A well-defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy-based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy-based modeling uncovered specific quantitative features of short-range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos.
Transcriptional regulatory information, represented by patterns of protein-binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein-binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis-regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well-defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short-range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development.
The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency.
We generated specific descriptions for each regulatory element using fractional occupancy-based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short-range repressors, including a non-monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators.
By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology.
Systems biology seeks a genomic-level interpretation of transcriptional regulatory information represented by patterns of protein-binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis-regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short-range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy-based modeling uncovered unexpected features of these proteins' activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms.