Abstract
Author SummaryTens of thousands of regulatory elements determine the spatiotemporal expression pattern of protein-coding genes in the metazoan genome. Each regulatory element, when bound by the appropriate transcription factors, can affect the temporal transcription of a nearby target gene in a particular cell type. Annotating the genome for regulatory elements, as well as determining the input transcription factors for each element, is a key challenge in genome biology. In this study, we introduce a computational method, cisTargetX, that predicts transcription factor binding motifs and their target genes through the integration of gene expression data and comparative genomics. We first validate this method in silico using public gene expression data and, then, apply cisTargetX to the developmental program governing photoreceptor neuron specification in the retina of Drosophila melanogaster. Particularly, we perturbed predicted key transcription factors during the initial steps of neurogenesis; measure gene expression by microarrays; identify motifs and predict target genes; validate the predictions in vivo using transgenic animals; and study several functional and evolutionary aspects of the validated regulatory elements for the proneural factor Atonal. Overall, we show that cisTargetX efficiently predicts genetic regulatory interactions and provides mechanistic insight into gene regulatory networks of postembryonic developmental systems.
Highlights
The development of the structural and functional properties of cells is largely determined via differential extraction of information from the genome by transcription factors (TFs)
The expression of most genes is regulated by combinations rather than single TFs, and extensive cross-regulations exist amongst TFs, often through feed-forward and feedback loops
The dl binding motif is available as a position weight matrix (PWM) (Figure 1A), and many of its direct target genes are known [24,25,26]
Summary
The development of the structural and functional properties of cells is largely determined via differential extraction of information from the genome by transcription factors (TFs). We introduce a computational method, cisTargetX, that predicts transcription factor binding motifs and their target genes through the integration of gene expression data and comparative genomics. ChIP-chip data alone were not specific enough, but combinations with computational binding-site predictions and with gene expression data under normal and TF perturbation conditions identified a significant number of bona fide regulatory interactions The limitations of this approach are the large amounts of material required for ChIP ( so far only successful for yeast cultures and large embryo collections) and the need for high quality, ‘‘ChIP-grade’’ antibodies. Drawing edges between TFs and their targets results in a transcriptional network underlying early retinal differentiation and defines the gene regulatory environs of Ato-dependent retinal differentiation
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