Videos

A "Bottom-up" Approach to Deciphering and Predicting Cis-regulatory Transcriptional Grammar in Drosophila

Presenter
March 4, 2008
Keywords:
  • Transcriptional Grammar
MSC:
  • 68Q42
Abstract
Joint work with Ahmet Ay2, Evan Dayringer2, Rupinder Sayal1, Chichia Chiu2, David N. Arnosti1. Cis regulatory information comprises a key portion of genetic coding, yet despite the abundance of genomic sequences now available, identifying and characterizing this information remains a major challenge. We are pursuing a unique “bottom-up” approach to understand the mechanistic processing of the regulatory elements (input codes) by the transcriptional machinery, using a well-defined and characterized set of repressor and activator transcription factors in Drosophila blastoderm embryos. We are identifying quantitative values for parameters affecting transcriptional regulation in vivo, which are used to build and test mathematical models that predict the outputs of novel cis-regulatory elements. Giant, Krüppel, Knirps are short-range transcriptional repressor proteins involved in the developmental patterning of Drosophila blastoderm embryo. Using defined regulatory modules tested in germline transformed embryos, we are measuring quantitative values of Giant protein (input) and lacZ mRNA (output) using confocal laser scanning microscopy technique. The expression of lacZ reporter gene is driven by Twist/Dorsal activator proteins. We build 3-scale mathematical models which consist of computer simulation of transcription factors (TF) dynamic, mathematical description of cis-regulatory elements (RE) along the DNA enhancer cassettes, and integration of TF and RE to predict transcription output. Our modeling at the DNA level will integrate all the key parameters of the binding sites including arrangement, spacing, stoichiometry, affinity, proximity to basal promoter and collaboration. We employ a nucleotide-base potential function for repressor and activator binding sites and partial differential equations to derive density functions representing the transcriptional map of clusters of binding sites. These models are being used to predict the output of novel permutations of binding sites, which will allow us to test and refine parameters used for the model. In one line of investigation, fluorescence quantitation of mRNA lacZ expression was used to measure the effect of moving Giant repressor binding sites from a position adjacent to Twist/Dorsal activator sites to a distal site 125bp upstream. Our mathematical model successfully predicted the distance effect of intermediate positions, such as 25, 50, 75 and 100bp compared to the experimental results. Enhancer cassettes with 1, 2 and 3 binding sites of Giant or Krüppel repressors upstream from Twist/Dorsal activator sites were analyzed for the effect of stoichiometry on lacZ expression. The in situ experimental results indicate a cooperative contribution within Giant and Krüppel repressor proteins on lacZ repression. Our model predicts a strong cooperativity within these repressor proteins. In other modules examined the effect of arrangement of Giant binding sites to the Twist/Dorsal activator sites, it showed a significant difference in transcriptional output providing a good evidence for the importance of modeling many key parameters of cis-transcriptional regulation. Extension of these predictive models to endogenous cis-elements will provide novel insights on regulatory element design and evolution, and should provide a bioinformatics tool for predicting quantitative output of novel regulatory elements. 1Department of Biochemistry & Molecular Biology 2Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA.