Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities
Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities
ABSTRACT Gene regulation plays a critical role in the cellular processes that underlie human health and disease. The regulatory relationship between transcription factors (TFs), key regulators of gene expression, and their target genes, the so called TF regulons, can be coupled with computational algorithms to estimate the activity of TFs. However, to interpret these findings accurately, regulons of high reliability and coverage are needed. In this study, we present and evaluate a collection of regulons created using the CollecTRI meta-resource containing signed TF-gene interactions for 1,183 TFs. In this context, we introduce a workflow to integrate information from multiple resources and assign the sign of regulation to TF-gene interactions that could be applied to other comprehensive knowledge bases. We find that the signed CollecTRI-derived regulons outperform other public collections of regulatory interactions in accurately inferring changes in TF activities in perturbation experiments. Furthermore, we showcase the value of the regulons by investigating hallmarks of TF activity profiles inferred from the transcriptomes of three different cancer types. Overall, the CollecTRI-derived TF regulons enable the accurate and comprehensive estimation of TF activities and thereby help to interpret transcriptomics data. GRAPHICAL ABSTRACTbiorxiv;2023.03.30.534849v1/UFIG1F1ufig1
Tsirvouli Eirini、Ramirez Flores Ricardo O.、Badia-i-Mompel Pau、Fallegger Robin、V¨￠zquez Miguel、Saez-Rodriguez Julio、L?greid Astrid、M¨1ller-Dott Sophia
Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology||Department of Biology, Norwegian University of Science and TechnologyHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational BiomedicineHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational BiomedicineHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational BiomedicineBarcelona Supercomputing CenterHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational BiomedicineDepartment of Clinical and Molecular Medicine, Norwegian University of Science and TechnologyHeidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine
基础医学分子生物学生物科学研究方法、生物科学研究技术
Tsirvouli Eirini,Ramirez Flores Ricardo O.,Badia-i-Mompel Pau,Fallegger Robin,V¨￠zquez Miguel,Saez-Rodriguez Julio,L?greid Astrid,M¨1ller-Dott Sophia.Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities[EB/OL].(2025-03-28)[2025-05-21].https://www.biorxiv.org/content/10.1101/2023.03.30.534849.点此复制
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