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Abstract Alternative end joining (alt-EJ) mechanisms, such as polymerase theta-mediated end joining, are increasingly recognized as important contributors to inaccurate double-strand break repair. We previously proposed an alt-EJ model whereby short DNA repeats near a double-strand break anneal to form secondary structures that prime limited DNA synthesis. The nascent DNA then pairs with microhomologous sequences on the other break end. This synthesis-dependent microhomology-mediated end joining (SD-MMEJ) explains many of the alt-EJ repair products recovered following I-SceI nuclease cutting in Drosophila. However, sequence-specific factors that influence SD-MMEJ repair remain to be fully characterized. Here, we expand the utility of the SD-MMEJ model through computational analysis of repair products at Cas9-induced double-strand breaks for 1100 different sequence contexts. We find evidence at single nucleotide resolution for sequence characteristics that drive successful SD-MMEJ repair. These include optimal primer repeat length, distance of repeats from the break, flexibility of DNA sequence between primer repeats, and positioning of microhomology templates relative to preferred primer repeats. In addition, we show that DNA polymerase theta is necessary for most SD-MMEJ repair at Cas9 breaks. The analysis described here includes a computational pipeline that can be utilized to characterize preferred mechanisms of alt-EJ repair in any sequence context. 

In the field of Human-Robot Interaction, researchers often techniques such as the Wizard-of-Oz paradigms in order to better study narrow scientific questions while carefully controlling robots’ capabilities unrelated to those questions, especially when those other capabilities are not yet easy to automate. However, those techniques often impose limitations on the type of collaborative tasks that can be used, and the perceived realism of those tasks and the task context. In this paper, we discuss how Augmented Reality can be used to address these concerns while increasing researchers’ level of experimental control, and discuss both advantages and disadvantages of this approach 

In previous work, researchers in Human-Robot Interaction (HRI) have demonstrated that user trust in robots depends on effective and transparent communication. This may be particularly true for robots used for transportation, due to user reliance on such robots for physical movement and safety. In this paper, we present the design of an experiment examining the importance of proactive communication by robotic wheelchairs, as compared to non-vehicular mobile robots, within a Virtual Reality (VR) environment. Furthermore, we describe the specific advantages – and limitations – of conducting this type of HRI experiment in VR.