Item

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

Ovek Baydar, Damla
; 
Rauluseviciute, Ieva
; 
Aronsen, Dina R.
; 
Blanc-Mathieu, Romain
; 
Bonthuis, Ine
; 
de Beukelaer, Herman
; 
Ferenc, Katalin
; 
Jegou, Alice
; 
Kumar, Vipin
; 
Lemma, Roza Berhanu
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Author
Ovek Baydar, Damla
Rauluseviciute, Ieva
Aronsen, Dina R.
Blanc-Mathieu, Romain
Bonthuis, Ine
de Beukelaer, Herman
Ferenc, Katalin
Jegou, Alice
Kumar, Vipin
Lemma, Roza Berhanu
Lucas, Jérémy
Pochon, Mathis
Yun, Chang M.
Ramalingam, Vivekanandan
Deshpande, Salil Sanjay
Patel, Aman
Marinov, Georgi K.
Wang, Austin T.
Aguirre, Alejandro
Castro-Mondragon, Jaime A.
Baranasic, Damir
Chèneby, Jeanne
Gundersen, Sveinung
Johansen, Morten
Khan, Aziz
Kuijjer, Marieke L.
Hovig, Eivind
Lenhard, Boris
Sandelin, Albin
Vandepoele, Klaas
Wasserman, Wyeth W.
Parcy, François
Kundaje, Anshul
Mathelier, Anthony
Supervisor
Department
Computational Biology
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Type
Journal article
Date
2025
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Language
English
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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.
Citation
D. Ovek Baydar et al., “JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models,” Nucleic Acids Res, vol. 1, no. 1256879, pp. 13–14, 2013, doi: 10.1093/NAR/GKAF1209
Source
Nucleic Acids Research
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Keywords
Transcription Factors, Gene Regulation, Binding Motifs, Deep Learning Models, Genomic Databases
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Publisher
Oxford University Press
DOI
10.1093/nar/gkaf1209
Additional links
https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkaf1209/8343514
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