JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models

JASPAR (https://jaspar.elixir.no/) is an open-access database that has provided high-quality, manually curated, and non-redundant DNA binding profiles for transcription factors (TFs) as position frequency matrices (PFMs) for over 20 years. We expanded the CORE (306 new profiles, 12% increase) and UNVALIDATED (433, 60% increase) collections with new PFMs and updated 13 existing profiles. We updated the TF binding site predictions and genome tracks for eight species. TF binding profile clusters and familial TF binding sites were updated accordingly. We integrate the inMOTIFin software to easily simulate regulatory sequences using JASPAR PFMs. To enrich TFs' annotations, we provide scientific literature-based human TF target information. Notably, this release features a deep learning (DL) collection, providing a paradigm shift in modeling and characterizing TF-DNA interactions with 1259 BPNet models trained on Homo sapiens ENCODE chromatin immunoprecipitation followed by sequencing (ChIP-seq) datasets from 240 TFs and interpreted to reveal predictive motif patterns for the models. The motifs associated with the same TF were clustered to provide a summary of the binding properties, resulting in 240 primary and 113 alternative motif patterns in the DL collection. The JASPAR 2026 collections lay a foundation for future endeavors in genomic research, serving the scientific community in uncovering the mechanisms of gene regulation.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-12-02
DOI
https://doi.org/10.1093/nar/gkaf1209
Citations
13
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
10.48

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article

JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models

Aman Patel, Georgi K. Marinov, François Parcy, Sveinung Gundersen et al.
13 citations
Nucleic Acids Research
Genomics and Chromatin Dynamics
10.48
article

JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models

Aman Patel, Georgi K. Marinov, François Parcy, Sveinung Gundersen, Jeanne Chèneby, Wyeth W. Wasserman, Albin Sandelin, Austin T. Wang, Ieva Rauluševičiūtė, Romain Blanc‐Mathieu, Damir Baranas̆ić, Damla Ovek, Aziz Khan, Vivekanandan Ramalingam, Boris Lenhard, Klaas Vandepoele, Dina Ruud Aronsen, Chang Min Yun, Katalin Ferenc, Jérémy Lucas, Herman De Beukelaer, Jaime A. Castro-Mondragón, Alejandro Aguirre, Morten Johansen, Marieke L. Kuijjer, Eivind Hovig, Anshul Kundaje, Anthony Mathelier, Roza Berhanu Lemma, Vipin Kumar, Salil Deshpande, Mathis Pochon, Ine Bonthuis, Alice Jegou
article en
13 citations

Abstract

JASPAR (https://jaspar.elixir.no/) is an open-access database that has provided high-quality, manually curated, and non-redundant DNA binding profiles for transcription factors (TFs) as position frequency matrices (PFMs) for over 20 years. We expanded the CORE (306 new profiles, 12% increase) and UNVALIDATED (433, 60% increase) collections with new PFMs and updated 13 existing profiles. We updated the TF binding site predictions and genome tracks for eight species. TF binding profile clusters and familial TF binding sites were updated accordingly. We integrate the inMOTIFin software to easily simulate regulatory sequences using JASPAR PFMs. To enrich TFs' annotations, we provide scientific literature-based human TF target information. Notably, this release features a deep learning (DL) collection, providing a paradigm shift in modeling and characterizing TF-DNA interactions with 1259 BPNet models trained on Homo sapiens ENCODE chromatin immunoprecipitation followed by sequencing (ChIP-seq) datasets from 240 TFs and interpreted to reveal predictive motif patterns for the models. The motifs associated with the same TF were clustered to provide a summary of the binding properties, resulting in 240 primary and 113 alternative motif patterns in the DL collection. The JASPAR 2026 collections lay a foundation for future endeavors in genomic research, serving the scientific community in uncovering the mechanisms of gene regulation.

Nucleic Acids ResearchVol. 54(D1)
University of Copenhagen (DK), Oslo University Hospital (NO), Centre National de la Recherche Scientifique (FR), University of Helsinki (FI), University of British Columbia (CA), University of Oslo (NO), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Akershus University Hospital (NO), Hammersmith Hospital (GB), CEA Grenoble (FR), Ghent University (BE), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), VIB-UGent Center for Plant Systems Biology (BE), Laboratoire Physiologie Cellulaire & Végétale (FR), Mohamed bin Zayed University of Artificial Intelligence (AE), Ruđer Bošković Institute (HR), BC Children's Hospital (CA), Institute of Mathematical Statistics (US), MRC London Institute of Medical Sciences (GB), Université Grenoble Alpes (FR), Stanford University (US)
Agence Nationale de la Recherche, Universitetet i Oslo, Norges Forskningsråd, Zayed University, National Institutes of Health, Livsvitenskap, Universitetet i Oslo
Openalex Percentile: Top 1%
Genomics and Chromatin Dynamics
10.48
DOIOpen Access PDFOpenAlex
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