Nucleic Acids Research Advance Access published online on October 25, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp805
© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
PlnTFDB: updated content and new features of the plant transcription factor database
Paulino Pérez-Rodríguez1,2,
Diego Mauricio Riaño-Pachón1,3,*,
Luiz Gustavo Guedes Corrêa1,4,
Stefan A. Rensing5,
Birgit Kersten1,3 and
Bernd Mueller-Roeber1,4
1Department of Molecular Biology, Institute of Biochemistry and Biology, GoFORSYS, University of Potsdam, Karl-Liebknecht-Str. 24-25, Haus 20, 14476 Potsdam-Golm, Germany, 2Colegio de Postgraduados, Km. 36.5 Carretera México, Texcoco, Montecillo, Estado de México. C.P. 56230, Mexico, 3GabiPD Team, Bioinformatics Group, Max Planck Institute of Molecular Plant Physiology, 4Cooperative Research Group, Max Planck Institute of Molecular Plant Physiology, Wissenschaftspark Golm, Am Mühlenberg 1, 14476 Potsdam - Golm and 5FRISYS, Faculty of Biology, University of Freiburg, Hauptstr. 1, D-79104 Freiburg, Germany
*To whom correspondence should be addressed. Tel: +49-(0)331-567-8752; Fax: +49-(0)331-567-89-8750; Email: riano{at}mpimp-golm.mpg.de
Received July 10, 2009. Accepted September 13, 2009.
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ABSTRACT
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The Plant Transcription Factor Database (PlnTFDB;
http://plntfdb.bio.uni-potsdam.de/v3.0/)
is an integrative database that provides putatively complete
sets of transcription factors (TFs) and other transcriptional
regulators (TRs) in plant species (
sensu lato) whose genomes
have been completely sequenced and annotated. The complete sets
of 84 families of TFs and TRs from 19 species ranging from unicellular
red and green algae to angiosperms are included in PlnTFDB,
representing >1.6 billion years of evolution of gene regulatory
networks. For each gene family, a basic description is provided
that is complemented by literature references, and multiple
sequence alignments of protein domains. TF or TR gene entries
include information of expressed sequence tags, 3D protein structures
of homologous proteins, domain architecture and cross-links
to other computational resources online. Moreover, the different
species in PlnTFDB are linked to each other by means of orthologous
genes facilitating cross-species comparisons.
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INTRODUCTION
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In order to fulfil their biological functions, genes must be
expressed in specific spatiotemporal patterns. These patterns
are to a large extent established by controlling the transcription
of the genes through which RNA copies are generated from the
DNA template. In this process, a protein complex composed of
general transcription factors (TFs) is mandatory to sustain
the expression of all genes encoded by the genome. In addition,
other regulatory proteins enhance or repress the transcriptional
rate of target genes in response to biotic and abiotic stimuli,
and intrinsic developmental processes. These proteins are TFs
that bind, in a sequence-specific manner, to
cis-elements in
the target promoters, and other transcriptional regulators (TRs)
that exert their regulatory function through protein–protein
interactions or chromatin remodeling. The identification of
such TFs and TRs from an appreciable number of organisms of
divergent lineages represents an important first step towards
the understanding of gene regulatory networks and their evolution.
For plants, this step has already been made by several groups
through the development of databases dedicated to the presentation
of TFs and TRs and accompanying information of relevance to
the research community (
1–6). Here we present the current
status of the Plant Transcription Factor Database, PlnTFDB (
4),
which in its updated version (v3.0) provides information about
the putatively complete sets of TFs and TRs from 19 plant species
(
sensu lato) encompassing a broad phylogenetic range of >1.6
billion years of divergent evolution (
7).
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DATA SOURCES, ANALYSES AND IMPLEMENTATION
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Species and proteomes covered
In order to identify putatively complete sets of TFs and TRs,
we applied our previously established analysis pipeline to the
proteomes of species whose genomes have been completely sequenced
and annotated (
4). The PlnTFDB v3.0 covers 19 different plant
species ranging from unicellular red and green algae to angiosperms,
therewith expanding the species spectrum of the previous version
by 12 new species. The species analysed and the sources of the
sequence data used to establish PlnTFDB v3.0 are listed in
Table 1.
Identification of protein domains and new domain models
The identification of TFs and TRs and their classification into
families exploits the presence of protein domains and their
combination within proteins (
4). To generate the current release
of PlnTFDB, domains were identified using the Pfam protein families
database v23.0 (
21) and the software package HMMER v2.3.2 (
http://hmmer.janelia.org/).
Domain hits with a score higher than or equal to the gathering
cut-off (–cut_ga) defined for each hidden Markov model
(HMM) were kept for further analyses.
For some families, there is no domain represented in the Pfam database; in such cases we developed profile HMMs based on sequence alignments of the respective domains. For the current version of PlnTFDB, we established HMMs for the characteristic domains of the families NOZZLE and VARL. An HMM for the NOZZLE family is available in the Pfam database; however, this model only recovers members from the Brassicaceae family (e.g. Arabidopsis sp.). Hence we used the Arabidopsis thaliana sequences to perform a PSI-BLAST search against the non-redundant protein database at NCBI (http://www.ncbi.nlm.nih.gov/). This allowed us building a multiple sequence alignment and HMM of NOZZLE proteins from several angiosperms, i.e. A. thaliana, Brassica juncea, Medicago truncatula and Vitis vinifera.
The HMM for the VARL family was built by using the alignment reported in Duncan et al. (22), with sequences from Chlamydomonas reinhardtii and Volvox carteri. The alignments used to create the new HMMs are available through the database web interface.
After building these HMMs, a score threshold had to be defined, beyond which the hits are considered significant. To this end, we run an HMM search with the newly created models using a very permissive preliminary threshold (e-value 
10). Subsequently, the known members of the family were localized within the list of hits, which allowed us identifying putative true positives (TPs) and putative true negatives (TNs), thus defining the score threshold as the average between the minimum score obtained by a TP and the maximum score obtained by a TN. This procedure is illustrated in Figure 1.
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Figure 1. Selecting the significance score threshold in newly created profile HMMs. The graphic shows the scores obtained for proteins in the V. carteri proteome when searched with the VARL HMM with an e-value cut-off of 10. Known members of the family in this species (TPs) are highlighted in green. The putative TN with the highest score is indicated by a purple arrow. The TP with the minimum score is highlighted by a green arrow. The significance score threshold (black line) is computed as the average between the minimum score for TPs (green line) and the maximum score for TNs (purple line). For this family, the selected threshold is –4.25 bits.
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Rules for the classification of TFs and TRs
Compared with version 2.0 of the database, we have increased
the number of rules established for the classification of TFs
and TRs by Riaño-Pachón
et al. (
4). We have now
included 16 additional families, totalling 84 in PlnTFDB v3.0.
Briefly, the classification rules ask for the presence of a
single domain in 77 cases, and a combination of domains in the
remaining 7 cases. In addition to these ‘required’
domains, the rules for some families include ‘forbidden’
domains. The forbidden domains allow establishing a mutually
exclusive classification system ensuring that each individual
protein is classified as a member of a single TF or TR family
only. The current sets of ‘required’ and ‘forbidden’
domains of each individual family are listed in
Supplementary Data, Appendix 1.
We included two meta-rules in our classification scheme: (i)
if a protein harbours domains characteristic of a TF family
and a TR family, we assigned it to the TF family, e.g.
A. thaliana protein AT3G51120.1 could be assigned to families C3H (TF) and
SWI/SNF-BAF60b (TR), but according to this meta-rule it is assigned
to C3H. (ii) When the protein of interest contains domains characteristic
of more than one TF family or more than one TR family, it was
assigned to the family to which its characteristic domains matched
with the lowest
e-value. For example, protein 425147 from
Selaginella moellendorffii could be classified as C2H2 (TF,
e-value 7.3e-3)
or RWP-RK (TF,
e-value 6.1e-11), according to the meta-rule
it was assigned to the RWP-RK family.
Database interface and availability
The information about the different regulatory proteins and their classification into families, as well as sequence alignments, 3D structures, literature references and links to other databases are stored in a relational database, powered by MySQL (http://www.mysql.com; database schema in Supplementary Data, Appendix 2). The interface of the database to the World Wide Web (WWW) was developed by using PHP, JavaScript and Java applets (Jmol, http://www.jmol.org/; and Jalview, http://www.jalview.org/) following HTML 4.01 and CCS v2.1 W3 standards to ensure browser interoperability.
PlnTFDB can be queried using keywords or sequences (using blastp or blastx), and it is freely accessible through the WWW via http://plntfdb.bio.uni-potsdam.de/v3.0/ using any modern web browser. The Java Runtime Environment (JRE) 1.6.0.12
[EC]
or newer is required in order to visualize domain alignments and protein 3D structures.
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3D PROTEIN STRUCTURES, EXPRESSED SEQUENCE TAGS AND ORTHOLOGUES
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To widen the information provided for each TF and TR in PlnTFDB,
we have performed similarity-based searches against the database
of sequences with known protein tertiary structures available
from the Protein Data Bank (PDB) and the expressed sequence
tag (EST) databases available from GenBank. To identify related
ESTs, we used BLAST as search engine, keeping as significant
all hits with an
e-value
10
–10 and an alignment identity
of
50% over a length of
80 amino acids. For the detection of
homologous 3D protein structures, we used the package hhsearch
(
http://toolkit.tuebingen.mpg.de/hhpred) that employs HMM—HMM
comparisons to detect remote homologues. Hits were considered
significant if the probability of the target being a TP was
>98%. The 3D structures of proteins similar to entries in
PlnTFDB can be visualized with the Jmol applet (
Figure 2), and
links are provided to the PDB web site.
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Figure 2. Screenshot of a web page displaying details for a TF gene in PlnTFDB. (A) Every gene page in PlnTFDB displays basic information (including species name and gene family assignment) for a given TF or TR. If gene names had been assigned (only for A. thaliana and O. sativa ssp. japonica) they will be displayed as well. (B) The best hits (hhsearch, probability of being a TP 98%) to PDB protein 3D structures are visualized as static images, a link is provided to the embedded Java applet Jmol where basic operations on the 3D structure can be performed. (C) Links to orthologues in PlnTFDB are provided. (D) Users can query PlnTFDB through similarity searches (BLAST) using a protein or a nucleotide sequence as query. (E) Domain architecture is displayed with links to the original domain databases (Pfam or our local database, see section ‘Identification of protein domains and new domains models’). (F) Links to the protein and transcript sequences of the gene are provided.
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The genomes of some species covered by PlnTFDB, e.g.
A. thaliana and
Oryza sativa ssp.
japonica, are relatively well annotated
with respect to the biological functions of the proteins they
encode, whereas genomes of others, including
C. reinhardtii,
are still in a preliminary status of annotation of biological
functions. As orthologous genes often have the same function
in different species (
23), we have used InParanoid (
24) to detect
clusters of orthologous genes between pairs of species in PlnTFDB.
This will ease the transfer of functional information and provide
effective cross-references among the species in PlnTFDB.
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QUALITY CONTROL
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To evaluate the quality of the putatively complete sets of TFs
and TRs reported in PlnTFDB, we compared our predictions to
published datasets on detailed single-family phylogenetic studies,
and defined the published analyses as gold standards. We calculated
the sensitivity and the positive predicted value (PPV) as described
before (
4). The results of this evaluation are shown in
Table 2.
In all cases, both measures are >80%, and for most families
the sensitivity and PPV values are >90% (shown in bold face
in
Table 2), evidencing low rates of false negatives (FNs) and
positives (FPs).
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MAIN RESULTS
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In the current version of PlnTFDB (v3.0), we present a total
of 84 different TF and TR families that occur in 19 different
plant species and encompass 26 184 distinct proteins. A summary
of the content of the database is shown in
Table 1; there is
a tendency that the number of TFs and TRs per family, as well
as the number of families, increases along with the organismic
complexity. Correlation analyses support this observation (
Supplementary Data,
Appendix 3).
The wide spectrum of gene families covered by PlnTFDB has already been exploited by researchers, e.g. for use in genome annotations (12,40,41), functional studies of TFs and TRs (42,43) and detailed phylogenetic studies of TF families in the whole plant lineage (28), among others.
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OUTLOOK
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As the cost of genome sequencing continues to decrease, the
number of newly sequenced genomes will increase dramatically
in the near future. The computational analysis pipeline behind
PlnTFDB will be applied to these new genomes, increasing even
further its wide phylogenetic coverage. We envisage that PlnTFDB
will increasingly be exploited in genome annotation projects
as a primary repository serving the identification of transcription
regulatory proteins.
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SUPPLEMENTARY DATA
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Supplementary Data are available at NAR Online.
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FUNDING
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Bundesministerium fuer Bildung und Forschung, Germany (GABI-FUTURE
grant 0315046, GoFORSYS grant 0313924 and FRISYS grant 0313921);
Subdirección de Investigación: Línea 15,
Colegio de Postgraduados, México; Deutscher Akademischer
Austauschdienst (DAAD). Funding for open access charge: GoFORSYS.
Conflict of interest statement. None declared.
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ACKNOWLEDGEMENTS
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We would like to express our gratitude to the people and institutions
working on the sequencing and annotation of the plant genomes
analyzed in this study. We are particularly thankful to Andreas
Weber and Detlef Weigel who allowed us to explore plant genome
data not published yet.
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Footnotes
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The authors wish it to be known that, in their opinion, the
first two authors should be regarded as joint First Authors.
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ABSTRACT
INTRODUCTION