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Global landscape of mouse and human cytokine transcriptional regulation.
Carrasco Pro, Sebastian; Dafonte Imedio, Alvaro; Santoso, Clarissa Stephanie; Gan, Kok Ann; Sewell, Jared Allan; Martinez, Melissa; Sereda, Rebecca; Mehta, Shivani; Fuxman Bass, Juan Ignacio.
Affiliation
  • Carrasco Pro S; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Dafonte Imedio A; Bioinformatics Program, Boston University, Boston, MA 02215, USA.
  • Santoso CS; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Gan KA; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Sewell JA; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Martinez M; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Sereda R; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Mehta S; Department of Biology, Boston University, Boston, MA 02215, USA.
  • Fuxman Bass JI; Department of Biology, Boston University, Boston, MA 02215, USA.
Nucleic Acids Res ; 46(18): 9321-9337, 2018 10 12.
Article in En | MEDLINE | ID: mdl-30184180
Cytokines are cell-to-cell signaling proteins that play a central role in immune development, pathogen responses, and diseases. Cytokines are highly regulated at the transcriptional level by combinations of transcription factors (TFs) that recruit cofactors and the transcriptional machinery. Here, we mined through three decades of studies to generate a comprehensive database, CytReg, reporting 843 and 647 interactions between TFs and cytokine genes, in human and mouse respectively. By integrating CytReg with other functional datasets, we determined general principles governing the transcriptional regulation of cytokine genes. In particular, we show a correlation between TF connectivity and immune phenotype and disease, we discuss the balance between tissue-specific and pathogen-activated TFs regulating each cytokine gene, and cooperativity and plasticity in cytokine regulation. We also illustrate the use of our database as a blueprint to predict TF-disease associations and identify potential TF-cytokine regulatory axes in autoimmune diseases. Finally, we discuss research biases in cytokine regulation studies, and use CytReg to predict novel interactions based on co-expression and motif analyses which we further validated experimentally. Overall, this resource provides a framework for the rational design of future cytokine gene regulation studies.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Transcription Factors / Gene Expression Regulation / Cytokines / Databases, Genetic / Gene Regulatory Networks Type of study: Prognostic_studies Limits: Animals / Humans Language: En Year: 2018 Type: Article

Full text: 1 Database: MEDLINE Main subject: Transcription Factors / Gene Expression Regulation / Cytokines / Databases, Genetic / Gene Regulatory Networks Type of study: Prognostic_studies Limits: Animals / Humans Language: En Year: 2018 Type: Article