA stability and mutability. A few lines of evidence point towards a putative significance of mtDNA in aging and longevity. Firstly, mtDNA mutations accumulate with advanced age (5,11,12). Secondly, strong correlative links between mammalian MLS and mtDNA compositional features have been found (4,6,(13)(14)(15)(16)(17)(18). The rapidly increasing number of species with fully sequenced mtDNA genomes, together with accumulated data on longevity records, provide now a strong basis for * To whom correspondence should be addressed. Tel: +972 8 6477292; Fax: +972 8 6477626; Email: vadim.fraifeld@gmail.com † These authors contributed equally to the paper as first authors. comprehensive comparative analysis of the links between mtDNA features and animal longevity. Yet, efficient processing of such amount of data is computationally demanding. In turn, this generates a need for appropriate databases and bioinformatics tools. With the creation of MitoAge, we aim to encourage the modeling of mtDNA-longevity relationships, providing the scientific community with one single place to access, compare and analyze the data, based on most updated resources. MitoAge (www.mitoage.org, www.mitoage.info) is a curated, publicly available database, which contains an extensive repository of mtDNA data integrated with longevity records and the results of the statistical and correlative analysis of the links between them. To date, 5337 entries with complete mitochondrial genomes and 4237 entries with longevity records are available at NCBI RefSeq database and the AnAge database, respectively (see the Data Sources section). The overlap of these two data sets after curation, encompassing 922 animal species covering 304 families, 106 orders and 13 classes from the Kingdom Animalia, was included in MitoAge, Build 1.0. As seen in Table 1, the vast majority of species are vertebrates, with only few representatives of invertebrates. MitoAge contains compositional features (base content, GC%, AT%, sequence length) of the entire mitochondrial genome, mtDNA coding (tRNA, rRNA, protein-coding genes) and non-coding (D-loop) regions for each species and taxonomic group. For protein-coding genes of a given species, codon usage with distribution of codons by base position (e.g. codons with first base G, C, A or T) and amino acids frequencies are included. Along with mtDNA data, longevity records (MLS) are presented. Additionally, the MitoAge database tools provide the user with a number of options for (i) computation of basic statistics (range, median, mean ± standard deviation, coefficient of variation, Pearson's coefficient of correlation with log-transformed MLS); (ii) comparison of stats between selected taxonomic groups (two or more); (iii) data export for a data set of interest (in a CSV format), without downloading the entire database. If a user needs a more complex analysis, the website allows downloading the entire database, which can be done from the Download page in versioned releases (numbered database builds). MitoAge has a user-friendly website interface with simple and intuitive navigation tools (Figures 1 and 2). Searching can be done either by species common or scientific name, or by taxonomy groups (i.e. by classes, orders or families). Alternatively, the data can be reached by Browsing in three different ways: (i) Browsing Taxonomy (classes, orders, families or species); (ii) Browsing Stats, which calculates on-thefly statistical information for the total mtDNA or specific genes/regions for the selected taxonomic group; (iii) Brows-  ing Genes, an option similar to that of browsing stats, but providing data restricted to a gene of interest. The MitoAge database was constructed using publicly available data, is being constantly updated through automatic tools and is manually curated for problematic issues. Complete mtDNA sequences were taken from NCBI RefSeq database (www.ncbi.nlm.nih.gov/refseq) (19); longevity records were retrieved from the HAGR: Human Ageing Genomic Resources--AnAge database (genomics.senescence.info/species) (9), and full taxonomy data were retrieved from the Integrated Taxonomic Information System (ITIS) on-line database [31-Jul-2015 Build] (www.itis.gov). Most of the data included in the MitoAge database were computed offline, using a series of automated scripts and programs developed in our lab, with a number of parameters computed on-the-fly through the website. Together with a series of administration tools, this ensures frequent updates of the database. Data were computed and analyzed as follows: (i) base composition and size were generated for total mtDNA and its specific regions/genes (D-loop, protein-coding genes, rRNA-coding genes and tRNA-coding genes); (ii) for each protein-coding gene and for the total protein-coding sequence, both base composition and codon usage/amino acids frequency were computed. All data available at MitoAge have undergone a threestep validation: (i) the collected raw data from NCBI Ref-Seq was processed through our software and log files were generated; (ii) reports of errors and inconsistencies from log files were then manually curated; and finally (iii) additional tests for database consistency (e.g. duplicates, faulty values, etc.) were performed by the administrative tools in the MitoAge website. The list of errors and inconsistencies found in the mtDNA sequence annotations were reported to the NCBI admin and subsequently corrected by the NCBI team. Upon successful validation, the corrected data were uploaded into the MitoAge database and various statistical metrics were computed. The compositional features of the mtDNA heavy strand (H-strand) were mostly considered (unless indicated otherwise), since the H-strand represents a primary target for the directional mutation pressure (20). For computing codon usage, data were taken from the complement of the coding strand and Thymine (T) was replaced with Uracil (U) (i.e. transforming it into the mRNA sequence). When combining multiple genes (e.g. when computing the total proteincoding genes), we append one gene to another and use the entire sequence for the analysis. In case of overlap between genes, we count the overlapping sequences only once for the computation of base composition, and we count them twice for the computation of codon usage and amino acids frequencies for each gene. Sequences are always analyzed from 5 to 3 (both for DNA and RNA). The MitoAge database is available at www.mitoage.org and www.mitoage.info, with the data made available under the permissive Creative Commons license, allowing data to be used in other analyses. There are options to either download the entire database or its parts, or to export specific results of the website. Feedback via email is welcome. The MitoAge database is an integrated web resource for comparative analysis of mtDNA, with a special focus on animal longevity. Thus, it fills the gap in one of the 'hot spots' at the crossroad of aging research, evolutionary and mitochondrial biology. MitoAge novelties, together with a userfriendly interface, provide unique capabilities for in-depth investigation of: (i) the abundance of mtDNA bases and its variability across animal taxa with different MLS; (ii) the links between longevity and the mtDNA compositional features (total, region or gene-specific), including codon usage and amino acids frequency. Using the MitoAge database, we revealed more than 3780 statistically significant correlations between mtDNA features and animal longevity in different taxonomic groups. MitoAge could be also a useful supporting tool for building predictive models of animal longevity, involving mtDNA features. 
INTRODUCTION DATABASE CONTENT AND INTERFACE DATA SOURCES AND DATA CURATION DATA CALCULATION AVAILABILITY CONCLUSION CFigure 1 . Figure 2 . FUNDING Table 1 .
Taxa (scientific name) 
