Using the Human Ageing Genomic Resources
There are several tools and databases available at HAGR. The two key resources, however, are the GenAge and AnAge databases, the former divided into human genes and genes in model organisms. What follows is a succinct user manual for each of them followed by an overview of the other major features in HAGR.
GenAge: The Ageing Gene Database
GenAge has two main resources: a database of ageing- and longevity-associated genes identified in model organisms and a database of human ageing genes. Both databases are manually curated, but the human database is more detailed and contains substantially more data and information. It also features data-mining tools, as described below.
The dataset of genes associated with longevity or ageing in model organisms is essentially a list of genes with a single primary reference, a brief description of the phenotype or effects of genetic manipulations of the gene, human homologues of the gene, and a few external links. For a gene to be featured, its association with ageing and/or longevity must be unambigous, and hence most genes were selected based on genetic manipulations and not mere correlations such as a gene's upregulation with age in which causality is impossible to determine. This dataset of genes from model organisms may be useful as a reference and educational resource for researchers. It also serves as the primary resource for deriving the list of genes that may be associated with human ageing. Typically, the best genes from model organisms serve as basis for deriving the dataset of putative human ageing-related genes, as further described below.
The human dataset in GenAge is a curated database of genes that may regulate human ageing or that at least might be considerably associated with the human ageing phenotype. It is a functional genomics database designed to provide up-to-date information in the context of ageing. Because our focus is on the fundamental ageing process, what some authors call senescence, and not just age-related pathologies, the human dataset features primarily genes related to biological ageing rather than genes that only affect longevity by having an impact on overall health. This is an important point because longevity can be influenced by factors unrelated to ageing, and the distinction is crucial, albeit often difficult. (For those interested in genes associated with human longevity, a list of genes analyzed for their possible association with human longevity in also available). When using the human dataset, you should not expect to find genes solely associated with a given age-related pathology but rather genes that can regulate the ageing process as a whole or at least multiple aspects of the ageing phenotype. As mentioned above, genes in the human dataset are by and large selected based on findings in model organisms, and thus they must be classified as putative, not proven, cases of genes associated with human ageing. Below we explain how genes are selected for inclusion in the human dataset.
Each gene in the human dataset was selected after an extensive review of the literature. We identified genes associated with ageing in model organisms as well as those that may directly modulate ageing in mammals, including humans. Of course, genes related to ageing in model systems may or may not be related to human ageing, and so we reviewed the literature concerning human and mouse homologues of genes identified in lower organisms. Each gene was selected or excluded based on its association with ageing in the different model systems, with priority being given to organisms biologically and evolutionary more closely related to humans. Because our focus is on the genetic basis of human ageing, we do not provide an in-depth description of ageing in model systems but rather incorporate the information gathered from multiple models to gather clues about the genetics of human ageing.
We grouped genes associated with organismal ageing to obtain functional groups. These are groups of genes that share similar functions or are associated with similar pathways. Identifying the largest groups and those most strongly associated with ageing allowed us to select a number of other genes for inclusion in the human dataset due to their association with other genes or pathways previously linked to ageing. Information from several other databases was also evaluated and, in some cases, integrated into GenAge. Several genes only indirectly linked to ageing are featured as we prefer false positives to false negatives; while users can ignore entries they consider irrelevant, false negatives can impact on research conducted using GenAge.
In each human gene entry the main reason for inclusion in the database is given. The following criteria are used:
- Evidence directly linking the gene product to ageing in humans (human)
- Evidence directly linking the gene product to ageing in a mammalian model organism (mammal)
- Evidence directly linking the gene product to ageing in a non-mammalian model organism (model)
- Evidence directly linking the gene product to ageing in a cellular model system (cell)
- Evidence directly linking the gene product to the regulation or control of genes previously linked with ageing (upstream)
- Evidence linking the gene product to a pathway or mechanism linked with ageing (functional)
- Evidence showing the gene product to act downstream of a pathway, mechanism, or other gene product linked with ageing (downstream)
- Indirect or inconclusive evidence linking the gene product to ageing (putative)
Searching the human dataset can be done from its main page or from its query page. GenAge symbols follow the HUGO Gene Nomenclature Committee (HGNC), but genes' common names and frequently-used aliases can also be searched. For instance, searching for "ghbp" would retrieve the growth hormone receptor (GHR) because "GHBP" is a common alias of GHR. The search engine of GenAge is case-insensitive. At present wildcards are not accepted in the searches, except "*" as in "abc*" will match "abc", "abcd", "abcde", etc. Lastly, you can view the whole list of genes in one page.
Once you find an entry of interest, GenAge can be used as a reference database, particularly for human genes. A wealth of biological data is provided for each entry, including annotation in the context of gerontology. For example, in GHR's entry, apart from basic biological information, the potential link between GHR and ageing is described complete with bibliographical references: GHR gene products have been linked to ageing in mice, and this was the major reason for GHR's inclusion in the human dataset, but not in humans, even though mutations in the human gene have been described. Importantly, each entry in the human dataset represents not merely a summary of the bibliography but a manually curated summary which aims for accuracy and relevance in the context of ageing.
Of course, GenAge has its limits as our aim is to include the most relevant information, but not all the data available. If further, more detailed information is required then a selection of bibliographic references is available in each entry including hyperlinks to PubMed abstracts. Hyperlinks to top databases such as OMIM and SWISS-PROT are also included to help researchers quickly locate additional information within other or broader biological scopes.
Arguably, the human dataset offers an overall view of what is presently known about the genetics of human ageing. To investigate the human dataset as a whole the most adequate tool is its browser. Using the browser it is possible to, among other things, retrieve only those entries that pass certain criteria related to the selection process or annotation. You may choose different criteria by holding down the CTRL key. If you choose one sole criterion, the resulting list will be ordered accordingly. Users can select all or a sub-group of the genes retrieved using the check boxes on the left, which can then be further analysed using the simple statistical tools available in GenAge by pressing the analyse button at the end of the list of genes being displayed. Genes can also be analysed from the query page described above as the navigation system of GenAge makes it easy to quickly access different tools.
A few simple tools are available in gene analysis tools, and we recommend users experiment with the engine. For example, you may select to investigate whether a groups of entries has similar functions or you may retrieve homologues in mice for a group of pre-selected proteins. Hyperlinks to external databases and tools are also included. For more advanced analyzes, users are encourage to download the database and use it locally.
One particularly useful tool are protein-protein interactions. Protein-protein interactions can be visualized for each entry or they can be downloaded for use with more advanced biological pathway analysis software. Protein-protein interactions using one or more genes as query can also be visualized using the browser feature described above. While displaying protein-protein interactions, red means the gene was selected based on observations linking it to human ageing, blue indicates it was selected based on mammalian models, and green means the gene was identified in model organisms.
The human dataset in GenAge can be helpful in more classical genetic studies of ageing and longevity. For example, if a given chromosomal region is identified, it is now possible to look up which genes are present in that region.
Although GenAge is not a bibliographic database, the bibliographic references in the human dataset can be a useful resource. It is possible to search the bibliography using an engine similar to the query page described above. "Impact" represents the number of times a given reference is cited in the database. You may enter keywords appearing in the reference's title or its PubMed accession number. Authors' names are only included in references not present in PubMed.
Bibliographic data-mining is also possible. The system employs the simple principle of text co-occurrence with the assumption being that genes or proteins mentioned in the same academic work have higher chances of being related. Consequently, it is now possible to search through the bibliography of GenAge to find human genes referred to in the same work to generate putative functional links. To use this feature users are encouraged to select the human genes they wish to look up using the browser or query pages, and then set the threshold defining how many references in common two genes must have for them to be considered linked.
Linking to GenAge is straightforward. To create link to a human gene please use (preferred):
http://genomics.senescence.info/genes/entry.php?hugo=x
And replace x by the HGNC symbol. Or (deprecated):
http://genomics.senescence.info/genes/entry.php?id=XXXX
And replace XXXX by the appropriate HAGRID. Using HGNC, however, is preferable because HAGRID numbers are not static and may thus change in future releases.
For example, to link to TP53 please use (preferred):
http://genomics.senescence.info/genes/entry.php?hugo=tp53
Or (deprecated)
http://genomics.senescence.info/genes/entry.php?id=0006
To create link to a gene from a model organism please use (preferred):
http://genomics.senescence.info/genes/details.php?gene=x&organism=y
And replace x by the gene symbol and y by the organism's genus. Or (deprecated):
http://genomics.senescence.info/genes/details.php?id=x
And replace x by the appropriate ID. Using the gene symbol, however, is preferable because ID numbers are not static.
For example, to link to age-1 please use (preferred):
http://genomics.senescence.info/genes/details.php?gene=age-1&organism=elegans
Or (deprecated)
http://genomics.senescence.info/genes/details.php?id=7
AnAge is a database of longevity, ageing, and life history in extant species employing the same engine of GenAge. You can query AnAge as described above for GenAge. The only wildcard allowed is "*", and you can search the database by keywords that include the organism's common name or taxonomic classification. Given the larger number of entries in AnAge, you cannot view all entries in the same page.
The most important trait in AnAge is maximum longevity because it is the most widely used parameter for comparing rate of ageing between species. Maximum longevity is estimated from record longevity. Of course, many factors can bias longevity records, such as population size and whether animals are kept in captivity or not. Because we want maximum longevity to be a reliable term for comparisons between species, we try to minimize these problems. Briefly, we make a great effort to obtain the original source of each longevity record and verify its authenticity; anecdotes are not used to estimate maximum longevity, though they are mentioned in the observations section; and species for which maximum longevity is suspicious of being significantly underestimated have generally a maximum longevity classified as "not yet available". The criteria used to classify the maximum longevity of a given species as "not yet available" is more stringent for mammals than for other classes.
Entries in AnAge can be useful for researchers to learn more about the ageing process of a particular species. Species with unique ageing phenotypes or of special interest to gerontologists, such as species with negligible senescence and commonly used model organisms, are included. Apart from longevity, observations about physiological and pathological changes with age in animals are featured where available. Although demographic measurements of ageing are included in AnAge, these require detailed animal studies which are rarely available and thus represent only a small fraction of the data in AnAge. If possible, we determined the mortality rate doubling time (MRDT) for a given species using the Gompertz equation, as described elsewhere.
Typical values of major life history traits such as adult body size and age at sexual maturity are also featured in AnAge, at least for most mammals. Estimates of metabolic rates, such as resting or basal metabolic rate, are also featured for some species. Nonetheless, while we try to consult the original source regarding longevity records (as described above), for other life history traits and metabolic rates we usually rely on reviews and large-scale datasets. We do try to minimize errors, however, and observed discrepancies (e.g., between male and female ages at sexual maturity or between inter-litter interval and litters per year) reflect inconsistencies in these large-scale data sources.
For mammals, also included is the maximum longevity (tmax) residual, expressed as a percentage of the expected maximum longevity calculated from the adult body size (M) and derived from the mammalian allometric equation: tmax = 4.88M0.153. This is useful to identify species that live longer than expected for their body size. Cetaceans were excluded because we have less confidence in their longevity records, obtained from studies in the wild often using indirect methods, than in those from other mammalian taxa.
Included for some mammals and birds are growth rates. These values represent postnatal growth rate and are expressed in days-1. They were calculated by fitting empirical data taken from published growth curves to sigmoidal growth functions and are considered appropriate for comparative analyses within the same taxonomic class. Please be aware, however, that growth rates for mammals were derived from the Gompertz function while growth rates for birds were derived from the logistic function, so comparisons between the two classes need to take this into account.
Again, like GenAge, AnAge has its limits and external hyperlinks point users to further sources of information such as the websites of the Tree of Life and Animal Diversity Web.
AnAge's browser works differently than GenAge's browser, though, as it allows users to browse through the taxa in AnAge. Once a given set of entries has been selected it can be surveyed to gather simple descriptive statistics. Again, the species of interest can be selected with a mouse click and the average value for the parameter of interest can be calculated. For instance, to search for turtles one would simply type "testudines", the order to which turtles belong to. The list of turtles in AnAge would then be displayed and ordered according to taxonomy or longevity, and one could then obtain the averages and standard deviations for longevity, adult body size, age at sexual maturity, or other major traits present in AnAge. Like in GenAge, it is easy to navigate between the different tools in AnAge due to extensive cross-links between the different pages.
Often, additional information relevant to a particular species can be found in the higher taxa of that species. For example, as it concerns mammals, it is stated that longevity records are usually obtained from specimens in captivity, unless otherwise stated. So if you are looking at a particular mammalian species, you can assume that the maximum longevity was estimated in captivity. There are exceptions, though. For instance, in bats most longevity records come from studies in the wild. Therefore, users are encouraged not just to accept the values in each entry, such as maximum longevity, but to read the observations related to the species of interest as well as the taxa it belongs to.
Because our ultimate aim is to help understand human ageing, priority is given to species evolutionary closer to humans. Though there is a special focus on mammals, other taxa are also represented, including some non-animal species. Species are classified according to: Kingdom, Phylum, Class, Order, Family, Genus, and Species. The taxonomy of AnAge follows that of the Integrated Taxonomic Information System (ITIS).
The phylogeny of the species selected can be inferred from their taxonomy using the Phylogenetic Tree Plotter, though its use is limited to fewer than 50 species and because this tool is considered "work-in-progress" it should not be employed as a replacement for published phylogenies.
The bibliography of AnAge is also available for search, working exactly as described above for GenAge.
Linking to AnAge is also simple. Just use the species' name (preferred):
http://genomics.senescence.info/species/entry.php?species=x_y
And replace x by the organism's genus and y by the organism's species. This method is preferable because if for some reason an entry happens to be deleted you will get an error rather than a different entry. You may also create links using the HAGRID numbers (deprecated):
http://genomics.senescence.info/species/entry.php?id=XXXXX
And replace XXXXX by the appropriate HAGRID. Using species' names, however, is preferable because HAGRID numbers may change in future releases of the database.
For example, to link to the human species Homo sapiens use (preferred):
http://genomics.senescence.info/species/entry.php?species=homo_sapiens
Or (deprecated)
http://genomics.senescence.info/species/entry.php?id=03116
Additional Features in HAGR
In HAGR you will also find a collection of bioinformatic tools, in particular a Perl toolkit entitled the Ageing Research Computational Tools (ARCT). Documentation and examples are included in ARCT's distribution and it is recommended that you read it before installing ARCT or any of its modules. A method to estimate the rate of ageing of a given population is also available together with an SPSS script to aid in the calculations.
As you may have noticed, HAGR uses an accession number called HAGRID, which stands for Human Ageing Genomic Resources ID, not the gamekeeper in Harry Potter. HAGRID numbers can be used to search and retrieve entries from the databases. As mentioned above, however, HAGRID numbers change often and hence their usage should be kept to a minimum.
We recommend that users read our scientific strategy to understand the goals of HAGR and better use our resources. Also, for both legal and practical reasons, HAGR is part of senescence.info, an informational website about the biology of ageing that is an excellent introduction to the topic.
Included in HAGR are several ways to search HAGR and external databases as well as extensive links.
Feedback is always welcomed. If you have any problem, suggestion, idea, etc., please feel free to contact us.