Developmental genes can have complex cis-regulatory regions with multiple enhancers. Early work revealed remarkable modularity of enhancers, whereby distinct DNA regions drive gene expression in defined spatiotemporal domains. Nevertheless, a few reports have shown that enhancers function in multiple developmental stages, implying that enhancers can be pleiotropic. Here, we have studied the activity of the enhancers of the shavenbaby gene throughout D. melanogaster development. We found that all seven shavenbaby enhancers drive expression in multiple tissues and developmental stages. We explored how enhancer pleiotropy is encoded in two of these enhancers. In one enhancer, the same transcription factor binding sites contribute to embryonic and pupal expression, revealing site pleiotropy, whereas for a second enhancer, these roles are encoded by distinct sites. Enhancer pleiotropy may be a common feature of cis-regulatory regions of developmental genes, and site pleiotropy may constrain enhancer evolution in some cases.

The spatial association between fluorescently tagged biomolecules in situ provides valuable insight into their biological relationship. Within the limits of diffraction, such association can be measured using either Pearson's Correlation Coefficient (PCC) or Spearman's Rank Coefficient (SRC), which are designed to measure linear and monotonic correlations, respectively. However, the relationship between real biological signals is often more complex than these measures assume, rendering their results difficult to interpret. Here, we have adapted methods from the field of information theory to measure the association between two probes' concentrations based on their statistical dependence. Our approach is mathematically more general than PCC or SRC, making no assumptions about the type of relationship between the probes. We show that when applied to biological images, our measures provide more intuitive results that are also more robust to outliers and the presence of multiple relationships than PCC or SRC. We also devise a display technique to highlight regions in the input images where the probes' association is higher versus lower. We expect that our methods will allow biologists to more accurately and robustly quantify and visualize the association between two probes in a pair of fluorescence images. © 2018 International Society for Advancement of Cytometry.