No abstract

Fighting between different species is widespread in the animal kingdom, yet this phenomenon has been relatively understudied in the field of aggression research. Particularly lacking are studies that test the effect of genetic distance, or relatedness, on aggressive behaviour between species. Here we characterized male–male aggression within and between species of fruit flies across the Drosophila phylogeny. We show that male Drosophila discriminate between conspecifics and heterospecifics and show a bias for the target of aggression that depends on the genetic relatedness of opponent males. Specifically, males of closely related species treated conspecifics and heterospecifics equally, whereas males of distantly related species were overwhelmingly aggressive towards conspecifics. To our knowledge, this is the first study to quantify aggression between Drosophila species and to establish a behavioural bias for aggression against conspecifics versus heterospecifics. Our results suggest that future study of heterospecific aggression behaviour in Drosophila is warranted to investigate the degree to which these trends in aggression among species extend to broader behavioural, ecological and evolutionary contexts.

Recent advances in computer hardware and software, particularly the availability of machine learning (ML) libraries, allow the introduction of data-based topics such as ML into the biophysical curriculum for undergraduate and graduate levels. However, there are many practical challenges of teaching ML to advanced level students in biophysics majors, who often do not have a rich computational background. Aiming to overcome such challenges, we present an educational study, including the design of course topics, pedagogic tools, and assessments of student learning, to develop the new methodology to incorporate the basis of ML in an existing biophysical elective course and engage students in exercises to solve problems in an interdisciplinary field. In general, we observed that students had ample curiosity to learn and apply ML algorithms to predict molecular properties. Notably, feedback from the students suggests that care must be taken to ensure student preparations for understanding the data-driven concepts and fundamental coding aspects required for using ML algorithms. This work establishes a framework for future teaching approaches that unite ML and any existing course in the biophysical curriculum, while also pinpointing the critical challenges that educators and students will likely face.

24Fighting between different species is widespread in the animal kingdom, yet this phenomenon 25 has been relatively understudied in the field of aggression research. Particularly lacking are 26 studies that test the effect of genetic distance, or relatedness, on aggressive behavior between 27 species. Here we characterized male-male aggression within and between species of fruit flies 28 across the Drosophila phylogeny. We show that male Drosophila discriminate between 29 conspecifics and heterospecifics and show a bias for the target of aggression that depends on the 30 genetic relatedness of opponent males. Specifically, males of closely related species treated 31 conspecifics and heterospecifics equally, whereas males of distantly related species were 32 overwhelmingly aggressive toward conspecifics. To our knowledge, this is the first study to 33 quantify aggression between Drosophila species and to establish a behavioral bias for aggression 34 against conspecifics versus heterospecifics. Our results suggest that future study of heterospecific 35 aggression behavior in Drosophila is warranted to investigate the degree to which these trends in 36 aggression among species extend to broader behavioral, ecological, and evolutionary contexts. 37 38 Keywords: agonistic behavior, territoriality, heterospecific aggression 39 al., Dow and von Schilcher, 1975; Hoffmann, 1987; Hoffmann and Cacoyianni, 1990; 56 Sturtevant, 1915; White and Rundle, 2015), heterospecific aggression is largely uncharacterized, 57 except for limited qualitative observations of heterospecific aggression among the Hawaiian 58Drosophila (Spieth, 1981). 59Here we characterized male-male aggression in Drosophila in a multi-species context 60 using a behavioral choice assay, in order to (1) quantify the extent to which male Drosophila 61 discriminate between conspecifics and heterospecifics during aggressive social interactions and 62 4 (2) test the effect of phylogenetic distance between opponent species on the distributional bias in 63 aggressive targeting (heterospecific vs. conspecific). We report that males showed significant 64 bias in aggression toward either conspecifics or heterospecifics in a majority of species-species 65 interactions. Among species pairs that were more distantly related, the direction of aggression 66 was biased toward conspecifics, whereas closely related species treated conspecifics and 67 heterospecifics equally. To our knowledge, this is the first study to quantify aggression between 68Drosophila species and to establish a behavioral bias for aggression against conspecific vs. 69 heterospecific opponents. 70 Materials and Methods 71Drosophila species and husbandry 72 Seven species were selected from the ananassae, melanogaster, and pseudoobscura subgroups 73 within the subgenus Sophophora (Fig. 1). Among these seven species, we assayed aggressive 74 interactions between two species at-a-time for a total of six species pairs. Three of these species 75 pairs are relatively closely related sibling species: i) D. an...

we found that the coding region of the HCV genome is also highly structured with large domains located along the trajectory of the molecule, including a $380 nt single domain located in the 5BSL/VSL region of the genome. Conformational variations of these domains, including the identification of newly, previously uncharacterized domains will be discussed.