 |
Center for Nonlinear Studies |
To understand how transcription factors function, it is essential to determine the range of genes that they each bind and regulate in vivo and also to develop predictive, quantitative models for how these proteins generate complex spatial and temporal patterns of gene expression. We have established multiple, large scale datasets that measure key aspects of the transcription network that regulates early Drosophila embryogenesis. Analysis of these data show that most sequence specific transcription factors each bind to a majority of genes over a quantitative series of DNA occupancy levels. These continua span functional, quasi-functional, and non-functional DNA binding events. Factor regulatory specificities are distinguished by quantitative differences in DNA occupancy patterns. These results contrast with popular descriptions of transcription networks, which define discrete sets of direct target and non-target genes and thus do not capture the full complexity we have measured in vivo. In addition, we have built computational models that predict levels of in vivo DNA occupancy and 3D transcriptional output as a step towards a detailed biochemical understanding of transcription factor targeting and combinatorial control.
Host: Jeff Drocco, T-4 and CNLS