Nucleic Acids Research Advance Access originally published online on October 25, 2007
Nucleic Acids Research 2008 36(Database issue):D491-D496; doi:10.1093/nar/gkm899
Nucleic Acids Research, 2008, Vol. 36, Database issue D491-D496
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-com
PhylomeDB: a database for genome-wide collections of gene phylogenies
Jaime Huerta-Cepas,
Anibal Bueno,
Joaquín Dopazo and
Toni Gabaldón*
Bioinformatics Department, Centro de Investigación Príncipe Felipe, Avda. Autopista del Saler, 13 Valencia 46013, Spain
* To whom correspondence should be addressed. Tel: +34 963289680; Fax: +34 963289701; Email: tgabaldon{at}cipf.es
Received August 14, 2007. Revised October 3, 2007. Accepted October 4, 2007.
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ABSTRACT
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The complete collection of evolutionary histories of all genes
in a genome, also known as phylome, constitutes a valuable source
of information. The reconstruction of phylomes has been previously
prevented by large demands of time and computer power, but is
now feasible thanks to recent developments in computers and
algorithms. To provide a publicly available repository of complete
phylomes that allows researchers to access and store large-scale
phylogenomic analyses, we have developed PhylomeDB. PhylomeDB
is a database of complete phylomes derived for different genomes
within a specific taxonomic range. All phylomes in the database
are built using a high-quality phylogenetic pipeline that includes
evolutionary model testing and alignment trimming phases. For
each genome, PhylomeDB provides the alignments, phylogentic
trees and tree-based orthology predictions for every single
encoded protein. The current version of PhylomeDB includes the
phylomes of Human, the yeast
Saccharomyces cerevisiae and the
bacterium
Escherichia coli, comprising a total of 32 289 seed
sequences with their corresponding alignments and 172 324 phylogenetic
trees. PhylomeDB can be publicly accessed at
http://phylomedb.bioinfo.cipf.es
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INTRODUCTION
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A phylome is defined as the complete collection of phylogenies
reconstructed for every single gene encoded in a genome (
1).
Although the term was coined several years ago, the development
of high-quality, genome-wide collections of phylogenetic trees
has been previously prevented due to large demands of time and
computer power. Only recently, and thanks to new and faster
algorithms and computers, the application of phylogenetics to
whole genomes has become feasible. Large-scale phylogenetic
studies provide very valuable information on the evolutionary
relationships between genes of different species (
2). Among
other applications, the availability of complete phylomes can
be exploited to map duplication and speciation events and thus
infer orthology relationships (
3), to determine the evolutionary
relationships among taxa (
4) and even to reconstruct ancestral
metabolisms (
5). Although some databases provide automatically
derived and curated phylogenies (
6–9), these follow a
family-based approach, since they first group the genes into
families and subsequently build a single phylogeny for each
family. Moreover, the selection of species included is determined
by the specific scopes of these databases. PhylomeDB provides
phylomes reconstructed following a gene-based approach (
3),
in which the same high-quality phylogenetic pipeline is applied
to each single gene encoded in a given genome. The resulting
trees, alignments and tree-based orthology predictions can be
easily accessed, queried and downloaded through a user-friendly
web interface. In this article, the data content and web features
of the first release of PhylomeDB are described.
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DATABASE STRUCTURE AND CONTENT
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General features
The current version of PhylomeDB contains the phylomes of three
relevant organisms, including human and the two model species
Saccharomyces cerevisiae and
Escherichia coli. Future releases
of PhylomeDB will incorporate phylomes for new species as well
as novel versions of existing phylomes that may include different
phylogenetic ranges or updated releases of their respective
proteomes. To store all data associated with the phylomes, PhylomeDB
uses a relational database. For each phylome, PhylomeDB provides:
(i) a
feature page, which contains general information on the
proteomes included in the specific phylome as well as all the
details of the phylogenetic pipeline used (e.g.
http://phylomedb.bioinfo.cipf.es/index.html?Hsapiens001 for Hsapiens001 phylome); and (ii) an individual entry (
Figure 1)
for each protein encoded in the seed genome that provides the
sequences, multiple sequence alignments and phylogenetic trees
rendered by the phylogenetic pipeline. The database has been
implemented in MySQL (
http://www.mysql.com) but users can access
all data via a user-friendly web interface that provides several
query options (see below). To facilitate the interactivity,
speed and functionality of the website, the web interface has
been developed in Asynchronous JavaScript and XML (AJAX) technology.
Although the use of the web interface of PhylomeDB is quite
intuitive, a user's manual is provided in the form of a wiki
page (
http://www.mediawiki.org). This provides an easy mechanism
by which registered users can help PhylomeDB developers correcting
and expanding the documentation.
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Figure 1. Screenshot of a PhylomeDB entry page. The entry page of an individual seed protein (Hsa0017176) of the human phylome (Hsapiens001), includes information on the sequence and links to (i) the feature page containing all necessary information of the phylogenetic pipeline used; (ii) all the phylogenetic trees derived by the different programs and models used in the pipeline, in this case a NJ tree, ML trees derived from JTT, WAG, RtREV and BLOSUM62 models, and the consensus tree derived from the Bayesian analyses; (iii) the raw and trimmed (clean) alignments and (iv) the list of tree-based orthology predictions for the species included in the tree.
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Phylome reconstruction pipeline
All phylomes included in PhylomeDB have been generated following
a similar high-quality phylogenetic pipeline that is described
more extensively elsewhere (
3). The particularities of each
phylome as well as the list of species included are comprehensively
described in the corresponding
feature pages that can be accessed
by clicking on the phylome code (e.g. Hsapiens001). Each phylome
is defined by the proteome of the seed species and a specific
dataset of proteomes, including several other species. The proteomes
are downloaded from sequence databases such as Ensembl, EBI
and those from specific genome sequencing projects, details
of the source of the sequences are provided in the
feature pages of the phylomes. In summary, the pipeline proceeds as follows:
for each protein of the seed proteome, a Smith–Waterman
(
10) search is performed against the corresponding proteome
dataset to retrieve a set of proteins with a significant similarity
(
e-value <10
–3). Only sequences that align with a continuous
region longer than 50% of the query sequence are selected as
homologs. These sets of homologous sequences are subsequently
aligned using MUSCLE 3.6 (
11) with default parameters. Positions
in the alignment with gaps in more than 10% of the sequences
are removed, unless such procedure removes more than one-third
of the positions in the alignment. In such cases, the percentage
of sequences with gaps allowed is automatically increased until
at least two-thirds of the initial positions are conserved.
Phylogenetic trees are derived from the resulting alignments
by using several methods, which may include: (i) Neighbor Joining
(NJ) trees using scoredist distances as implemented in BioNJ
(
12); (ii) Maximum Likelihood (ML) as implemented in PhyML v2.4.4
(
13) assuming a discrete gamma-distribution model with four
rate categories and invariant sites, where the gamma shape parameter
and the fraction of invariant sites are estimated from the data
only in the case of the human phylome and (iii) Bayesian phylogenetic
reconstruction using Mr Bayes for 100 000 generations in two
rounds of two chains each (
14). Since, both ML and Bayesian
analyses are model-based approaches that can provide divergent
results when different evolutionary models are assumed. In such
cases, all phylogenetic trees derived from the different models
are provided and the model best fitting the data, as judged
by the AIC criterion (
15), is indicated. The models used in
the different phylomes are listed in
Table 1.
Data formats
Inspired by the success of the information standard for microarray
analyses (MIAMA), the need for a similar minimum information
about a phylogenetic analysis standard (MIAPA) has been suggested
(
16). Although the developing of MIAPA standards is still on
progress, several general guidelines have been proposed (
16).
In accordance to these guidelines, PhylomeDB provides comprehensive
information on the programs and parameters used for each step
of the pipeline so that the phylogenetic reconstruction can
be reproduced. Since the same phylogenetic pipeline is applied
to all seed proteins in a phylome, such details are provided
in the
features page of the corresponding phylome. Moreover,
all alignments and trees rendered by the phylogenetic pipeline
are provided in standard newick and phylip formats, respectively.
As soon as new guidelines and MIAPA standards are developed,
these will be implemented in PhylomeDB. Besides phylogenetic
trees and alignments, PhylomeDB provides tree-based orthology
and paralogy predictions. These predictions are generated from
the seed sequence by mapping duplication and speciation events
on the tree as determined by a species-overlap algorithm (
3).
In contrast to alternative, phylogeny-based methods that use
reconciliation of the gene tree with the species tree, the PhylomeDB
algorithm uses the level of overlap in the species connected
to two related nodes to decide whether their parental node represents
a duplication or speciation event. Briefly, the algorithm visits
all nodes that connect the seed protein to the root of the tree
and marks it as a duplication event if one or more species are
shared by its two children nodes.
When the orthology prediction algorithm is launched, phylomeDB displays the list of predicted orthologs and paralogs for the seed sequence, as well as a tree with the corresponding speciation and duplication edges indicated in red and blue (Figure 3A), respectively, are provided. The full set of predicted orthology and paralogy relationships for each phylome can be downloaded from the download section of the database.
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Figure 3. Visualization of phylogenetic trees: different views of the ML phylogenetic tree, using JTT evolutionary model, for the seed protein (Hsa0017176), as displayed by the environment for tree exploration tool (ETE). Trees can be represented in rectangular (A), circular (B) or radial (C) modes. Several information labels such as support values or branch distances (A) can be displayed on nodes and edges, which can also be colored to indicate different evolutionary event. In (A) an example is shown where the lineages leading to the seed protein (Hsa0017176) are colored in blue or red to mark duplications and speciation events, respectively. This feature is shown after running the orthology prediction algorithm by clicking on the ‘orthologs’ icon. Using the ETE toolbar (icons on the top of the section A), the user can navigate within the tree and browse it using different visualization options.
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All protein sequences included in PhylomeDB are given a unique
alpha-numeric ID (PhylomeID), which includes a three-letters
code designating the species, followed by a sequential number.
Codes for the 443 organisms included in PhylomeDB are listed
in the features page of the corresponding phylomes. Correspondence
between PhylomeIDs and IDs from external databases such as Swissprot
and Ensembl are given in the corresponding sequence entries.
Moreover, an ID converter tool provides the equivalences between
Phylome ID and other selected IDs.
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DATABASE ACCESS AND WEB FEATURES
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Browsing and querying
PhylomeDB is publicly accessible at
http://phylomedb.bioinfo.cipf.es.
There are various ways in which users can access data stored
in PhylomeDB. The database can be browsed by selecting a specific
phylome from the home or content pages. In this case, a table
appears that lists the entries to all the seed proteins included
in the phylome. By clicking in a specific PhylomeID, the corresponding
entry is shown. Each entry contains information on the seed
protein and the homologous proteins included in the phylogenetic
analysis together with the corresponding alignments and phylogenetic
trees.
Moreover, an ID text-based search is available for users to search for specific proteins by their PhylomeID, Swissprot or Ensembl IDs, among others, and, finally, the user can search using a specific protein sequence. In such case, a Smith–Waterman search is performed against all seed proteins included in the database and the significant hits (e-value = 10–3), with links to their entry pages, are displayed.
Visualization
PhylomeDB provides all alignments, sequences and trees in separate files in a plain text format, so that the files can be downloaded and visualized with the user's favorite tool. Moreover, PhylomeDB incorporates multiple sequence alignment and tree visualization tools to facilitate the online visualization of the data. Alignments can be visualized with Jalview (Figure 2), which is a java application enabling fast viewing of large multiple sequence alignments (17). PhylomeDB implements a web plugin of the program ETE (Environment for Tree Exploration) developed by J. Huerta-Cepas. This program is an interactive tree viewer that implements different visualization, search and browse modes (Figure 3). Some of its most interesting features include the visualization of trees using rectangular, circular or radial representation modes, rooting options and functions to collapse and/or extract sub-trees. Selected (sub) tree visualization can be downloaded as standard PNG images. A complete description about the ETE interface can be accessed through the PhylomeDB user's manual page.
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Figure 2. Visualization of multiple sequence alignments: Example of the trimmed (clean) multiple sequence alignment of the example entry (Hsa0017176) as displayed by JalView (17). Sequence names are indicated by PhylomeID names, which include the three-letters species code followed by a number. The levels of sequence conservation and quality of each column, as well as a consensus sequence are indicated bellow. Colors, sequence format and visualization options can be changed using JalView interface.
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PhylomeDB entries can be easily linked to from external pages
using the following URL scheme:
http://phylomedb.bioinfo.cipf.es/index.html?Hsapiens001&Hsa0000001 to link to the entry Hsa0000001 of Hsapiens001 phylome. In this
manner, protein databases not specifically focused in phylogenetic
information can provide links to the phylogenies of their proteins.
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FUTURE PERSPECTIVES
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In summary, PhylomeDB has been developed as a database for storing
and querying complete collections of gene phylogenies for complete
genomes. We are continuing to expand the PhylomeDB database
to incorporate data from other model species using the pipeline
described above. We encourage other groups to contact us in
order to suggest new phylomes to be generated or to submit phylomes
generated with similar procedures. In any case, only phylomes
that have been reconstructed following similar high-quality
procedures will be stored in PhylomeDB. New enhancements that
we are focusing on for the short- to medium-term include the
following: (i) increase links to other external databases providing
additional information such as functional annotation; (ii) provide
enriched newick format with information on the nodes such as
labels for speciation and duplication events and (iii) implement
a topology search tool so that trees can be searched for the
presence of a given topology. A new release of PhylomeDB is
expected on a yearly basis.
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ACKNOWLEDGEMENTS
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J.H.-C. is supported by a grant from the Fundación Genoma
España and the Instituto Nacional de Bioinformática.
T.G. is recipient of a post-doctoral fellowship from the European
Molecular Biology Organization (EMBO LTF 402-2005) and of an
ISCIII Grant from the Spanish Ministry of Health (06/00213).
A fraction of the phylogenetic trees stored in PhylomeDB was
reconstructed using the super-computer
Mare Nostrum, from the
Barcelona Supercomputing Centre. We are grateful to J. Burguet
for providing technical support and to L. Arbiza for critically
reading the manuscript. Funding to pay the Open Access publication
charges for this article was provided by ISCIII Grant from the
Spanish Ministry of Health (06/00213).
Conflict of interest statement. None declared.
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ABSTRACT
INTRODUCTION