The goal of this proposal is to discover and interpret the code by which cis-regulatory DNA controls gene expression. This regulatory DNA controls the speci?cation of cell fates with exquisite precision in multicellular organisms, including humans, and its dysregulation underlies both developmental diseases and cancer. The manner in which this control is coded into the genome remains poorly understood. Moreover, the recent discovery that metazoan genes are transcribed in random bursts raises the problem of understanding how this random process is controlled to give rise to the highly precise distribution of mature transcripts observed. Both of these problems constitute a roadblock to further progress in basic science and translational medicine, and we propose to remove them by the work proposed here. The key supporting tool is an established model of transcriptional control that takes DNA sequence and the concentrations of transcription factors as inputs and gives RNA synthesis rate as output. This model is not limited to enhancers, but can also treat an entire genetic locus. We previously used this model to understand how conservation of enhancer function across phylogeneti- cally distant species occurred in the absence of conservation of DNA sequence. We found that the conserved entities were small clusters of binding sites in which the exact positions of binding sites and the identity of bound transcription factors can vary, but only within certain limits. These clusters, which we call ?soft codons,? may have a role as essential as the structural genetic code. To test this, we propose to Aim 1: (a) Discover and model soft codons in the entire eve locus of D. melanogaster, D. virilis, and D. erecta in their native context, and selected enhancers from distant dipterans in the genuses Megaselia, Clogmia, and Chironomus expressed in D. melanogaster. The random bursts of transcription observed in vivo are also under the control of transcription factors. We propose to extend our transcription model to treat control of these bursts by a program of parallel experimen- tation and modeling. All experiments will be conducted in the context of a native intact locus, in which we will analyze the effects of a series of carefully selected perturbations. Speci?cally, we propose to Aim 2: Perform an in vivo regulatory dissection of the Drosophila eve locus in which we will monitor bursting in (a) The whole locus; (b) A series of key stripe two enhancer constructs designed to vary strength and variability of transcription; (c) Rearrangements of enhancers within the whole locus; and (d) Pure transvective constructs in which all interactions between the enhancer and basal promoter are in trans. We will use the resulting data, together with our preexisting quantitative atlas of gene expression at cellular resolution to Aim 3: Construct a new stochastic model of transcriptional control by coupling our current model of transcription to a simple model of stochastic transcription initiation.

Public Health Relevance

Although the function of that portion of DNA sequence that codes for protein is understood, the function of the part that determines how DNA turns genes on and off remains to be elucidated. The goal of this project is to understand how DNA sequence controls gene expression using the fruit ?y as an experimental system. The basic science developed in this project will have long term medical applications because cancer and many birth defects result from genes being turned on and off incorrectly. 1

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Research Project (R01)
Project #
2R01OD010936-27A1
Application #
10072649
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Zou, Sige
Project Start
2011-01-01
Project End
2024-05-31
Budget Start
2020-07-01
Budget End
2021-05-31
Support Year
27
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Chicago
Department
Biology
Type
Schools of Medicine
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637
Barr, Kenneth A; Martinez, Carlos; Moran, Jennifer R et al. (2017) Synthetic enhancer design by in silico compensatory evolution reveals flexibility and constraint in cis-regulation. BMC Syst Biol 11:116
Hope, C Matthew; Rebay, Ilaria; Reinitz, John (2017) DNA Occupancy of Polymerizing Transcription Factors: A Chemical Model of the ETS Family Factor Yan. Biophys J 112:180-192
Barr, Kenneth A; Reinitz, John (2017) A sequence level model of an intact locus predicts the location and function of nonadditive enhancers. PLoS One 12:e0180861
Vakulenko, Sergei; Radulescu, Ovidiu; Morozov, Ivan et al. (2017) Centralized Networks to Generate Human Body Motions. Sensors (Basel) 17:
Lou, Zhihao; Reinitz, John (2016) Parallel Simulated Annealing Using an Adaptive Resampling Interval. Parallel Comput 53:23-31
Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno (2016) Hamiltonian dynamics for complex food webs. Phys Rev E 93:032413
Bertolino, Eric; Reinitz, John; Manu (2016) The analysis of novel distal Cebpa enhancers and silencers using a transcriptional model reveals the complex regulatory logic of hematopoietic lineage specification. Dev Biol 413:128-44
Jiang, Pengyao; Ludwig, Michael Z; Kreitman, Martin et al. (2015) Natural variation of the expression pattern of the segmentation gene even-skipped in melanogaster. Dev Biol 405:173-81
Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John (2015) Gene regulation and noise reduction by coupling of stochastic processes. Phys Rev E Stat Nonlin Soft Matter Phys 91:020701
Grigoriev, D; Reinitz, J; Vakulenko, S et al. (2014) Punctuated evolution and robustness in morphogenesis. Biosystems 123:106-13

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