Abstract
Modeling a gene's expression from its intergenic locus and trans-regulatory context is a fundamental goal in computational biology. Owing to the distributed nature of cis-regulatory information and the poorly understood mechanisms that integrate such information, gene locus modeling is a more challenging task than modeling individual enhancers. Here we report the first quantitative model of a gene's expression pattern as a function of its locus. We model the expression readout of a locus in two tiers: 1) combinatorial regulation by transcription factors bound to each enhancer is predicted by a thermodynamics-based model and 2) independent contributions from multiple enhancers are linearly combined to fit the gene expression pattern. The model does not require any prior knowledge about enhancers contributing toward a gene's expression. We demonstrate that the model captures the complex multi-domain expression patterns of anterior-posterior patterning genes in the early Drosophila embryo. Altogether, we model the expression patterns of 27 genes; these include several gap genes, pair-rule genes, and anterior, posterior, trunk, and terminal genes. We find that the model-selected enhancers for each gene overlap strongly with its experimentally characterized enhancers. Our findings also suggest the presence of sequence-segments in the locus that would contribute ectopic expression patterns and hence were “shut down” by the model. We applied our model to identify the transcription factors responsible for forming the stripe boundaries of the studied genes. The resulting network of regulatory interactions exhibits a high level of agreement with known regulatory influences on the target genes. Finally, we analyzed whether and why our assumption of enhancer independence was necessary for the genes we studied. We found a deterioration of expression when binding sites in one enhancer were allowed to influence the readout of another enhancer. Thus, interference between enhancer activities was a possible factor necessitating enhancer independence in our model.
Highlights
Gene regulation is key to understanding of a variety of biological processes ranging from development [1] to disease [2]
Studies of early embryonic development in Drosophila [5] have revealed the roles of various transcription factors (TFs) in setting up precise spatio-temporal gene expression patterns, and delineated many ‘‘enhancers’’ that mediate the activities of combinations of TFs
We have presented for the first time a quantitative model that relates gene expression to the sequence of an entire gene locus, using information on the trans-regulatory context (TF concentrations)
Summary
Gene regulation is key to understanding of a variety of biological processes ranging from development [1] to disease [2]. We have today a fairly detailed knowledge of the transcriptional regulatory network involved in patterning of the anterior-posterior (A/P) and dorso-ventral (D/V) axes in the blastoderm-stage Drosophila embryo [6,7,8] This knowledge has spurred the development of quantitative models of gene regulation that aim to map the sequence of a given enhancer to the expression pattern driven by that enhancer [9,10,11,12,13,14,15,16,17]. The ultimate goal is to build a computational tool that automatically predicts the expression of any gene in any cellular condition based solely on the genome sequence and a quantitative description of the trans-regulatory context [18] Such a computational tool will embody our knowledge of the so-called ‘‘cis-regulatory code’’ [19,20]. It will help us annotate the regulatory genome at a single nucleotide resolution, and predict the effects of genotypic changes (in cis or in trans) on gene expression and phenotype
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