title: Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo.
abstract: Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale.
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, United States.|Department of Biochemistry, DAV University, Jalandhar, India.
authors.forename: Rupinder
authors.initials: R
authors.lastname: Sayal
authors.affiliation: Department of Mathematics, Michigan State University, East Lansing, United States.|Department of Mathematics and Computer Science, Clark University, Worcester, United States.
authors.forename: Jacqueline M
authors.initials: JM
authors.lastname: Dresch
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, United States.|Stowers Institute for Medical Research, Kansas City, United States.
authors.forename: Irina
authors.initials: I
authors.lastname: Pushel
authors.affiliation: Department of Computer Science and Engineering, Michigan State University, East Lansing, United States.|School of Computer Science, Georgia Institute of Technology, Atlanta, United States.
authors.forename: Benjamin R
authors.initials: BR
authors.lastname: Taylor
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, United States.
authors.forename: David N
authors.identifier: 0000-0003-0983-6982
authors.initials: DN
authors.lastname: Arnosti
mesh_terms: D000818:Animals; D019521:Body Patterning / Q000235:genetics*; D029721:Drosophila Proteins / Q000235:genetics*; D004331:Drosophila melanogaster / Q000235:genetics* / Q000254:growth & development; D004742:Enhancer Elements, Genetic; D018507:Gene Expression Regulation, Developmental; D053263:Gene Regulatory Networks / Q000235:genetics; D049750:Genome, Insect; D008962:Models, Theoretical; D009687:Nuclear Proteins / Q000235:genetics*; D010750:Phosphoproteins / Q000235:genetics*; D014157:Transcription Factors / Q000235:genetics*
chemical_list: D029721:Drosophila Proteins; D009687:Nuclear Proteins; D010750:Phosphoproteins; D014157:Transcription Factors; C062236:dl protein, Drosophila
keywords: D. melanogaster; cis-regulatory grammar; computational biology; enhancers; systems biology; thermodynamic modeling; transcription