Kenneth A Barr1,2, Carlos Martinez3, Jennifer R Moran4,5, Ah-Ram Kim6, Alexandre F Ramos7,8, John Reinitz9,10,5,11. 1. Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Zoology 111, 1101 E 57th St, Chicago, 60637, Illinois, USA. kenneth.a.barr@gmail.com. 2. Department of Ecology and Evolution, The University of Chicago, Chicago, 60637, Illinois, USA. kenneth.a.barr@gmail.com. 3. Department Biochemistry and Molecular Genetics, Northwestern University, Chicago, 60611, Illinois, USA. 4. Department Human Genetics, The University of Chicago, Chicago, 60637, Illinois, USA. 5. Institute for Genomics & Systems Biology, The University of Chicago, Chicago, 60637, Illinois, USA. 6. School of Life Science, Handong Global University, Pohang, 37554, Gyeongbuk, South Korea. 7. Departamento de Radiologia - Faculdade de Medicina, Universidade de São Paulo & Instituto do Câncer do Estado de São Paulo, São Paulo, SP CEP, 05403-911, Brazil. 8. Escola de Artes, Ciências e Humanidades & Núcleo de Estudos Interdisciplinares em Sistemas Complexos, Universidade de São Paulo, Av. Arlindo Béttio, São Paulo, 1000 CEP 03828-000, SP, Brazil. 9. Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Zoology 111, 1101 E 57th St, Chicago, 60637, Illinois, USA. 10. Department of Ecology and Evolution, The University of Chicago, Chicago, 60637, Illinois, USA. 11. Department Statistics, The University of Chicago, 5747 S. Ellis Avenue Jones 312, Chicago, 60637, IL, USA.
Abstract
BACKGROUND: Models that incorporate specific chemical mechanisms have been successful in describing the activity of Drosophila developmental enhancers as a function of underlying transcription factor binding motifs. Despite this, the minimum set of mechanisms required to reconstruct an enhancer from its constituent parts is not known. Synthetic biology offers the potential to test the sufficiency of known mechanisms to describe the activity of enhancers, as well as to uncover constraints on the number, order, and spacing of motifs. RESULTS: Using a functional model and in silico compensatory evolution, we generated putative synthetic even-skipped stripe 2 enhancers with varying degrees of similarity to the natural enhancer. These elements represent the evolutionary trajectories of the natural stripe 2 enhancer towards two synthetic enhancers designed ab initio. In the first trajectory, spatially regulated expression was maintained, even after more than a third of binding sites were lost. In the second, sequences with high similarity to the natural element did not drive expression, but a highly diverged sequence about half the length of the minimal stripe 2 enhancer drove ten times greater expression. Additionally, homotypic clusters of Zelda or Stat92E motifs, but not Bicoid, drove expression in developing embryos. CONCLUSIONS: Here, we present a functional model of gene regulation to test the degree to which the known transcription factors and their interactions explain the activity of the Drosophila even-skipped stripe 2 enhancer. Initial success in the first trajectory showed that the gene regulation model explains much of the function of the stripe 2 enhancer. Cases where expression deviated from prediction indicates that undescribed factors likely act to modulate expression. We also showed that activation driven Bicoid and Hunchback is highly sensitive to spatial organization of binding motifs. In contrast, Zelda and Stat92E drive expression from simple homotypic clusters, suggesting that activation driven by these factors is less constrained. Collectively, the 40 sequences generated in this work provides a powerful training set for building future models of gene regulation.
BACKGROUND: Models that incorporate specific chemical mechanisms have been successful in describing the activity of Drosophila developmental enhancers as a function of underlying transcription factor binding motifs. Despite this, the minimum set of mechanisms required to reconstruct an enhancer from its constituent parts is not known. Synthetic biology offers the potential to test the sufficiency of known mechanisms to describe the activity of enhancers, as well as to uncover constraints on the number, order, and spacing of motifs. RESULTS: Using a functional model and in silico compensatory evolution, we generated putative syntheticeven-skippedstripe 2 enhancers with varying degrees of similarity to the natural enhancer. These elements represent the evolutionary trajectories of the natural stripe 2 enhancer towards two synthetic enhancers designed ab initio. In the first trajectory, spatially regulated expression was maintained, even after more than a third of binding sites were lost. In the second, sequences with high similarity to the natural element did not drive expression, but a highly diverged sequence about half the length of the minimal stripe 2 enhancer drove ten times greater expression. Additionally, homotypic clusters of Zelda or Stat92E motifs, but not Bicoid, drove expression in developing embryos. CONCLUSIONS: Here, we present a functional model of gene regulation to test the degree to which the known transcription factors and their interactions explain the activity of the Drosophilaeven-skippedstripe 2 enhancer. Initial success in the first trajectory showed that the gene regulation model explains much of the function of the stripe 2 enhancer. Cases where expression deviated from prediction indicates that undescribed factors likely act to modulate expression. We also showed that activation driven Bicoid and Hunchback is highly sensitive to spatial organization of binding motifs. In contrast, Zelda and Stat92E drive expression from simple homotypic clusters, suggesting that activation driven by these factors is less constrained. Collectively, the 40 sequences generated in this work provides a powerful training set for building future models of gene regulation.
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