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Cryogenic-electron tomography enables the visualization of cellular environments in extreme detail, however, tools to analyze the full amount of information contained within these densely packed volumes are still needed. Detailed analysis of macromolecules through subtomogram averaging requires particles to first be localized within the tomogram volume, a task complicated by several factors including a low signal to noise ratio and crowding of the cellular space. Available methods for this task suffer either from being error prone or requiring manual annotation of training data. To assist in this crucial particle picking step, we present TomoTwin: an open source general picking model for cryogenic-electron tomograms based on deep metric learning. By embedding tomograms in an information-rich, high-dimensional space that separates macromolecules according to their three-dimensional structure, TomoTwin allows users to identify proteins in tomograms de novo without manually creating training data or retraining the network to locate new proteins.

Cryoelectron tomography enables the visualization of cellular environments in extreme detail through the lens of a benign observer; what remains lacking however are tools to analyze the full amount of information contained within these densely packed volumes. Detailed analysis of macromolecules through subtomogram averaging requires particles to first be localized within the tomogram volume, a task complicated by several factors including a low signal to noise ratio and crowding of the cellular space. Available methods for this task suffer either from being error prone or requiring manual annotation of training data. To assist in this crucial particle picking step, we present TomoTwin: a robust, first in class general picking model for cryo-electron tomograms based on deep metric learning. By embedding tomograms in an information-rich, high-dimensional space which separates macromolecules according to their 3-dimensional structure, TomoTwin allows users to identify proteins in tomograms de novo without manually creating training data or retraining the network each time a new protein is to be located. TomoTwin is open source and available at https://github.com/MPI-Dortmund/tomotwin-cryoet.

The model organism Drosophila melanogaster has become a focal system for investigations of rapidly evolving genital morphology as well as the development and functions of insect reproductive structures. To follow up on a previous paper outlining unifying terminology for the structures of the male terminalia in this species, we offer here a detailed description of the female terminalia of D. melanogaster. Informative diagrams and micrographs are presented to provide a comprehensive overview of the external and internal reproductive structures of females. We propose a collection of terms and definitions to standardize the terminology associated with the female terminalia in D. melanogaster and we provide a correspondence table with the terms previously used. Unifying terminology for both males and females in this species will help to facilitate communication between various disciplines, as well as aid in synthesizing research across publications within a discipline that has historically focused principally on male features. Our efforts to refine and standardize the terminology should expand the utility of this important model system for addressing questions related to the development and evolution of animal genitalia, and morphology in general.

The evolution of gene expression via cis-regulatory changes is well established as a major driver of phenotypic evolution. However, relatively little is known about the influence of enhancer architecture and intergenic interactions on regulatory evolution. We address this question by examining chemosensory system evolution in Drosophila. Drosophila prolongata males show a massively increased number of chemosensory bristles compared to females and males of sibling species. This increase is driven by sex-specific transformation of ancestrally mechanosensory organs. Consistent with this phenotype, the Pox neuro transcription factor (Poxn), which specifies chemosensory bristle identity, shows expanded expression in D. prolongata males. Poxn expression is controlled by nonadditive interactions among widely dispersed enhancers. Although some D. prolongata Poxn enhancers show increased activity, the additive component of this increase is slight, suggesting that most changes in Poxn expression are due to epistatic interactions between Poxn enhancers and trans-regulatory factors. Indeed, the expansion of D. prolongata Poxn enhancer activity is only observed in cells that express doublesex (dsx), the gene that controls sexual differentiation in Drosophila and also shows increased expression in D. prolongata males due to cis-regulatory changes. Although expanded dsx expression may contribute to increased activity of D. prolongata Poxn enhancers, this interaction is not sufficient to explain the full expansion of Poxn expression, suggesting that cis-trans interactions between Poxn, dsx, and additional unknown genes are necessary to produce the derived D. prolongata phenotype. Overall, our results demonstrate the importance of epistatic gene interactions for evolution, particularly when pivotal genes have complex regulatory architecture.