I helped with the experimental design and execution of the generation of a new single-cell transcriptomics dataset containing 6 transcription factors. This dataset contained a high number of cells (>200) for each transcription factor, which enabled us to map the fine changes of dosage sensitivity genome-wide across varied levels of dosage. We also included several combinations of transcription factors to be able to learn how two potentially synergistic or antagonistic transcription factors would interact. I created a computational method that can enable us to accurately assess and iteratively refine different potential biological mechanisms that may be underlying the dataset at hand. The various common cellular processes, modalities, and mechanisms (Figure 1c) that are used to understand transcription factor data are included, but it is easy to expand with other processes/modalities depending on the biological system. This removes the monolithic nature of previous frameworks and democratizes model building. We found that dosage and cell cycle have much more extensive effects than previously thought. We found extensive number of non-monotonic gene responses, particularly in Homeobox TFs. Gradients of homeobox TF expression have been described in several studies, often caused by upstream gradients in morphogen concentration during development. Our analysis suggests that non-monotonic transcriptional regulation is a general, feature of this TF family and that these TFs often alter their mode of gene regulation depending on their concentration. We also applied Latenta to understand how the cell cycle may interact with, and here again found that cell cycle interactions are the rule rather than exception. We also observed considerable differences in dosage dependencies when analyzing combinations of TFs, one of the key objectives within the DoA. In particular, we found that the antagonism or synergism between two TFs can change depending on the respective dosages of the TF, with a second TF being seemingly synergistic if its dosage is relatively low compared to the main TF under study.
