Anthony Mathelier

• Nothnagel, Patrizia Maria Christiane; Meslin, Paul-Arthur Richard; Wik, Jonas Aakre; Dufour, Damien; Strøm, Yunna Erika & Bjørås, Magnar [Vis alle 11 forfattere av denne artikkelen] (2026). Transient SUMOylation inhibition in human pre-adipocytes stably imprints a transcriptional beiging fate. Nucleic Acids Research (NAR). ISSN 0305-1048. 54(6), s. 1–22. doi: 10.1093/nar/gkag232. Fulltekst i vitenarkiv Vis sammendrag

  SUMOylation regulates chromatin states and transcriptional programs that preserve cellular identity, yet how perturbation of the SUMOylation pathway impacts adipocyte plasticity remains unclear. Here, we show that brief pharmacologic inhibition of SUMOylation in human pre-adipocytes using TAK-981 primes stable de novo beige differentiation in the presence of the PPARG agonist rosiglitazone. Transient TAK-981 exposure produces changes in the transcriptome and metabolism of mature adipocytes, including robust induction of canonical beiging markers like UCP1 and increased mitochondrial respiration. Mechanistically, ATAC-seq and RNA-sequencing revealed immediate chromatin remodeling and early mobilization of CEBP family members, followed by stable activation of CEBPA and PPARG regulatory networks. ChIP experiments demonstrated loss of H3K27me3 and gain of H3K27ac at PPAR response elements at thermogenic enhancers, and increased PPARG occupancy across the UCP1 regulatory unit. This mechanism is enforced by enhanced cAMP-PKA-p38 signaling and stabilization of beiging transcription activators. We propose that transient relief of SUMO-mediated repression unlocks dominant regulatory units, notably the UCP1 enhancer cluster, producing a monomorphic reprogramming toward adaptive thermogenesis. These findings identify SUMOylation as a reversible epigenetic barrier to adipocyte beiging and suggest that temporally controlled SUMO pathway inhibition combined with PPARG activation could be exploited to modulate adipose tissue thermogenic capacity.

• Ferenc, Katalin Terezia; Martini, Lorenzo; Rauluseviciute, Ieva; Sandve, Geir Kjetil Ferkingstad & Mathelier, Anthony (2026). inMOTIFin: a lightweight end-to-end simulation software for regulatory sequences. Bioinformatics. ISSN 1367-4803. doi: 10.1093/bioinformatics/btag026. Fulltekst i vitenarkiv Vis sammendrag

  The accurate development, assessment, interpretation, and benchmarking of bioinformatics frameworks for analyzing transcriptional regulatory grammars rely on controlled simulations to validate the underlying methods. However, existing simulators often lack end-to-end flexibility or ease of integration, which limits their practical use. We present inMOTIFin, a lightweight, modular, and user-friendly Python-based software that addresses these gaps by providing versatile and efficient simulation and modification of DNA regulatory sequences. inMOTIFin enables users to simulate or modify regulatory sequences efficiently for the customizable generation of motifs and insertion of motif instances with precise control over their positions, co-occurrences, and spacing, as well as direct modification of real sequences, facilitating a comprehensive evaluation of motif-based methods and interpretation tools. We demonstrate inMOTIFin applications for the assessment of de novo motif discovery, the analysis of transcription factor cooperativity, and the support of explainability analyses for deep learning models. inMOTIFin ensures robust and reproducible analyses for studying transcriptional regulatory grammars.

• Kumar, Vipin; Rossini, Roberto; Paulsen, Jonas & Mathelier, Anthony (2025). BHiCect 2.0: Multi-resolution clustering of Hi-C data. EarthArXiv preprint platform. doi: 10.48550/ARXIV.2512.17512. Fulltekst i vitenarkiv
• Puig, Rafael Riudavets; Brorson, Ina Skaara; O’Mahony, Denise; Kristensen, Vessela N. & Mathelier, Anthony (2025). HiFIseek: gene-specific enrichment of high-impact mutations in associated genomic regions. bioRxiv (preprint article). doi: 10.1101/2025.06.12.659305. Fulltekst i vitenarkiv Vis sammendrag

  Transcription is regulated through the sequence-specific binding of transcription factors (TFs) to cis-regulatory regions (CRRs). Although scattered along the genome, multiple CRRs are brought in close spatial proximity to the genes they regulate through the formation of DNA loops. The sequence component of transcriptional regulation suggests that DNA variants in CRRs could disrupt TF-DNA interactions and gene regulatory networks through a cascading effect. To date, only a few cases of recurrent cis-regulatory variants have been described. As an alternative to variant recurrence, some methods utilize genomic annotations that indicate the functional impact (FI) of a variant and the CRRs of each gene to detect the enrichment of high-impact cis-regulatory variants (CRVs). However, the agreement across the different associations and FI scoring methods remains unexplored. This work demonstrates that gene-CRR and FI scoring methods exhibit little consensus, highlighting the impact of the choice of a specific CRR-score combination in a given analysis. In addition, we demonstrate that cancer genes exhibit a higher frequency of FI variants compared to non-cancer genes. Based on this, we developed HiFIseek, a Snakemake pipeline exploring the enrichment of FI variants in associated genomic regions using all region-score combinations and two enrichment detection methods. We apply HiFIseek to detect genes exhibiting high FI CRVs in eight cancer cohorts and a set of breast cancer risk-associated single-nucleotide polymorphisms (SNPs). In the cancer cohorts, we observe a small degree of agreement across CRR-score combinations. Although HiFIseek detected known cancer-related genes with FI CRVs, most of them did not show significant changes in their expression. In the SNPs cohort, HiFIseek found small consensus across CRR-score combinations. However, one of the combinations returned 18 known cancer-related genes, including BRCA1 , showing an enrichment of high-impact CRVs.

• Nothnagel, Patrizia Maria Christiane; Meslin, Paul-Arthur Richard; Wik, Jonas Aakre; Strøm, Yunna Erika; Bjørås, Magnar & Enserink, Jorrit [Vis alle 10 forfattere av denne artikkelen] (2025). Transient SUMOylation Inhibition In Human Pre-adipocytes Stably Imprints a Transcriptional Beiging Fate. bioRxiv (preprint article). 54(6). doi: 10.1101/2025.03.07.642034. Fulltekst i vitenarkiv Vis sammendrag

  Abstract SUMOylation regulates chromatin states and transcriptional programs that preserve cellular identity, yet how transient perturbation of the SUMO pathway impacts adipocyte plasticity remains unclear. Here we show that brief pharmacologic inhibition of SUMO conjugation in human pre-adipocytes using TAK-981 primes stable de novo beige differentiation in the presence of the PPARG agonist rosiglitazone. Transient TAK-981 exposure before adipogenic induction produces long-lasting changes in the transcriptome and metabolism of mature adipocytes, including robust induction of canonical beiging markers like UCP1 and increased mitochondrial respiration. Mechanistically, ATAC-seq and transcription factor footprinting revealed immediate and durable chromatin remodeling and early mobilization of CEBP family members, followed by stable activation of CEBPA and PPARG regulatory networks. ChIP experiments demonstrated loss of H3K27me3 and gain of H3K27ac at PPAR response elements within key thermogenic enhancers, with increased PPARG occupancy across the UCP1 regulatory unit. This mechanism is enforced by enhanced cAMP-PKA-p38 signaling, and stabilization of beiging transcriptional activators. Our data support a model in which transient relief of SUMO-mediated repression unlocks dominant regulatory units, notably the UCP1 enhancer cluster, producing a monomorphic, cell type specific reprogramming toward adaptive thermogenesis. These findings identify SUMOylation as a reversible epigenetic barrier to adipocyte beiging and suggest that temporally controlled SUMO pathway inhibition combined with PPARG activation could be exploited to modulate adipose tissue thermogenic capacity. Graphical abstract SUMOylation restricts de novo differentiation of pre-adipocytes into beige adipocytes by repressing cAMP signaling and preventing epigenetic and transcriptional reprogramming of white adipocytes.

• Zeitlinger, Julia; Roy, Sushmita; Ay, Ferhat; Mathelier, Anthony; Medina-Rivera, Alejandra & Mahony, Shaun [Vis alle 8 forfattere av denne artikkelen] (2025). Perspective on recent developments and challenges in regulatory and systems genomics. Bioinformatics Advances. 5(1). doi: 10.1093/bioadv/vbaf106. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Summary: Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective, we discuss recent computational progress and challenges toward solving this fundamental problem. We describe how cis-regulatory elements are mapped with various genomics assays and how studies of the 3D chromatin organization could help identifying long-range regulatory effects. We discuss how the cis-regulatory sequence rules can be learned and interpreted with sequence-to-function neural networks, with the goal of identifying genetic variants in human disease. We also describe current methods for mapping gene regulatory networks to describe biological processes. We point out current gaps in knowledge along with technical limitations and benchmarking challenges of computational methods. Finally, we discuss newly emerging technologies, such as spatial transcriptomics, and outline strategies for creating a more general model of the cis-regulatory code that is more broadly applicable across cell types and individuals.

• Baydar, Damla Övek; Rauluseviciute, Ieva; Aronsen, Dina Ruud; Blanc-Mathieu, Romain; Bonthuis, Ine & de Beukelaer, Herman [Vis alle 34 forfattere av denne artikkelen] (2025). JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models. Nucleic Acids Research (NAR). ISSN 0305-1048. 54(D1), s. D184–D193. doi: 10.1093/nar/gkaf1209. Fulltekst i vitenarkiv Vis sammendrag

  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.

• Pop, Romana Tabita; Hsieh, Ping-Han; Belova, Tatiana; Mathelier, Anthony & Kuijjer, Marieke (2025). Gene regulatory network integration with multi-omics data enhances survival predictions in cancer. Briefings in Bioinformatics. ISSN 1467-5463. 26(4). doi: 10.1093/bib/bbaf315. Fulltekst i vitenarkiv Vis sammendrag

  The emergence of high-throughput omics technologies has resulted in their wide application to cancer studies, greatly increasing our understanding of the disruptions occurring at different molecular levels. To fully harness these data, integrative approaches have emerged as essential tools, enabling the combination of multiple omics modalities to uncover disease mechanisms. However, many such approaches overlook gene regulatory mechanisms, which play a central role in the development and progression of cancer. Patient-specific gene regulatory networks (GRNs), representing interactions between regulators (such as transcription factors) and their target genes in each individual tumour, offer a powerful framework to bridge this gap and investigate the regulatory landscape of cancer. In this study, we introduce a novel approach for integrating patient-specific GRNs with multi-omic data and assess whether their inclusion in joint dimensionality reduction models improves survival prediction across multiple cancer types. By applying our method on ten cancer datasets from The Cancer Genome Atlas, we demonstrate that incorporating GRNs enhances associations with patient survival in several cancer types. Focusing on liver cancer, with validation in independent data, our methodology identifies potential mechanisms of gene regulatory dysregulation associated with cancer progression. These were linked to dysregulated fatty acid metabolism, and identified JUND as a potential novel transcriptional regulator driving these processes. Our findings highlight the value of network-based multi-omics integration for uncovering clinically relevant regulatory mechanisms and improving our understanding of cancer biology at the patient-specific level.

• Ferenc, Katalin Terezia; Rauluseviciute, Ieva; Hovan, Ladislav; Kumar, Vipin; Kuijjer, Marieke & Mathelier, Anthony (2024). Improving bioinformatics software quality through teamwork. Bioinformatics. ISSN 1367-4803. 40(11). doi: 10.1093/bioinformatics/btae632. Fulltekst i vitenarkiv Vis sammendrag

  Since high-throughput techniques became a staple in biological science laboratories, computational algorithms, and scientific software have boomed. However, the development of bioinformatics software usually lacks software development quality standards. The resulting software code is hard to test, reuse, and maintain. We believe that the root of inefficiency in implementing the best software development practices in academic settings is the individualistic approach, which has traditionally been the norm for recognizing scientific achievements and, by extension, for developing specialized software. Software development is a collective effort in most software-heavy endeavors. Indeed, the literature suggests teamwork directly impacts code quality through knowledge sharing, collective software development, and established coding standards. In our computational biology research groups, we sustainably involve all group members in learning, sharing, and discussing software development while maintaining the personal ownership of research projects and related software products. We found that group members involved in this endeavor improved their coding skills, became more efficient bioinformaticians, and obtained detailed knowledge about their peers’ work, triggering new collaborative projects. We strongly advocate for improving software development culture within bioinformatics through collective effort in computational biology groups or institutes with three or more bioinformaticians.

• Ankill, Jørgen; Zhao, Zhi; Tekpli, Xavier; Kure, Elin Wenche Hegland; Kristensen, Vessela N. & Mathelier, Anthony [Vis alle 7 forfattere av denne artikkelen] (2024). Integrative pan-cancer analysis reveals a common architecture of dysregulated transcriptional networks characterized by loss of enhancer methylation. PLoS Computational Biology. ISSN 1553-734X. 20:e1012565(11), s. 1–33. doi: 10.1371/journal.pcbi.1012565. Fulltekst i vitenarkiv Vis sammendrag

  Aberrant DNA methylation contributes to gene expression deregulation in cancer. However, these alterations’ precise regulatory role and clinical implications are still not fully understood. In this study, we performed expression-methylation Quantitative Trait Loci (emQTL) analysis to identify deregulated cancer-driving transcriptional networks linked to CpG demethylation pan-cancer. By analyzing 33 cancer types from The Cancer Genome Atlas, we identified and confirmed significant correlations between CpG methylation and gene expression (emQTL) in cis and trans, both across and within cancer types. Bipartite network analysis of the emQTL revealed groups of CpGs and genes related to important biological processes involved in carcinogenesis including proliferation, metabolism and hormone-signaling. These bipartite communities were characterized by loss of enhancer methylation in specific transcription factor binding regions (TFBRs) and the CpGs were topologically linked to upregulated genes through chromatin loops. Penalized Cox regression analysis showed a significant prognostic impact of the pan-cancer emQTL in many cancer types. Taken together, our integrative pan-cancer analysis reveals a common architecture where hallmark cancer-driving functions are affected by the loss of enhancer methylation and may be epigenetically regulated.

• Rauluseviciute, Ieva; Launay, Timothée; Barzaghi, Guido; Nikumbh, Sarvesh; Lenhard, Boris & Krebs, Arnaud Regis [Vis alle 8 forfattere av denne artikkelen] (2024). Identification of transcription factor co-binding patterns with non-negative matrix factorization. Nucleic Acids Research (NAR). ISSN 0305-1048. 52(18), s. e85–e85. doi: 10.1093/nar/gkae743. Fulltekst i vitenarkiv Vis sammendrag

  Transcription factor (TF) binding to DNA is critical to transcription regulation. Although the binding properties of numerous individual TFs are well-documented, a more detailed comprehension of how TFs interact cooperatively with DNA is required. We present COBIND, a novel method based on non-negative matrix factorization (NMF) to identify TF co-binding patterns automatically. COBIND applies NMF to one-hot encoded regions flanking known TF binding sites (TFBSs) to pinpoint enriched DNA patterns at fixed distances. We applied COBIND to 5699 TFBS datasets from UniBind for 401 TFs in seven species. The method uncovered already established co-binding patterns and new co-binding configurations not yet reported in the literature and inferred through motif similarity and protein-protein interaction knowledge. Our extensive analyses across species revealed that 67% of the TFs shared a co-binding motif with other TFs from the same structural family. The co-binding patterns captured by COBIND are likely functionally relevant as they harbor higher evolutionarily conservation than isolated TFBSs. Open chromatin data from matching human cell lines further supported the co-binding predictions. Finally, we used single-molecule footprinting data from mouse embryonic stem cells to confirm that the COBIND-predicted co-binding events associated with some TFs likely occurred on the same DNA molecules.

• Shahrouzi, Parastoo; Forouz, Farzaneh; Mathelier, Anthony; Kristensen, Vessela N. & Duijf, Pascal Hubertus Gerardus (2024). Copy number alterations: a catastrophic orchestration of the breast cancer genome. Trends in Molecular Medicine. ISSN 1471-4914. 30(8), s. 750–764. doi: 10.1016/j.molmed.2024.04.017. Fulltekst i vitenarkiv Vis sammendrag

  Breast cancer (BCa) is a prevalent malignancy that predominantly affects women around the world. Somatic copy number alterations (CNAs) are tumor-specific amplifications or deletions of DNA segments that often drive BCa development and therapy resistance. Hence, the complex patterns of CNAs complement BCa classification systems. In addition, understanding the precise contributions of CNAs is essential for tailoring personalized treatment approaches. This review highlights how tumor evolution drives the acquisition of CNAs, which in turn shape the genomic landscapes of BCas. It also discusses advanced methodologies for identifying recurrent CNAs, studying CNAs in BCa and their clinical impact.

• Lind, Sara Marie; Sletten, Marit; Hellenes, Mona; Mathelier, Anthony; Tekpli, Xavier & Tinholt, Mari [Vis alle 7 forfattere av denne artikkelen] (2024). Coagulation factor V in breast cancer: a p53-regulated tumor suppressor and predictive marker for treatment response to chemotherapy. Journal of Thrombosis and Haemostasis. ISSN 1538-7933. 22(6), s. 1569–1582. doi: 10.1016/j.jtha.2024.02.008. Fulltekst i vitenarkiv Vis sammendrag

  Background Patients with cancer are at an increased risk of developing coagulation complications, and chemotherapy treatment increases the risk. Tumor progression is closely linked to the hemostatic system. Breast cancer tumors express coagulation factor V (FV), an essential factor in blood coagulation. The functional role of FV during treatment with chemotherapy is poorly understood and was explored in this study. Objectives We aimed to investigate the role of FV in breast cancer progression by exploring associations with treatment response, gene regulation, and the functional effects of FV. Methods The receiver operating characteristic plotter was used to explore the predictive value of FV mRNA (F5) expression for treatment with FEC (5-fluorouracil, anthracycline, and cyclophosphamide). Breast cancer cohorts were analyzed to study treatment response to FEC. The effect of chemotherapy on F5 expression, the regulation of F5, and the functional effects of FV dependent and independent of chemotherapy were studied in breast cancer cell lines. Results F5 tumor expression was significantly higher in responders to FEC than in nonresponders. In vitro experiments revealed that anthracycline treatment increased the expression of F5. Inhibition and knockdown of p53 reduced the anthracycline-induced F5 expression. Mutation of a p53 half-site (c.158+1541/158+1564) in a luciferase plasmid reduced luciferase activity, suggesting that p53 plays a role in regulating F5. FV overexpression increased apoptosis and reduced proliferation slightly during anthracycline treatment. Conclusion Our study identified F5 as a p53-regulated tumor suppressor candidate and a promising marker for response to chemotherapy. FV may have functional effects that are therapeutically relevant in breast cancer.

• Hsieh, Ping-Han; Hsiao, Ru-Xiu; Ferenc, Katalin; Mathelier, Anthony; Burkholz, Rebekka & Chen, Chien-Yu [Vis alle 9 forfattere av denne artikkelen] (2024). CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell data. arXiv.org. ISSN 2331-8422. doi: 10.48550/arXiv.2405.18655. Fulltekst i vitenarkiv
• Rauluseviciute, Ieva; Riudavets-Puig, Rafael; Blanc-Mathieu, Romain; Mondragon, Jaime Abraham Castro; Ferenc, Katalin Terezia & Kumar, Vipin [Vis alle 20 forfattere av denne artikkelen] (2023). JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Research (NAR). ISSN 0305-1048. 52(D1), s. D174–D182. doi: 10.1093/nar/gkad1059. Fulltekst i vitenarkiv Vis sammendrag

  JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs’ structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF binding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.

• Fornes, Oriol; Av-Shalom, Tamar V; Korecki, Andrea J; Farkas, Rachelle A; Arenillas, David J & Mathelier, Anthony [Vis alle 8 forfattere av denne artikkelen] (2023). OnTarget: In silico design of MiniPromoters for targeted delivery of expression. Nucleic Acids Research (NAR). ISSN 0305-1048. 51(W1), s. W379–W386. doi: 10.1093/nar/gkad375. Fulltekst i vitenarkiv Vis sammendrag

  Abstract MiniPromoters, or compact promoters, are short DNA sequences that can drive expression in specific cells and tissues. While broadly useful, they are of high relevance to gene therapy due to their role in enabling precise control of where a therapeutic gene will be expressed. Here, we present OnTarget (http://ontarget.cmmt.ubc.ca), a webserver that streamlines the MiniPromoter design process. Users only need to specify a gene of interest or custom genomic coordinates on which to focus the identification of promoters and enhancers, and can also provide relevant cell-type-specific genomic evidence (e.g. accessible chromatin regions, histone modifications, etc.). OnTarget combines the provided data with internal data to identify candidate promoters and enhancers and design MiniPromoters. To illustrate the utility of OnTarget, we designed and characterized two MiniPromoters targeting different cell populations relevant to Parkinson Disease.

• Rauluseviciute, Ieva; Launay, Timothée; Barzaghi, Guido; Nikumbh, Sarvesh; Lenhard, Boris & Krebs, Arnaud Regis [Vis alle 8 forfattere av denne artikkelen] (2023). Identification of transcription factor co-binding patterns with non-negative matrix factorization. BioRxiv. ISSN 0362-4331. doi: 10.1101/2023.04.28.538684. Fulltekst i vitenarkiv
• Bjørklund, Sunniva; Aure, Miriam Ragle; Häkkinen, Jari; Vallon-Christersson, Johan; Kumar, Surendra & Evensen, Katrine Bull [Vis alle 34 forfattere av denne artikkelen] (2022). Subtype and cell type specific expression of lncRNAs provide insight into breast cancer. Communications Biology. 5(1), s. 1–14. doi: 10.1038/s42003-022-03559-7. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.

• Rossini, Roberto; Kumar, Vipin; Mathelier, Anthony; Rognes, Torbjørn & Paulsen, Jonas (2022). MoDLE: high-performance stochastic modeling of DNA loop extrusion interactions. Genome Biology. ISSN 1465-6906. 23(1). doi: 10.1186/s13059-022-02815-7. Fulltekst i vitenarkiv Vis sammendrag

  DNA loop extrusion emerges as a key process establishing genome structure and function. We introduce MoDLE, a computational tool for fast, stochastic modeling of molecular contacts from DNA loop extrusion capable of simulating realistic contact patterns genome wide in a few minutes. MoDLE accurately simulates contact maps in concordance with existing molecular dynamics approaches and with Micro-C data and does so orders of magnitude faster than existing approaches. MoDLE runs efficiently on machines ranging from laptops to high performance computing clusters and opens up for exploratory and predictive modeling of 3D genome structure in a wide range of settings.

• Lemma, Roza Berhanu; Fleischer, Thomas; Martinsen, Emily; Ledsaak, Marit; Kristensen, Vessela N. & Eskeland, Ragnhild [Vis alle 8 forfattere av denne artikkelen] (2022). Pioneer transcription factors are associated with the modulation of DNA methylation patterns across cancers. Epigenetics & Chromatin. 15. doi: 10.1186/s13072-022-00444-9. Fulltekst i vitenarkiv Vis sammendrag

  Methylation of cytosines on DNA is a prominent modification associated with gene expression regulation. Aberrant DNA methylation patterns have recurrently been linked to dysregulation of the regulatory program in cancer cells. To shed light on the underlying molecular mechanism driving this process, we hypothesised that aberrant methylation patterns could be controlled by the binding of specific transcription factors (TFs) across cancer types. By combining DNA methylation arrays and gene expression data with TF binding sites (TFBSs), we explored the interplay between TF binding and DNA methylation in 19 cancer types. We performed emQTL (expression–methylation quantitative trait loci) analyses independently in each cancer type and identified 13 TFs whose expression levels are correlated with local DNA methylation patterns around their binding sites in at least 2 cancer types. The 13 TFs are mainly associated with local demethylation and are enriched for pioneer function, suggesting a specific role for these TFs in modulating chromatin structure and transcription in cancer patients. Furthermore, we confirmed that de novo methylation is precluded across cancers at CpGs lying in genomic regions enriched for TF binding signatures associated with SP1, CTCF, NRF1, GABPA, KLF9, and/or YY1. The modulation of DNA methylation associated with TF binding was observed at cis-regulatory regions controlling immune- and cancer-associated pathways, corroborating that the emQTL signals were derived from both cancer and tumor-infiltrating cells. As a case example, we experimentally confirmed that FOXA1 knock-down is associated with higher methylation in regions bound by FOXA1 in breast cancer MCF-7 cells. Finally, we reported physical interactions between FOXA1 with TET1 and TET2 both in an in vitro setup and in vivo at physiological levels in MCF-7 cells, adding further support for FOXA1 attracting TET1 and TET2 to induce local demethylation in cancer cells.

• Rossini, Roberto; Kumar, Vipin; Rognes, Torbjørn; Mathelier, Anthony & Paulsen, Jonas (2022). MoDLE: High-performance stochastic modeling of DNA loop extrusion interactions. BioRxiv. ISSN 0362-4331. doi: 10.1101/2022.04.13.488157. Fulltekst i vitenarkiv
• Mondragon, Jaime Abraham Castro; Aure, Miriam Ragle; Lingjærde, Ole Christian; Langerød, Anita; Martens, John WM & Børresen-Dale, Anne-Lise [Vis alle 8 forfattere av denne artikkelen] (2022). Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers. Nucleic Acids Research (NAR). ISSN 0305-1048. 50(21), s. 12131–12148. doi: 10.1093/nar/gkac1143. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells’ regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells’ regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.

• Strømme, Jonas Meier; Johannessen, Bjarne; Kidd, Susanne Gundersen; Bogaard, Mari; Carm, Kristina Totland & Zhang, Xiaokang [Vis alle 12 forfattere av denne artikkelen] (2022). Expressed prognostic biomarkers for primary prostate cancer independent of multifocality and transcriptome heterogeneity. Cancer Gene Therapy. ISSN 0929-1903. 29(8-9), s. 1276–1284. doi: 10.1038/s41417-022-00444-7. Fulltekst i vitenarkiv Vis sammendrag

  The majority of prostate cancer patients are diagnosed with multiple primary malignant foci. The distinct foci are exceptionally heterogeneous with regard to DNA mutations, but whether this is recapitulated at the transcriptome level remains unknown. In this study, inter- and intrafocal heterogeneity has been assessed by whole-transcriptome sequencing of 87 tissue samples from 23 patients with localized prostate cancer treated with radical prostatectomy. From each patient, multiple samples were taken from one or more malignant foci, in addition to one sample from benign prostate tissue. Transcriptomic profiles of different malignant foci from the same patient showed a similar level of heterogeneity as tumors from different patients. This applies to expression of genes, fusion genes, and somatic mutations. Within-patient pair-wise analyses identified expression patterns linked to ETS status and extraprostatic extension. A set of 62 genes were found with low intrapatient heterogeneity and high interpatient heterogeneity, retaining stable expression profiles across foci within the same patient. Among these, 16 genes are associated with biochemical recurrence in a separately published study and are therefore nominated as biomarkers with prognostic value regardless of which malignant focus is sampled. In conclusion, an extensive heterogeneity in multifocal prostate cancer is confirmed at the gene expression level. Diagnostic biomarkers were identified for ETS positive samples and samples from extraprostatic extensions. Finally, prognostic biomarkers independent of multifocal heterogeneity were found.

• Mondragon, Jaime Abraham Castro; Puig, Rafael Riudavets; Rauluseviciute, Ieva; Lemma, Roza Berhanu; Turchi, Laura & Blanc-Mathieu, Romain [Vis alle 23 forfattere av denne artikkelen] (2021). JASPAR 2022: the 9th release of the open-acess database of transcription factor binding profiles. Nucleic Acids Research (NAR). ISSN 0305-1048. doi: 10.1093/nar/gkab1113. Fulltekst i vitenarkiv Vis sammendrag

  Abstract JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

• Korecki, Andrea J; Cueva-Vargas, Jorge; Fornes, Oriol; Agostinone, Jessica; Farkas, Rachelle & Hickmott, Jack W [Vis alle 12 forfattere av denne artikkelen] (2021). Human MiniPromoters for ocular-rAAV expression in ON bipolar, cone, corneal, endothelial, Müller glial, and PAX6 cells. Gene Therapy. ISSN 0969-7128. doi: 10.1038/s41434-021-00227-z. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Small and cell-type restricted promoters are important tools for basic and preclinical research, and clinical delivery of gene therapies. In clinical gene therapy, ophthalmic trials have been leading the field, with over 50% of ocular clinical trials using promoters that restrict expression based on cell type. Here, 19 human DNA MiniPromoters were bioinformatically designed for rAAV, tested by neonatal intravenous delivery in mouse, and successful MiniPromoters went on to be tested by intravitreal, subretinal, intrastromal, and/or intravenous delivery in adult mouse. We present promoter development as an overview for each cell type, but only show results in detail for the recommended MiniPromoters: Ple265 and Ple341 ( PCP2 ) ON bipolar, Ple349 ( PDE6H ) cone, Ple253 ( PITX3 ) corneal stroma, Ple32 ( CLDN5 ) endothelial cells of the blood–retina barrier, Ple316 ( NR2E1 ) Müller glia, and Ple331 ( PAX6 ) PAX6 positive. Overall, we present a resource of new, redesigned, and improved MiniPromoters for ocular gene therapy that range in size from 784 to 2484 bp, and from weaker, equal, or stronger in strength relative to the ubiquitous control promoter smCBA. All MiniPromoters will be useful for therapies involving small regulatory RNA and DNA, and proteins ranging from 517 to 1084 amino acids, representing 62.9–90.2% of human proteins.

• Mileti, Enrichetta; Kwok, Kelvin H.M.; Andersson, Daniel P.; Mathelier, Anthony; Raman, Amitha & Bäckdahl, Jesper [Vis alle 14 forfattere av denne artikkelen] (2021). Human White Adipose Tissue Displays Selective Insulin Resistance in the Obese State. Diabetes. ISSN 0012-1797. 70(7), s. 1486–1497. doi: 10.2337/db21-0001. Fulltekst i vitenarkiv
• Aure, Miriam Ragle; Fleischer, Thomas; Bjørklund, Sunniva; Ankill, Jørgen; Mondragón, Jaime Abraham Castro & Børresen-Dale, Anne-Lise [Vis alle 11 forfattere av denne artikkelen] (2021). Crosstalk between microRNA expression and DNA methylation drives the hormone-dependent phenotype of breast cancer. Genome Medicine. 13:72, s. 1–21. doi: 10.1186/s13073-021-00880-4. Fulltekst i vitenarkiv Vis sammendrag

  Background Abnormal DNA methylation is observed as an early event in breast carcinogenesis. However, how such alterations arise is still poorly understood. microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play key roles in various biological processes. Here, we integrate miRNA expression and DNA methylation at CpGs to study how miRNAs may affect the breast cancer methylome and how DNA methylation may regulate miRNA expression. Methods miRNA expression and DNA methylation data from two breast cancer cohorts, Oslo2 (n = 297) and The Cancer Genome Atlas (n = 439), were integrated through a correlation approach that we term miRNA-methylation Quantitative Trait Loci (mimQTL) analysis. Hierarchical clustering was used to identify clusters of miRNAs and CpGs that were further characterized through analysis of mRNA/protein expression, clinicopathological features, in silico deconvolution, chromatin state and accessibility, transcription factor binding, and long-range interaction data. Results Clustering of the significant mimQTLs identified distinct groups of miRNAs and CpGs that reflect important biological processes associated with breast cancer pathogenesis. Notably, two major miRNA clusters were related to immune or fibroblast infiltration, hence identifying miRNAs associated with cells of the tumor microenvironment, while another large cluster was related to estrogen receptor (ER) signaling. Studying the chromatin landscape surrounding CpGs associated with the estrogen signaling cluster, we found that miRNAs from this cluster are likely to be regulated through DNA methylation of enhancers bound by FOXA1, GATA2, and ER-alpha. Further, at the hub of the estrogen cluster, we identified hsa-miR-29c-5p as negatively correlated with the mRNA and protein expression of DNA methyltransferase DNMT3A, a key enzyme regulating DNA methylation. We found deregulation of hsa-miR-29c-5p already present in pre-invasive breast lesions and postulate that hsa-miR-29c-5p may trigger early event abnormal DNA methylation in ER-positive breast cancer. Conclusions We describe how miRNA expression and DNA methylation interact and associate with distinct breast cancer phenotypes.

• Riudavets, Rafael; Boddie, Paul; Khan, Aziz; Mondragon, Jaime Abraham Castro & Mathelier, Anthony (2021). UniBind: maps of high-confidence direct TF-DNA interactions across nine species. BMC Genomics. 22(482), s. 1–17. doi: 10.1186/s12864-021-07760-6. Fulltekst i vitenarkiv Vis sammendrag

  Background Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq). Results In this study, we processed ~ 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~ 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface (https://unibind.uio.no/), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions. Conclusions UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.

• Pladsen, Arne Valebjørg; Nilsen, Gro; Rueda, Oscar M.; Aure, Miriam Ragle; Borgan, Ørnulf & Liestøl, Knut [Vis alle 18 forfattere av denne artikkelen] (2020). DNA copy number motifs are strong and independent predictors of survival in breast cancer. Communications Biology. 3. doi: 10.1038/s42003-020-0884-6. Fulltekst i vitenarkiv Vis sammendrag

  Somatic copy number alterations are a frequent sign of genome instability in cancer. A precise characterization of the genome architecture would reveal underlying instability mechanisms and provide an instrument for outcome prediction and treatment guidance. Here we show that the local spatial behavior of copy number profiles conveys important information about this architecture. Six filters were defined to characterize regional traits in copy number profiles, and the resulting Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to tumors in four breast cancer cohorts (n = 2919). The derived motifs represent a layer of information that complements established molecular classifications of breast cancer. A score reflecting presence or absence of motifs provided a highly significant independent prognostic predictor. Results were consistent between cohorts. The nonsite-specific occurrence of the detected patterns suggests that CARMA captures underlying replication and repair defects and could have a future potential in treatment stratification.

• Khan, Aziz; Puig, Rafael Riudavets; Boddie, Paul & Mathelier, Anthony (2020). BiasAway: command-line and web server to generate nucleotide composition-matched DNA background sequences. Bioinformatics. ISSN 1367-4803. doi: 10.1093/bioinformatics/btaa928. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Motivation Accurate motif enrichment analyses depend on the choice of background DNA sequences used, which should ideally match the sequence composition of the foreground sequences. It is important to avoid false positive enrichment due to sequence biases in the genome, such as GC-bias. Therefore, relying on an appropriate set of background sequences is crucial for enrichment analysis. Results We developed BiasAway, a command line tool and its dedicated easy-to-use web server to generate synthetic sequences matching any k-mer nucleotide composition or select genomic DNA sequences matching the mononucleotide composition of the foreground sequences through four different models. For genomic sequences, we provide precomputed partitions of genomes from nine species with five different bin sizes to generate appropriate genomic background sequences. Availability and implementation BiasAway source code is freely available from Bitbucket (https://bitbucket.org/CBGR/biasaway) and can be easily installed using bioconda or pip. The web server is available at https://biasaway.uio.no and a detailed documentation is available at https://biasaway.readthedocs.io. Supplementary information Supplementary data are available at Bioinformatics online.

• Fromm, Bastian; Domanska, Diana Ewa; Høye, Eirik; Ovchinnikov, Vladimir; Kang, Wenjing & Aparicio-Puerta, Ernesto [Vis alle 13 forfattere av denne artikkelen] (2019). MirGeneDB 2.0: the metazoan microRNA complement. Nucleic Acids Research (NAR). ISSN 0305-1048. 48(D1), s. D132–D141. doi: 10.1093/nar/gkz885. Fulltekst i vitenarkiv Vis sammendrag

  Small non-coding RNAs have gained substantial attention due to their roles in animal development and human disorders. Among them, microRNAs are special because individual gene sequences are conserved across the animal kingdom. In addition, unique and mechanistically well understood features can clearly distinguish bona fide miRNAs from the myriad other small RNAs generated by cells. However, making this distinction is not a common practice and, thus, not surprisingly, the heterogeneous quality of available miRNA complements has become a major concern in microRNA research. We addressed this by extensively expanding our curated microRNA gene database - MirGeneDB - to 45 organisms, encompassing a wide phylogenetic swath of animal evolution. By consistently annotating and naming 10,899 microRNA genes in these organisms, we show that previous microRNA annotations contained not only many false positives, but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA complements of closely related organisms are very similar and can be used to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust platform for microRNA-based research, providing deeper and more significant insights into the biology and evolution of miRNAs as well as biomedical and biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.

• Korecki, Andrea J; Hickmott, Jack W; Lam, Siu Ling; Dreolini, Lisa; Mathelier, Anthony & Baker, Oliver [Vis alle 17 forfattere av denne artikkelen] (2019). Twenty-seven tamoxifen-inducible icre-driver mouse strains for eye and brain, including seventeen carrying a new inducible-first constitutive-ready allele. Genetics. ISSN 0016-6731. 211(4), s. 1155–1177. doi: 10.1534/genetics.119.301984. Fulltekst i vitenarkiv
• Fornes, Oriol; Mondragón, Jaime Abraham Castro; Khan, Aziz; der, Lee Robin van; Zhang, Xi & Richmond, Phillip A. [Vis alle 19 forfattere av denne artikkelen] (2019). JASPAR 2020: update of the open-access database of transcription factor binding profiles. Nucleic Acids Research (NAR). ISSN 0305-1048. 48, s. 87–92. doi: 10.1093/nar/gkz1001. Fulltekst i vitenarkiv Vis sammendrag

  JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.

• Itkonen, Harri; Urbanucci, Alfonso; ES, Martin Sara; Khan, Aziz; Mathelier, Anthony & Thiede, Bernd [Vis alle 8 forfattere av denne artikkelen] (2019). High OGT activity is essential for MYC-driven proliferation of prostate cancer cells. Theranostics. 9(8), s. 2183–2197. doi: 10.7150/thno.30834. Fulltekst i vitenarkiv Vis sammendrag

  O-GlcNAc transferase (OGT) is overexpressed in aggressive prostate cancer. OGT modifies intra-cellular proteins via single sugar conjugation (O-GlcNAcylation) to alter their activity. We recently discovered the first fast-acting OGT inhibitor OSMI-2. Here, we probe the stability and function of the chromatin O-GlcNAc and identify transcription factors that coordinate with OGT to promote proliferation of prostate cancer cells. Methods: Chromatin immunoprecipitation (ChIP) coupled to sequencing (seq), formaldehyde-assisted isolation of regulatory elements, RNA-seq and reverse-phase protein arrays (RPPA) were used to study the importance of OGT for chromatin structure and transcription. Mass spectrometry, western blot, RT-qPCR, cell cycle analysis and viability assays were used to establish the role of OGT for MYC-related processes. Prostate cancer patient data profiled for both mRNA and protein levels were used to validate findings. Results: We show for the first time that OGT inhibition leads to a rapid loss of O-GlcNAc chromatin mark. O-GlcNAc ChIP-seq regions overlap with super-enhancers (SE) and MYC binding sites. OGT inhibition leads to down-regulation of SE-dependent genes. We establish the first O-GlcNAc chromatin consensus motif, which we use as a bait for mass spectrometry. By combining the proteomic data from oligonucleotide enrichment with O-GlcNAc and MYC ChIP-mass spectrometry, we identify host cell factor 1 (HCF-1) as an interaction partner of MYC. Inhibition of OGT disrupts this interaction and compromises MYC's ability to confer androgen-independent proliferation to prostate cancer cells. We show that OGT is required for MYC-mediated stabilization of mitotic proteins, including Cyclin B1, and/or the increased translation of their coding transcripts. This implies that increased expression of mRNA is not always required to achieve increased protein expression and confer aggressive phenotype. Indeed, high expression of Cyclin B1 protein has strong predictive value in prostate cancer patients (p=0.000014) while mRNA does not. Conclusions: OGT promotes SE-dependent gene expression. OGT activity is required for the interaction between MYC and HCF-1 and expression of MYC-regulated mitotic proteins. These features render OGT essential for the androgen-independent, MYC-driven proliferation of prostate cancer cells. Androgen-independency is the major mechanism of prostate cancer progression, and our study identifies OGT as an essential mediator in this process.

• Ha, Thomas J.; Zhang, Peter G.Y.; Robert, Remi; Yeung, Joanna; Swanson, Douglas J. & Mathelier, Anthony [Vis alle 17 forfattere av denne artikkelen] (2019). Identification of novel cerebellar developmental transcriptional regulators with motif activity analysis. BMC Genomics. 20(718), s. 1–17. doi: 10.1186/s12864-019-6063-9. Fulltekst i vitenarkiv Vis sammendrag

  Background The work of the FANTOM5 Consortium has brought forth a new level of understanding of the regulation of gene transcription and the cellular processes involved in creating diversity of cell types. In this study, we extended the analysis of the FANTOM5 Cap Analysis of Gene Expression (CAGE) transcriptome data to focus on understanding the genetic regulators involved in mouse cerebellar development. Results We used the HeliScopeCAGE library sequencing on cerebellar samples over 8 embryonic and 4 early postnatal times. This study showcases temporal expression pattern changes during cerebellar development. Through a bioinformatics analysis that focused on transcription factors, their promoters and binding sites, we identified genes that appear as strong candidates for involvement in cerebellar development. We selected several candidate transcriptional regulators for validation experiments including qRT-PCR and shRNA transcript knockdown. We observed marked and reproducible developmental defects in Atf4, Rfx3, and Scrt2 knockdown embryos, which support the role of these genes in cerebellar development. Conclusions The successful identification of these novel gene regulators in cerebellar development demonstrates that the FANTOM5 cerebellum time series is a high-quality transcriptome database for functional investigation of gene regulatory networks in cerebellar development.

• Salvatore, Stefania; Rand, Knut Dagestad; Grytten, Ivar; Ferkingstad, Egil; Domanska, Diana & Holden, Lars [Vis alle 10 forfattere av denne artikkelen] (2019). Beware the Jaccard: the choice of similarity measure is important and non-trivial in genomic colocalisation analysis. Briefings in Bioinformatics. ISSN 1467-5463. s. 1–8. doi: 10.1093/bib/bbz083. Fulltekst i vitenarkiv
• Gheorghe, Marius; Sandve, Geir Kjetil; Khan, Aziz; Cheneby, Jeanne; Ballester, Benoit & Mathelier, Anthony (2019). A map of direct TF–DNA interactions in the human genome. Nucleic Acids Research (NAR). ISSN 0305-1048. 47(4), s. e21–e21. doi: 10.1093/nar/gky1210. Fulltekst i vitenarkiv Vis sammendrag

  Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the most popular assay to identify genomic regions, called ChIP-seq peaks, that are bound in vivo by transcription factors (TFs). These regions are derived from direct TF–DNA interactions, indirect binding of the TF to the DNA (through a co-binding partner), nonspecific binding to the DNA, and noise/bias/artifacts. Delineating the bona fide direct TF–DNA interactions within the ChIP-seq peaks remains challenging. We developed a dedicated software, ChIP-eat, that combines computational TF binding models and ChIP-seq peaks to automatically predict direct TF–DNA interactions. Our work culminated with predicted interactions covering >2% of the human genome, obtained by uniformly processing 1983 ChIP-seq peak data sets from the ReMap database for 232 unique TFs. The predictions were a posteriori assessed using protein binding microarray and ChIP-exo data, and were predominantly found in high quality ChIP-seq peaks. The set of predicted direct TF–DNA interactions suggested that high-occupancy target regions are likely not derived from direct binding of the TFs to the DNA. Our predictions derived co-binding TFs supported by protein-protein interaction data and defined cis-regulatory modules enriched for disease- and trait-associated SNPs. We provide this collection of direct TF–DNA interactions and cis-regulatory modules through the UniBind web-interface (http://unibind.uio.no).

• Lecellier, Charles-Henri; Wasserman, Wyeth W. & Mathelier, Anthony (2018). Human enhancers harboring specific sequence composition, activity, and genome organization are linked to the immune response. Genetics. ISSN 0016-6731. 209(4), s. 1055–1071. doi: 10.1534/genetics.118.301116. Fulltekst i vitenarkiv
• Khan, Aziz; Mathelier, Anthony & Zhang, Xuegong (2018). Super-enhancers are transcriptionally more active and cell type-specific than stretch enhancers. Epigenetics. ISSN 1559-2294. 13(9), s. 910–922. doi: 10.1080/15592294.2018.1514231. Fulltekst i vitenarkiv
• Fornes, Oriol; Gheorghe, Marius; Richmond, Phillip A.; Arenillas, David J.; Wasserman, Wyeth W. & Mathelier, Anthony (2018). MANTA2, update of the Mongo database for the analysis of transcription factor binding site alterations. Scientific Data. 5:180141, s. 1–7. doi: 10.1038/sdata.2018.141. Fulltekst i vitenarkiv Vis sammendrag

  Interpreting the functional impact of noncoding variants is an ongoing challenge in the field of genome analysis. With most noncoding variants associated with complex traits and disease residing in regulatory regions, altered transcription factor (TF) binding has been proposed as a mechanism of action. It is therefore imperative to develop methods that predict the impact of noncoding variants at TF binding sites (TFBSs). Here, we describe the update of our MANTA database that stores: 1) TFBS predictions in the human genome, and 2) the potential impact on TF binding for all possible single nucleotide variants (SNVs) at these TFBSs. TFBSs were predicted by combining experimental ChIP-seq data from ReMap and computational position weight matrices (PWMs) derived from JASPAR. Impact of SNVs at these TFBSs was assessed by means of PWM scores computed on the alternate alleles. The updated database, MANTA2, provides the scientific community with a critical map of TFBSs and SNV impact scores to improve the interpretation of noncoding variants in the human genome.

• Sugiaman-Trapman, Debora; Vitezic, Morana; Jouhilahti, Eeva-Mari; Mathelier, Anthony; Lauter, Gilbert & Misra, Sougat [Vis alle 9 forfattere av denne artikkelen] (2018). Characterization of the human RFX transcription factor family by regulatory and target gene analysis. BMC Genomics. 19(181). doi: 10.1186/s12864-018-4564-6. Fulltekst i vitenarkiv Vis sammendrag

  Background Evolutionarily conserved RFX transcription factors (TFs) regulate their target genes through a DNA sequence motif called the X-box. Thereby they regulate cellular specialization and terminal differentiation. Here, we provide a comprehensive analysis of all the eight human RFX genes (RFX1–8), their spatial and temporal expression profiles, potential upstream regulators and target genes. Results We extracted all known human RFX1–8 gene expression profiles from the FANTOM5 database derived from transcription start site (TSS) activity as captured by Cap Analysis of Gene Expression (CAGE) technology. RFX genes are broadly (RFX1–3, RFX5, RFX7) and specifically (RFX4, RFX6) expressed in different cell types, with high expression in four organ systems: immune system, gastrointestinal tract, reproductive system and nervous system. Tissue type specific expression profiles link defined RFX family members with the target gene batteries they regulate. We experimentally confirmed novel TSS locations and characterized the previously undescribed RFX8 to be lowly expressed. RFX tissue and cell type specificity arises mainly from differences in TSS architecture. RFX transcript isoforms lacking a DNA binding domain (DBD) open up new possibilities for combinatorial target gene regulation. Our results favor a new grouping of the RFX family based on protein domain composition. We uncovered and experimentally confirmed the TFs SP2 and ESR1 as upstream regulators of specific RFX genes. Using TF binding profiles from the JASPAR database, we determined relevant patterns of X-box motif positioning with respect to gene TSS locations of human RFX target genes. Conclusions The wealth of data we provide will serve as the basis for precisely determining the roles RFX TFs play in human development and disease.

• Fleischer, Thomas; Tekpli, Xavier; Mathelier, Anthony; Wang, Shixiong; Nebdal, Daniel J.H. & Dhakal, Hari Prasad [Vis alle 16 forfattere av denne artikkelen] (2017). DNA methylation at enhancers identifies distinct breast cancer lineages. Nature Communications. 8(1379). doi: 10.1038/s41467-017-00510-x. Fulltekst i vitenarkiv Vis sammendrag

  Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression, we apply genome-wide expression–methylation quantitative trait loci (emQTL) analysis between DNA methylation and gene expression. On a whole genome scale, in cis and in trans, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association in three breast cancer cohorts (n = 104, n = 253 and n = 277). The expression–methylation quantitative trait loci associations form two main clusters; one relates to tumor infiltrating immune cell signatures and the other to estrogen receptor signaling. In the estrogen related cluster, using ChromHMM segmentation and transcription factor chromatin immunoprecipitation sequencing data, we identify transcriptional networks regulated in a cell lineage-specific manner by DNA methylation at enhancers. These networks are strongly dominated by ERα, FOXA1 or GATA3 and their targets were functionally validated using knockdown by small interfering RNA or GRO-seq analysis after transcriptional stimulation with estrogen.

• Khan, Aziz & Mathelier, Anthony (2017). JASPAR RESTful API: accessing JASPAR data from any programming language. Bioinformatics. ISSN 1367-4803. 34(9), s. 1612–1614. doi: 10.1093/bioinformatics/btx804. Fulltekst i vitenarkiv Vis sammendrag

  JASPAR is a widely used open-access database of curated, non-redundant transcription factor binding profiles. Currently, data from JASPAR can be retrieved as flat files or by using programming language-specific interfaces. Here, we present a programming language-independent application programming interface (API) to access JASPAR data using the Representational State Transfer (REST) architecture. The REST API enables programmatic access to JASPAR by most programming languages and returns data in eight widely used formats. Several endpoints are available to access the data and an endpoint is available to infer the TF binding profile(s) likely bound by a given DNA binding domain protein sequence. Additionally, it provides an interactive browsable interface for bioinformatics tool developers.

• rie, D de; Abugesaissa, I; Alam, T; Arner, E; Ashoor, H & Åström, G [Vis alle 70 forfattere av denne artikkelen] (2017). An integrated expression atlas of miRNAs and their promoters in human and mouse. Nature Biotechnology. ISSN 1087-0156. 35(9), s. 872–878. doi: 10.1038/nbt.3947. Fulltekst i vitenarkiv
• Cheneby, J; Gheorghe, Marius; Artufel, M; Mathelier, Anthony & Ballester, B (2017). ReMap 2018: an updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments. Nucleic Acids Research (NAR). ISSN 0305-1048. 46(D1), s. D267–D275. doi: 10.1093/nar/gkx1092. Fulltekst i vitenarkiv Vis sammendrag

  With this latest release of ReMap (http://remap.cisreg.eu), we present a unique collection of regulatory regions in human, as a result of a large-scale integrative analysis of ChIP-seq experiments for hundreds of transcriptional regulators (TRs) such as transcription factors, transcriptional co-activators and chromatin regulators. In 2015, we introduced the ReMap database to capture the genome regulatory space by integrating public ChIP-seq datasets, covering 237 TRs across 13 million (M) peaks. In this release, we have extended this catalog to constitute a unique collection of regulatory regions. Specifically, we have collected, analyzed and retained after quality control a total of 2829 ChIP-seq datasets available from public sources, covering a total of 485 TRs with a catalog of 80M peaks. Additionally, the updated database includes new search features for TR names as well as aliases, including cell line names and the ability to navigate the data directly within genome browsers via public track hubs. Finally, full access to this catalog is available online together with a TR binding enrichment analysis tool. ReMap 2018 provides a significant update of the ReMap database, providing an in depth view of the complexity of the regulatory landscape in human.

• Khan, Aziz; Fornes, O; Stigliani, A; Gheorghe, Marius; Mondragón, Jaime Abraham Castro & Lee, R van der [Vis alle 19 forfattere av denne artikkelen] (2017). JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework. Nucleic Acids Research (NAR). ISSN 0305-1048. 46(1), s. D260–D266. doi: 10.1093/nar/gkx1126. Fulltekst i vitenarkiv Vis sammendrag

  JASPAR (http://jaspar.genereg.net) is an open-access 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 package.

• Khan, Aziz & Mathelier, Anthony (2017). Intervene: a tool for intersection and visualization of multiple gene or genomic region sets. BMC Bioinformatics. 18(287). doi: 10.1186/s12859-017-1708-7. Fulltekst i vitenarkiv Vis sammendrag

  Background: A common task for scientists relies on comparing lists of genes or genomic regions derived from high-throughput sequencing experiments. While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited. Results: To address this gap, we have developed the Intervene tool, which provides an easy and automated interface for the effective intersection and visualization of genomic region or list sets, thus facilitating their analysis and interpretation. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps. Intervene, and its interactive web ShinyApp companion, generate publication-quality figures for the interpretation of genomic region and list sets. Conclusions: Intervene and its web application companion provide an easy command line and an interactive web interface to compute intersections of multiple genomic and list sets. They have the capacity to plot intersections using easy-to-interpret visual approaches. Intervene is developed and designed to meet the needs of both computer scientists and biologists. The source code is freely available at https://bitbucket.org/CBGR/intervene, with the web application available at https://asntech.shinyapps.io/intervene.

• Lizio, Marina; Harshbarger, Jayson; Abugessaisa, Imad; Noguchi, Shuei; Kondo, Atsushi & Severin, Jessica [Vis alle 25 forfattere av denne artikkelen] (2017). Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals. Nucleic Acids Research (NAR). ISSN 0305-1048. 45(D1), s. D737–D743. doi: 10.1093/nar/gkw995. Fulltekst i vitenarkiv Vis sammendrag

  Upon the first publication of the fifth iteration of the Functional Annotation of Mammalian Genomes collaborative project, FANTOM5, we gathered a series of primary data and database systems into the FANTOM web resource (http://fantom.gsc.riken.jp) to facilitate researchers to explore transcriptional regulation and cellular states. In the course of the collaboration, primary data and analysis results have been expanded, and functionalities of the database systems enhanced. We believe that our data and web systems are invaluable resources, and we think the scientific community will benefit for this recent update to deepen their understanding of mammalian cellular organization. We introduce the contents of FANTOM5 here, report recent updates in the web resource and provide future perspectives.

• Arenillas, David J.; Forrest, Alistair R.R.; Kawaji, Hideya; Lassmann, Timo; Wasserman, Wyeth W. & Mathelier, Anthony (2016). CAGEd-oPOSSUM: Motif enrichment analysis from CAGE-derived TSSs. Bioinformatics. ISSN 1367-4803. 32(18), s. 2858–2860. doi: 10.1093/bioinformatics/btw337. Fulltekst i vitenarkiv
• Shi, Wenqiang; Fornes, Oriol; Mathelier, Anthony & Wasserman, Wyeth W. (2016). Evaluating the impact of single nucleotide variants on transcription factor binding. Nucleic Acids Research (NAR). ISSN 0305-1048. 44(21), s. 10106–10116. doi: 10.1093/nar/gkw691. Fulltekst i vitenarkiv
• Mathelier, Anthony; Xin, Beibei; Chiu, Tsu-Pei; Yang, Lin; Rohs, REmo & Wasserman, Wyeth W. (2016). DNA Shape Features Improve Transcription Factor Binding Site Predictions In Vivo. Cell Systems. ISSN 2405-4712. 3, s. 278–286. doi: 10.1016/j.cels.2016.07.001. Fulltekst i vitenarkiv
• Mathelier, Anthony; Zhao, Xiaobei; Zhang, Allen W.; Parcy, François; Worsley-Hunt, Rebecca & Arenillas, David J. [Vis alle 17 forfattere av denne artikkelen] (2014). JASPAR 2014: An extensively expanded and updated open-access database of transcription factor binding profiles. Nucleic Acids Research (NAR). ISSN 0305-1048. 42(1), s. D142–D147. doi: 10.1093/nar/gkt997. Fulltekst i vitenarkiv Vis sammendrag

  JASPAR (http://jaspar.genereg.net) is the largest open-access database of matrix-based nucleotide profiles describing the binding preference of transcription factors from multiple species. The fifth major release greatly expands the heart of JASPAR—the JASPAR CORE subcollection, which contains curated, non-redundant profiles—with 135 new curated profiles (74 in vertebrates, 8 in Drosophila melanogaster, 10 in Caenorhabditis elegans and 43 in Arabidopsis thaliana; a 30% increase in total) and 43 older updated profiles (36 in vertebrates, 3 in D. melanogaster and 4 in A. thaliana; a 9% update in total). The new and updated profiles are mainly derived from published chromatin immunoprecipitation-seq experimental datasets. In addition, the web interface has been enhanced with advanced capabilities in browsing, searching and subsetting. Finally, the new JASPAR release is accompanied by a new BioPython package, a new R tool package and a new R/Bioconductor data package to facilitate access for both manual and automated methods.

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• Mathelier, Anthony (2023). Insights into the disruption of gene regulatory programs in cancers. Fulltekst i vitenarkiv
• Mathelier, Anthony (2023). Insights into the disruption of gene regulatory programs in cancers. Fulltekst i vitenarkiv
• Ferenc, Katalin Terezia; Hsieh, Ping-Han; Mathelier, Anthony & Sandve, Geir Kjetil Ferkingstad (2022). Method development for the identification of cis-regulatory signatures of cell types. Fulltekst i vitenarkiv
• Ferenc, Katalin Terezia; Mathelier, Anthony; Hsieh, Ping-Han & Sandve, Geir Kjetil Ferkingstad (2022). Method development for the identification of cis-regulatory signatures of cell types. Fulltekst i vitenarkiv
• Ferenc, Katalin Terezia; Hsieh, Ping-Han; Mathelier, Anthony & Sandve, Geir Kjetil Ferkingstad (2022). Method development for the identification of cis-regulatory signatures of cell types. Fulltekst i vitenarkiv
• Lemma, Roza Berhanu; Castro-Mondragon, Jaime Abraham & Mathelier, Anthony (2022). Large-scale investigation of noncoding elements associated with transcriptional deregulation involved in carcinogenesis. Fulltekst i vitenarkiv
• Rauluseviciute, Ieva; Castro-Mondragon, Jaime A. & Mathelier, Anthony (2022). Identification of transcription factor co-binding patterns with non-negative matrix factorization. Fulltekst i vitenarkiv
• Rauluseviciute, Ieva; Castro-Mondragon, Jaime A. & Mathelier, Anthony (2022). Identification of transcription factor co-binding patterns with non-negative matrix factorization. Fulltekst i vitenarkiv
• Rauluseviciute, Ieva; Castro-Mondragon, Jaime A. & Mathelier, Anthony (2022). Identification of transcription factor co-binding partners with non-negative matrix factorization. Fulltekst i vitenarkiv
• Mathelier, Anthony (2022). Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers. Fulltekst i vitenarkiv
• Mathelier, Anthony (2021). Insights into the interplay between transcription factor binding and cis-regulatory disruptions in cancers. Fulltekst i vitenarkiv
• Fromm, Bastian; Domanska, Diana; Høye, Eirik; Ovchinnikov, Vladimir; Kang, Wenjing & Aparicio-Puerta, Ernesto [Vis alle 13 forfattere av denne artikkelen] (2020). Erratum: MirGeneDB 2.0: The metazoan microRNA complement (Nucleic Acids Research (2019) DOI: 10.1093/nar/gkz885). Nucleic Acids Research (NAR). ISSN 0305-1048. 48(1), s. D1172–D1172. doi: 10.1093/nar/gkz1016. Fulltekst i vitenarkiv
• Gheorghe, Marius; Sandve, Geir Kjetil Ferkingstad; Khan, Aziz; Chèneby, Jeanne; Ballester, Benoit & Mathelier, Anthony (2019). Erratum: A map of direct TF-DNA interactions in the human genome (Nucleic acids research (2019) 47 4 (e21)). Nucleic Acids Research (NAR). ISSN 0305-1048. 47(14), s. 7715–7715. doi: 10.1093/nar/gkz582. Fulltekst i vitenarkiv
• Khan, Aziz; Montenegro-Montero, Alejandro & Mathelier, Anthony (2018). Put science first and formatting later. doi: 10.15252/embr.201845731. Fulltekst i vitenarkiv

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