One of the greatest challenges in animal biology is to learn how genonnic sequence information is read by transcription factors to produce patterns of gene expression within the context of regulatory networks in developing embryos. This Project is part of a broader Program Project that will integrate computational modeling and wet laboratory methods to address this challenge in the belief that only quantitative and predictive mathematical models that have been validated experimentally can provide the rigorous understanding required for modeling transcriptional networks of animals. This Project's contribution to the overall Program will be to derive data on the binding of sequence specific transcription factors to DNA in the embryo. Ours and other groups in vivo DNA binding data is limited currently in that it localizes binding to 200 - 500 bp genomic regions that generally include several ~6-12 base pair (bp) recognition sites for the factor under study. Mechanistic computational models, however, must describe the relative levels of occupancy of transcription factors at each recognition site. Therefore, we will derive in vivo DNA binding data at considerably higher resolution using an Exo-ChIP method recently developed by Frank Pugh's laboratory that can map the location of protein/DNA crosslinks to within a few base pairs of transcription factors'cognate recognition sites. For our first Specific Aim, data will be derived both for the 32 transcription factors defined by genetics as the principal regulators of the Drosophila blastoderm network as well as for additional ubiquitously expressed transcription factors that may provide further specificity information. For our second Specific Aim, the change in DNA occupancy that results from the mutation of key nucleotides within recognition sites will also be measured using transgenic lines provided by Project 2. Binding of transcription factors to the mutated sites and also at nearby sites will be assayed to test if interactions between transcription factors affect DNA occupancy levels in vivo or not. All of the data produced by Project 1 will be essential in testing our current generalized HMM and in developing more accurate second generation models of in vivo DNA binding and transcriptional activity (Projects 3 and 4). By helping to establishing how to read transcriptional information in animal genomes, this Project will aid both the development of therapeutics for human genetic diseases and the understanding of animal development.
| Li, Jingyi Jessica; Chew, Guo-Liang; Biggin, Mark D (2017) Quantitating translational control: mRNA abundance-dependent and independent contributions and the mRNA sequences that specify them. Nucleic Acids Res 45:11821-11836 |
| Li, Jingyi Jessica; Bickel, Peter J; Biggin, Mark D (2014) System wide analyses have underestimated protein abundances and the importance of transcription in mammals. PeerJ 2:e270 |
| Knowles, David W; Biggin, Mark D (2013) Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution. Wiley Interdiscip Rev Dev Biol 2:767-79 |
| Fisher, William W; Li, Jingyi Jessica; Hammonds, Ann S et al. (2012) DNA regions bound at low occupancy by transcription factors do not drive patterned reporter gene expression in Drosophila. Proc Natl Acad Sci U S A 109:21330-5 |
