SUMMARYPhagocytic clearance of degenerating dendrites or axons is critical for maintaining tissue homeostasis and preventing neuroinflammation. Externalized phosphatidylserine (PS) has been postulated to be an ‘‘eat-me’’ signal allowing recognition of degenerating neurites by phagocytes. Here we show that in Drosophila, PS is dynamically exposed on degenerating dendrites during developmental pruning and after physical injury, but PS exposure is suppressed when dendrite degeneration is genetically blocked. Ectopic PS exposure via phospholipid flippase knockout and scramblase overexpression induced PS exposure preferentially at distal dendrites and caused distinct modes of neurite loss that differ in larval sensory dendrites and in adult olfactory axons. Surprisingly, extracellular lactadherin that lacks the integrin-interaction domain induced phagocyte-dependent degeneration of PS-exposing dendrites, revealing an unidentified bridging function that potentiates phagocytes. Our findings establish a direct causal relationship between PS exposure and neurite degeneration in vivo.

Tissue-specific loss-of-function (LOF) analysis is essential for characterizing gene function. Here, we present a simple, yet highly efficient, clustered regularly interspaced short palindromic repeats (CRISPR)-mediated tissue-restricted mutagenesis (CRISPR-TRiM) method for ablating gene function in Drosophila. This binary system consists of a tissue-specific Cas9 and a ubiquitously expressed multi-guide RNA (gRNA) transgene. We describe convenient toolkits for making enhancer-driven Cas9 lines and multi-gRNAs that are optimized for mutagenizing somatic cells. We demonstrate that insertions or deletions in coding sequences more reliably cause somatic mutations than DNA excisions induced by two gRNAs. We further show that enhancer-driven Cas9 is less cytotoxic yet results in more complete LOF than Gal4-driven Cas9 in larval sensory neurons. Finally, CRISPR-TRiM efficiently unmasks redundant soluble N-ethylmaleimide-sensitive factor attachment protein receptor gene functions in neurons and epidermal cells. Importantly, Cas9 transgenes expressed at different times in the neuronal lineage reveal the extent to which gene products persist in cells after tissue-specific gene knockout. These CRISPR tools can be applied to analyze tissue-specific gene function in many biological processes.

Systems biology is an approach to dissection of complex traits that explicitly recognizes the impact of genetic, physiological, and environmental interactions in the generation of phenotypic variation. We describe comprehensive transcriptional and metabolic profiling in Drosophila melanogaster across four diets, finding little overlap in modular architecture. Genotype and genotype-by-diet interactions are a major component of transcriptional variation (24 and 5.3% of the total variation, respectively) while there were no main effects of diet (<1%). Genotype was also a major contributor to metabolomic variation (16%), but in contrast to the transcriptome, diet had a large effect (9%) and the interaction effect was minor (2%) for the metabolome. Yet specific principal components of these molecular phenotypes measured in larvae are strongly correlated with particular metabolic syndrome-like phenotypes such as pupal weight, larval sugar content and triglyceride content, development time, and cardiac arrhythmia in adults. The second principal component of the metabolomic profile is especially informative across these traits with glycine identified as a key loading variable. To further relate this physiological variability to genotypic polymorphism, we performed evolve-and-resequence experiments, finding rapid and replicated changes in gene frequency across hundreds of loci that are specific to each diet. Adaptation to diet is thus highly polygenic. However, loci differentially transcribed across diet or previously identified by RNAi knockdown or expression QTL analysis were not the loci responding to dietary selection. Therefore, loci that respond to the selective pressures of diet cannot be readily predicted a priori from functional analyses.

Neurons sometimes completely fill available space in their receptive fields with evenly spaced dendrites to uniformly sample sensory or synaptic information. The mechanisms that enable neurons to sense and innervate all space in their target tissues are poorly understood. Using somatosensory neurons as a model, we show that heparan sulfate proteoglycans (HSPGs) Dally and Syndecan on the surface of epidermal cells act as local permissive signals for the dendritic growth and maintenance of space-filling nociceptive C4da neurons, allowing them to innervate the entire skin. Using long-term time-lapse imaging with intact larvae, we found that dendrites grow into HSPG-deficient areas but fail to stay there. HSPGs are necessary to stabilize microtubules in newly formed high-order dendrites. In contrast to C4da neurons, non-space-filling sensory neurons that develop in the same microenvironment do not rely on HSPGs for their dendritic growth. Furthermore, HSPGs do not act by transporting extracellular diffusible ligands or require leukocyte antigen-related (Lar), a receptor protein tyrosine phosphatase (RPTP) and the only known HSPG receptor, for promoting dendritic growth of space-filling neurons. Interestingly, another RPTP, Ptp69D, promotes dendritic growth of C4da neurons in parallel to HSPGs. Together, our data reveal an HSPG-dependent pathway that specifically allows dendrites of space-filling neurons to innervate all target tissues in.

In adulthood, sleep-wake rhythms are one of the most prominent behaviors under circadian control. However, during early life, sleep is spread across the 24-hour day. The mechanism through which sleep rhythms emerge, and the consequent advantage conferred to a juvenile animal, are unknown. In 2nd instar Drosophila larvae (L2), like human infants, sleep is not under circadian control. Here, we identify the precise developmental timepoint when the circadian clock begins to regulate sleep in Drosophila, leading to the emergence of sleep rhythms at the early 3rd instar stage (L3). At this stage, a cellular connection forms between DN1a clock neurons and arousal-promoting Dh44 neurons, bringing arousal under clock control to drive the emergence of circadian sleep. Finally, we demonstrate that L3 but not L2 larvae exhibit long-term memory (LTM) of an aversive cue, and that this LTM depends upon deep sleep generated once sleep rhythms begin. We propose that the developmental emergence of circadian sleep enables more complex cognitive processes, including the onset of enduring memories.

During prolonged nutrient restriction, developing animals redistribute vital nutrients to favor brain growth at the expense of other organs. In Drosophila, such brain sparing relies on a glia-derived growth factor to sustain proliferation of neural stem cells. However, whether other aspects of neural development are also spared under nutrient restriction is unknown. Here we show that dynamically growing somatosensory neurons in the Drosophila peripheral nervous system exhibit organ sparing at the level of arbor growth: Under nutrient stress, sensory dendrites preferentially grow as compared to neighboring non-neural tissues, resulting in dendrite overgrowth. These neurons express lower levels of the stress sensor FoxO than neighboring epidermal cells, and hence exhibit no marked induction of autophagy and a milder suppression of Tor signaling under nutrient stress. Preferential dendrite growth allows for heightened animal responses to sensory stimuli, indicative of a potential survival advantage under environmental challenges.

Natural populations of the fruit fly, Drosophila melanogaster, segregate genetic variation that leads to cardiac disease phenotypes. One nearly isogenic line from a North Carolina peach orchard, WE70, is shown to harbor two genetically distinct heart phenotypes: elevated incidence of arrhythmias, and a dramatically constricted heart diameter in both diastole and systole, with resemblance to restrictive cardiomyopathy in humans. Assuming the source to be rare variants of large effect, we performed Bulked Segregant Analysis using genomic DNA hybridization to Affymetrix chips to detect single feature polymorphisms, but found that the mutant phenotypes are more likely to have a polygenic basis. Further mapping efforts revealed a complex architecture wherein the constricted cardiomyopathy phenotype was observed in individual whole chromosome substitution lines, implying that variants on both major autosomes are sufficient to produce the phenotype. A panel of 170 Recombinant Inbred Lines (RIL) was generated, and a small subset of mutant lines selected, but these each complemented both whole chromosome substitutions, implying a non-additive (epistatic) contribution to the “disease” phenotype. Low coverage whole genome sequencing was also used to attempt to map chromosomal regions contributing to both the cardiomyopathy and arrhythmia, but a polygenic architecture had to be again inferred to be most likely. These results show that an apparently simple rare phenotype can have a complex genetic basis that would be refractory to mapping by deep sequencing in pedigrees. We present this as a cautionary tale regarding assumptions related to attempts to map new disease mutations on the assumption that probands carry a single causal mutation.

BackgroundDistributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighboring nodes. This suggests a probability distribution approximating an inverse power-law of random phenotypic variation. Zero phenotypic variation, however, is impossible, because random molecular and cellular processes are essential to normal development. Consequently, a more realistic distribution should have a y-intercept close to zero in the lower tail, a mode greater than zero, and a long (fat) upper tail. The double Pareto-lognormal (DPLN) distribution is an ideal candidate distribution. It consists of a mixture of a lognormal body and upper and lower power-law tails.Objective and MethodsIf our assumptions are true, the DPLN distribution should provide a better fit to random phenotypic variation in a large series of single-gene knockout lines than other skewed or symmetrical distributions. We fit a large published data set of single-gene knockout lines in Saccharomyces cerevisiae to seven different probability distributions: DPLN, right Pareto-lognormal (RPLN), left Pareto-lognormal (LPLN), normal, lognormal, exponential, and Pareto. The best model was judged by the Akaike Information Criterion (AIC).ResultsPhenotypic variation among gene knockouts in S. cerevisiae fits a double Pareto-lognormal (DPLN) distribution better than any of the alternative distributions, including the right Pareto-lognormal and lognormal distributions.Conclusions and SignificanceA DPLN distribution is consistent with the hypothesis that developmental stability is mediated, in part, by distributed robustness, the resilience of gene regulatory, metabolic, and protein-protein interaction networks. Alternatively, multiplicative cell growth, and the mixing of lognormal distributions having different variances, may generate a DPLN distribution.