D260–D266 Nucleic Acids Research, 2018, Vol. 46, Database issue Published online 13 November 2017
doi: 10.1093/nar/gkx1126
JASPAR 2018: update of the open-access database of
transcription factor binding profiles and its web
framework
Aziz Khan1,†
, Oriol Fornes2,†
, Arnaud Stigliani3,†
, Marius Gheorghe1
, Jaime
A. Castro-Mondragon1
, Robin van der Lee2
, Adrien Bessy3
, Jeanne Ch`eneby4,5
, Shubhada
R. Kulkarni6,7,8
, Ge Tan9,10
, Damir Baranasic9,10
, David J. Arenillas2
, Albin Sandelin11,*
,
Klaas Vandepoele6,7,8
, Boris Lenhard9,10,12,*
, Benoˆıt Ballester4,5
, Wyeth W. Wasserman2,*
,
Franc¸ois Parcy3
and Anthony Mathelier1,13,*
1
Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway,
2
Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children’s Hospital Research
Institute, University of British Columbia, 950 28th Ave W, Vancouver, BC V5Z 4H4, Canada, 3
University of Grenoble
Alpes, CNRS, CEA, INRA, BIG-LPCV, 38000 Grenoble, France, 4
INSERM, UMR1090 TAGC, Marseille, F-13288,
France, 5
Aix-Marseille Universit´e, UMR1090 TAGC, Marseille, F-13288, France, 6
Ghent University, Department of
Plant Biotechnology and Bioinformatics, Technologiepark 927, 9052 Ghent, Belgium, 7
VIB Center for Plant Systems
Biology, Technologiepark 927, 9052 Ghent, Belgium, 8
Bioinformatics Institute Ghent, Ghent University,
Technologiepark 927, 9052 Ghent, Belgium, 9
Institute of Clinical Sciences, Faculty of Medicine, Imperial College
London, London W12 0NN, UK, 10
Computational Regulatory Genomics, MRC London Institute of Medical Sciences,
London W12 0NN, UK, 11
The Bioinformatics Centre, Department of Biology and Biotech Research & Innovation
Centre, University of Copenhagen, DK2200 Copenhagen N, Denmark, 12
Sars International Centre for Marine
Molecular Biology, University of Bergen, N-5008 Bergen, Norway and 13
Department of Cancer Genetics, Institute for
Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
Received September 25, 2017; Revised October 17, 2017; Editorial Decision October 18, 2017; Accepted October 27, 2017
ABSTRACT
JASPAR (http://jaspar.genereg.net) is an openaccess
database of curated, non-redundant transcription
factor (TF)-binding profiles stored as position
frequency matrices (PFMs) and TF flexible models
(TFFMs) for TFs across multiple species in six taxonomic
groups. In the 2018 release of JASPAR, the
CORE collection has been expanded with 322 new
PFMs (60 for vertebrates and 262 for plants) and 33
PFMs were updated (24 for vertebrates, 8 for plants
and 1 for insects). These new profiles represent a
30% expansion compared to the 2016 release. In addition,
we have introduced 316 TFFMs (95 for vertebrates,
218 for plants and 3 for insects). This release
incorporates clusters of similar PFMs in each taxon
and each TF class per taxon. The JASPAR 2018 CORE
vertebrate collection of PFMs was used to predict
TF-binding sites in the human genome. The predictions
are made available to the scientific community
through a UCSC Genome Browser track data hub. Finally,
this update comes with a new web framework
with an interactive and responsive user-interface,
along with new features. All the underlying data can
be retrieved programmatically using a RESTful API
and through the JASPAR 2018 R/Bioconductor pack-
age.
INTRODUCTION
Transcription factors (TFs) are sequence-specific DNAbinding
proteins involved in the transcriptional regulation
of gene expression (1). TFs bind to DNA through their
DNA-binding domain(s) (DBDs), which are used for TF
classification (2). DNA regions at which TFs bind are defined
as TF-binding sites (TFBSs) and can be identified
*To whom correspondence should be addressed. Tel: +47 228 40 561; Email: anthony.mathelier@ncmm.uio.no
Correspondence may also be addressed to Albin Sandelin. Tel: +45 2245 6668; Fax: +45 3532 2128; Email: albin@binf.ku.dk
Correspondence may also be addressed to Boris Lenhard. Tel: +44 20 8383 8353; Email: b.lenhard@imperial.ac.uk
Correspondence may also be addressed to Wyeth W. Wasserman. Tel: +1 604 875 3812; Fax: +1 604 875 3840; Email: wyeth@cmmt.ubc.ca
†
These authors contributed equally to the paper as first authors.
C The Author(s) 2017. 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-nc/4.0/), which
permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact
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Nucleic Acids Research, 2018, Vol. 46, Database issue D261
Table 1. Overview of the growth of the number of PFMs in the JASPAR 2018 CORE collection compared to the JASPAR 2016 CORE collection
Taxonomic group
Non-redundant
PFMs in JASPAR
2016
New non-redundant
PFMs in JASPAR
2018
Updated PFMs in
JASPAR 2018
Total PFMs
(non-redundant) in
JASPAR 2018
Total PFMs (all versions)
in JASPAR 2018
Vertebrates 519 60 24 579 719
Plants 227 262 8 489 501
Insects 133 0 1 133 140
Nematodes 26 0 0 26 26
Fungi 176 0 0 176 177
Urochordata 1 0 0 1 1
Total 1082 322 33 1404 1564
in vivo by methods such as chromatin immunoprecipitation
(ChIP) or in vitro by methods based on binding of
large pools of DNA fragments (e.g. Systematic evolution
of ligands by exponential enrichment (SELEX) or proteinbinding
microarrays (PBM)) (reviewed in (3)). Analysis of
TFBSs for a given TF provides models for its specific DNAbinding
preferences, which in turn can be used to predict
TFBSs in DNA sequences (4). This is important as experiments
can only identify TFBSs that are bound in the cell
and state analyzed.
The computational representation of TF binding preferences
has evolved over the years, from simple consensus sequences
to position frequency matrices (PFMs). A PFM
summarizes experimentally determined DNA sequences
bound by an individual TF by counting the number of occurrences
of each nucleotide at each position within aligned
TFBSs. Such matrices can be converted into position weight
matrices (PWMs), also known as position-specific scoring
matrices, which are probabilistic models that can be used to
predict TFBSs in DNA sequences (reviewed in (5)).
PFMs/PWMs have been the standard models for describing
binding preferences of TFs for many years. The
JASPAR database is among the most popular and longest
maintained databases for PFMs and a standard resource
in the field. In particular, the JASPAR CORE collection of
the database, which is the most used, stores non-redundant
TF binding profiles, providing a single representative DNA
binding model per TF decided by expert curators. Exceptionally,
multiple TF-binding profiles are associated to a
TF when it is known to interact with DNA with multiple
distinct sequence preferences, due to differential splicing
for example (6,7). JASPAR was created and persists under
three guiding principles: (i) unrestricted open-access; (ii)
manual curation and non-redundancy of profiles; and (iii)
ease-of-use. The 2016 release of the JASPAR CORE collection
stored 1082 non-redundant and manually curated TFbinding
profiles as PFMs for TFs from six different taxonomic
groups (vertebrates, plants, insects, nematodes, fungi
and urochordata) (8).
An intrinsic limitation to PFMs/PWMs is that they ignore
inter-nucleotide dependencies within TFBSs (9–13).
TF–DNA interaction data derived from next-generation sequencing
assays has improved the computational modeling
of TF binding (14–19). For example, the TF flexible models
(TFFMs) (14), based on first-order hidden Markov models,
capture dinucleotide dependencies within TFBSs and were
introduced in the 2016 release of the JASPAR database.
In this report, we describe the seventh release of JASPAR
(8,20–24), which comes with a major expansion and update
of the CORE collection of TF-binding profiles as PFMs and
TFFMs. These models have been manually assessed by expert
curators who reconciled recent high-throughput data
with available literature and linked the models to the classification
of their TF DBDs from TFClass (2). The CORE collection
expansion is supported by a range of new functionalities
and resources, including PFM clustering, genome-wide
UCSC tracks of predicted TFBSs and fully redesigned user
and programming interfaces.
EXPANSION AND UPDATE OF THE JASPAR CORE
COLLECTION
In this 2018 release of the JASPAR database, we added
355 new PFMs for TFs from plants (270), vertebrates (84)
and insects (1) to the JASPAR CORE collection (Table 1).
Specifically, we added 322 PFMs (262 for plants, a 118%
increase and 60 for vertebrates, an 11% increase) for TF
monomers and dimers that were not previously present in
JASPAR and updated 33 (8 in plants, 3% of JASPAR 2016,
24 in vertebrates, 5% of JASPAR 2016 and 1 in insects).
The PFMs were manually curated using independent external
literature supporting the candidate TF-binding preferences,
as previously described in (23). The curated PFMs
were derived from ChIP-seq (from ReMap (25) and (26–
30)), DAP-seq (31), SMiLE-seq (32), PBM (33) and HTSELEX
(34) experiments. The JASPAR CORE collection
now includes 1404 non-redundant PFMs (579 for vertebrates,
489 for plants, 176 for fungi, 133 for insects, 26 for
nematodes and 1 for urochordata) (Table 1).
We continued with the incorporation of TFFM models,
initiated in JASPAR 2016. In this release of JASPAR, we introduced
316 new TFFMs for vertebrates (95), plants (218)
and Drosophila (3), which represents a 243% increase in the
number of non-redundant TFFMs stored in the JASPAR
CORE collection.
HIERARCHICAL CLUSTERING OF TF-BINDING PRO-
FILES
While the non-redundancy of binding profiles is one of the
guiding principles of JASPAR, TFs with similar DBDs often
have similar binding preferences (35,36). To facilitate the
exploration of similar profiles in the JASPAR CORE collection,
we performed hierarchical clustering of PFMs using
the RSAT matrix-clustering tool (37). Specifically, the
tool was applied to PFMs in each taxon independently as
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D262 Nucleic Acids Research, 2018, Vol. 46, Database issue
Figure 1. JASPAR PFM clustering. (A) Radial tree representing the clusterization of the JASPAR CORE vertebrate PFMs. (B) Zoom in view of the radial
tree where the predicted clusters are highlighted at the branches and the TF classes are indicated with different colors at the leaves. (C) Clicking on a leaf
in the radial tree will open a link to the corresponding motif description page on the JASPAR website (the MA0148.3 profile associated to FOXA1 is
provided here as an example).
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Nucleic Acids Research, 2018, Vol. 46, Database issue D263
Figure 2. Overview of the JASPAR 2018 new web interface with interactive searching activity. (A) A quick and detailed search feature on the homepage.
(B) A responsive table lists the searched profile(s), which can be further selected and added to the cart listed on the right panel for users to perform their
own analyses. (C) A detailed page for the GATA3 matrix profile, which is divided into sub-panels including the profile summary, sequence logo, PFM, TFbinding
information, external links, version information, ChIP-seq centrality, TFFM and other details. (D) The PFM for the GATA3 profile (MA0037.2)
is downloaded in MEME format using the RESTful API.
well as in each TF class per taxon. The clustering results are
provided as radial trees (Figure 1), which can further be explored
through dedicated web pages (http://jaspar.genereg.
net/matrix-clusters).
JASPAR UCSC TRACKS FOR GENOME-WIDE ANALYSES
OF TFBSs
A typical application of JASPAR TF-binding profiles in
gene regulation studies is the identification of TFBSs in
DNA sequences for further analyses. Although, we recognize
that genome-wide PWM-based predictions contain a
high number false positives, we believe that they are a powerful
resource for the research community in the context
of a variety of genomic information, including transcription
start site activity, DNA accessibility, histone marks,
evolutionary conservation or in vivo TF binding (38–46).
To facilitate such integrative analyses, we have performed
TFBS predictions on the human genome using the JASPAR
CORE vertebrate PFMs (see Supplementary Data for details
on the computation). The predicted TFBSs are publicly
available through a UCSC Genome Browser data hub (47)
containing tracks for the human genome assemblies hg19
and hg38 (http://jaspar.genereg.net/genome-tracks/).
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D264 Nucleic Acids Research, 2018, Vol. 46, Database issue
A NEW, POWERFUL AND USER-FRIENDLY WEB IN-
TERFACE
A new web interface
The JASPAR 2018 release comes with a completely redesigned
web interface that meets modern web standards.
This interactive web framework is implemented using
Django, a model-view-controller based web-framework for
Python. We used MySQL as a backend database to store
profile metadata and Bootstrap as a frontend template engine.
We have greatly improved the visibility and usability
of existing functionality, created easier navigation with semantic
URLs, and enhanced browsing and searching. On
the homepage, we provide a dynamic tour of JASPAR 2018,
walking users through the main features of the new website.
A video of the tour is available at http://jaspar.genereg.net/
tour. The database can be browsed for individual collections
by using the navigation links on the left sidebar. Moreover,
it can be searched for each of the six different taxonomic
groups included in the JASPAR CORE collection using
the tabs available on the homepage (Figure 2). TF-binding
profiles can be further filtered through the case insensitive
search option available on the homepage. In addition,
through the ‘Advanced Options’, the search criteria can be
further restricted (Figure 2A). Search results are presented
in a responsive and paginated table along with sequence logos
of the PFMs, which can be selected for download or to
perform a variety of analyses available on the right panel
(Figure 2B). All information in the tables can be downloaded
as comma-separated value files. Profile IDs and sequence
logos can be clicked to view the detailed profile
pages (Figure 2C). PFMs can be downloaded in several formats
including JASPAR, TRANSFAC and MEME (Figure
2D). Furthermore, we have incorporated new features to the
web interface, such as ‘Add to Cart’, where users can add TF
profiles of interest for download or further analyses (Figure
2B). Finally, we have introduced semantic URLs to facilitate
external linking to the detailed pages of individual profiles
(e.g. http://jaspar.genereg.net/matrix/MA0059.1/). We
have implemented a URL redirection mechanism to correctly
direct the links pointing to previous JASPAR URL
patterns from external resources.
RESTful API
In previous releases, the underlying data could be retrieved
as flat files or by using programming language-specific
modules. Associated with this release, we introduced a
RESTful API to access the JASPAR database programmatically
(see https://www.biorxiv.org/content/early/2017/
07/06/160184 for details). The RESTful API enables programmatic
access to JASPAR by most programming languages
and returns data in seven widely used formats:
JSON, JSONP, JASPAR, MEME, PFM, TRANSFAC and
YAML. Further, it provides a browsable interface and access
to the JASPAR motif inference tool for bioinformatics
tool developers. The RESTful API is implemented in
Python using the Django REST Framework and is freely
accessible at http://jaspar.genereg.net/api/. The source code
for the website and RESTful API are freely available at
https://bitbucket.org/CBGR/jaspar under GPL v3 license.
CONCLUSION AND PERSPECTIVES
In this seventh release of the JASPAR database, we continue
our commitment to provide the research community with
high-quality, non-redundant TF-binding profiles for TFs in
six taxa. As in previous releases, we have greatly expanded
the number of available profiles in the database, both for
PFMs and TFFMs. We also greatly improved user experience
through a new easy-to-use website and a RESTful API
that grants universal programmatic access to the database.
Moreover, for the PFMs in the JASPAR CORE collection,
we provide a hierarchical clustering and genome-wide
TFBS predictions for the hg19 and hg38 human genome assemblies
as UCSC tracks.
During the curation process, hundreds of PFMs were
discarded because our curators failed to find any support
from existing literature. As new experiments and data become
available, binding preferences for these TFs will be
considered for JASPAR incorporation. For instance, we reexamined
data from (34) to incorporate seven previously excluded
PFMs into JASPAR 2018. In the future, we would
like to engage the scientific community in the curation process
to increase our capacity to introduce new TF-binding
profiles in JASPAR. We plan to dedicate a specific section of
the website to hosting the profiles that were not introduced
into JASPAR, to encourage researchers to perform experiments
and/or point us to literature that our curators missed
in order to support these profiles. We believe that the engagement
of the scientific community to support JASPAR
will further improve our capacity to expand the collection
of high quality TF-binding profiles.
SUPPLEMENTARY DATA
Supplementary Data are available at NAR Online.
ACKNOWLEDGEMENTS
We thank the scientific community for performing experimental
assays of TF–DNA interactions and for publicly
releasing the data. We thank Georgios Magklaras and
his team for IT support. We thank Jos´e Manuel Franco
for sharing the plant PBM data, Jens De Ceukeleire for
help with plant ChIP-seq data processing and Jos´e Luis
Villanueva-Ca˜nas for sharing the Drosophila TFFMs prior
to publication. We thank Rachelle Farkas for proofreading
the manuscript.
FUNDING
Norwegian Research Council, Helse Sør-Øst, and University
of Oslo through the Centre for Molecular Medicine
Norway (NCMM) (to A.M., M.G., A.K.); Genome
Canada and Canadian Institutes of Health Research (OnTarget
Grants) [255ONT and BOP-149430 to W.W.W., O.F.,
R.v.d.L., D.J.A.]; Natural Sciences and Engineering Research
Council of Canada (Discovery Grant) [RGPIN-
2017–06824 to W.W.W.]; Weston Brain Institute [20R74681
to O.F.]; Agence Nationale de la Recherche [ANR-10LABX-49–01
to F.P., A.S.]; IDEX graduate schoool
(to A.S.); CNRS (to A.B., F.P.); Research Foundation–
Flanders Grant [G001015N to S.R.K.]; French Ministry
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Nucleic Acids Research, 2018, Vol. 46, Database issue D265
of Higher Education and Research (MESR) PhD Fellowship
(to J.A.C.-M.); Lundbeck Foundation (to A.S.); Independent
Research Fund Denmark (to A.S.); Innovation
Fund Denmark (to A.S.); Elixir Denmark (to A.S.); Wellcome
Trust [106954 to G.T., D.B., B.L.]; Biotechnology
and Biological Sciences Research Council [BB/N023358/1
to G.T., D.B., B.L.]; Medical Research Council UK
[MC UP 1102/1 to G.T., D.B., B.L.]. The open access publication
charge for this paper has been waived by Oxford
University Press - NAR Editorial Board members are entitled
to one free paper per year in recognition of their work
on behalf of the journal.
Conflict of interest statement. None declared.
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