Welcome to the SwissOrthology Flowchart. Here, you can interactively find information to help guide you to choose between different SwissOrthology tools. For some applications, either OMA or OrthoDB is better suited. For others, both orthology resources are fine. In the flowchart, you can interactively decide which resource to use based on one of the following criteria:
Click on one of the above to begin exploring how SwissOrthology can work for you.
Both OMA and OrthoDB predict orthologs for a diversity of animal, plant, fungal, and bacterial genomes.
OMA predicts orthologs over many species, including animal, fungal, plant, archaea, bacteria. The latest OMA release (Dec 2018) covers 2198 species. OMA also infers orthologs across kingdoms. A full list of species and their update dates is available on the release information page.
OrthoDB’s latest release predicts orthologs among 7275 species and 6488 viruses: 448 metazoan, 117 plant, 549 fungal, 148 protist, 5609 bacterial, 404 archaeal genomes, and 6488 viruses, picking up the best sequenced and annotated representatives for each species or operational taxonomic unit. The latest species list can be found here.
In addition to the 7275 eukaryotic, bacteria, and archaea species, OrthoDB v10 covers 6488 viruses.
Both OMA and OrthoDB allow for using your own sequenced genomes as input data.
The OMA pipeline can run on custom genomic/transcriptomic data using the OMA standalone software, and it is even possible to combine precomputed data with custom data by exporting parts of the OMA database, which saves time on the all-against-all step.
The OrthoDB software is also freely available from https://www.orthodb.org/software.
Additionally, in OrthoDB users can upload and analyze online their genome of interest. As many genomes are newly sequenced and analysis is needed for the first publication, OrthoDB has the possibility for users to create a registered account. After uploading the data, the analysis is performed automatically. The registered user can then see the OrthoDB interface with the new data and benefit from annotations of related orthologous groups in OrthoDB and other dababases.
The OMA Browser reports different subtypes of orthologous and paralogous relationships.
Evolutionary relationships are often described as pairwise relationships. Pairwise orthologs in OMA are those which are inferred at the base of the OMA algorithm. They are formed by looking for the evolutionarily closest protein sequences between two genomes within a confidence interval.
Users can find a list of all ortholog pairs for a given gene of interest by searching for their gene on the omabrowser. See the OMA How To Guide on how to find pairwise orthologs via the omabrowser.
Alternatively, users can download a list of all predicted ortholog pairs between genomes of interest. The result is returned as a tab-separated text file.
Both OMA and OrthoDB report groups of orthologous genes.
OrthoDB was the first database to introduce hierarchical orthologous groups. The concept of orthologous groups is inherently hierarchical, as each phylogenetic clade or subclade of species has a distinct common ancestor. The ortholog delineation procedure is applied at each major radiation of the species taxonomy to produce more finely resolved groups of closely related species and to allow users to select the most relevant level.
OMA also reports Hierarchical Orthologous Groups or HOGs. HOGs are sets of genes that are defined with respect to particular taxonomic ranges of interest. They group genes that have descended from a single common ancestral genes in that taxonomic range. Currently, HOGs can be retrieved from the omabrowser by first retrieving one of its gene members, and then clicking on the “hierarchical orthologous groups” tab. For more detailed information, see OMA How To: Get orthologs via HOG method. Additionally, all the HOGs from the current release can be downloaded in OrthoXML format and parsed and analysed with pyham.
Another type of orthologous group that OMA reports are called OMA Groups. OMA groups contain sets of genes which are all orthologous to one another within group. This implies that there is at most one entry from each species in a group.
OMA reports three “types” of orthologs: pairwise-induced orthologs, Hierarchical Orthologous Groups (HOGs), and OMA Groups. These are three different methods, so they might not report identical orthologs. However, HOG and OMA Group orthologs are based on pairwise orthologs so they should be similar. For more information, see: https://omabrowser.org/oma/type/.
|Pairwise orthologs||Hierarchical Orthologous Groups (HOGs)||OMA Groups|
|Algorithm||Built by mutually-closest protein sequences within a confidence interval||Built by merging groups of pairwise orthologs at different taxonomic levels using a guide tree||Built by searching for cliques of pairwise orthologs (i.e. all genes that are pairwise orthologs to all others in the group)|
|Genomes included||Compares 2 genomes at a time||Compares all genomes at a time||Compares all genomes at a time|
|Types of homologs||Strictly orthologs, but can be 1:m or n:m.||Groups of orthologs and in-paralogs for a specific speciation event of reference.||Strictly orthologs, at most 1 per species reported, although there may be more not reported.|
Both OMA and OrthoDB report paralogs.
OMA reports paralogs by several ways:
OrthoDB reports in-paralogs with respect to a given taxonomic level. Users can see online or download paralogs in orthologous groups; the paralogs are genes from the same species in the same orthologous group.
OMA reports homoeologs for allopolyploid species in the database.
Homoeologs are pairs of genes that originated by speciation and were brought back together in the same genome by allopolyploidization. Homoeologs can be thought of as orthologs between subgenomes.
OMA reports homoeologs for 3 species: Triticum aestivum (bread wheat), Gossypium hirsutum (upland cotton), and Brassica napus (rapeseed).
Both OMA and OrthoDB provide orthologous marker genes.
Orthologous marker genes (also known as phylogenetic marker genes) are sets of genes which are all orthologous to one another within the group. These marker genes should be 1:1, implying that there is at most one entry from each species in a group, and thus these marker genes are especially useful when creating a phylogenetics tree-- the gene tree will should match the species tree.
OMA identifies cliques of orthologous pairs (“OMA groups”), which are especially useful as marker genes for phylogenetic reconstruction and tend to be very specific. Since many users are only interested in a small subset of genomes, there is a function to retrieve, for a given subset of species, the most complete OMA groups. This functionality, entitled ‘Export marker genes’, is accessible under the ‘Compute’ menu. Users can optionally choose a minimum proportion of species present in each group (‘occupancy’), and a maximum number of groups to export. From the choice of species and parameters, the OMA server identifies the most complete groups and produces a compressed archive file containing one fasta file per marker gene (i.e. per OMA group).
OrthoDB identifies single copy Orthologous Groups (OGs): groups with 1:1 representatives in all (or >90%, >80%) of species, as well as universal orthologous groups, meaning groups with members present in all (or >90%, >80%) of species at any selected taxonomic level. Using such filters, users can choose the numbers of OGs they want to build a species tree at the level of interest.
It is possible to obtain gene families, or groups of orthologous genes, from both OMA and OrthoDB, which are necessary to build a gene tree.
In OMA, you can obtain the HOGs, which are groups orthologs and paralogs which descended from a common ancestral gene at any given taxonomic level. To streamline the process of building a gene tree, you can:
OrthoDB provides an “Advanced” search with a PhyloProfile option. There, one can select single copy groups for tree building. “PhyloProfile” allows the user to filter single-copy orthologous groups and their presence in most species (100%, 90% or 80%); this can be done at a selected taxonomic level, as well as coupled with specific annotations (i.e. certain functions). Afterwards, sequences for selected groups can be downloaded in an unaligned Fasta format and usedto build a MSA and a tree.
OMA lets you trace the evolutionary history of a gene family in terms of gene duplications and losses.
The evolutionary history of gene families can be complex due to duplications and losses. As provided by several orthology databases, hierarchical orthologous groups (HOGs) are sets of genes that are inferred to have descended from a common ancestral gene within a species clade. By keeping track of HOG composition along the species tree, it is possible to infer the emergence, duplications and losses of genes within a gene family of interest.
The OMA browser allows for viewing HOGs with an interactive widget called iham to visualize and explore gene family history encoded in HOGs. Additionally, one can query the HOGs for evolutionary events programmatically using the python library called pyham.
See the guide: How to Get the Evolutionary History of Your Favorite Gene in OMA to find out how to get to and use iham. You can also learn more about iham by watching the YouTube tutorial.
OrthoDB for each orthologous group offers the following set of evolutionary descriptors: Phyletic Profile, Duplicability, Evolutionary Rate and Gene Architecture.
Synteny is the conservation of gene order and/or overall chromosomal location. Synteny can be viewed on a global or local level, where global synteny looks at the overall chromosomal conservation, and local synteny looks in a smaller neighborhood for conservation of gene homology and order.
Both OMA and OrthoDB let you export orthologs for external synteny packages.
Many synteny programs exist for computation and visualization of syntenic regions between two genomes, such as i-ADHoRe, MCScanX, circos, among others. Generally the input for these programs is a text file of pairwise orthologous relations or orthologous groups.
OMA lets you visualize the global synteny between two chromosomes of different or the same genomes.
These are the steps to use the OMA Synteny Dot Plot:
A wide range of operations can then be applied to the selected chromosome pair:
OMA allows for visualization of local synteny.
The synteny view provides an overview of the genomic context of a particular entry and its orthologs in other species. This enables to see conservation or divergence of syntenic regions across species. As synteny is computed with respect to a reference entry, please first search for a protein sequence of interest and click on the “Local Synteny” tab.
Both OMA and OrthoDB report domain annotations for the proteins in the databases.
OMA integrates domain annotations from Gene3D for individual protein entries. For each protein, the sequence of annotated domains is depicted using the conventional ‘colored-boxes-on-a-line’ representation, which we include in most protein lists. This makes it possible to easily check whether the domain architecture of a protein is conserved among orthologs, or to identify entries which are likely to be truncated or otherwise problematic. CATH domains (28) are depicted in colors specific to their first and second level classification.
OrthoDB provides InterPro attributes associated with individual member proteins. Additionally, at the group level, domain information is summerized.
An important application of orthology is the ability to transfer gene function annotations from the few well-studied model organisms to the large number of poorly studied genomes. Gene Ontology (GO) is a way of consistently organizing annotated functions of genes.
Both OMA and OrthoDB report GO annotations for proteins in their databases.
One key motivation for orthology inference is to computationally predict the roles that genes play in living organisms—e.g. Cellular Component, Molecular Function and Biological Process of the Gene Ontology. Gene Ontology (GO) annotations from the UniProt-GOA database have been linked to all sequences in OMA, as well as inferred annotations based on orthology relationships: within the orthologous groups, OMA propagates GO annotations across different species. Amongst the available annotations, most are computationally inferred; OMA’s own predictions constitute about 20% of the available annotations. In OrthoDB currently, about 51% of clusters have GO annotation.
Both OMA and OrthoDB provide GO annotations for orthologous groups.
In OrthoDB, Gene Ontology and InterPro attributes associated with individual member proteins provide a general description for the Orthologous Group as a whole. These are summed over the member proteins to indicate the most frequently occurring attributes associated with the Orthologous Group.
OMA now provides a feature to annotate custom protein sequences through a fast approximate search with all the sequences in OMA. The user can upload a fasta formatted file and will receive the GO annotations (GAF 2.1 format) based on the closest sequence in OMA. These results can directly be further analyzed using other tools, e.g. to perform a gene enrichment analysis. This functionality is accessible under the Compute menu in the OMA browser.
OMA and OrthoDB both provide access to their orthology predictions in various formats: