Genome-Wide Modeling of Transcription Preinitiation Complex Disassembly Mechanisms using ChIP-chip Data

Apparent occupancy levels of proteins bound to DNA in vivo can now be routinely measured on a genomic scale. A challenge in relating these occupancy levels to assembly mechanisms that are defined with biochemically isolated components lies in the veracity of assumptions made regarding the in vivo system. Assumptions regarding behavior of molecules in vivo can neither be proven true nor false, and thus is necessarily subjective. Nevertheless, within those confines, connecting in vivo protein-DNA interaction observations with defined biochemical mechanisms is an important step towards fully defining and understanding assembly/disassembly mechanisms in vivo. To this end, we have developed a computational program PathCom that models in vivo protein-DNA occupancy data as biochemical mechanisms under the assumption that occupancy levels can be related to binding duration and explicitly defined assembly/disassembly reactions. We exemplify the process with the assembly of the general transcription factors (TBP, TFIIB, TFIIE, TFIIF, TFIIH, and RNA polymerase II) at the genes of the budding yeast Saccharomyces. Within the assumption inherent in the system our modeling suggests that TBP occupancy at promoters is rather transient compared to other general factors, despite the importance of TBP in nucleating assembly of the preinitiation complex. PathCom is suitable for modeling any assembly/disassembly pathway, given that all the proteins (or species) come together to form a complex.Author Summary: For proper cell function, cells need to precisely coordinate the expression of their genes on their DNA at precise times. In order to better understand how the cell works, it is important to understand how, when, and why a cell needs to turn on or off certain genes at certain times. In order to assist the cell to properly express its genes, there are hundreds of proteins that can bind and access DNA. Each protein has a unique function and these proteins assemble together into a very large complex to turn on genes. The assembly of these proteins has defined to some extent, however the whole process of assembly and disassembly of this complex in the cell is still poorly understood. In our modeling analysis, we have attempted to utilize genome-wide binding data to better understand how the transcription machinery that “reads” genes might disassemble, in light of what is known about the assembly process. This knowledge helps us better understand how cells coordinate their on/off-switching of their genes.