Animal species display enormous variation for innate behaviours, but little is known about how this diversity arose. Here, using an unbiased genetic approach, we map a courtship song difference between wild isolates of Drosophila simulans and Drosophila mauritiana to a 966 base pair region within the slowpoke (slo) locus, which encodes a calcium-activated potassium channel. Using the reciprocal hemizygosity test, we confirm that slo is the causal locus and resolve the causal mutation to the evolutionarily recent insertion of a retroelement in a slo intron within D. simulans. Targeted deletion of this retroelement reverts the song phenotype and alters slo splicing. Like many ion channel genes, slo is expressed widely in the nervous system and influences a variety of behaviours; slo-null males sing little song with severely disrupted features. By contrast, the natural variant of slo alters a specific component of courtship song, illustrating that regulatory evolution of a highly pleiotropic ion channel gene can cause modular changes in behaviour.

Many motor control systems generate multiple movements using a common set of muscles. How are premotor circuits able to flexibly generate diverse movement patterns? Here, we characterize the neuronal circuits that drive the distinct courtship songs of Drosophila melanogaster. Male flies vibrate their wings towards females to produce two different song modes – pulse and sine song – which signal species identity and male quality. Using cell-type specific genetic reagents and the connectome, we provide a cellular and synaptic map of the circuits in the male ventral nerve cord that generate these songs and examine how activating or inhibiting each cell type within these circuits affects the song. Our data reveal that the song circuit is organized into two nested feed-forward pathways, with extensive reciprocal and feed-back connections. The larger network produces pulse song, the more complex and ancestral song form. A subset of this network produces sine song, the simpler and more recent form. Such nested organization may be a common feature of motor control circuits in which evolution has layered increasing flexibility on to a basic movement pattern.

Animals flexibly switch between different actions by changing neural activity patterns for motor control. Courting Drosophila melanogaster males produce two different acoustic signals, pulse and sine song, each of which can be promoted by artificial activation of distinct neurons. However, how the activity of these neurons implements flexible song production is unknown. Here, we developed an assay to record neuronal calcium signals in the ventral nerve cord, which contains the song motor circuit, in singing flies. We found that sine-promoting neurons, but not pulse-promoting neurons, show strong activation during sine song. In contrast, both pulse- and sine-promoting neurons are active during pulse song. Furthermore, population calcium imaging in the song circuit suggests that sine song involves activation of a subset of neurons that are also active during pulse song. Thus, differential activation of overlapping, rather than distinct, neural populations underlies flexible motor actions during acoustic communication in D. melanogaster.

It is unclear where in the nervous system evolutionary changes tend to occur. To localize the source of neural evolution that has generated divergent behaviors, we developed a new approach to label and functionally manipulate homologous neurons across Drosophila species. We examined homologous descending neurons that drive courtship song in two species that sing divergent song types and localized relevant evolutionary changes in circuit function downstream of the intrinsic physiology of these descending neurons. This evolutionary change causes different species to produce divergent motor patterns in similar social contexts. Artificial stimulation of these descending neurons drives multiple song types, suggesting that multifunctional properties of song circuits may facilitate rapid evolution of song types.

While insects such as are flying, aerodynamic instabilities require that they make millisecond time scale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units-prominent components of the fly's steering muscle system-modulate specific elements of the PI controller: the angular displacement (integral) and angular velocity (proportional), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

While insects like Drosophila are flying, aerodynamic instabilities require that they make millisecond-timescale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units—prominent components of the fly’s steering muscles system—modulate specific elements of the PI controller: the angular displacement (integral, I) and angular velocity (proportional, P), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

While insects like Drosophila are flying, aerodynamic instabilities require that they make millisecond-timescale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units—prominent components of the fly's steering muscles system—modulate specific elements of the PI controller: the angular displacement (integral, I) and angular velocity (proportional, P), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

Multilocus sequence typing (MLST) has become the preferred method for genotyping many biological species, and it is especially useful for analyzing haploid eukaryotes. MLST is rigorous, reproducible, and informative, and MLST genotyping has been shown to identify major phylogenetic clades, molecular groups, or subpopulations of a species, as well as individual strains or clones. MLST molecular types often correlate with important phenotypes. Conventional MLST involves the extraction of genomic DNA and the amplification by PCR of several conserved, unlinked gene sequences from a sample of isolates of the taxon under investigation. In some cases, as few as three loci are sufficient to yield definitive results. The amplicons are sequenced, aligned, and compared by phylogenetic methods to distinguish statistically significant differences among individuals and clades. Although MLST is simpler, faster, and less expensive than whole genome sequencing, it is more costly and time-consuming than less reliable genotyping methods (e.g. amplified fragment length polymorphisms). Here, we describe a new MLST method that uses next-generation sequencing, a multiplexing protocol, and appropriate analytical software to provide accurate, rapid, and economical MLST genotyping of 96 or more isolates in single assay. We demonstrate this methodology by genotyping isolates of the well-characterized, human pathogenic yeast Cryptococcus neoformans.

Transcription factors bind low-affinity DNA sequences for only short durations. It is not clear how brief, low-affinity interactions can drive efficient transcription. Here we report that the transcription factor Ultrabithorax (Ubx) utilizes low-affinity binding sites in the Drosophila melanogastershavenbaby (svb) locus and related enhancers in nuclear microenvironments of high Ubx concentrations. Related enhancers colocalize to the same microenvironments independently of their chromosomal location, suggesting that microenvironments are highly differentiated transcription domains. Manipulating the affinity of svb enhancers revealed an inverse relationship between enhancer affinity and Ubx concentration required for transcriptional activation. The Ubx cofactor, Homothorax (Hth), was co-enriched with Ubx near enhancers that require Hth, even though Ubx and Hth did not co-localize throughout the nucleus. Thus, microenvironments of high local transcription factor and cofactor concentrations could help low-affinity sites overcome their kinetic inefficiency. Mechanisms that generate these microenvironments could be a general feature of eukaryotic transcriptional regulation.

In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how descending neurons control an insect's movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies and we associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a large collection of descending neurons, we found that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically-activated behaviors were often dependent on the behavioral state prior to activation.