Bilaterally symmetric motor patterns-those in which left-right pairs of muscles contract synchronously and with equal amplitude (such as breathing, smiling, whisking, and locomotion)-are widespread throughout the animal kingdom. Yet, surprisingly little is known about the underlying neural circuits. We performed a thermogenetic screen to identify neurons required for bilaterally symmetric locomotion in Drosophila larvae and identified the evolutionarily conserved Even-skipped(+) interneurons (Eve/Evx). Activation or ablation of Eve(+) interneurons disrupted bilaterally symmetric muscle contraction amplitude, without affecting the timing of motor output. Eve(+) interneurons are not rhythmically active and thus function independently of the locomotor CPG. GCaMP6 calcium imaging of Eve(+) interneurons in freely moving larvae showed left-right asymmetric activation that correlated with larval behavior. TEM reconstruction of Eve(+) interneuron inputs and outputs showed that the Eve(+) interneurons are at the core of a sensorimotor circuit capable of detecting and modifying body wall muscle contraction.

Mice (Mus musculus) form large and dynamic social groups and emit ultrasonic vocalizations in a variety of social contexts. Surprisingly, these vocalizations have been studied almost exclusively in the context of cues from only one social partner, despite the observation that in many social species the presence of additional listeners changes the structure of communication signals. Here, we show that male vocal behavior elicited by female odor is affected by the presence of a male audience - with changes in vocalization count, acoustic structure and syllable complexity. We further show that single sensory cues are not sufficient to elicit this audience effect, indicating that multiple cues may be necessary for an audience to be apparent. Together, these experiments reveal that some features of mouse vocal behavior are only expressed in more complex social situations, and introduce a powerful new assay for measuring detection of the presence of social partners in mice.

Courtship rituals serve to reinforce reproductive barriers between closely related species. Drosophila melanogaster and Drosophila simulans exhibit reproductive isolation, owing in part to the fact that D. melanogaster females produce 7,11-heptacosadiene, a pheromone that promotes courtship in D. melanogaster males but suppresses courtship in D. simulans males. Here we compare pheromone-processing pathways in D. melanogaster and D. simulans males to define how these sister species endow 7,11-heptacosadiene with the opposite behavioural valence to underlie species discrimination. We show that males of both species detect 7,11-heptacosadiene using homologous peripheral sensory neurons, but this signal is differentially propagated to P1 neurons, which control courtship behaviour. A change in the balance of excitation and inhibition onto courtship-promoting neurons transforms an excitatory pheromonal cue in D. melanogaster into an inhibitory cue in D. simulans. Our results reveal how species-specific pheromone responses can emerge from conservation of peripheral detection mechanisms and diversification of central circuitry, and demonstrate how flexible nodes in neural circuits can contribute to behavioural evolution.

Ascidian species of the Phallusia and Ciona genera are distantly related, their last common ancestor dating several hundred million years ago. Although their genome sequences have extensively diverged since this radiation, Phallusia and Ciona species share almost identical early morphogenesis and stereotyped cell lineages. Here, we explored the evolution of transcriptional control between P. mammillata and C. robusta. We combined genome-wide mapping of open chromatin regions in both species with a comparative analysis of the regulatory sequences of a test set of 10 pairs of orthologous early regulatory genes with conserved expression patterns. We find that ascidian chromatin accessibility landscapes obey similar rules as in other metazoa. Open-chromatin regions are short, highly conserved within each genus and cluster around regulatory genes. The dynamics of chromatin accessibility and closest-gene expression are strongly correlated during early embryogenesis. Open-chromatin regions are highly enriched in cis-regulatory elements: 73% of 49 open chromatin regions around our test genes behaved as either distal enhancers or proximal enhancer/promoters following electroporation in Phallusia eggs. Analysis of this datasets suggests a pervasive use in ascidians of "shadow" enhancers with partially overlapping activities. Cross-species electroporations point to a deep conservation of both the trans-regulatory logic between these distantly-related ascidians and the cis-regulatory activities of individual enhancers. Finally, we found that the relative order and approximate distance to the transcription start site of open chromatin regions can be conserved between Ciona and Phallusia species despite extensive sequence divergence, a property that can be used to identify orthologous enhancers, whose regulatory activity can partially diverge.

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

Genetically wired neural mechanisms inhibit mating between species because even naive animals rarely mate with other species. These mechanisms can evolve through changes in expression or function of key genes in sensory pathways or central circuits. Gr32a is a gustatory chemoreceptor that, in D. melanogaster, is essential to inhibit interspecies courtship and sense quinine. Similar to D. melanogaster, we find that D. simulans Gr32a is expressed in foreleg tarsi, sensorimotor appendages that inhibit interspecies courtship, and it is required to sense quinine. Nevertheless, Gr32a is not required to inhibit interspecies mating by D. simulans males. However, and similar to its function in D. melanogaster, Ppk25, a member of the Pickpocket family, promotes conspecific courtship in D. simulans. Together, we have identified distinct evolutionary mechanisms underlying chemosensory control of taste and courtship in closely related Drosophila species.

Pheromones, chemical signals that convey social information, mediate many insect social behaviors, including navigation and aggregation. Several studies have suggested that behavior during the immature larval stages of Drosophila development is influenced by pheromones, but none of these compounds or the pheromone-receptor neurons that sense them have been identified. Here we report a larval pheromone-signaling pathway. We found that larvae produce two novel long-chain fatty acids that are attractive to other larvae. We identified a single larval chemosensory neuron that detects these molecules. Two members of the pickpocket family of DEG/ENaC channel subunits (ppk23 and ppk29) are required to respond to these pheromones. This pheromone system is evolving quickly, since the larval exudates of D. simulans, the sister species of D. melanogaster, are not attractive to other larvae. Our results define a new pheromone signaling system in Drosophila that shares characteristics with pheromone systems in a wide diversity of insects.

Biological systems display extraordinary robustness. Robustness of transcriptional enhancers results mainly from clusters of binding sites for the same transcription factor, and it is not clear how robust enhancers can evolve loss of expression through point mutations. Here, we report the high-resolution functional dissection of a robust enhancer of the shavenbaby gene that has contributed to morphological evolution. We found that robustness is encoded by many binding sites for the transcriptional activator Arrowhead and that, during evolution, some of these activator sites were lost, weakening enhancer activity. Complete silencing of enhancer function, however, required evolution of a binding site for the spatially restricted potent repressor Abrupt. These findings illustrate that recruitment of repressor binding sites can overcome enhancer robustness and may minimize pleiotropic consequences of enhancer evolution. Recruitment of repression may be a general mode of evolution to break robust regulatory linkages.

Novel body structures are often generated by the redeployment of ancestral components of the genome. In this issue of Developmental Cell, Glassford et al. (2015) present a thorough analysis of the co-option of a gene regulatory network in the origin of an evolutionary novelty.

Learning in deep neural networks is known to depend critically on the knowledge embedded in the initial network weights. However, few theoretical results have precisely linked prior knowledge to learning dynamics. Here we derive exact solutions to the dynamics of learning with rich prior knowledge in deep linear networks by generalising Fukumizu's matrix Riccati solution \citep{fukumizu1998effect}. We obtain explicit expressions for the evolving network function, hidden representational similarity, and neural tangent kernel over training for a broad class of initialisations and tasks. The expressions reveal a class of task-independent initialisations that radically alter learning dynamics from slow non-linear dynamics to fast exponential trajectories while converging to a global optimum with identical representational similarity, dissociating learning trajectories from the structure of initial internal representations. We characterise how network weights dynamically align with task structure, rigorously justifying why previous solutions successfully described learning from small initial weights without incorporating their fine-scale structure. Finally, we discuss the implications of these findings for continual learning, reversal learning and learning of structured knowledge. Taken together, our results provide a mathematical toolkit for understanding the impact of prior knowledge on deep learning.