TY - JOUR
T1 - Jaspar 2026
T2 - expansion of transcription factor binding profiles and integration of deep learning models
AU - Ovek baydar, Damla
AU - Rauluseviciute, Ieva
AU - Aronsen, Dina R.
AU - Blanc-Mathieu, Romain
AU - Bonthuis, Ine
AU - De beukelaer, Herman
AU - Ferenc, Katalin
AU - Jegou, Alice
AU - Kumar, Vipin
AU - Lemma, Roza Berhanu
AU - Lucas, Jeremy
AU - Pochon, Mathis
AU - Yun, Chang M.
AU - Ramalingam, Vivekanandan
AU - Deshpande, Salil Sanjay
AU - Patel, Aman
AU - Marinov, Georgi k
AU - Wang, Austin T.
AU - Aguirre, Alejandro
AU - Castro-Mondragon, Jaime a
AU - Baranasic, Damir
AU - Cheneby, Jeanne
AU - Gundersen, Sveinung
AU - Johansen, Morten
AU - Khan, Aziz
AU - Kuijjer, Marieke L.
AU - Hovig, Eivind
AU - Lenhard, Boris
AU - Sandelin, Albin
AU - Vandepoele, Klaas
AU - Wasserman, Wyeth w
AU - Parcy, Francois
AU - Kundaje, Anshul
AU - Mathelier, Anthony
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - Mouse
U2 - 10.1093/nar/gkaf1209
DO - 10.1093/nar/gkaf1209
M3 - Journal article
C2 - 41325984
SN - 0305-1048
VL - 54
SP - D184–D193
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - D1
ER -